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Adakah terdapat organisma dengan kurang daripada 1000 neuron?

Adakah terdapat organisma dengan kurang daripada 1000 neuron?


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Saya sedang membangunkan rangkaian saraf yang terdiri daripada hanya 3 hingga 10 lapisan neuron maya dan saya ingin tahu sama ada terdapat otak serangga di luar sana dengan kurang daripada seribu neuron?

  • Adakah terdapat mana-mana makhluk kecil dengan bilangan neuron yang kecil?
  • Adakah peta neuron ada untuk sistem saraf sederhana itu?

Jawapan pendek
Setahu saya, peta saraf lengkap (connectome) hanya tersedia untuk cacing gelang C. elegens, nematod dengan hanya 302 neuron (rajah 1).


Rajah 1. C. elegans (kiri, saiz: ~1 mm) dan penghubung C. elegans (kanan).
sumber: Universiti Utrecht & Farber (2012)

Latar belakang
Melihat haiwan yang paling rumit akan menjadi taruhan terbaik dan nematoda (cacing gelang) seperti anda Caenorhabditis elegans sudah pasti pilihan yang baik. C. elegans mempunyai kira-kira 300 neuron. Di bawah ialah skema phyla dalam Rajah.2.

Anda menyebut tentang serangga; makhluk ini jauh lebih kompleks daripada cacing gelang. Jumlah keseluruhan neuron berbeza dengan setiap serangga, tetapi untuk perbandingan: salah satu serangga yang kurang kompleks seperti lalat buah Drosophila sudah mempunyai kira-kira 100k neuron, manakala lebah madu biasa mempunyai kira-kira satu juta (sumber: Bio Teaching).

Kerumitan organisma sememangnya merupakan penunjuk bilangan neuron yang dijangkakan. Span, misalnya (Gambar 1) sama sekali tidak mempunyai neuron, jadi haiwan yang paling kompleks tidak akan menolong anda. barisan seterusnya ialah Cnidaria (Gamb. 2). The Cnidaria masukkan ikan agar-agar, dan sebagai contoh Hydra vulgaris mempunyai 5.6k neuron.

Jadi mengapa ikan jeli mempunyai lebih banyak neuron? Kerana ukuran juga penting. Hydra vulgaris boleh membesar 15 mm, manakala C. elegans tumbuh hanya sehingga 1 mm. Lihat halaman wikipedia untuk senarai maklumat #neuron dalam pelbagai spesies.

Peta sambungan neuron yang baik (a penghubung) hanya wujud untuk C. elegans (Gambar 1) sejauh yang saya tahu, walaupun peta lain (Drosophila (Meinertzhagen, 2016) dan manusia) sedang dijalankan.

Rujukan
- Farber, Sci Am Februari 2012
- Meinertzhagen, J Neurogenet (2016); 30(2): 62-8


Rajah 2. Phyla dalam kerajaan animalia. sumber: Kolej Universiti Tennessee Barat Daya


Organisma yang anda cari ialah nematod C. elegans, yang sentiasa mempunyai bilangan neuron yang sama, 302, dan telah dipetakan sepenuhnya, lihat WormWeb atau anda boleh mengejar penerbitan asal dari sana. C. elegans sangat sesuai untuk pekerjaan seperti ini kerana ia mempunyai bilangan sel yang tetap yang terbahagi dalam susunan yang dapat diramalkan dan neuronnya membentuk hubungan yang dapat diramalkan. Organisma yang lebih besar, seperti lalat, mempunyai bilangan sel yang berubah-ubah dan neuronnya tidak membentuk hubungan yang dapat diramalkan dengan tepat. Jumlah pengetahuan yang sangat besar tentang C. elegans, teknik manipulasi genetik lanjutan, dan badan yang telus juga membantu.

Saya tidak menyedari adanya serangga dengan otak kecil seperti itu, bahkan seekor lalat buah mempunyai lebih banyak pesanan.


Saya percaya terdapat jenis siput air dengan 8 neuron yang berbeza dalam ganglia, terdapat sedikit maklumat di sini: molluscs.at. Badan sel neuron adalah besar, boleh dilihat di bawah mikroskop membedah standard, jadi ia popular di kalangan ahli elektrofisiologi awal. Saya rasa mungkin ada lebih banyak neuron di sekitar siput, tetapi ia pasti salah satu "otak" paling sederhana di sekitar ...


Re: saiz otak serangga

Artikel berikut mempunyai ringkasan yang baik - ringkasnya sistem saraf serangga berkisar antara 7400 hingga 850000 neuron:

http://blogs.discovermagazine.com/notrocketscience/2011/11/30/how-fairy-wasps-cope-with-being-smaller-than-amoebas/

Mungkin ada harapan untuk serangga parasit, mis. Dicopomorpha echmepterygis di mana lelaki tidak mempunyai sayap atau mata, tidak mungkin otak mereka menjadi lebih sederhana.


Neuron Otak dan Sinaps

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Konsep dalam Tindakan

Tonton video ahli biologi Mark Kirschner ini yang membincangkan fenomena evolusi vertebrata yang "membalik".

Sistem saraf terdiri daripada neuron, sel khusus yang dapat menerima dan menghantar isyarat kimia atau elektrik, dan glia, sel yang menyediakan fungsi sokongan untuk neuron dengan memainkan peranan pemprosesan maklumat yang menjadi pelengkap kepada neuron. Neuron boleh dibandingkan dengan wayar elektrik—ia menghantar isyarat dari satu tempat ke tempat lain. Glia dapat dibandingkan dengan pekerja di syarikat elektrik yang memastikan wayar pergi ke tempat yang betul, menjaga wayar, dan melepaskan wayar yang rosak. Walaupun glia telah dibandingkan dengan pekerja, bukti terkini menunjukkan bahawa ia juga merampas beberapa fungsi isyarat neuron.

Terdapat kepelbagaian besar dalam jenis neuron dan glia yang terdapat di pelbagai bahagian sistem saraf. Terdapat empat jenis neuron utama, dan mereka berkongsi beberapa komponen sel penting.


Kandungan

Neuron ialah sel yang menghantar maklumat dalam sistem saraf haiwan supaya ia dapat merasakan rangsangan daripada persekitarannya dan berkelakuan sewajarnya. Tidak semua haiwan mempunyai neuron Trichoplax dan span kekurangan sel saraf sama sekali.

Neuron boleh dikemas untuk membentuk struktur seperti otak vertebrata atau ganglion saraf serangga.

Bilangan neuron dan kelimpahan relatifnya di bahagian otak yang berlainan adalah penentu fungsi saraf dan, akibatnya, tingkah laku.

Semua nombor untuk neuron (kecuali Caenorhabditis dan Ciona), dan semua nombor untuk sinaps (kecuali Ciona) adalah anggaran.

Korteks serebrum adalah struktur kepentingan tertentu di persimpangan antara neuroanatomi perbandingan dan psikologi kognitif perbandingan. Dari segi sejarah, diasumsikan bahawa kerana hanya mamalia yang mempunyai korteks serebrum, mereka hanya mendapat manfaat dari fungsi pemprosesan maklumat yang berkaitan dengannya, terutama kesedaran dan pemikiran. [57] Kini diketahui bahawa reptilia bukan burung juga mempunyai korteks serebrum dan burung mempunyai fungsi yang setara dipanggil rabung ventrikel dorsal (DVR), yang sebenarnya nampaknya merupakan pengubahsuaian selepas korteks reptilia. Pemahaman moden tentang neuroanatomi perbandingan kini menunjukkan bahawa untuk semua vertebrata, pallium secara kasarnya sepadan dengan struktur bersekutu deria umum ini. [58] Ini juga merupakan pandangan yang diterima secara luas bahawa arthropoda dan cacing yang berkaitan erat memiliki struktur yang setara, corpora pedunculata, yang lebih dikenal sebagai badan cendawan. Sebenarnya struktur ini dalam invertebrata dan pallium dalam vertebrata mungkin mempunyai asal evolusi yang sama dari nenek moyang yang sama. [59]

Memandangkan fungsi jelas struktur bersekutu deria, telah dicadangkan bahawa jumlah bilangan neuron dalam pallium atau setara dengannya mungkin merupakan peramal kecerdasan terbaik apabila membandingkan spesies, lebih mewakili daripada jumlah jisim atau isipadu otak, otak- nisbah jisim kepada badan, atau quotient encephalization (EQ). [1] Oleh itu, dapat diandaikan secara munasabah bahawa jumlah neuron dalam struktur asosiasi deria haiwan berkaitan dengan tahap kesedaran, luas dan pelbagai pengalaman subjektif, dan kecerdasannya. [1]

Kaedah yang digunakan untuk mencapai nombor dalam senarai ini termasuk kiraan neuron mengikut pempecahan isotropik, pemfraksion optik atau anggaran berdasarkan korelasi yang diperhatikan antara bilangan neuron kortikal dan jisim otak dalam taksa yang berkait rapat. Fraksinasi isotropik selalunya dianggap lebih mudah dan boleh dipercayai daripada pecahan optik yang mungkin menghasilkan kedua-dua anggaran berlebihan dan anggaran rendah. [60] Anggaran berdasarkan jisim otak dan takson harus dianggap sebagai kaedah yang paling tidak boleh dipercayai.


Perbincangan

Kami menggunakan penemuan miRNA sinergistik untuk menganalisis 94 set data sRNA-seq manusia, menghasilkan 2,469 calon miRNA novel. Ini masing-masing disokong oleh struktur jepit rambut RNA khas dan pemetaan sRNA sekitar 22-nukleotida ke jepit rambut sesuai dengan pemprosesan Dicer dan dikesan dalam sekurang-kurangnya dua eksperimen penjujukan. Di samping itu, kami mencirikan calon miRNA novel dengan lebih terperinci dalam dua sistem sel. Dalam sistem sel neuron, kami mendapati bahawa calon kami bertindak balas sama dengan miRNA yang diketahui apabila komponen laluan biogenesis dirobohkan atau apabila sel-sel didorong untuk membezakan.

Kami menggunakan data awam daripada saluran sel buah pinggang manusia untuk menunjukkan bahawa bilangan novel yang setanding dan miRNA yang diketahui berinteraksi dengan protein utama DGCR8, Ago1 dan Ago2, dalam kedudukan jepit rambut yang mematuhi biogenesis miRNA. Banyaknya rangkaian urutan novel yang terikat pada Ago1 dan Ago2 menunjukkan bahawa mereka tidak hanya menjalani interaksi kebetulan dengan mesin biogenesis, tetapi juga digabungkan oleh protein efektor. Terakhir, bukti dari data CLASH menunjukkan bahawa miRNA novel mempunyai ikatan kanonik terhadap mRNA sasaran. Kekuatan interaksi dan pengecaman benih menyerupai miRNA yang diketahui tetapi bukan urutan rawak, seperti yang dijangkakan jika penggabungan Argonaute adalah palsu. Beberapa miRNA novel berinteraksi dengan pelbagai mRNA dalam sel buah pinggang, dan kelihatan membentuk sebahagian daripada rangkaian pengawalseliaan.

Walaupun sistem dua sel ini tidak memberikan liputan jenuh dari semua calon miRNA baru, kami tidak mempunyai alasan untuk meragui bahawa eksperimen dalam sistem sel lain akan menghasilkan hasil positif yang serupa. Secara ringkasnya, kami telah menyediakan bukti tambahan untuk biogenesis 1, 098 calon miRNA novel (Fail tambahan 4: Rajah S6). Oleh itu, kami telah membentangkan bukti yang meyakinkan bahawa bilangan gen miRNA manusia lebih besar daripada yang dijangkakan pada lebih tiga ribu gen.

Semasa memperkayakan calon miRNA novel kami dengan sistem penangkapan miRNA khusus yang pertama kali dijelaskan, kami menunjukkan bahawa mereka bertindak balas serupa dengan miRNA yang diketahui, tetapi bukan tRNA dan rRNA, semasa pembezaan sel yang disebabkan. Ini menunjukkan bahawa miRNA novel bukanlah hasil transkripsi bocor, tetapi berkait rapat dengan proses pengawalseliaan. Selanjutnya, sistem tangkapan SureSelect menunjukkan janji yang hebat: ia diperkaya dengan kuat untuk sRNA sasaran sambil bersifat kuantitatif sepenuhnya. Pada penjujukan laluan rendah, ia meningkatkan pengesanan sasaran (Rajah 6a, b) dan pada penjujukan tepu ia meningkatkan kedalaman pemprofilan sasaran (Rajah 6c-f). Dengan beberapa pematangan, sistem penangkapan miRNA khusus dapat digunakan untuk profil puluhan sampel miRNA pada instrumen miSeq Illumina dalam waktu kurang dari satu hari. Ini jelas mempunyai aplikasi klinikal yang berpotensi dengan pemprosesan set sampel pesakit yang cepat.

Secara keseluruhannya, calon novel kami mempunyai ciri yang serupa dengan miRNA yang diketahui, khususnya kami perhatikan bahawa mereka berinteraksi dengan protein efektor Argonaute dan memaparkan ciri jujukan sasaran biasa. Tahap ekspresi spesifik dan rendah calon novel dijangka, kerana terdapat kecenderungan penemuan yang kuat yang memihak kepada transkrip yang banyak. Ekspresi rendah yang jelas pada tisu tidak mengecualikan kemungkinan bahawa beberapa miRNA novel mungkin sangat dinyatakan dan mempunyai fungsi penting dalam jenis sel tertentu [21]. Ini adalah hipotesis yang menarik kerana miRNA calon novel terlalu banyak diwakili dalam otak manusia, yang diketahui mempunyai kepelbagaian besar jenis sel neuron. Oleh itu katalog kami mungkin menyediakan sumber yang berharga kerana medan RNA kecil memasuki era sel tunggal, memudahkan penilaian keadaan fisiologi tertentu ekspresi gen pada peringkat selular, yang dikawal ketat oleh miRNA.

Terakhir, dalam kajian ini kami telah mengemukakan bukti biogenesis miRNA manusia baru kami. Walau bagaimanapun, biogenesis tidak semestinya membayangkan fungsi biologi yang memberikan kelebihan penyesuaian. Ia boleh dibayangkan bahawa jepit rambut boleh memasuki laluan biogenesis miRNA tetapi mempunyai kesan yang tidak ketara pada transkrip kerana ia dinyatakan rendah atau tidak merekrut faktor bersama yang diperlukan [43]. Malah, kajian genetik populasi kami mencadangkan bahawa banyak, tetapi mungkin tidak semua, miRNA manusia novel kami berada di bawah tekanan pemilihan. Secara umum, tidak mudah untuk mengetahui jika miRNA tertentu mempunyai fungsi. Fungsi biokimia miRNA dapat disahkan menggunakan ujian wartawan yang menyatakan transkrip pada tahap fisiologi, tetapi ini sangat memakan masa. MiRNA yang dipelihara secara mendalam berkemungkinan berfungsi, tetapi sebaliknya tidak semestinya berlaku, kerana terdapat contoh miRNA khusus spesies dengan fungsi yang jelas [44]. Kami berpendapat bahawa anotasi miRNA adalah penting untuk memastikan kajian masa depan akan mengambil urutan yang mengubah corak ekspresi semasa pembangunan atau dalam penyakit, dalam tisu atau dalam sel tunggal. MiRNA ini kemudiannya dapat dilakukan dengan ujian fungsi yang berhati-hati. Ketepuan anotasi miRNA berisiko mencairkan jujukan yang dipelihara dan dikaji dengan baik yang disimpan di sana, tetapi ini boleh dielakkan dengan mudah dengan menyusun urutan mengikut keyakinan. miRBase telah menyusun 'anotasi teras' miRNA dengan bukti yang menarik untuk biogenesis [45], dan kajian baru-baru ini telah mengenal pasti subset urutan yang disokong oleh bukti berfungsi [46]. Begitu juga, kami telah mengkategorikan calon miRNA novel kami menjadi lima tahap keyakinan berdasarkan bukti yang dikemukakan dalam kajian kami (Fail tambahan 3: Jadual S2), yang membolehkan para penyelidik memutuskan tahap ketegasan mereka sendiri.

Untuk menyiasat sama ada spesies lain mempunyai sejumlah besar miRNA yang belum ditemui, kami mengulangi ramalan dalam tetikus, menggunakan data penjujukan awam volum yang setanding dengan data yang digunakan dalam manusia, yang disusun daripada 11 kajian yang berbeza. Ini menghasilkan 1, 520 calon miRNA tikus novel (keputusan tidak diterbitkan). Menariknya, ini adalah satu pertiga kurang daripada jumlah yang dilaporkan pada manusia, walaupun data tetikus mempunyai liputan tisu yang sangat baik, termasuk sampel dari otak dan dari beberapa titik masa perkembangan [41]. Mengkaji semula data manusia dengan simulasi, kami mendapati bahawa jumlah calon yang dilaporkan berskala hampir secara linear dengan jumlah data yang dianalisis (Gambar 7), menunjukkan bahawa penemuan miRNA manusia belum mencapai tahap jenuh, bahkan dengan set tambahan kami. Ini menunjukkan bahawa masih banyak lagi miRNA yang masih belum dijumpai, baik dalam organisma model yang dikaji dengan baik dan pada manusia.

Ketepuan ramalan miRNA novel. Untuk menilai pengaruh magnitud data pada analisis, lengkung tepu 94 set data telah dilakukan. (a) Keluk pemenuhan kedalaman penjujukan, dari 10% hingga 100% bacaan dipertahankan. Bagi setiap set data peratusan bacaan (dipilih secara rawak) ini dikekalkan dan seterusnya analisis ramalan miRNA diulang. Jumlah bilangan miRNA novel yang dilaporkan (coklat) atau miRNA novel berkeyakinan tinggi (oren) ditunjukkan. Bilangan miRNA yang diketahui yang dikesan oleh padanan urutan mudah ditunjukkan dalam warna hijau. (b) Seperti sebelum ini, kecuali keseluruhan set data dan bukannya bacaan individu telah dibuang atau disimpan.


Pembelajaran dan Ingatan

Maklumat di bawah telah disesuaikan daripada OpenStax Biology 35.2

Salah satu fungsi utama yang dilakukan oleh otak adalah proses pembelajaran dan ingatan. Pembelajaran adalah kemampuan untuk memperoleh pengetahuan baru, dan ingatan adalah keupayaan untuk mengingatinya kemudian. Pembelajaran dan ingatan melibatkan kedua-dua struktur otak tertentu serta proses neuron tertentu. Hipotesis semasa menyatakan bahawa neuron tertentu di korteks serebrum bertanggungjawab untuk menyimpan ingatan secara fizikal, dan bahawa pembelajaran dan ingatan dimediasi oleh perubahan kimia dan struktur dalam sinapsis neuron-neuron ini.

Kenangan jangka pendek difikirkan disimpan dalam korteks prefrontal (sebahagian lobus frontal). The kuda nil di dalam lobus temporal adalah penting untuk menyatukan kenangan jangka pendek ini menjadi kenangan jangka panjang, tetapi kenangan itu sebenarnya tidak disimpan dalam hippocampus. Lokasi penyimpanan memori yang tepat tidak diketahui, tetapi walaupun komponen ingatan yang berbeza mungkin disimpan di lokasi yang berbeza dalam korteks serebrum, dan pengambilan ingatan jangka panjang mungkin melibatkan korteks prefrontal.

Penyimpanan dan akses hanya separuh daripada cerita untuk belajar dan ingatan, separuh lagi adalah perubahan kimia dan struktur dalam sinapsis, atau keplastikan saraf: pembentukan baru dan kehilangan sambungan saraf sedia ada. Menjelang akhir embriogenesis pada manusia, separuh daripada semua neuron embrio mengalami kematian sel yang diprogramkan, dan separuh daripada sinaps awal hilang. Seni bina neural asas ini kemudiannya diubahsuai secara berterusan semasa kehidupan individu & # 8217. Bagaimanakah keplastikan saraf berkaitan dengan pembelajaran dan ingatan? Perubahan kimia dan struktur dalam sinaps (keplastikan sinaptik, pemangkasan sinaptik, sinaptogenesis) menengahi akses dan kekuatan kenangan ini seperti berikut:

  • Neurogenesis, atau pertumbuhan neuron baru. Pada satu masa, saintis percaya bahawa orang dilahirkan dengan semua neuron yang mereka akan ada, tetapi penyelidikan yang dilakukan dalam beberapa dekad yang lalu menunjukkan bahawa neurogenesis, kelahiran neuron baru, berterusan sehingga dewasa. Neurogenesis pertama kali ditemui pada burung penyanyi yang menghasilkan neuron baru semasa belajar lagu. Bagi mamalia, neuron baru juga memainkan peranan penting dalam pembelajaran: kira-kira 1000 neuron baru berkembang dalam hippocampus (struktur otak yang terlibat dalam pembelajaran dan ingatan) setiap hari. Walaupun kebanyakan neuron baru akan mati, penyelidik mendapati bahawa peningkatan bilangan neuron baru yang masih hidup dalam hippocampus berkorelasi dengan seberapa baik tikus mempelajari tugas baru. Menariknya, kedua-dua senaman dan beberapa ubat antidepresan juga mendorong neurogenesis pada hippocampus. Tekanan mempunyai kesan sebaliknya.
  • Sinaptogenesis, atau pertumbuhan sinaps baharu antara dua neuron sedia ada, dan pemangkasan sinaptik, atau pemusnahan sinaps yang ada antara dua neuron.
  • Keplastikan sinaptik, atau pengukuhan atau kelemahan sambungan sinaptik sedia ada. Dua proses khususnya, potensiasi jangka panjang (LTP) dan kemurungan jangka panjang (LTD) ialah bentuk penting keplastikan sinaptik yang berlaku dalam sinaps dalam hippocampus, kawasan otak yang terlibat dalam menyimpan kenangan.
    • Potensi jangka panjang (LTP) ialah pengukuhan jangka panjang sambungan sinaptik. LTP didasarkan pada idea bahawa & # 8220sel yang menyala bersama-sama. & # 8221 Terdapat pelbagai mekanisme yang mendasari penguatan sinaptik yang dilihat dengan LTP, termasuk peningkatan jumlah neurotransmitter yang dilepaskan oleh neuron presinaptik, dan peningkatan tindak balas terhadap jumlah neurotransmitter yang sama oleh neuron postsynaptic. LTP boleh mengakibatkan pemekaan, di mana terdapat peningkatan tindak balas terhadap rangsangan luaran yang sama.
    • Kemurungan jangka panjang (LTD) pada asasnya adalah kebalikan LTP: ia merupakan kelemahan jangka panjang sambungan sinaptik. Walaupun kelihatannya berlawanan dengan intuisi, LTD mungkin sama pentingnya untuk belajar dan ingatan seperti LTP: sinaps yang lemah yang tidak digunakan memungkinkan sambungan yang tidak penting terputus dan membuat sinaps yang telah menjalani LTP jauh lebih kuat dibandingkan. LTD boleh mengakibatkan kebiasaan, di mana terdapat penurunan tindak balas kepada rangsangan luar yang sama.

    Potensiasi jangka panjang boleh berlaku setelah rangsangan berulang pada terminal sinaptik (panel 1) melalui beberapa mekanisme, termasuk pengeluaran lebih banyak reseptor neurotransmitter pada neuron postsynaptic (panel 2) dan pengeluaran lebih banyak molekul neurotransmitter oleh neuron presinaptik (panel 3). Hubungan yang lebih kuat antara neuron (panel 4) akan berlaku akibat daripada salah satu daripada perubahan ini. Kredit imej: pengubahsuaian kerja oleh Tomwsulcer – Kerja sendiri, CC0, https://commons.wikimedia.org/w/index.php?curid=15509518

    Video ini menyediakan gambaran ringkas pembelajaran dan ingatan dalam model organisma yang biasa digunakan untuk mengkaji proses ini:

    Dan akhirnya, video ini memberikan gambaran ringkas mengenai dua hasil pembelajaran, pemekaan atau pembiasaan biasa:


    Nota kaki

    Bahan tambahan elektronik boleh didapati dalam talian di https://doi.org/10.6084/m9.figshare.c.5427713.

    Diterbitkan oleh Royal Society di bawah syarat Lesen Atribusi Creative Commons http://creativecommons.org/licenses/by/4.0/, yang membenarkan penggunaan tanpa had, dengan syarat pengarang dan sumber asal dikreditkan.

    Rujukan

    . 2010 Dua pandangan fungsi otak . Tren Cogn. Sains. 14, 180-190. (doi:10.1016/j.tics.2010.01.008) Crossref, PubMed, ISI, Google Scholar

    Friston KJ, Frith CD, Dolan RJ, Price CJ, Zeki S, Ashburner JT, Penny W.

    2004 Fungsi otak manusia. Oxford, UK: Elsevier. Cendekiawan Google

    . 1989 Struktur dan fungsi testis dan epididimis normal. J. Am. Coll. Toksikol. 8, 457-471. (doi: 10.3109 / 10915818909014532) Crossref, Google Cendekiawan

    Nieschlag E, Behre HM, Nieschlag S

    . 2010 Fisiologi fungsi testis. Dalam Andrologi: kesihatan pembiakan lelaki dan disfungsi (eds GF Weinbaver, CM Luetjens, M Simoni, E Nieschlag), ms 1-629. Berlin, Jerman: Springer. Crossref, Google Scholar

    Guo J, Zhu P, Wu C, Yu L, Zhao S, Gu X

    . 2003 Dalam analisis silico menunjukkan pola ekspresi gen yang serupa antara otak manusia dan testis. Cytogenet. Genom Res. 103, 58-62. (doi: 10.1159 / 000076290) Crossref, PubMed, ISI, Google Scholar

    Guo JH, Huang Q, Studholme DJ, Wu CQ, Zhao SY

    . 2005 Analisis transkriptomik menyokong persamaan ekspresi gen antara otak dan testis pada manusia serta tetikus. Sitogenet. Genom Res. 111, 107-109. (doi:10.1159/000086378) Crossref, PubMed, ISI, Google Scholar

    Arden R, Gottfredson LS, Miller G, Pierce A

    . Kepintaran dan kualiti air mani 2009 berkorelasi positif. Kepintaran 37, 277-282. (doi:10.1016/j.intel.2008.11.001) Crossref, ISI, Google Scholar

    2017 Kemandulan faktor lelaki dan risiko sklerosis berganda: kajian kohort berasaskan daftar . Pelbagai. Scler. J. 24, 1835-1842. (doi: 10.1177 / 1352458517734069) Crossref, PubMed, Google Cendekiawan

    Fode M, Krogh-jespersen S, Brackett NL, Ohl DA, Lynne CM, Sønksen J

    . 2012 Disfungsi seksual lelaki dan ketidaksuburan yang berkaitan dengan gangguan neurologi. Asia J. Androl. 14, 61-68. (doi: 10.1038 / aja.2011.70) Crossref, PubMed, ISI, Google Scholar

    . 2019 Unit saraf asas otak: neuron, sinaps dan potensi tindakan. arXiv. (http://arxiv.org/abs/1906.01703) Cendekiawan Google

    . 2017 Sel glial dan fungsinya dalam otak dewasa: perjalanan melalui sejarah ablasi mereka . Depan. Neurosci Sel. 11, 1-17. (doi:10.3389/fncel.2017.00024) Crossref, PubMed, ISI, Google Scholar

    . 1984 Organisasi dan morfogenesis epitelium seminiferus manusia. Sel Tisu Sel. 237, 395-407. (doi: 10.1007 / BF00228424) Crossref, PubMed, ISI, Google Cendekia

    Svechnikov K, Landreh L, Weisser J, Izzo G, Colón E, Svechnikov I, Söder O

    et al. 2010 Asal, pembangunan dan pengawalseliaan sel leydig manusia . Horm. Res. Pediatr. 73, 93-101. (doi:10.1159/000277141) Crossref, PubMed, ISI, Google Scholar

    Kıray H, Lindsay SL, Hosseinzadeh S, Barnett SC

    . 2016 Peranan pelbagai aspek astrosit dalam mengatur myelination. Tamat Neurol. 283, 541-549. (doi:10.1016/j.expneurol.2016.03.009) Crossref, PubMed, ISI, Google Scholar

    Fu C, Rojas T, Chin AC, Cheng W, Bernstein IA, Albacarys LK, Wright WW, Snyder SH

    . 2018 Pelbagai aspek perkembangan sel kuman lelaki dan interaksi dengan sel Sertoli memerlukan inositol hexakisphosphate kinase-1. Sains. Rep. 8, 1-13. (doi:10.1038/s41598-018-25468-8) Crossref, PubMed, ISI, Google Scholar

    . 2018 Pemprofilan khusus tisu transkrip yang berkaitan dengan tekanan oksidatif dalam model tetikus yang sihat . Int. J. Mol. Sains. 19, 3174. (doi: 10.3390 / ijms19103174) Crossref, ISI, Google Scholar

    Falkowska A, Gutowska I, Goschorska M, Nowacki P

    . 2015 Metabolisme tenaga otak, termasuk kerjasama antara astrosit dan neuron, terutamanya dalam konteks metabolisme glikogen . Int. J. Mol. Sains. 16, 25 959-25 981. (doi: 10.3390 / ijms161125939) Crossref, ISI, Google Scholar

    . 2004 Laktat dan metabolisme tenaga dalam sel kuman lelaki. Trend Endokrinol. Metab. 15, 345-350. (doi: 10.1016 / j.tem.2004.07.003) Crossref, PubMed, ISI, Google Cendekiawan

    Rato L, Alves MG, Socorro S, Duarte AI, Cavaco JE, Oliveira PF

    . 2012 Regulasi metabolik adalah penting untuk spermatogenesis. Nat. Rev. Urol. 9, 330-338. (doi:10.1038/nrurol.2012.77) Crossref, PubMed, ISI, Google Scholar

    Pitts MW, Kremer PM, Hashimoto AC, Torres DJ, Byrns CN, Williams CS, Berry MJ

    . Persaingan 2015 antara otak dan testis dalam keadaan selenium yang dikompromikan: pandangan mengenai perbezaan jantina dalam metabolisme selenium dan risiko penyakit saraf. J. Neurosci. 35, 15 326-15 338. (doi:10.1523/JNEUROSCI.2724-15.2015) Crossref, ISI, Google Scholar

    Kabuto H, Amakawa M, Shishibori T

    . 2004 Pendedahan kepada bisphenol A semasa hayat embrio/janin dan bayi meningkatkan kecederaan oksidatif dan menyebabkan keterbelakangan perkembangan otak dan testis pada tikus . Kehidupan Sci. 74, 2931-2940. (doi: 10.1016 / j.lfs.2003.07.060) Crossref, PubMed, ISI, Google Cendekia

    Zhao Z, Nelson AR, Betsholtz C, Zlokovic BV

    . 2015 Penubuhan dan disfungsi penghalang darah-otak . sel 163, 1064-1078. (doi:10.1016/j.cell.2015.10.067) Crossref, PubMed, ISI, Google Scholar

    Mital P, Hinton BT, Dufour JM

    . 2011 Penghalang darah-testis dan epididimis darah lebih daripada sekadar persimpangan yang ketat1. biol. Reproduk. 84, 851-858. (doi:10.1095/biolreprod.110.087452) Crossref, PubMed, ISI, Google Scholar

    Crawford MA, Broadhurst CL, Ghebremeskel K, Sinclair AJ, Saugstad LF, Schmidt WF, Sinclair AJ, Cunnane SC

    . 2008 Peranan asid docosahexaenoic dan arachidonic sebagai penentu evolusi dan perkembangan otak hominid. Dalam Fish Glob Welf Environ 5th World Fish Congr, hlm. 57-76. Tokyo, Jepun: JSFS. Cendekiawan Google

    Lenzi A, Gandini L, Maresca V, Rago R, Sgrò P, Dondero F, Picardo M

    . 2000 Komposisi asid lemak spermatozoa dan sel kuman yang belum matang. Mol. Hum. Reproduk. 6, 226-231. (doi:10.1093/molehr/6.3.226) Crossref, PubMed, ISI, Google Scholar

    Davidoff MS, Middendorff R, Köfüncü E, Müller D, Ježek D, Holstein AF

    . 2002 Sel Leydig pada testis manusia mempunyai molekul penanda astrosit dan oligodendrosit . Acta Histochem. 104, 39-49. (doi: 10.1078 / 0065-1281-00630) Crossref, PubMed, ISI, Google Scholar

    Schulze W, Davidoff MS, Holstein AF

    . 1987 Adakah sel Leydig berasal dari saraf? Imunoreaktiviti seperti bahan P dalam tisu testis manusia. Acta Endocrinol (Copenh). 115, 373-377. (doi:10.1530/acta.0.1150373) Crossref, PubMed, Google Scholar

    Davidoff MS, Schulze W, Middendorff R, Holstein AF

    . 1993 Sel Leydig testis manusia: ahli baru sistem neuroendokrin meresap. Sel Tisu Sel. 271, 429-439. (doi:10.1007/BF02913725) Crossref, PubMed, ISI, Google Scholar

    Davidoff MS, Middendorff R, Pusch W, Müller D, Wichers S, Holstein AF

    . 1999 Sel Sertoli dan Leydig dari testis manusia menyatakan protein triofet neurofilamen. Histochem. Sel Biol. 111, 173-187. (doi:10.1007/s004180050347) Crossref, PubMed, ISI, Google Scholar

    . Motor molekul Cytoskeleton 2016: struktur dan fungsinya dalam neuron. Int. J. Biol. Sains. 12, 1083-1092. (doi:10.7150/ijbs.15633) Crossref, PubMed, ISI, Google Scholar

    . 2017 Kinesins dalam spermatogenesis †. biol. Reproduk. 96, 267-276. (doi:10.1095/biolreprod.116.144113) Crossref, PubMed, ISI, Google Scholar

    Liu XA, Rizzo V, Puthanveettil SV

    . 2012 Patologi pengangkutan aksonal dalam penyakit neurodegeneratif. Terjemahan Neurosci. 3, 355-372. Crossref, PubMed, ISI, Google Scholar

    Zhang Y, Ou Y, Cheng M, Shojaei Saadi H, Thundathil JC, van der Hoorn FA

    . 2012 KLC3 terlibat dalam pembentukan bahagian tengah ekor sperma dan fungsi sperma. Penipu biol. 366, 101-110. (doi: 10.1016 / j.ydbio.2012.04.026) Crossref, PubMed, ISI, Google Cendekia

    Jenama A, Münzel PA, Bock KW

    . 2000 Kajian hibridisasi in situ ekspresi UDP-glucuronosyltransferase UGT1A6 dalam testis tikus dan otak. Biokimia. Pharmacol. 59, 1441-1444. (doi: 10.1016 / S0006-2952 (00) 00274-4) Crossref, PubMed, ISI, Google Scholar

    . 1995 Protein pengikat RNA otak-testis, protein pengikat RNA pengatur translasi testis, terdapat di otak dan mengikat ke 3 regions kawasan yang tidak diterjemahkan mRNA otak yang diangkut1. biol. Reproduk. 53, 707-717. (doi:10.1095/biolreprod53.3.707) Crossref, PubMed, ISI, Google Scholar

    Ibberson M, Riederer BM, Uldry M, Guhl B, Roth J, Thorens B

    . 2002 Imunolokalisasi GLUTX1 dalam testis dan ke kawasan otak tertentu dan neuron yang mengandungi vasopressin. Endokrinologi 143, 276-284. (doi: 10.1210 / endo.143.1.8587) Crossref, PubMed, ISI, Google Cendekia

    Maeda K, Inui S, Tanaka H, ​​Sakaguchi N

    . 1999 Ahli baru α4 molekul berkaitan (α4-b) yang mengikat protein fosfatase 2A dinyatakan secara selektif di otak dan testis. Eur. J. Biokim. 264, 702-706. (doi:10.1046/j.1432-1327.1999.00571.x) Crossref, PubMed, Google Scholar

    Marazziti D, Gallo A, Golini E, Matteoni R, Tocchini-Valentini GP

    . 1998 Pengklonan molekul dan penyetempatan kromosom gen Gpr37 tikus yang mengekodkan reseptor peptida G-protein yatim yang dinyatakan dalam otak dan testis. Genomik 53, 315-324. (doi:10.1006/geno.1998.5433) Crossref, PubMed, ISI, Google Scholar

    Mayer H, Bauer H, Breuss J, Ziegler S, Prohaska R

    . 2001 Pencirian tikus LANCL1, ahli novel keluarga protein seperti lanthionine synthetase C, sangat dinyatakan dalam testis dan otak . Gen 269, 73-80. (doi:10.1016/S0378-1119(01)00463-2) Crossref, PubMed, ISI, Google Scholar

    Tanja O, Facchinetti P, Rose C, Bonhomme MC, Gros C, Schwartz JC

    . 2000 Neprilysin II: metalloprotease novel yang berpotensi dan isoformnya di CNS dan testis. Biokimia. Biophys. Res. Commun. 271, 565-570. (doi:10.1006/bbrc.2000.2664) Crossref, PubMed, ISI, Google Scholar

    Yamamoto H, Ochiya T, Takahama Y, Ishii Y, Osumi N, Sakamoto H, Terada M

    . 2000 Pengesanan penyetempatan spatial ekspresi gen Hst-1/Fgf-4 dalam otak dan testis daripada tikus dewasa. Onkogen 19, 3805-3810. (doi: 10.1038 / sj.onc.1203752) Crossref, PubMed, ISI, Google Cendekia

    Danielsson A, Djureinovic D, Fagerberg L, Hallstro B, Ponte F, Lindskog C, Uhlén M, Ponten F

    . 2014 Proteom khusus testis manusia yang ditakrifkan oleh transkriptomi dan pemprofilan berasaskan antibodi . Mol. Hum. Reproduk. 20, 476-488. (doi: 10.1093 / molehr / gau018) Crossref, PubMed, ISI, Google Cendekia

    Liu T-Y, Huang HH, Wheeler D, Xu Y, Wells JA, Song YS, Wiita AP

    . 2017 Proteomik yang diselesaikan masa memanjangkan pengukuran berasaskan profil ribosom dinamik sintesis protein . Sistem Sel. 4, 636-644. e9. (doi:10.1016/j.cels.2017.05.001) Crossref, PubMed, ISI, Google Scholar

    Wilda M, Bächner D, Zechner U, Kehrer-Sawatzki H, Vogel W, Hameister H

    . 2000 Adakah kekangan spesiasi manusia menyebabkan ekspresi set gen yang sama dalam otak, testis dan plasenta? Cytogenet. Genet Sel. 91, 300-302. (doi: 10.1159 / 000056861) Crossref, PubMed, Google Scholar

    Khaitovich P, Enard W, Lachmann M, Pääbo S

    . 2006 Evolusi ekspresi gen primata . Nat. Rev. Genet. 7, 693-702. (doi:10.1038/nrg1940) Crossref, PubMed, ISI, Google Scholar

    . 2019 Tempat liputan untuk gen baharu . Elife 8, 8-10. Crossref, ISI, Google Scholar

    . 2013 Perkembangan sperma yang gagal sebagai penghalang pengasingan pembiakan antara spesies. Evol. Penipu 15, 458-465. (doi:10.1111/ede.12054) Crossref, PubMed, ISI, Google Scholar

    . 2011 De novo asal gen pengekod protein manusia. Genetik PLoS. 7, 11. Crossref, ISI, Google Scholar

    2018 Gen NOTCH2NL khusus manusia mengembangkan neurogenesis kortikal melalui peraturan delta/takik . sel 173, 1370-1384.e16. (doi: 10.1016 / j.cell.2018.03.067) Crossref, PubMed, ISI, Google Scholar

    . 2005 Membandingkan genom manusia dan cimpanzi: mencari jarum dalam timbunan jerami . Genom Res. 15, 1746-1758. (doi: 10.1101 / gr.3737405) Crossref, PubMed, ISI, Google Scholar

    . 1971 Perubahan testis berkaitan dengan kecacatan sistem saraf pusat TFIE dan terencat akal. Acta Pathol. Mikrobiol. Scand. Pathol. 79A, 249-256. (doi: 10.1111 / j.1699-0463.1971.tb01816.x) Cendekiawan Google

    2002 Mutasi ARX menyebabkan perkembangan abnormal otak depan dan testis pada tikus dan lissencephaly berkaitan X dengan alat kelamin yang tidak normal pada manusia. Nat. Genet. 32, 359-369. (doi: 10.1038 / ng1009) Crossref, PubMed, ISI, Google Cendekia

    Dragatsis I, Levine MS, Zeitlin S

    . 2000 Penyahaktifan Hdh dalam otak dan testis mengakibatkan kemerosotan saraf progresif dan kemandulan pada tikus. Nat. Genet. 26, 300-306. (doi:10.1038/81593) Crossref, PubMed, ISI, Google Scholar

    Mascaro JS, Hackett PD, Rilling JK

    . 2013 Jumlah testis berkorelasi songsang dengan aktiviti otak yang berkaitan dengan asuhan dalam bapa manusia. Pro. Natl Acad.Sci. USA 110, 15 746-15 751. (doi: 10.1073 / pnas.1305579110) Crossref, ISI, Google Scholar

    . 2004 Sperma, neuron dengan ekor: reseptor 'neuronal' pada sperma mamalia. biol. Rev. Camb. Philos. Soc. 79, 713-732. (doi: 10.1017 / S1464793103006407) Crossref, PubMed, ISI, Google Cendekiawan

    Ren X, Chen X, Wang Z, Wang D

    . 2017 Adakah transkripsi dalam sperma pegun atau dinamik? J. Reprod. Penipu 63, 439-443. (doi:10.1262/jrd.2016-093) Crossref, PubMed, ISI, Google Scholar

    . 2013 Persimpangan jurang neuron: membuat dan memutuskan sambungan semasa pembangunan dan kecederaan . Trend Neurosci. 36, 227-236. (doi: 10.1016 / j.tins.2012.11.001) Crossref, PubMed, ISI, Google Scholar

    . 2002 Snares dan munc18 dalam pelakuran vesikel sinaptik. Nat. Rev. Neurosci. 3, 641-653. (doi: 10.1038 / nrn898) Crossref, PubMed, ISI, Google Scholar

    Michaut M, De Blas G, Tomes CN, Yunes R, Fukuda M, Mayorga LS

    . 2001 Synaptotagmin VI mengambil bahagian dalam tindak balas akrosom spermatozoa manusia. Penipu biol. 235, 521-529. (doi:10.1006/dbio.2001.0316) Crossref, PubMed, ISI, Google Scholar

    Tomes CN, Michaut M, De BG, Visconti P, Matti U, Mayorga LS

    . Pemasangan kompleks SNARE 2002 diperlukan untuk tindak balas akrosom sperma manusia. Penipu biol. 243, 326-338. (doi: 10.1006 / dbio.2002.0567) Crossref, PubMed, ISI, Google Cendekia

    Hutt DM, Cardullo RA, Baltz JM, Ngsee JK

    . 2002 Synaptotagmin VIII disetempatkan pada kepala sperma tikus dan mungkin berfungsi dalam eksositosis akrosomal1 . biol. Reproduk. 66, 50-56. (doi:10.1095/biolreprod66.1.50) Crossref, PubMed, ISI, Google Scholar

    Pierce A, Miller G, Arden R, Gottfredson LS

    . 2009 Mengapa kecerdasan dikaitkan dengan kualiti air mani? Commun. Integr. biol. 2, 1-3. (doi:10.4161/cib.2.5.8716) PubMed, Google Scholar

    Harper CV, Cummerson JA, White MRH, Publicover SJ, Johnson PM

    . 2008 Penyelesaian dinamik eksositosis akrosom pada sperma manusia. J. Sel Sci. 121, 2130-2135. (doi:10.1242/jcs.030379) Crossref, PubMed, ISI, Google Scholar

    Ritta MN, Calamera JC, Bas DE

    . 1998 Kejadian reseptor GABA dan GABA pada spermatozoa manusia. Mol. Hum. Reproduk. 4, 769-773. (doi:10.1093/molehr/4.8.769) Crossref, PubMed, ISI, Google Scholar

    Bray C, Son J-H, Kumar P, Harris JD, Meizel S

    . 2002 Peranan untuk reseptor glisin sperma manusia / saluran Cl − dalam tindak balas akrosom yang dimulakan oleh rekombinan ZP31 . biol. Reproduk. 66, 91-97. (doi:10.1095/biolreprod66.1.91) Crossref, PubMed, ISI, Google Scholar

    Baccetti B, Burrini AG, Collodel GC, Falugi C, Moretti E, Piomboni P

    . 1995 Penyetempatan dua kelas molekul reseptor asetilkolin dalam sperma spesies haiwan yang berbeza. Zigot 3, 207-217. (doi:10.1017/S0967199400002604) Crossref, PubMed, ISI, Google Scholar

    Ramírez-Reveco A, Villarroel-Espíndola F, Rodríguez-Gil JE, Concha II

    . 2017 Repertoir isyarat neuron dalam fungsi sperma mamalia. biol. Reproduk. 96, 505-524. (doi: 10.1095 / biolreprod.116.144154) Crossref, PubMed, ISI, Google Scholar

    Schulz DJ, Baines RA, Hempel CM, Li L, Liss B, Misonou H

    . 2006 Keceriaan selular dan peraturan identiti neuron berfungsi: dari ekspresi gen kepada neuromodulasi. J. Neurosci. 26, 10 362-10 367. (doi:10.1523/JNEUROSCI.3194-06.2006) Crossref, ISI, Google Scholar

    Jagannathan S, Publicover SJ, Barratt CLR

    . 2002 Saluran kalsium yang dikendalikan oleh voltan dalam sel kuman lelaki. Pembiakan 123, 203-215. (doi:10.1530/rep.0.1230203) Crossref, PubMed, ISI, Google Scholar

    Darszon A, Labarca P, Nishigaki T, Espinosa F

    . 1999 Saluran ion dalam fisiologi sperma. Fisiol. Pendeta 79, 481-510. (doi:10.1152/physrev.1999.79.2.481) Crossref, PubMed, ISI, Google Scholar

    Darszon A, Nishigaki T, Beltran C, Treviño CL

    . 2011 Calcium channels in the development, maturation, and function of spermatozoa . Fisiol. Pendeta 91, 1305-1355. (doi:10.1152/physrev.00028.2010) Crossref, PubMed, ISI, Google Scholar

    . 2007 Key role of calcium signaling in synaptic transmission . Neurophysiology 39, 248-250. (doi:10.1007/s11062-007-0034-5) Crossref, ISI, Google Scholar

    Brini M, Calì T, Ottolini D, Carafoli E

    . 2014 Neuronal calcium signaling: function and dysfunction . Sel. Mol. Kehidupan Sci. 71, 2787-2814. (doi:10.1007/s00018-013-1550-7) Crossref, PubMed, ISI, Google Scholar

    . 2009 Egg coat proteins activate calcium entry into mouse sperm via CATSPER channels1 . biol. Reproduk. 80, 1092-1098. (doi:10.1095/biolreprod.108.074039) Crossref, PubMed, ISI, Google Scholar

    . 2018 CatSper: a unique calcium channel of the sperm flagellum . Curr. Pendapat. Fisiol. 2, 109-113. (doi:10.1016/j.cophys.2018.02.004) Crossref, PubMed, ISI, Google Scholar

    Publicover S, Harper CV, Barratt C

    . 2007 [Ca 2+ ]i signalling in sperm: making the most of what you've got . Nat. Sel. biol. 9, 235-242. (doi:10.1038/ncb0307-235) Crossref, PubMed, ISI, Google Scholar

    Amoako AA, Marczylo TH, Marczylo EL, Elson J, Willets JM, Taylor AH, Konje JC

    . 2013 Anandamide modulates human sperm motility: implications for men with asthenozoospermia and oligoasthenoteratozoospermia . Hum. Reproduk. 28, 2058-2066. (doi:10.1093/humrep/det232) Crossref, PubMed, ISI, Google Scholar

    Castillo P, Younts T, Chávez A, Hashimotodani Y

    . 2013 Endocannabinoid signaling and synaptic function . Neuron 76, 70-81. (doi:10.1016/j.neuron.2012.09.020) Crossref, ISI, Google Scholar

    Koch S, Acebron SP, Koch S, Acebron SP, Herbst J, Hatiboglu G, Niehrs C

    . 2015 Post-transcriptional Wnt signaling governs epididymal sperm maturation post-transcriptional Wnt signaling . sel 163, 1225-1236. (doi:10.1016/j.cell.2015.10.029) Crossref, PubMed, ISI, Google Scholar

    . 2013 WNT signaling in neuronal maturation and synaptogenesis . Depan. Sel. Neurosci. 7, 1-11. (doi:10.3389/fncel.2013.00103) Crossref, PubMed, ISI, Google Scholar

    Silva JV, Cabral M, Correia R, Carvalho P, Sousa M, Oliveira PF, Fardilha M

    . 2019 mTOR signaling pathway regulates sperm quality in older men . sel 8, 1-13. (doi:10.3390/cells8060629) ISI, Google Scholar

    . 2014 mTOR signaling and its roles in normal and abnormal brain development . Depan. Mol. Neurosci. 7, 1-12. (doi:10.3389/fnmol.2014.00028) Crossref, PubMed, ISI, Google Scholar

    Santiago J, Vieira Silva J, Fardilha M

    . 2019 First insights on the presence of the unfolded protein response in human spermatozoa . Int. J. Mol. Sains. 20, 1-16. (doi:10.3390/ijms20215518) Crossref, ISI, Google Scholar

    Chaerkady R, Kerr CL, Marimuthu A, Kelkar DS, Kashyap MK, Gucek M, Gearhart JD, Pandey A

    . 2009 Temporal analysis of neural differentiation using quantitative proteomics . J. Proteome Res. 8, 1315-1326. (doi:10.1021/pr8006667) Crossref, PubMed, ISI, Google Scholar

    Dammer EB, Duong DM, Diner I, Gearing M, Feng Y, Lah JJ, Levey AI, Seyfried NT

    . 2013 Neuron enriched nuclear proteome isolated from human brain . J. Proteome Res. 12, 3193-3206. (doi:10.1021/pr400246t) Crossref, PubMed, ISI, Google Scholar

    Djuric U, Rodrigues DC, Batruch I, Ellis J, Shannon P, Diamandis P

    . 2017 Spatiotemporal proteomic profiling of human cerebral development . Mol. Sel. Proteom. 16, 1558-1562. (doi:10.1074/mcp.M116.066274) Crossref, ISI, Google Scholar

    Drummond ES, Nayak S, Ueberheide B, Wisniewski T

    . 2015 Proteomic analysis of neurons microdissected from formalin-fixed, paraffin-embedded Alzheimer's disease brain tissue . Sains. Rep. 5, 1-8. (doi:10.1038/srep15456) Crossref, ISI, Google Scholar

    Fathi A, Hatami M, Vakilian H, Han CL, Chen YJ, Baharvand H, Salekdeh GH

    . 2014 Quantitative proteomics analysis highlights the role of redox hemostasis and energy metabolism in human embryonic stem cell differentiation to neural cells . J. Proteomics 101, 1-16. (doi:10.1016/j.jprot.2014.02.002) Crossref, PubMed, ISI, Google Scholar

    Ramachandran U, Manavalan A, Sundaramurthi H, Sze SK, Feng ZW, Hu JM, Heese K

    . 2012 Tianma modulates proteins with various neuro-regenerative modalities in differentiated human neuronal SH-SY5Y cells . Neurochem. Int. 60, 827-836. (doi:10.1016/j.neuint.2012.03.012) Crossref, PubMed, ISI, Google Scholar

    Villeneuve L, Tiede LM, Morsey B, Fox HS

    . 2013 Quantitative proteomics reveals oxygen-dependent changes in neuronal mitochondria affecting function and sensitivity to rotenone . J. Proteome Res. 12, 4599-4606. (doi:10.1021/pr400758d) Crossref, PubMed, ISI, Google Scholar


    Elephants Have The Most Neurons. Why Aren't They The Smartest Animals?

    Why aren't elephants the smartest animals since they have the most neurons? mula-mula muncul di Quora: tempat untuk menimba dan berkongsi pengetahuan, memperkasakan orang ramai untuk belajar daripada orang lain dan lebih memahami dunia.

    Answer by Fabian van den Berg, Neuropsychologist, on Quora:

    Why aren't elephants the smartest animals since they have the most neurons?

    We often hear 'bigger is better' which might be true for pay-checks but not for other things. I’m of course talking about brains, what else? Nature has an astounding diversity of life, each with a unique brain. Some of those brains grow to be massive organs, like that of the African Elephant with a 5kg brain (11lbs) and 257 billion neurons. Some brains stay tiny, like that of roundworms which comes in at only a fraction of a gram with about 300 neurons in total. Humans rank in between, with a 1.4kg (3lbs) brain and give or take 86 billion neurons.

    That begs the question, if humans are outranked by animals such as elephants, why are we the self-proclaimed smartest creature on earth? How is it that an elephant with almost 3 times the number of neurons isn’t laughing at our struggle with quantum mechanics?

    Like a late night news-report, the reason might surprise you. To put it bluntly, humans aren’t all that special. Like mentioned above, we don’t have the biggest brain with the most neurons. Nor do we have the brain with the biggest surface area dolphins beat us there with their amazingly complex brain folds. We get a bit closer if we take body size into account, but we’d lose from a marmoset (a sort of small monkey which honestly isn’t all that bright). A new measure was developed called the ‘encephalisation quotient’ (EQ), which takes into account that the relationship between brain and body size isn’t linear. It’s a whole formula, but it gave us what we needed for our ego, we were on top! Based on our size we have a brain that is 7 times larger than it should be. Sounds great for us, but the measure failed a bit for other animals. The rhesus monkey should be smarter than a gorilla if we were to believe their EQ, which isn’t the case. That puts us back to square one.

    Humans don’t stand out that much in general, except when it comes to intelligence. Absolute brain size isn’t what makes us smart, neither is surface area, EQ, or neuron density. Then why is it that an elephant, with a huge brain and more neurons, isn’t as smart or even smarter than a human? This is where neuroscience and biology get a bit tricky, an example might help.

    Consider the fastest supercomputer in the world. At the time of writing, that is the Summit made by IBM. It has an impressive 9.216 CPUs, 27.648 GPUs and can make 200 quadrillion calculations per second. For comparison, it would take every person on earth working together, doing 1 calculation per second for almost a year to do what this machine can do in 1 second. It is set to model the universe, explore cancer, and figure out genetics on a scale we cannot imagine. But can it run Minecraft? No it cannot. Yet my old i7 quad-core laptop can run Minecraft just fine. Weird isn’t it, an immense computer with more memory and processing power than fits in my apartment can’t run a simple game that my rickety laptop can? So much for “super” computers.

    The truth is, the thing isn’t designed to run Minecraft. It’s made to run those complex astronomical and biological models, while my laptop is designed to run games and various other tasks useful to me. I’m sure with some fiddling you can get any game running on those systems, but you’d definitely get in trouble for that. When comparing brains, the absolute neuron count isn’t the only thing we need to look at. Just like absolute processing power isn’t the only thing you look for when you need to play Minecraft. What’s in a machine, how it’s connected, how it interfaces, all change depending on a computer’s purpose.

    Human brains and Elephant brain are different in more ways than one. Different parts have different concentrations of neurons for example. Despite having three times as many neurons, elephants only have a third as many neurons in their cerebral cortex. The cortex just so happens to be the part of the brain we associate with a lot of “higher cognitive functions” and intelligence. All those elephant brain cells are concentrated in other areas, like the cerebellum which is used for movements (that trunk does look very capable).

    The way the brain is put together is another factor. We estimate that Neanderthals had bigger brains than us they had the capacity for a 1600cm3 brain. When researchers recently grew some Neanderthal brain-matter, we saw that they were very different from our own. Human mini-brains were nice, smooth spheres, whereas Neanderthal brains were more like popcorn. The consequences are still not clear, but it does bring us to this point: brains are complicated. Brains aren’t homogenous masses of neurons and support cells. Brains have structure to them, neurons form columns and layers, have specific pathways to send and receive specific information. The way neurons are structured and connected affects what and how they process information. Different animals have different needs, different senses, and different bodies. Brains are formed to deal with all of that. An elephant needs to control its trunk to get food, not solve math problems to get good grades.

    As mentioned in the beginning, nature has an astounding diversity of life and brains. Those brains have been sculpted by evolution over millions of years, and evolution doesn’t care about intelligence as much as we do. Evolution is a process without goals instead it takes more of a “good enough” pendekatan. An organism has to function within its environment. For our elephant, an elephant brain is absolutely perfect for doing elephant things, it’s the pinnacle of elephantness.

    Humans had different survival tactics and evolutionary challenges. We didn’t have claws and weren’t very big and strong, instead we were smart and social. In evolutionary terms we bet everything on our brain, which is reflected by our cerebral cortex. Unlike other measurements, our cerebral cortex usually comes out on top compared to other animals. Even when compared to other primates, our cortex is astounding (more so in organization than size). It does require a lot of fuel, making it very reasonable to assume we beat other primates in the intelligence game because we started cooking. But that’s a story for another day.

    Intelligence is an elusive concept we don’t really know for sure what makes one species smarter than another. It’ll be a while before we have definitive answers, but we do know it has to do with a lot of factors. Brain size, number of neurons, number of connections, different structures, densities, how they are connected, they all play a role. No single measure can explain why some animals are smarter than others, let alone why some humans are smarter than others.

    An elephant is not as intelligent as a human, because an elephant brain is formed and wired to do elephant things. Just like a supercomputer isn’t made to play Minecraft, but rather focuses on simulating supernovae. Human brains do human things instead of elephant things in fact we make terrible elephants.

    It’s not the size of the brain that matters it’s how you use it.

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    Kandungan

    The roundworm Caenorhabditis elegans is a free-living, transparent nematode, about 1 mm in length, [6] that lives in temperate soil environments. It is the type species of its genus. [7]

    C. elegans has one of the simplest nervous systems of any organism, with its hermaphrodite type having only 302 neurons. Furthermore, the structural connectome of these neurons is fully worked out. There are fewer than one thousand cells in the whole body of a C. elegans worm, and because C. Elegans is a model organism, each has a unique identifier and comprehensive supporting literature. Being a model organism, the genome is fully known, along with many well characterized mutants readily available, a comprehensive literature of behavioural studies, etc. With so few neurons and new calcium 2 photon microscopy techniques it should soon be possible to record the complete neural activity of a living organism. By manipulating the neurons through optogenetic techniques, combined with the above recording capacities the project is in an unprecedented position to be able to fully characterize the neural dynamics of an entire organism.

    In the process of trying to build an "in silico" model of a relatively simple organism like C. elegans, new tools are being developed which will make it easier to model progressively more complex organisms.

    Although the ultimate goal is to simulate all features of C. elegans' behaviour, the project is new and the first behaviour the OpenWorm community decided to simulate is a simple motor response: teaching the worm to crawl. To do so, the virtual worm must be placed in a virtual environment. A full feedback loop must be established: Environmental Stimulus > Sensory Transduction > Interneuron Firing > Motor Neuron Firing > Motor Output > Environmental Change > Sensory Transduction.

    There are two main technical challenges here: modelling the neural/electrical properties of the brain as it processes the information, and modelling the mechanical properties of the body as it moves. The neural properties are being modeled by a Hodgkin-Huxley model, and the mechanical properties are being modeled by a Smoothed Particle Hydrodynamic algorithm.

    The OpenWorm team built an engine called Geppetto which could integrate these algorithms and due to its modularity will be able to model other biological systems (like digestion) which the team will tackle at a later time.

    The team also built an environment called NeuroConstruct which is able to output neural structures in NeuroML. Using NeuroConstruct the team reconstructed the full connectome of C. elegans.

    Using NeuroML the team has also built a model of a muscle cell. Note that these models currently only model the relevant properties for the simple motor response: the neural/electrical and the mechanical properties discussed above.

    The next step is to connect this muscle cell to the six neurons which synapse on it and approximate their effect.

    The rough plan is to then both:

    • Approximate the synapses which synapse on those neurons
    • Repeat the process for other muscle cells

    Progress Edit

    As of January 2015 [update] , the project is still awaiting peer review, and researchers involved in the project are reluctant to make bold claims about its current resemblance to biological behavior project coordinator Stephen Larson estimates that they are "only 20 to 30 percent of the way towards where we need to get". [8]

    In 1998 Japanese researchers announced the Perfect C. elegans Project. A proposal was submitted, but the project appears to have been abandoned. [9] [10]

    In 2004 a group from Hiroshima began the Virtual C. elegans Project. They released two papers which showed how their simulation would retract from virtual prodding. [11] [12]

    In 2005 a Texas researcher described a simplified C. elegans simulator based on a 1-wire network incorporating a digital Parallax Basic Stamp processor, sensory inputs and motor outputs. Inputs employed 16-bit A/D converters attached to operational amplifier simulated neurons and a 1-wire temperature sensor. Motor outputs were controlled by 256-position digital potentiometers and 8-bit digital ports. Artificial muscle action was based on Nitinol actuators. It used a "sense-process-react" operating loop which recreated several instinctual behaviors. [13]

    These early attempts of simulation have been criticized for not being biologically realistic. Although we have the complete structural connectome, we do not know the synaptic weights at each of the known synapses. We do not even know whether the synapses are inhibitory or excitatory. To compensate for this the Hiroshima group used machine learning to find some weights of the synapses which would generate the desired behaviour. It is therefore no surprise that the model displayed the behaviour, and it may not represent true understanding of the system.

    The Open Worm community is committed to the ideals of open science. Generally this means that the team will try to publish in open access journals and include all data gathered (to avoid the file drawer problem). Indeed, all the biological data the team has gathered is publicly available, and the five publications the group has made so far are available for free on their website. All the software that OpenWorm has produced is completely free and open source.

    Open Worm is also trying a radically open model of scientific collaboration. The team consists of anyone who wishes to be a part of it. There are over one hundred "members" who are signed up for the high volume technical mailing list. Of the most active members who are named on a publication there are collaborators from Russia, Brazil, England, Scotland, Ireland and the United States. To coordinate this international effort, the team uses "virtual lab meetings" and other online tools that are detailed in the resources section.


    The Secret To Chimp Strength

    February's brutal chimpanzee attack, during which a pet chimp inflicted devastating injuries on a Connecticut woman, was a stark reminder that chimps are much stronger than humans&mdashas much as four-times stronger, some researchers believe. But what is it that makes our closest primate cousins so much stronger than we are? One possible explanation is that great apes simply have more powerful muscles.

    Indeed, biologists have uncovered differences in muscle architecture between chimpanzees and humans. But evolutionary biologist Alan Walker, a professor at Penn State University, thinks muscles may only be part of the story.

    In an article published in the April issue of Current Anthropology, Walker argues that humans may lack the strength of chimps because our nervous systems exert more control over our muscles. Our fine motor control prevents great feats of strength, but allows us to perform delicate and uniquely human tasks.

    Walker's hypothesis stems partly from a finding by primatologist Ann MacLarnon. MacLarnon showed that, relative to body mass, chimps have much less grey matter in their spinal cords than humans have. Spinal grey matter contains large numbers of motor neurons&mdashnerves cells that connect to muscle fibers and regulate muscle movement.

    More grey matter in humans means more motor neurons, Walker proposes. And having more motor neurons means more muscle control.

    Our surplus motor neurons allow us to engage smaller portions of our muscles at any given time. We can engage just a few muscle fibers for delicate tasks like threading a needle, and progressively more for tasks that require more force. Conversely, since chimps have fewer motor neurons, each neuron triggers a higher number of muscle fibers. So using a muscle becomes more of an all-or-nothing proposition for chimps. As a result, chimps often end up using more muscle than they need.

    "[A]nd that is the reason apes seem so strong relative to humans," Walker writes.

    Our finely-tuned motor system makes a wide variety of human tasks possible. Without it we couldn't manipulate small objects, make complex tools or throw accurately. And because we can conserve energy by using muscle gradually, we have more physical endurance&mdashmaking us great distance runners.

    Great apes, with their all-or-nothing muscle usage, are explosive sprinters, climbers and fighters, but not nearly as good at complex motor tasks. In other words, chimps make lousy guests in china shops.

    In addition to fine motor control, Walker suspects that humans also may have a neural limit to how much muscle we use at one time. Only under very rare circumstances are these limits bypassed&mdashas in the anecdotal reports of people able to lift cars to free trapped crash victims.

    "Add to this the effect of severe electric shock, where people are often thrown violently by their own extreme muscle contraction, and it is clear that we do not contract all our muscle fibers at once," Walker writes. "So there might be a degree of cerebral inhibition in people that prevents them from damaging their muscular system that is not present, or not present to the same degree, in great apes."

    Walker says that testing his hypothesis that humans have more motor neurons would be fairly straightforward. However, he concedes that testing whether humans have increased muscle inhibition could be a bit more problematic.


    The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now?

    Cognitive abilities, brain size and number of neurons

    To conclude that the human brain is a linearly scaled-up primate brain, with just the expected number of neurons for a primate brain of its size, is not to state that it is unremarkable in its capabilities. However, as studies on the cognitive abilities of non-human primates and other large-brained animals progress, it becomes increasingly likely that humans do not have truly unique cognitive abilities, and hence must differ from these animals not qualitatively, but rather in the combination and extent of abilities such as theory of mind, imitation and social cognition (Marino et al., 2009). Quantitative changes in the neuronal composition of the brain could therefore be a main driving force that, through the exponential combination of processing units, and therefore of computational abilities, leads to events that may look like “jumps” in the evolution of brains and intelligence (Roth and Dicke, 2005). Such quantitative changes are likely to be warranted by increases in the absolute (rather than relative) numbers of neurons in relevant cortical areas and, coordinately, in the cerebellar circuits that interact with them (Ramnani, 2006). Moreover, viewing the human brain as a linearly scaled-up primate brain in its cellular composition does not diminish the role that particular neuroanatomical arrangements, such as changes in the relative size of functional cortical areas (for instance, Semendeferi et al., 2001 Rilling and Seligman, 2002), in the volume of prefrontal white matter (Schoenemann et al., 2005) or in the size of specific portions of the cerebellum (Ramnani, 2006) may play in human cognition. Rather, such arrangements should contribute to brain function in combination with the large number of neurons in the human brain. Our analysis of numbers of neurons has so far been restricted to large brain divisions, such as the entire cerebral cortex and the ensemble of brainstem, diencephalon and basal ganglia, but an analysis of the cellular scaling of separate functional cortical areas and the related subcortical structures is underway. Such data should allow us to address important issues such as mosaic evolution through concerted changes in the functionally related components of distributed systems, and the presumed increase in relative number of neurons in systems that increase in importance (Barton and Harvey, 2000 Barton, 2006).

    If cognitive abilities among non-human primates scale with absolute brain size (Deaner et al., 2007) and brain size scales linearly across primates with its number of neurons (Herculano-Houzel et al., 2007), it is tempting to infer that the cognitive abilities of a primate, and of other mammals for that matter, are directly related to the number of neurons in its brain. In this sense, it is interesting to realize that, if the same linear scaling rules are considered to apply to great apes as to other primates, then similar three-fold differences in brain size and in brain neurons alike apply to humans compared to gorillas, and to gorillas compared to baboons. This, however, is not to say that any cognitive advantages that the human brain may have over the gorilla and that the gorilla may have over the baboon are equally three-fold – although these differences are difficult to quantify. Since neurons interact combinatorially through the synapses they establish with one another, and further so as they interact in networks, the increase in cognitive abilities afforded by increasing the number of neurons in the brain can be expected to increase exponentially with absolute number of neurons, and might even be subject to a thresholding effect once critical points of information processing are reached. In this way, the effects of a three-fold increase in numbers of neurons may be much more remarkable when comparing already large brains, such as those of humans and gorillas, than when comparing small brains, such as those of squirrel monkeys and galagos.

    Intraspecific variability in size, numbers and abilities

    One final caveat to keep in mind when studying scaling of numbers of brain neurons, particularly in regard to cognition, is that relationships observed across species need not apply to comparisons across individuals of the same species. Not only the extent of intraspecific variation is much smaller (on the order of 10�%) than interspecific variation (which spans five orders of magnitude within mammals Tower, 1954 Stolzenburg et al., 1989), but also the mechanisms underlying interspecific and intraspecific variation are also likely to differ. Our own preliminary data suggest that, indeed, variations in brain size across rats of the same age are not correlated with variations in numbers of neurons (Morterá and Herculano-Houzel, unpublished observations). There is no justification, therefore, to extend the linear correlation between brain size and number of neurons across primates to a putative correlation across persons of different brain sizes (which might be used, inappropriately, as grounds for claims that larger-brained individuals have more neurons, and are therefore “smarter”, than smaller-brained persons). In fact, although men have been reported to have more neurons in the cerebral cortex than women (Pakkenberg and Gundersen, 1997 Pelvig et al., 2008), there is no significant correlation between brain size and general cognitive ability within families (Schoenemann et al., 2000). Across these individuals, other factors such as variations in number and identity of synaptic connections within and across structures, building on a statistically normal, albeit variable, number of neurons, and depending on genetics and life experiences such as learning, are more likely to be determinant of the individual cognitive abilities (see, for instance, Mollgaard et al., 1971 Black et al., 1990 Irwin et al., 2000 Draganski et al., 2004).

    Concluding remarks: our place in nature

    Novel quantitative data on the cellular composition of the human brain and its comparison to other primate brains strongly indicate that we need to rethink our notions about the place that the human brain holds in nature and evolution, and rewrite some of the basic concepts that are taught in textbooks. Accumulating evidence (Deacon, 1997 Roth and Dicke, 2005 Deaner et al., 2007) indicates that an alternative view of the source of variations in cognitive abilities across species merits investigation: one that disregards body and brain size and examines absolute numbers of neurons as a more relevant parameter instead. Now that these numbers can be determined in various brains and their structures, direct comparisons can be made across species and orders, with no assumptions about body𠄻rain size relationships required. Complementarily, however, it now becomes possible to examine how numbers of neurons in the brain, rather than brain size, relate to body mass and surface as well as metabolism, parameters that have been considered relevant in comparative studies (Martin, 1981 Fox and Wilczynski, 1986 MacLarnon, 1996 Schoenemann, 2004), in order to establish what mechanisms underlie the loosely correlated scaling of body and brain.

    According to this now possible neuron-centered view, rather than to the body-centered view that dominates the literature (see Gazzaniga, 2008, for a comprehensive review), the human brain has the number of neurons that is expected of a primate brain of its size a cerebral cortex that is exactly as large as expected for a primate brain of 1.5 kg just as many neurons as expected in the cerebral cortex for the size of this structure and, despite having a relatively large cerebral cortex (which, however, a rodent brain of 1.5 kg would also be predicted to have), this enlarged cortex holds just the same proportion of brain neurons in humans as do other primate cortices (and rodent cortices, for that matter). This final observation calls for a reappraisal of the view of brain evolution that concentrates on the expansion of the cerebral cortex, and its replacement with a more integrated view of coordinate evolution of cellular composition, neuroanatomical structure, and function of cerebral cortex and cerebellum (Whiting and Barton, 2003).

    Other �ts” that deserve updating are the ubiquitous quote of 100 billion neurons (a value that lies outside of the margin of variation found so far in human brains Azevedo et al., 2009), and, more strikingly, the widespread remark that there are 10× more glial cells than neurons in the human brain. As we have shown, glial cells in the human brain are at most 50% of all brain cells, which is an important finding since it is one more brain characteristic that we share with other primates (Azevedo et al., 2009).

    Finally, if being considered the bearer of a linearly scaled-up primate brain does not sound worthy enough for the animal that considers himself the most cognitively able on Earth, one can note that there are, indeed, two advantages to the human brain when compared to others – even if it is not an outlier, nor unique in any remarkable way. First, the human brain scales as a primate brain: this economical property of scaling alone, compared to rodents, assures that the human brain has many more neurons than would fit into a rodent brain of similar size, and possibly into any other similar-sized brain. And second, our standing among primates as the proud owners of the largest living brain assures that, at least among primates, we enjoy the largest number of neurons from which to derive cognition and behavior as a whole. It will now be interesting to determine whether humans, indeed, have the largest number of neurons in the brain among mammals as a whole.