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About the Authors: Emily D. Crawford Affiliations Chan Zuckerberg Biohub, San Francisco, California, United States of America, University of California San Francisco, Department of Microbiology and Immunology, San Francisco, California, United States of America Irene Acosta Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Vida Ahyong Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Erika C. Anderson Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Shaun Arevalo Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Daniel Asarnow Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Shannon Axelrod Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Patrick Ayscue Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Camillia S. Azimi Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Caleigh M. Azumaya Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Stefanie Bachl Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Iris Bachmutsky Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Aparna Bhaduri Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Jeremy Bancroft Brown Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Joshua Batson Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Astrid Behnert Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Ryan M. Boileau Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Saumya R. Bollam Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Alain R. Bonny Affiliation: University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America David Booth Affiliation: University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America Michael Jerico B. Borja Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America David Brown Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Bryan Buie Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Cassandra E. Burnett Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Lauren E. Byrnes Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Katelyn A. Cabral Affiliations University of California San Francisco, School of Medicine, San Francisco, California, United States of America, University of California San Francisco, Institute for Neurodegenerative Diseases, San Francisco, California, United States of America Joana P. Cabrera Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Saharai Caldera Affiliations Chan Zuckerberg Biohub, San Francisco, California, United States of America, University of California San Francisco, Division of Infectious Disease, San Francisco, California, United States of America Gabriela Canales Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Gloria R. Castañeda Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Agnes Protacio Chan Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Christopher R. Chang Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Arthur Charles-Orszag Affiliations University of California San Francisco, School of Medicine, San Francisco, California, United States of America, Howard Hughes Medical Institute, Chevy Chase, Maryland, United States of America Carly Cheung Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Unseng Chio Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Eric D. Chow Affiliation: University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America Y. Rose Citron Affiliation: University of California, Berkeley, California, United States of America Allison Cohen Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Lillian B. Cohn Affiliations Chan Zuckerberg Biohub, San Francisco, California, United States of America, University of California San Francisco, Department of Experimental Medicine, San Francisco, California, United States of America Charles Chiu Affiliation: University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States of America Mitchel A. Cole Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Daniel N. Conrad Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Angela Constantino Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Andrew Cote Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Tre’Jon Crayton-Hall Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Spyros Darmanis Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Angela M. Detweiler Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Rebekah L. Dial Affiliation: University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America Shen Dong Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Elias M. Duarte Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America David Dynerman Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Rebecca Egger Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Alison Fanton Affiliation: University of California, Berkeley, California, United States of America Stacey M. Frumm Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Becky Xu Hua Fu Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Valentina E. Garcia Affiliation: University of California San Francisco, Department of Biochemistry and Biophysics, San Francisco, California, United States of America Julie Garcia Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Christina Gladkova Affiliations University of California San Francisco, School of Medicine, San Francisco, California, United States of America, Howard Hughes Medical Institute, Chevy Chase, Maryland, United States of America Miriam Goldman Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Rafael Gomez-Sjoberg Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America M. Grace Gordon Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America James C. R. Grove Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Shweta Gupta Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Alexis Haddjeri-Hopkins Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Pierce Hadley Affiliations University of California San Francisco, School of Medicine, San Francisco, California, United States of America, University of California San Francisco, Institute for Neurodegenerative Diseases, San Francisco, California, United States of America John Haliburton Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America Samantha L. Hao Affiliation: Chan Zuckerberg Biohub, San Francisco, California, United States of America George Hartoularos Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Nadia Herrera Affiliation: University of California San Francisco, School of Medicine, San Francisco, California, United States of America Melissa Hilberg Affiliation: University of California San Francisco, Departm

Defining the subcellular distribution of all human proteins and its remodeling across cellular states remains a central goal in cell biology. Here, we present a high-resolution strategy to map subcellular organization using organelle immuno-capture coupled to mass spectrometry. We apply this proteomics workflow to a cell-wide collection of membranous and membrane-less compartments. A graph-based representation of our data reveals the subcellular localization of over 7,600 proteins, defines spatial protein networks, and uncovers interconnections between cellular compartments. We demonstrate that our approach can be deployed to comprehensively profile proteome remodeling during cellular perturbation. By characterizing the cellular landscape following hCoV-OC43 viral infection, we discover that many proteins are regulated by changes in their spatial distribution rather than by changes in their total abundance. Our results establish that proteome-wide analysis of subcellular remodeling provides essential insights for the elucidation of cellular responses. Our dataset can be explored at organelles.czbiohub.org.Competing Interest StatementThe authors have declared no competing interest.

Abstract We create and share a new red fluorophore, along with a set of strains, reagents and protocols, to make it faster and easier to label endogenous C. elegans proteins with fluorescent tags. CRISPR-mediated fluorescent labeling of C. elegans proteins is an invaluable tool, but it is much more difficult to insert fluorophore-size DNA segments than it is to make small gene edits. In principle, high-affinity asymmetrically split fluorescent proteins solve this problem in C. elegans: the small fragment can quickly and easily be fused to almost any protein of interest, and can be detected wherever the large fragment is expressed and complemented. However, there is currently only one available strain stably expressing the large fragment of a split fluorescent protein, restricting this solution to a single tissue (the germline) in the highly autofluorescent green channel. No available C. elegans lines express unbound large fragments of split red fluorescent proteins, and even state-of-the-art split red fluorescent proteins are dim compared to the canonical split-sfGFP protein. In this study, we engineer a bright, high-affinity new split red fluorophore, split-wrmScarlet. We generate transgenic C. elegans lines to allow easy single-color labeling in muscle or germline cells and dual-color labeling in somatic cells. We also describe ‘glonads’, a novel expression strategy for the germline, where traditional expression strategies struggle. We validate these strains by targeting split-wrmScarlet to several genes whose products label distinct organelles, and we provide a protocol for easy, cloning-free CRISPR/Cas9 editing. As the collection of split-FP strains for labeling in different tissues or organelles expands, we will post updates at doi.org/10.5281/zenodo.3993663 Competing Interest Statement The authors have declared no competing interest.

Elucidating the wiring diagram of the human cell is a central goal of the post-genomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery, and uncovers that RNA-binding proteins form a specific sub-group defined by unique interaction and localization properties. Furthermore, we discover that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions. Paired with a fully interactive website (opencell.czbiohub.org), we provide a resource for the quantitative cartography of human cellular organization. Competing Interest Statement J.S.W. declares outside interest in Chroma Therapeutics, KSQ Therapeutics, Maze Therapeutics, Amgen, Tessera Therapeutics and 5 AM Ventures. M. M. is an indirect shareholder in EvoSep Biosystems. Footnotes * https://opencell.czbiohub.org/

Loss of habitats or ecosystems arising from development projects (e.g., infrastructure, resource extraction, urban expansion) are frequently addressed through biodiversity offsetting. As currently implemented, offsetting typically requires an outcome of “no net loss” of biodiversity, but only relative to a baseline trajectory of biodiversity decline. This type of “relative” no net loss entrenches ongoing biodiversity loss, and is misaligned with biodiversity targets that require “absolute” no net loss or “net gain.” Here, we review the limitations of biodiversity offsetting, and in response, propose a new framework for compensating for biodiversity losses from development in a way that is aligned explicitly with jurisdictional biodiversity targets. In the framework, targets for particular biodiversity features are achieved via one of three pathways: Net Gain, No Net Loss, or (rarely) Managed Net Loss. We outline how to set the type (“Maintenance” or “Improvement”) and amount of ecological compensation that is appropriate for proportionately contributing to the achievement of different targets. This framework advances ecological compensation beyond a reactive, ad‐hoc response, to ensuring alignment between actions addressing residual biodiversity losses and achievement of overarching targets for biodiversity conservation.

Background In 2014, the government of Togo implemented a pilot unconditional cash transfer (UCT) program in rural villages that aimed at improving children’s nutrition, health, and protection. It combined monthly UCTs (approximately US$8.40 /month) with a package of community activities (including behavior change communication [BCC] sessions, home visits, and integrated community case management of childhood illnesses and acute malnutrition [ICCM-Nut]) delivered to mother–child pairs during the first “1,000 days” of life. We primarily investigated program impact at population level on children’s height-for-age z-scores (HAZs) and secondarily on stunting (HAZ < −2) and intermediary outcomes including household’s food insecurity, mother–child pairs’ diet and health, delivery in a health facility and low birth weight (LBW), women’s knowledge, and physical intimate partner violence (IPV).Methods and findings We implemented a parallel-cluster–randomized controlled trial, in which 162 villages were randomized into either an intervention arm (UCTs + package of community activities, n = 82) or a control arm (package of community activities only, n = 80). Two different representative samples of children aged 6–29 months and their mothers were surveyed in each arm, one before the intervention in 2014 (control: n = 1,301, intervention: n = 1,357), the other 2 years afterwards in 2016 (control: n = 996, intervention: n = 1,035). Difference-in-differences (DD) estimates of impact were calculated, adjusting for clustering. Children’s average age was 17.4 (± 0.24 SE) months in the control arm and 17.6 (± 0.19 SE) months in the intervention arm at baseline. UCTs had a protective effect on HAZ (DD = +0.25 z-scores, 95% confidence interval [CI]: 0.01–0.50, p = 0.039), which deteriorated in the control arm while remaining stable in the intervention arm, but had no impact on stunting (DD = −6.2 percentage points [pp], relative odds ratio [ROR]: 0.74, 95% CI: 0.51–1.06, p = 0.097). UCTs positively impacted both mothers’ and children’s (18–23 months) consumption of animal source foods (ASFs) (respectively, DD = +4.5 pp, ROR: 2.24, 95% CI: 1.09–4.61, p = 0.029 and DD = +9.1 pp, ROR: 2.65, 95% CI: 1.01–6.98, p = 0.048) and household food insecurity (DD = −10.7 pp, ROR: 0.63, 95% CI: 0.43–0.91, p = 0.016). UCTs did not impact on reported child morbidity 2 week’s prior to report (DD = −3.5 pp, ROR: 0.80, 95% CI: 0.56–1.14, p = 0.214) but reduced the financial barrier to seeking healthcare for sick children (DD = −26.4 pp, ROR: 0.23, 95% CI: 0.08–0.66, p = 0.006). Women who received cash had higher odds of delivering in a health facility (DD = +10.6 pp, ROR: 1.53, 95% CI: 1.10–2.13, p = 0.012) and lower odds of giving birth to babies with birth weights (BWs) <2,500 g (DD = −11.8, ROR: 0.29, 95% CI: 0.10–0.82, p = 0.020). Positive effects were also found on women’s knowledge (DD = +14.8, ROR: 1.86, 95% CI: 1.32–2.62, p < 0.001) and physical IPV (DD = −7.9 pp, ROR: 0.60, 95% CI: 0.36–0.99, p = 0.048). Study limitations included the short evaluation period (24 months) and the low coverage of UCTs, which might have reduced the program’s impact.Conclusions UCTs targeting the first “1,000 days” had a protective effect on child’s linear growth in rural areas of Togo. Their simultaneous positive effects on various immediate, underlying, and basic causes of malnutrition certainly contributed to this ultimate impact. The positive impacts observed on pregnancy- and birth-related outcomes call for further attention to the conception period in nutrition-sensitive programs.

Influenza virus (InfV) infection during pregnancy is a known risk factor for neurodevelopment abnormalities in the offspring, including the risk of schizophrenia, and has been shown to result in an abnormal behavioral phenotype in mice. However, previous reports have concentrated on neuroadapted influenza strains, whereas increased schizophrenia risk is associated with common respiratory InfV. In addition, no specific mechanism has been proposed for the actions of maternal infection on the developing brain that could account for schizophrenia risk. We identified two common isolates from the community with antigenic configurations H3N2 and H1N1 and compared their effects on developing brain with a mouse modified-strain A/WSN/33 specifically on the developing of dopaminergic neurons. We found that H1N1 InfV have high affinity for dopaminergic neurons in vitro, leading to nuclear factor kappa B activation and apoptosis. Furthermore, prenatal infection of mothers with the same strains results in loss of dopaminergic neurons in the offspring, and in an abnormal behavioral phenotype. We propose that the well-known contribution of InfV to risk of schizophrenia during development may involve a similar specific mechanism and discuss evidence from the literature in relation to this hypothesis.

A global goal of no net loss of natural ecosystems or better has recently been proposed, but such a goal would require equitable translation to country-level contributions. Given the wide variation in ecosystem depletion, these could vary from net gain (for countries where restoration is needed), to managed net loss (in rare circumstances where natural ecosystems remain extensive and human development imperative is greatest). National contributions and international support for implementation also must consider non-area targets (for example, for threatened species) and socioeconomic factors such as the capacity to conserve and the imperative for human development. A framework is presented for achieving global no net loss of biodiversity that accounts for inequity among countries in both pressures and ability to act.

Central retinal artery occlusion (CRAO) is a subtype of ischaemic stroke that results in acute monocular vision loss. Although open-label studies and meta-analyses have suggested that early intravenous thrombolysis might improve visual acuity, no randomised controlled trials have yet confirmed this benefit. We aimed to compare the safety and efficacy of intravenous alteplase with oral aspirin in patients with CRAO treated within 4·5 h of onset of severe vision loss. THEIA was a multicentre, double-dummy, patient-blinded, assessor-blinded, randomised, controlled, phase 3 trial conducted across 16 hospitals with stroke units in France. Adults (aged ≥18 years) presenting with sudden, severe, and persistent monocular vision loss (Snellen <20/400) due to suspected non-arteritic acute CRAO were eligible for inclusion. Participants were randomly assigned (1:1), stratified by centre, to receive either 0·9 mg/kg of bodyweight intravenous alteplase and oral placebo (alteplase group) or 300 mg oral aspirin and intravenous saline placebo (aspirin group) within 4·5 h of symptom onset. Patients, outcome assessors, and the study sponsor were masked to treatment allocation; treating nurses and neurologists were unmasked. The primary efficacy outcome was improvement in visual acuity of at least 0·3 logarithm of the minimum angle of resolution (LogMAR) from baseline to 1 month, analysed in the full analysis set, which included all patients who received the complete intervention and a visual acuity assessment at baseline. Safety outcomes included serious adverse events, particularly intracranial and extracranial bleeding, analysed in all randomly assigned participants. This study is registered at ClinicalTrials.gov (NCT03197194) and is completed. Between June 8, 2018, and Oct 2, 2023, 70 patients (mean age 70 years [SD 9]; 25 [36%] women and 45 [64%] men) were enrolled and randomly assigned to either the alteplase group (35 [50%]) or the aspirin group (35 [50%]). In total, 65 (93%) patients received the allocated treatment: 34 (97%) in the alteplase group and 31 (89%) in the aspirin group. Mean time from symptom onset to treatment initiation was 232·4 min (SD 43·6). Among 56 patients with available data on the primary endpoint, 19 (66%) of 29 patients in the alteplase group and 13 (48%) of 27 patients in the aspirin group showed an improvement in visual acuity of at least 0·3 LogMAR at 1 month (unadjusted risk difference 17·4 [95% CI –11·8 to 46·5]; adjusted odds ratio 1·1 [95% CI 0·07 to 18·39]; p=0·95). One asymptomatic intracranial haemorrhage related to study treatment was reported in the alteplase group. 14 serious adverse events unrelated to treatment occurred in 11 patients overall (six [17%] in the aspirin group and five [14%] in the alteplase group). No symptomatic haemorrhages or major bleeding related to study treatment were reported. Intravenous alteplase administered within 4·5 h of CRAO onset was not associated with a significant improvement in visual acuity compared with aspirin, despite a higher rate of improvement in the alteplase group. However, the study was likely underpowered to detect a statistical difference. Although no safety concerns related to alteplase were identified, the overall modest recovery rates underscore the need for individual patient-level data meta-analyses with forthcoming randomised controlled trials to clarify the potential benefit of thrombolysis or aspirin in patients with acute CRAO. French Ministry of Health and Boehringer Ingelheim, France.

Background: The popularity of nutrition-sensitive interventions calls for high-quality monitoring and evaluation tools. In this context, the Minimum Dietary Diversity for Women of Reproductive Age (MDD-W), validated as a proxy of micronutrient adequacy, does fill a gap. However, because it is a newly endorsed indicator, information on its linkages with other dimensions of food and nutrition security is still scarce. Objective: The objective of this study was to investigate whether the MDD-W is related to household food insecurity and farm production diversity. Methods: A cross-sectional survey on a representative sample of 5046 women of reproductive age was conducted in the region of Kayes, Mali, in 2013. Dietary diversity was assessed through qualitative 24-h recall, and MDD-W was computed. MDD-W equaled 1 if the women consumed at least 5 different food groups and 0 otherwise. Food insecurity was measured using the Household Food Insecurity Access Scale and the Household Hunger Scale (HHS), and a farm production diversity score (FPDS) was calculated based on a count of food crops/livestock groups produced. Logistic regressions were used to assess the relation between MDD-W and the indicators of household food security. Results: Only 27% of women reached the MDD-W. These women consumed animal source foods and/or vitamin A-rich vegetables and fruits more frequently than did other women. Women from extremely food insecure households (moderate to severe hunger according to the HHS) were less likely to reach the MDD-W (OR: 0.70; 95% CI: 0.50, 0.97). One more group in the FPDS increased the odds of attaining the MDD-W (OR: 1.12; 95% CI: 1.06, 1.18). Conclusion: In the rural region of Kayes, Mali, women's dietary diversity, as measured by the MDD-W, was associated with household-level food security indicators.