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  • Why is there a citations gender gap in Indian materials science?

    Why is there a citations gender gap in Indian materials science?

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    Shobhana Narasimhan talks into a mic while seated on stage

    Shobhana Narasimhan gives a talk in Bengaluru on the topic of women in science.Credit: CreativeMornings Bengaluru

    The global impact of India’s materials-science research is on the rise, with Nature Index data showing it has risen six places in the country ranking since 2019. But separate data from publisher Elsevier point to a more worrying problem: that papers authored by men in India have a greater citation impact than those written by women. And the gap is getting bigger. Elsevier’s data used a metric called field-weighted citation impact (FWCI), which compares citations received by individuals or groups with the average from similar papers in the field. In 2022, male materials scientists based in India had a 10% higher FWCI than women working in the country.

    The gender gap is not so pronounced within other fields; in the agricultural and biological sciences, for example, the FWCI of men is just 2.66% higher than that of women.

    According to computational nanoscientist, Shobhana Narasimhan, who chairs the Indian Academy of Science’s Women in Science Initiative, many factors are behind the gender impact gap and the separate, but related, issue of women continuing to be greatly outnumbered by males in the field.

    Why does materials science in particular seem to have a problem?

    I don’t have a simple answer. In India, we have quite a high percentage of women up to the PhD level, followed by a huge drop: almost half of science PhD students are women, yet they make up fewer than 20% of working scientists.

    Nature Index 2024 Materials science

    I couldn’t find specific statistics for materials science in India, so I just went to the web pages of about 14 university departments and counted the number of women who are on staff. What I saw was that 11.5% of the scientists are women. It ranged from departments with no women to one where 25% were women. It shows that there is still an uphill battle.

    Is there a link between women’s representation and their impact scores?

    I don’t get the impression that people in India have a perception that women are intellectually inferior, but there is a very strong belief of what women’s societal roles should be, and that they really should be wives and mothers first and then scientists second.

    This attitude makes it harder for women to get into prominent organizations, and research has shown it’s easier to publish your manuscripts if you work at prestigious institutions. The plum jobs go to men; it’s harder for women to break into the top-notch research groups and access their resources. One prestigious Indian institution tracked which of their applicants for academic jobs had been shortlisted and asked to give a ‘job talk’ presentation of their work and they found that between 15% and 20% of men had received such a request, compared with just 3% to 5% of women. This shows how that as a woman it’s harder to make a name for yourself and get ahead in the field.

    What needs to change to redress the balance?

    I’ve been asked this same question many times by people in the field. I usually say we need to change the perception that a good scientist is working 24/7. This viewpoint is common in India, and it hurts women because there are so many other societal expectations of us. It’s perfectly possible to work eight hours a day and do excellent science.

    Do you find men are engaged in this question and search for solutions?

    When you talk to them, they’ll often agree that it’s very bad. Some of them will say ‘you women should do something about it’. I tell them it’s not just up to women, and ask why they don’t do something about it, and they look at me in horror. It’s just unthinkable for many men to do something and that irritates me. What’s even worse is if I make a suggestion to a man in power, sometimes they say things like ‘you women don’t know how to help yourselves’. That’s offensive and patronizing. The response is too often ‘it’s your problem’, followed by them saying they know better when we try to improve things.

    Are you optimistic for future generations of women?

    Attitudes are not changing as fast as they should. You can say that we just have to wait for the dinosaurs to retire, but that’s not necessarily true. There are, however, reasons to hope that things will improve. In the science prizes that the government gives out, it now explicitly says in the criteria that gender can be considered, which was unthinkable not long ago. They have also included specific chapters on equity and inclusion in policy documents.

    I would like to suggest that in addition to announcing and rolling out initiatives to help women in science, the government could later check to see how well the programmes are working and to see what we can learn from what works and what doesn’t.

    I just wish that there were better statistics and more data. The kinds of questions that you’re asking are very important and it would be nice to have more validated answers to them, because a lot of what I’m saying is either speculation or anecdotal. It would be nice if there were detailed studies.

    This interview has been edited for length and clarity.

    This article is part of Nature Index 2024 Materials science, an editorially independent supplement. Advertisers have no influence over the content. For more information about Nature Index, see the homepage.

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  • Native DGC structure rationalizes muscular dystrophy-causing mutations

    Native DGC structure rationalizes muscular dystrophy-causing mutations

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  • Targeted mRNA therapy tackles deadly pregnancy condition in mice

    Targeted mRNA therapy tackles deadly pregnancy condition in mice

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    Download the Nature Podcast 11 December 2024

    In this episode:

    00:45 A potential treatment for pre-eclampsia

    Researchers have shown in mice experiments that an mRNA-based therapy can reverse the underlying causes of pre-eclampsia, a deadly complication of pregnancy for which treatment options are limited. Inspired by the success of mRNA vaccines, the team behind the work designed a method to deliver the genomic instructions for a blood-vessel growth factor directly into mouse placentas. This stimulated the production of extra blood vessels reducing the very high-blood pressure associated with the condition. Pre-eclampsia causes 15% of maternal deaths and 25% of foetal and newborn deaths worldwide and although the work is early and human trials will be required, the team hope that this work demonstrates the potential of using this approach to treat pre-eclampsia.

    Research Article: Swingle et al.

    News and Views: Lipid-delivery system could treat life-threatening pregnancy complication

    11:00 Research Highlights

    Stacks of mass-produced bowls suggest that people founded but then abandoned an ancient Mesopotamian civilization, and analysis of Venus’s gases suggests that the planet was always dry.

    Research Highlight: Ancient stacks of dishes tell tale of society’s dissolution

    Research Highlight: Has Venus ever had an ocean? Its volcanoes hint at an answer

    13:29 Programmable cellular switches

    A team of scientists have created cellular switches on the surface of cells, allowing them to control custom behaviours. Creating these switches has been a long-term goal for synthetic biologists — one target has been a group of proteins called G-protein-coupled receptors that already control many cellular processes. However, engineering these proteins has been challenging, as modifications can ruin their function. Instead, the team added another molecular component that blocked the receptors activity, but could be removed in response to specific signals. This allowed the researchers to activate these receptors on command, potentially opening up a myriad of new ways to control cell behaviour, such as controlling when neurons fire.

    Research Article: Kalogriopoulos et al.

    19:35 Google reaches a milestone in quantum computing

    A team at Google has shown it is possible to create a quantum computer that becomes more accurate as it scales up, a goal researchers have been trying to achieve for decades. Quantum computing could potentially open up applications beyond the capabilities of classical computers, but these systems are error-prone, making it difficult to scale them up without introducing errors into calculations. The team showed that by increasing the quality of all the components in a quantum computer they could create a system with fewer errors, and that this trend of improvement continued as the system became larger. This breakthrough could mean that quantum computers are getting very close to realising the useful applications that their proponents have long promised.

    Nature: ‘A truly remarkable breakthrough’: Google’s new quantum chip achieves accuracy milestone

    Subscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.

    Never miss an episode. Subscribe to the Nature Podcast on Apple Podcasts, Spotify, YouTube Music or your favourite podcast app. An RSS feed for the Nature Podcast is available too.

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  • Nanoscale imaging and control of altermagnetism in MnTe

    Nanoscale imaging and control of altermagnetism in MnTe

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    Our vector mapping includes the local real-space detection of the orientation of the altermagnetic order vector, L = M1 − M2, with respect to the MnTe crystal axes in the (0001)-plane by X-ray magnetic linear dichroism (XMLD)-PEEM, and of the sign of L for a given crystal orientation by including X-ray magnetic circular dichroism (XMCD)-PEEM. In antiferromagnets with opposite spin sublattices connected by translation or inversion, the \({\mathcal{T}}\)-odd XMCD is excluded by symmetry. In such cases, only the L axis can be detected by the \({\mathcal{T}}\)-even XMLD-PEEM, but the sign of L remains unresolved25,26,27,28,29,30. Contrary to this, the recent theoretical and experimental spectroscopic study of altermagnetic MnTe has demonstrated the presence of a sizable XMCD, reflecting the \({\mathcal{T}}\)-symmetry breaking in the electronic structure by the altermagnetic g-wave spin polarization12. Furthermore, the XMCD spectral shape owing to L pointing in the (0001) plane is qualitatively distinct from the XMCD spectral shape owing to a net magnetization M = M1 + M2 along the [0001] axis12. This was demonstrated in ref. 12 by comparing the measured XMCD spectral shapes at a zero magnetic field and at a 6-T field applied along the [0001] axis. In the former case, M is weak and the measured spectral shape agrees with the predicted spectral shape due to L. In the latter case, M is sizable and qualitatively modifies the spectral shape, again in agreement with theory. We performed normal incidence X-ray PEEM, which is the optimum geometry for measuring both the in-plane Néel axis in the XMLD, and the altermagnetic XMCD. Images are taken at zero external field, where the XMCD signal owing to the weak relativistic remnant M is negligible compared with the altermagnetic XMCD owing to \({\bf{L}}\parallel \langle 1\bar{1}00\rangle \) directions in the (0001) plane12. The latter gives rise to our measured XMCD-PEEM contrast as confirmed by its spectral dependence (Methods and Extended Data Fig. 1). In analogy to the d.c. anomalous Hall effect, the XMCD can be described by the Hall vector, \({\bf{h}}=({\sigma }_{zy}^{a},{\sigma }_{xz}^{a},{\sigma }_{yx}^{a})\), where σij = −σji are the antisymmetric components of the frequency-dependent conductivity tensor. For L in the (0001) plane of MnTe, h points along the [0001] axis, that is, \({\sigma }_{zy}^{a}={\sigma }_{xz}^{a}=0\) and \({\sigma }_{yx}^{a}\ne 0\), with the exception of \({\bf{L}}\parallel \langle 2\bar{1}\bar{1}0\rangle \) axes where \({\sigma }_{yx}^{a}=0\) by symmetry.

    The method of combining the XMCD-PEEM and XMLD-PEEM images into the vector map of L is illustrated in Fig. 1b. As the L vector subtends the angle, ϕ, in the MnTe (0001) plane relative to the \([1\bar{1}00]\) axis, the XMCD is proportional to cos(3ϕ), with maximum magnitude for \({\bf{L}}\parallel \langle 1\bar{1}00\rangle \) -axes and vanishing for \({\bf{L}}\parallel \langle 2\bar{1}\bar{1}0\rangle \) axes12. An XMCD-PEEM image of a 25–μm2 unpatterned area of MnTe is shown in Fig. 1c, where positive and negative XMCD appear as light and dark contrast, respectively. The corresponding three-colour XMLD-PEEM map, shown in Fig. 1d, was obtained from a set of PEEM images taken with the X-ray linear polarization rotated, within the MnTe (0001) plane, in 10° steps from −90° to +90° relative to the horizontal [\(1\bar{1}00\)] axis. In this image, the local L-vector axis is distinguished (by red–green–blue colours), but the absolute direction remains unresolved. This information is included by combining the XMCD-PEEM and XMLD-PEEM in a six-colour vector map, shown in Fig. 1e,f, where positive XMCD regions change the colour (red–green–blue to orange–yellow–purple) of the XMLD-PEEM map and negative XMCD regions leave it unchanged. The Mn L2,3 X-ray absorption and altermagnetic XMCD spectra are shown in Fig. 1g. The XMCD-PEEM images are obtained at fixed energy corresponding to the peak in the altermagnetic XMCD at the L2 edge. The XMCD contrast reverses between positive and negative peaks of the XMCD spectrum, as shown in Extended Data Fig. 1, and vanishes at elevated temperatures where the spontaneous anomalous Hall effect is absent, as shown in Extended Data Fig. 2.

    The characteristic vector mapping of L in our unpatterned MnTe film, shown in Fig. 1e,f, shows a rich landscape of (meta)stable textures akin to earlier reports in compensated magnets26,27,28,29,30. There exist 60° and 120° domain walls separating domains with L aligned along the different easy axes, as well as vortex-like textures. Highlighted in Fig. 1f is an example of an altermagnetic vortex–antivortex pair, analogous to magnetic textures previously detected in antiferromagnets such as CuMnAs (ref. 30). However, only the XMLD-PEEM was available in the antiferromagnet30, that is, only the spatially varying Néel-vector axis could be identified, similar to our XMLD-PEEM image in Fig. 1d. In our altermagnetic case, we can add the information from the measured XMCD-PEEM (Fig. 1c). This allows us to plot the vector map of L, as shown in Fig. 1e,f. We directly experimentally determine that the L vector makes a clockwise rotation by 360° around the first vortex nanotexture, indicated by the magenta–white circle, whereas the other nanotexture is an antivortex with an opposite winding of the L vector, indicated by the cyan–white circle.

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  • Placenta-tropic VEGF mRNA lipid nanoparticles ameliorate murine pre-eclampsia

    Placenta-tropic VEGF mRNA lipid nanoparticles ameliorate murine pre-eclampsia

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  • π-HuB: the proteomic navigator of the human body

    π-HuB: the proteomic navigator of the human body

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  • State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China

    Fuchu He, Cheng Chang, Ying Jiang, Yang Li, Aihua Sun, Liujun Tang, Chanjuan Wang, Xiaowen Wang, Yan Wang, Linhai Xie, Xiao Yang, Lingqiang Zhang, Yunping Zhu, Chenxi Jia, Chaoying Li, Dong Li, Yanchang Li, Zhongyang Liu, Jian Wang, Ping Xu, Wantao Ying & Xiaobo Yu

  • International Academy of Phronesis Medicine (Guangdong), Guangdong, China

    Fuchu He, Yuezhong He, Tianhao Xu & Yu Zi Zheng

  • Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland

    Ruedi Aebersold

  • Macquarie Medical School, Macquarie University, Sydney, New South Wales, Australia

    Mark S. Baker

  • Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing, China

    Xiuwu Bian

  • Institute of Health Service and Transfusion Medicine, Beijing, China

    Xiaochen Bo

  • Department of Pathology and The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA

    Daniel W. Chan & Daniel W. Chan

  • Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China

    Luonan Chen

  • Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People’s Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, China

    Xiangmei Chen

  • Institute of Chemistry, Academia Sinica, Taipei, China

    Yu-Ju Chen

  • National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, College of Future Technology, Peking University, Beijing, China

    Heping Cheng

  • School of Biological Sciences, Queen’s University of Belfast, Belfast, UK

    Ben C. Collins

  • Functional Proteomics Laboratory, Centro Nacional de Biotecnología-CSIC, Madrid, Spain

    Fernando Corrales

  • Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany

    Jürgen Cox

  • AI for Science Institute, Beijing, China

    Weinan E & Weinan E

  • Center for Machine Learning Research, Peking University, Beijing, China

    Weinan E & Weinan E

  • Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA

    Jennifer E. Van Eyk & Jennifer E. Van Eyk

  • Department of Liver Surgery and Transplantation, Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China

    Jia Fan & Qiang Gao

  • Centre for Cancer Research, Hudson Institute of Medical Research, Clayton, Victoria, Australia

    Pouya Faridi

  • Monash Proteomics and Metabolomics Platform, Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia

    Pouya Faridi

  • School of Pharmaceutical Sciences and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada

    Daniel Figeys

  • The D. H. Chen School of Universal Health, Zhejiang University, Hangzhou, China

    George Fu Gao

  • Pengcheng Laboratory, Shenzhen, China

    Wen Gao

  • School of Electronic Engineering and Computer Science, Peking University, Beijing, China

    Wen Gao

  • Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada

    Zu-Hua Gao & Yu Zi Zheng

  • Department of Chemistry, University of Tokyo, Tokyo, Japan

    Keisuke Goda

  • Department of Bioengineering, University of California, Los Angeles, California, USA

    Keisuke Goda

  • Institute of Technological Sciences, Wuhan University, Wuhan, Hubei, China

    Keisuke Goda

  • Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    Wilson Wen Bin Goh

  • School of Medicine, Southern University of Science and Technology, Shenzhen, China

    Dongfeng Gu

  • Department of Nutrition, Tianjin Institute of Environmental and Operational Medicine, Tianjin, China

    Changjiang Guo & Xinxing Wang

  • School of Medicine, Westlake University, Hangzhou, China

    Tiannan Guo & Yi Zhu

  • Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China

    Tiannan Guo & Yi Zhu

  • Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou, China

    Tiannan Guo & Yi Zhu

  • Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, the Netherlands

    Albert J. R. Heck

  • Netherlands Proteomics Center, Utrecht, the Netherlands

    Albert J. R. Heck

  • European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK

    Henning Hermjakob & Juan Antonio Vizcaíno

  • Molecular and Cell Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA

    Tony Hunter

  • Department of Head & Neck Surgery, Division of Surgery & Surgical Oncology, Division of Medical Sciences, National Cancer Centre Singapore, Singapore, Singapore

    Narayanan Gopalakrishna Iyer

  • OncoProteomics Laboratory, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands

    Connie R. Jimenez

  • Advanced Glycoscience Research Cluster, School of Biological and Chemical Sciences, University of Galway, Galway, Ireland

    Lokesh Joshi

  • Departments of Molecular Biosciences, Departments of Chemistry, Northwestern University, Evanston, IL, USA

    Neil L. Kelleher

  • David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

    Ming Li

  • Central China Institute of Artificial Intelligence, Henan, China

    Ming Li

  • Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore

    Qingsong Lin

  • CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China

    Cui Hua Liu

  • Department of Structural Biology, Leibniz-Forschungsinstitut für MolekularePharmakologie (FMP), Berlin, Germany

    Fan Liu

  • State Key Laboratory of Membrane Biology, Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    Guang-Hui Liu

  • Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, USA

    Yansheng Liu

  • State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Zhihua Liu

  • UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia

    Teck Yew Low

  • Department of Critical Care Medicine and Hematology, The Third Xiangya Hospital, Central South University; Department of Hematology and Critical Care Medicine, The Third Xiangya Hospital, Central South University, Changsha, China

    Ben Lu

  • Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany

    Matthias Mann

  • School of Life Sciences, Tsinghua University, Tsinghua-Peking Center for Life Sciences, Beijing, China

    Anming Meng & Wei Xie

  • Institute for Systems Biology, Seattle, WA, USA

    Robert L. Moritz

  • Clinical Biomarker Discovery and Validation, Monash University, Clayton, Victoria, Australia

    Edouard Nice

  • Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Guang Ning

  • Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai, China

    Guang Ning

  • Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Guang Ning

  • Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    Gilbert S. Omenn

  • Department of Oral Biological and Medical Sciences, University of British Columbia, Vancouver, British Columbia, Canada

    Christopher M. Overall

  • Yonsei Frontier Lab, Yonsei University, Seoul, Republic of Korea

    Christopher M. Overall

  • Glycoproteomics Laboratory, Department of Parasitology, University of São Paulo, Sao Paulo, Brazil

    Giuseppe Palmisano

  • Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    Yaojin Peng

  • Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China

    Yaojin Peng

  • University of the Chinese Academy of Sciences, Beijing, China

    Yaojin Peng

  • Institut de Recherche en Santé Environnement et Travail, Univ. Rennes, Inserm, EHESP, Irset, Rennes, France

    Charles Pineau

  • Pilot Laboratory, MOE Frontier Science Centre for Precision Oncology, Centre for Precision Medicine Research and Training, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China

    Terence Chuen Wai Poon

  • Infection and Immunity Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Anthony W. Purcell

  • State Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

    Jie Qiao & Liying Yan

  • ProCan®, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia

    Roger R. Reddel, Phillip J. Robinson & Qing Zhong

  • Department of Health Sciences, University Magna Græcia of Catanzaro, Catanzaro, Italy

    Paola Roncada

  • Department of Systems Biology, Harvard Medical School, Boston, MA, USA

    Chris Sander

  • Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Chris Sander

  • State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China

    Jiahao Sha & Xuejiang Guo

  • Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Erwei Song & Shicheng Su

  • Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Erwei Song & Shicheng Su

  • Indian Institute of Technology Bombay, Mumbai, India

    Sanjeeva Srivastava

  • Department of Health Sciences, Faculty of Applied Health Sciences, Brock University, St. Catharines, Ontario, Canada

    Siu Kwan Sze

  • Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China

    Chao Tang

  • Department of Chemistry, Southern University of Science and Technology, Shenzhen, China

    Ruijun Tian & Chris Soon Heng Tan

  • State Key Laboratory of Respiratory Health and Multimorbidity, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China

    Chen Wang, Yushun Gao, Jie He & Catherine C. L. Wong

  • Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Clinical Research Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China

    Chen Wang

  • Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland

    Tobias Weiss

  • Technical University of Munich, Freising, Germany

    Mathias Wilhelm & Bernhard Kuster

  • Advanced Genomics Unit, Center for Research and Advanced Studies, Irapuato, Mexico

    Robert Winkler

  • Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland

    Bernd Wollscheid

  • Department of Computer Science, National University of Singapore, Singapore, Singapore

    Limsoon Wong

  • Department of Pathology, National University of Singapore, Singapore, Singapore

    Limsoon Wong

  • Guangzhou National Laboratory, Guangzhou, China

    Tao Xu, Jing Yang & Nan-Shan Zhong

  • School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China

    Tao Xu & Tao Xu

  • The Scripps Research Institute, La Jolla, CA, USA

    John Yates

  • China Science and Technology Exchange Center, Beijing, China

    Tao Yun

  • CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China

    Qiwei Zhai

  • Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA

    Bing Zhang

  • Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA

    Bing Zhang

  • Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Hui Zhang

  • State Key Laboratory of Medical Proteomics, National Chromatography R. & A. Center, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China

    Lihua Zhang, Yukui Zhang, Hongqiang Qin & Mingliang Ye

  • School of Mathematical Sciences, Peking University, Beijing, China

    Pingwen Zhang

  • Wuhan University, Wuhan, China

    Pingwen Zhang

  • Institutes of Biomedical Sciences, Fudan University, Shanghai, China

    Mingxia Gao, Haojie Lu, Liming Wei, Ying Zhang & Feng Zhou

  • Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China

    Jun He & Xiaofei Zhang

  • College of Life Science and Technology, Jinan University, Guangzhou, China

    Qing-Yu He & Tong Wang

  • Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China

    Jinlin Hou

  • State Key Laboratory of Biotherapy, West China Hospital, and West China School of Basic Sciences & Forensic Medicine, Sichuan University, Chengdu, China

    Canhua Huang

  • Peking University Cancer Hospital & Institute, Beijing, China

    Yan Li, Lin Shen & Qimin Zhan

  • BGI Group, Shenzhen, China

    Siqi Liu, Yan Ren & Huanming Yang

  • Xijing Hospital, Fourth Military Medical University, Xi’an, China

    Xiaonan Liu, Ya Liu, Yongzhan Nie & Jianjun Yang

  • Institute for Protein Research, Osaka University, Osaka, Japan

    Mariko Okada

  • Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Naval Medical University), Shanghai, China

    Guojun Qian & Feng Shen

  • School of Pharmaceutical Sciences, Tsinghua University, Beijing, China

    Yu Rao

  • School of Medicine, Tsinghua University, Beijing, China

    Zihe Rao

  • Changping Laboratory, Beijing, China

    Xianwen Ren, Xiaoliang Sunney Xie & Zemin Zhang

  • Experiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai, China

    Yan Ren

  • State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China

    Minjia Tan

  • School of Science and Engineering, Shenzhen Institute of Aggregate Science and Technology, The Chinese University of Hong Kong, Shenzhen, China

    Ben Zhong Tang

  • Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China

    Sheng-Ce Tao

  • Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China

    Xiaoliang Sunney Xie & Zemin Zhang

  • Department of Liver Surgery, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

    Li Xu

  • Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

    Yaxiang Yuan

  • Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Qingcun Zeng

  • Peking University International Cancer Institute, Beijing, China

    Qimin Zhan

  • Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing, China

    Xu Zhang

  • State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China

    Nan-Shan Zhong

    • F.H. conceived the concept of π-HuB and designed its scientific goals, and contributed ideas for phronesis medicine with L.X., F.H., R.A., M.S.B., X.W.B., X.C.B., D.W.C., C.C., L.C., X.C., H.C., F.C., W.E., J.F., P.F., D.F., G.F.G., W.G., Z.-H.G., K.G., W.W.B.G., D.G., C.G., T.G., A.J.R.H., H.H., T.H., N.G.I., Y.J., C.R.J., L.J., N.L.K., M.L., Y.L., Q.L., C.H.L., F.L., G.-H.L., Y.S.L., Z.L., T.Y.L., B.L., M.M., A.M., R.L.M., E.N., G.N., G.S.O., G.P., Y.P., C.P., T.C.W.P., A.P., J.Q., R.R., P.J.R., P.R., C.S., J.S., E.S., S.S., A.S., S.K.S., C.T., L.T., R.T., J.V.E., J.A.V., C.W., X.W.W., X.X.W., Y.W., T.W., M.W., R.W., B.W., L.W., L.X., W.X., Tao Xu, L.Y., J.Y., X.Y., J.R.Y., Q.W.Z., L.H.Z., L.Q.Z., Y.K.Z., Q.Z. and Y.P.Z. contributed ideas and suggestions for the conception and design of this project. T.G., L.T. and Y.W. contributed coordination of the π-HuB Consortium. J.Y. wrote the first draft of the manuscript, and created the figures with F.H., T.G., Y.L. and L.X. F.H., R.A., M.S.B., F.C., P.F., D.F., Z.-H.G., K.G., W.W.B.G., T.G., H.H., T.H., N.G.I., C.R.J., L.J., M.L., Q.L., F.L., Y.S.L., T.Y.L., R.L.M., G.S.O., T.C.W.P., A.P., R.R., P.J.R., C.S., S.K.S., J.A.V., T.W., R.W., B.W., L.W., J.Y., J.R.Y. and Q.Z. provided important edits to the manuscript. All authors contributed to review and editing of the manuscript. The π-HuB Consortium contributed to the discussion of strategic π-HuB research plans.

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  • Lithium extraction from low-quality brines

    Lithium extraction from low-quality brines

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