Biology subjects

Hill, A.

Publications and source records attributed to Hill, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Click Chemistry-Based Strategy for Modular Ligand Attachment to siRNAs: Toward Extrahepatic RNAi

Efficient extrahepatic delivery of siRNAs remains a major limitation for broadening their therapeutic potential. Using a modular, orthogonal click chemistry platform, we generated 28 siRNA conjugates varying in ligand class, valency, and spatial arrangement. Following systemic administration, fatty acid conjugates - particularly palmitic acid (C16) - outperformed sterol- and phospholipid-based designs in promoting extrahepatic gene silencing, with preferential activity observed in heart and skeletal muscle. Increasing ligand valency through 3',5'-bis-conjugation generally enhanced activity compared to 5-mono conjugation. Nevertheless, bis-C22 conjugates showed increased hepatic activity, suggesting a shift in tissue distribution linked to hydrophobicity. Architectural parameters further modulated outcomes: Branched 5' C16 conjugates, bearing two lipids on one terminus, were markedly less active than their bis counterparts and required short PEG spacers to restore activity. Notably, bis-lipid conjugation strategies that enhanced extrahepatic activity for an siRNA did not translate to an ASO gapmer, underscoring modality-specific constraints. Together, these findings delineate structure-activity relationships and establish bis-fatty-acid conjugation as a robust design principle for achieving extrahepatic RNAi. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/726808v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@b7af11org.highwire.dtl.DTLVardef@146b9c6org.highwire.dtl.DTLVardef@4e8948org.highwire.dtl.DTLVardef@16fa07_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

A Spatial Proteomic Atlas of Tertiary Lymphoid Structures in Non-Small Cell Lung Cancer Identifies a Novel Predictive Class of Lymphoid Aggregates

Tertiary lymphoid structures (TLS) predict benefit from immune checkpoint inhibitors (CPIs), yet mature, germinal-center-rich TLS are infrequent in solid tumors by histological review. Here, using 38-plex MIBI spatial proteomics across 165 lymphoid structures from 14 NSCLC resections, we establish a continuum of TLS maturity using high dimensional compositional, spatial, and molecular features. We demonstrate that histologically-defined lymphoid aggregates (LA) comprise a heterogeneous class of structures, which span this continuum of maturity. We identify a subset of lymphoid aggregates that harbor follicular dendritic cell networks, T follicular helper cells, and activated B cell states characteristic of mature TLS, yet are not readily distinguished from other LA structures in our histological review. We developed a novel digital pathology classifier to identify mature LAs in CPI trials, and demonstrate in a retrospective analysis of Atezolizumab in advanced NSCLC that the inclusion of mature LAs greatly expands the biomarker-eligible population while maintaining strong predicted benefit. Together, these data redefine the biological spectrum of tumor-associated lymphoid aggregates and provide a framework for implementing maturity-informed TLS biomarker strategies.

cancer biology↗

bioRxiv2026

Frequency-Specific Operant Learning in Neurofeedback Reveals Distinct Cortical Mechanisms: Evidence from Double-Blind ERSP and ERP Dissociations

Background: Neurofeedback reliably alters EEG activity, but two questions remain unresolved: what cortical mechanism underlies reward-contingent learning, and whether training produces durable resting-state change rather than transient within-session shifts. No study has examined reward-locked event-related spectral perturbations (ERSP) under double-blind, active-placebo-controlled conditions. Methods: Forty participants underwent five training sessions of single-channel EEG biofeedback (C3 SMR 12-15 Hz, n = 8; C3 Beta 15-18 Hz, n = 8; C4 SMR 12-15 Hz, n = 8; active-placebo sham, n = 16), plus a retention session a median of 29 days post-training, with concurrent 64-channel EEG recording. ERSP was computed from reward-locked epochs (approximately 600-700 trials per session) using Morlet wavelets (3-40 Hz) across four sessions. Resting-state alpha trajectories were modeled with growth-curve mixed-effects models on the pipeline's fixed 8-12 Hz alpha band, with an IAF-anchored reanalysis (IAF +/- 2 Hz) as a robustness check. Results: Under double-blind active-placebo control, SMR (but not Beta) neurofeedback produced a durable elevation of resting eyes-closed alpha persisting to the one-month follow-up (median 29 days). An LME growth curve confirmed SMR-specific accumulation (C3 SMR x Session B = 1.44, p = 0.004; C4 SMR B = 1.24, p = 0.012; Beta and sham flat), robust to IAF-anchored reanalysis (C3 SMR B = 1.21, p = 0.006; C4 SMR B = 1.10, p = 0.013) and present in 13 of 16 (81%) SMR participants versus 7 of 16 sham. Critically, the Beta group showed the largest immediate reward-locked ERD (d = -2.38 vs sham) yet the weakest consolidation, dissociating acute control from durable plasticity. Active groups produced frequency-specific event-related desynchronization (ERD) in the rewarded band (pooled Active vs Sham d = -1.23, p_adj = 0.001; C3 Beta and C4 SMR FDR-significant, |d| >= 1.12; C3 SMR trended, d = -0.80, p_adj = 0.081), absent in sham. A double dissociation emerged at C3: beta training produced the strongest ERD (d = -2.38), whereas C3 SMR training produced the largest P2 suppression (d = -1.33, BF01 = 0.10; smaller P2 at the trained electrode), consistent with distinct frequency-specific operant signatures. ERD magnitude did not track within-session resting shifts (r = -0.09, p = 0.67) and showed no detectable association with durable change at the individual level, consistent with consolidation as a property distinct from acute control. An ICA-based sensitivity analysis confirmed convergence of all primary findings. Conclusions: Neurofeedback engages frequency-specific, contingency-dependent cortical mechanisms whose consolidation profiles differ by protocol. The Beta arm controls the rhythm most strongly during training yet does not consolidate; both SMR arms show weaker acute control but durable resting-state growth. Consolidability, not session count or acute control, is the property that distinguishes protocols. The ERD-P2 dissociation suggests that beta and SMR training engage distinct frequency-specific mechanisms (C3 Beta: stronger spectral ERD with preserved P2; C3 SMR: moderate ERD with suppressed P2 at the trained site) with different capacities for offline consolidation. These findings support a multi-timescale model in which durable plasticity emerges only when the engaged circuit supports offline consolidation, a property not predicted by the magnitude of acute reward-locked control.

neuroscience↗

bioRxiv2026

Population genomics reveals multi-scale mechanisms sustaining schistosomiasis re-emergence in a near-elimination setting

In China, sustained snail control, environmental management, and mass drug administration with praziquantel reduced schistosomiasis to near-elimination levels, yet re-emergence in Sichuan Province during the early 2000s exposed vulnerabilities in late-stage control. We conducted a novel investigation of Schistosoma japonicum re-emergence in Sichuan in order to identify the processes underlying re-emergence and to showcase how genomic data can be used in such investigations. We sequenced whole genomes from 270 miracidia collected from 53 human hosts across 17 villages in 2007 - the year after re-emergence was documented. Population genomic analyses revealed a broadly cohesive regional parasite population with weak geographic structuring. Genome-wide diversity was substantial, and demographic reconstructions revealed no recent decline in effective population size, demonstrating that parasite populations were not demographically fragmented at the onset of re-emergence, hinting at maintenance in reservoir populations. At finer spatial scales, several villages exhibited low diversity and elevated inbreeding, consistent with localized transmission maintained by small founding populations. Estimates of pairwise genetic relatedness revealed dense within-village sibling clusters alongside second- and third-degree relationships spanning villages, and rare first- and second-degree cross-village links. These findings are consistent with highly focal transmission with episodic parasite dispersal across villages, leading to a regional transmission network. Inferred minimum worm burden across hosts varied from 1 to 11 adult worm pairs, indicating heterogeneity in within-host parasite diversity, although uneven sampling limited inference. Together, these findings indicate that schistosomiasis re-emergence in this near-elimination setting was likely facilitated by a diverse parasite population maintained in reservoir populations, and that transmission, while predominantly local was occurring across a network of connected villages. This work illustrates how population genomics can reveal mechanisms driving re-emergence in late-stage elimination in complex, multi-host transmission systems. Author SummarySchistosomiasis is a parasitic disease that affects millions of people worldwide. Understanding the factors that contribute to persistence and transmission, even in the face of control programs, is central to reducing and ultimately eliminating the disease. In China, decades of intensive control efforts have dramatically reduced infections, yet the disease continued to persist in some regions. In this study, we analyzed the genomes of 270 parasite larvae collected from infected humans across 17 villages in Sichuan Province, China, shortly after schistosomiasis re-emerged in the region. By examining genetic relationships among parasites, we reconstructed patterns of transmission across villages and within individual infections. Our findings suggest that, despite major reductions in human infection prevalence, parasite populations sizes do not show signatures of recent population decline, indicating that non-human hosts may serve as key reservoirs promoting persistence. We also find that local transmission pathways, including clonal infections infecting multiple humans derived from a relatively small number of snail hosts, maintain parasite transmission pathways. Collectively, these findings suggest non-human hosts, intact local transmission pathways, and regional connectivity together enabled re-emergence, highlighting important challenges for elimination programs

genomics↗

bioRxiv2026

Protocol-dependent cardiomyocyte states determine disease modelling capacity of human iPSCs

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are widely used to model cardiovascular disease, yet numerous differentiation protocols generate cardiomyocytes with heterogeneous molecular and functional properties, complicating experimental design. Here we systematically compare sixteen commonly used cardiomyocyte differentiation protocols and characterize their resulting cell states using single-nucleus RNA sequencing, functional phenotyping and computational integration with human genetic data. Despite similar cardiomyocyte yields, protocols produced distinct transcriptional programs, subtype compositions and physiological properties. By integrating protocol-specific gene expression signatures with genome-wide association studies of cardiovascular traits, we identify cardiomyocyte states enriched for genetic architectures underlying specific diseases. These analyses accurately predict protocols most suitable for modelling particular disease contexts, including electrophysiological defects associated with Brugada syndrome and metabolic vulnerability relevant to myocardial infarction. Our results demonstrate that differentiation protocols encode biologically distinct cardiomyocyte states with differential disease relevance and establish a framework for aligning stem-cell differentiation strategies with human complex trait genetics to guide model selection. This approach enables rational design of iPSC-based disease models and highlights how population-scale genetic data can inform experimental systems in stem cell biology.

systems biology↗

bioRxiv2025

Robotic Handling Preserves Induced Pluripotent Stem Cell Derived Vascular Smooth Muscle Cells Differentiation using a Weekend-free, Automatable, Low-variability, Low-cost (WALL) Protocol

Vascular disease modeling and tissue engineering require scalable, efficient, and reproducible methods for differentiating cells, however no studies have validated whether automation, essential for scale-up, preserves differentiation quality in cells. Here, we developed a differentiation protocol for induced pluripotent stem cell (iPSC)-derived vascular smooth muscle cells (iVSMCs) that is applicable to both manual, and automated robotic culture. iPSC lines generated from male and female donors across various ages were used to optimize the generation of iVSMCs. iVSMCs had consistent morphology and protein expression was largely similar to primary VSMCs, including expression of myosin heavy chain-11 (MYH11), -smooth muscle actin (-SMA), transgelin (TAGLN) and calponin (CNN1). Functionally, these iVSMCs could respond to the vasoconstrictor carbachol. Coupling this protocol with an automated Hamilton liquid-handling robotics system allowed the generation of iVSMCs in large quantities, morphologically similar to manually differentiated iVSMCs. Comparative proteomic analysis confirmed protein expression did not differ between automated and manual differentiation methods. Automation markedly reduced manual labor and facilitated increased production without sacrificing cell quality. This study demonstrates the feasibility of automating iVSMC differentiation, marking a significant step towards scalable VSMC manufacturing for three-dimensional applications, and for the ever-growing demands of organoid and tissue engineering applications. Statement of significanceThe rapidly expanding fields of tissue engineering and high-throughput disease modeling require large quantities of viable cells, making automation essential. Robotic liquid handling systems are increasingly employed for generating large quantities of induced pluripotent stem cell (iPSC)-derived cells, requiring the development of scalable protocols. No studies have yet evaluated whether the use of robotic liquid handling alters the differentiation of cells compared to traditional manual handling. Here, we report a scalable differentiation protocol that robustly generates iPSC-derived VSMCs (iVSMCs) from a cohort of female and male donors of varying age (n=5 lines). We demonstrate for the first time that iVSMCs, differentiated through an automated robotic pipeline, had no significant differences in morphological or proteomic phenotype compared to manual differentiation. The ability to automate this protocol facilitates robust and reproducible differentiation of large quantities of iVSMC, setting a precedent for the application of automation in generating iPSC-derived cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=57 SRC="FIGDIR/small/690512v1_ufig1.gif" ALT="Figure 1000"> View larger version (18K): org.highwire.dtl.DTLVardef@673d61org.highwire.dtl.DTLVardef@1eead89org.highwire.dtl.DTLVardef@c3089eorg.highwire.dtl.DTLVardef@6af2cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Nutrient stress activates Rab5b-mediated autophagy to remodel the synaptic proteome

Synaptic proteostasis is crucial for maintaining neuronal function and plasticity, yet how synapses adapt to metabolic stress remains poorly understood. Here, we show that nutrient deprivation, particularly serum withdrawal, induces robust autophagy-dependent remodeling of the synaptic proteome, while mTORC1 inhibition has more limited effects. Nutrient stress rapidly activates autophagy both globally and at synapses, with synaptic autophagy peaking within 1-2 hours of serum withdrawal. Mechanistically, we uncover that the LC3 lipidation complex (ATG5-ATG12-ATG16L1) is recruited to synapses via Rab5b-positive endosomes in a dynein-dependent manner. Live imaging reveals enhanced Rab5b-ATG16L1 co-trafficking and increased ATG5 mobility upon serum withdrawal, supporting a model of spatiotemporally controlled autophagy precursor delivery to synaptic compartments. Functionally, nutrient deprivation acutely dampens neuronal excitability in vitro, while a two-week fasting-mimicking diet in vivo triggers synaptic proteome remodeling that overlaps with starvation-induced autophagy cargo. In contrast, restriction of mTORC1-activating amino acids fails to induce comparable synaptic changes, suggesting that synaptic autophagy is regulated by nutrient signals beyond mTORC1. Our findings define a Rab5b-mediated trafficking mechanism that couples nutrient sensing to localized synaptic degradation, providing new insight into how neurons preserve proteostasis under metabolic challenge.

neuroscience↗

bioRxiv2025

Global monitoring of wildlife mortality through participatory science in near-real time

Detection of wildlife mortality events is critical for timely conservation and natural resource management. We present an open-source, web-based decision support tool that queries, aggregates and summarizes participatory science data from iNaturalist to monitor mortality events worldwide. We demonstrate the effectiveness of this approach using four case studies spanning taxonomic, spatial, and temporal scales. In Canada and the United States, high peaks of bird mortality coincided with zoonotic risk during avian influenza outbreaks. Across Latin America, we detected 75 mortality events of critically endangered species. In California, recorded mammal mortality was associated with human infrastructure, including proximity to roads, and to a lesser extent, the human footprint. Mortality of pumas (Puma concolor) was detected across nine countries, highlighting the need for international cooperation to conserve mobile species. Our tool enables resource managers to flag emerging threats and empowers participatory scientists to monitor and integrate mortality records for conservation.

ecology↗

bioRxiv2025

RNA liquid biopsy via nanopore sequencing for novel biomarker discovery and cancer early detection

Liquid biopsies detect disease noninvasively by profiling cell-free nucleic acids that are secreted into the circulation. However, existing methods exhibit low sensitivity for detecting early stages of diseases such as cancer. Here we show that long-read nanopore sequencing of full-length cell-free RNA in plasma from healthy individuals, precancerous Barretts esophagus patients with high-grade dysplasia, or patients with esophageal adenocarcinoma reveals a diverse cell-free RNA transcriptome that can be leveraged for detecting and treating disease. We discovered 270,679 novel, intergenic cell-free RNAs, which we used to build a custom transcriptome reference for quantification, feature selection, and machine learning to accurately classify both precancer and cancer. Moreover, we found potential therapeutic targets, including metabolic, signaling, and immune checkpoint pathways, that are highly upregulated in both precancer and cancer patients. Our findings highlight the utility of our RNA liquid biopsy platform technology for discovering and targeting early stages of disease with molecular precision.

genomics↗

bioRxiv2025

Simple controls exceed best deep learning algorithms and reveal foundation model effectiveness for predicting genetic perturbations

Modeling genetic perturbations and their effect on the transcriptome is a key area of pharmaceutical research. Due to the complexity of the transcriptome, there has been much excitement and development in deep learning (DL) because of its ability to model complex relationships. In particular, the transformer-based foundation model paradigm emerged as the gold-standard of predicting post-perturbation responses. However, understanding these increasingly complex models and evaluating their practical utility is lacking, along with simple but appropriate benchmarks to compare predictive methods. Here, we present a simple baseline method that outperforms both state of the art (SOTA) in DL and other proposed simpler neural architectures, setting a necessary benchmark to evaluate in the field of post-perturbation prediction. We also elucidate the utility of foundation models for the task of post-perturbation prediction via generalizable fine-tuning experiments that can be translated to different applications of transformer-based foundation models to tasks of interest. Furthermore, we provide a corrected version of a popular dataset used for benchmarking perturbation prediction models. Our hope is that this work will properly contextualize further development of DL models in the perturbation space with necessary control procedures.

bioinformatics↗

bioRxiv2024

Natural language processing charts transcriptome evolution to design combination cancer therapies

Combination treatment-the mainstay of cancer therapy-often fails because treatment interactions evoke complex resistance mechanisms that are hard to predict. Designing combination therapy to prevent treatment resistance is especially challenging for rare cancers. Here, we introduce REsistance through COntext DRift (RECODR): a computational pipeline that tracks how genes change their transcriptome context across cancer development and drug treatment conditions. By applying RECODR to a genetically modified mouse model of choroid plexus carcinoma-a rare brain tumour of young children-we identified patterns of transcriptome evolution, cellular heterogeneity and treatment targets that emerged as tumours were initiated and resisted combination treatment. This enabled the prediction of treatment resistance mechanisms and the design of highly effective therapeutic protocols that avoided treatment failure. RECODR can describe complex and dynamic changes in normal and diseased tissues that could be applied to multimodal data from a variety of settings, mitigating treatment resistance across cancers and other diseases.

cancer biology↗

bioRxiv2024

New, biomechanically sound tendon tissue after injection of uncultured, autologous, adipose derived regenerative cells in partial Achilles tendon defects in rabbits

BackgroundCurrent management options for partial tendon tears may not offer future potential to heal tissue and improve clinical results. This study tested the hypothesis that treatment of a partial rabbit common calcaneus tendon (CCT) defect with uncultured, autologous, adipose derived regenerative cells (UA-ADRCs) enables regenerative healing without scar formation, as recently observed in a biopsy of a human supraspinatus tendon. MethodsA full-thickness hole (diameter, 3 mm) was punched into the midsubstance of the right gastrocnemius tendon (GT; which is a part of the CCT) of adult, female New Zealand white rabbits. Immediately thereafter the rabbits were treated by application of an averaged 28.3x106 UA-ADRCs in 0.5 ml lactated Ringers solution (RLS) into the GT defect and surrounding tendon tissue, or underwent sham treatment. Rabbits were sacrificed either four weeks (W4) or twelve weeks (W12) post-treatment, and the CCTs were investigated using histology, immunohistochemistry and non-destructive biomechanical testing. ResultsNewly formed connective tissue was consistent with the formation of new tendon tissue after treatment with UA-ADRCs, and with the formation of scar tissue after sham treatment, at both W4 and W12 post-treatment. Biomechanical testing demonstrated a significantly higher mean percent relaxation after treatment with UA-ADRCs than after sham treatment (p < 0.05), and significant, negative correlations between the peak stress as well as the equilibrium stress and the cross-sectional area of the CCT (p < 0.05) after treatment with UA-ADRCs but not after sham treatment. ConclusionsManagement of partial tendon tears with UA-ADRCs has the potential to be truly "structure-modifying".

bioengineering↗

bioRxiv2024

Before and after delisting: population dynamics of North Atlantic humpback whales over two decades in the Gulf of Maine

Whales are long-lived, slow-reproducing species that were decimated by commercial whaling. Although some populations seem close to recovery, others are challenging to assess. We studied humpback whales (Megaptera novaeangliae) in the Gulf of Maine, an area of the North Atlantic (NA) with well-documented threats. Long-term studies and mark-recapture data were used to estimate humpback whale apparent survival, abundance and population growth from 2000 through 2019. Estimates were derived from a hierarchical, Bayesian state-space model with sex, age, and random time effects on survival while accounting for individual capture probability. Abundance increased from 744 (95% CI: 726-762) in 2000 to 1,706 (95% CI: 1,639-1,771) in 2019, with 4.6% mean annual growth. However, adult males exhibited higher survival and outnumbered adult females by the end of the study. Over time, fewer calves were observed, calf survival varied and the juvenile class declined. These are rare insights into the dynamics underlying whale abundance trends and they revealed similarities to an endangered species that is declining due to environmental and human impacts. The results inform a listing change under the U.S. Endangered Species Act, a mortality event of unprecedented magnitude off the U.S and humpback whale recovery from historical whaling in the NA.

ecology↗

bioRxiv2023

Heterogeneity analysis of acute exacerbations of chronic obstructive pulmonary disease and a deep learning framework with weak supervision and privacy protection

11.1 BackgroundChronic obstructive pulmonary disease (COPD) affects 5-10% of the adult US population and is a major cause of mortality. Acute exacerbations of COPD (AECOPDs) are a major driver of COPD morbidity and mortality, but there are no cost-effective methods to identify early AECOPDs when treatment is most likely to reduce the severity and duration of AECOPDs. 1.2 MethodsWe conducted the first long-term (> 12 months), real-time monitoring studies of AECOPD with wearable sensors and self-reporting. We applied a deep learning-based autoencoder for feature extractions, then applied K-means clustering to detect heterogeneity. Accordingly, we proposed a weakly supervised active learning framework to develop anomaly detection models for robust identification of early AECOPD, and a clustered federated learning approach to personalize the anomaly detection models for early detection of heterogeneous subtypes of AECOPD. We evaluated this model by comparing it with other unsupervised learning models and federated learning models. 1.3 FindingsWe identified two clusters based on the Silhouette score and SHAP analysis.One cluster shows high heart rate, low calories, and low steps; and the other has opposite characteristics. We also found out that a single subject could have exacerbation events from both clusters, indicating that there is not only subject-level heterogeneity but also event-level heterogeneity. Our weakly supervised framework outperformed unsupervised methods by 0.06 in average precision with 25 human annotation labels per subject. Our federated learning framework outperformed standard federated learning methods by 0.14 in F1 score and 0.17 in average precision. 1.4 InterpretationWe showed subject-level and event-level heterogeneity in AECOPD using mobile and wearable device data and developed a practical AECOPD detection framework with limited human annotated labels and keeping data private in each device.

bioinformatics↗

bioRxiv2023

STIL overexpression shortens lifespan and reduces tumor formation in mice

Centrosomes are the major microtubule organizing centers of animal cells. Supernumerary centrosomes are a common feature of human tumors and associated with karyotype abnormalities and aggressive disease, but whether they are cause or consequence of cancer remains controversial. Here, we analyzed the consequences of centrosome amplification by generating transgenic mice in which centrosome numbers can be increased by overexpression of the structural centrosome protein STIL. We show that STIL overexpression induces centrosome amplification and aneuploidy, leading to senescence, apoptosis, and impaired proliferation in mouse embryonic fibroblasts, and microcephaly with increased perinatal lethality and shortened lifespan in mice. Importantly, both overall tumor formation in mice with constitutive, global STIL overexpression and chemical skin carcinogenesis in animals with inducible, skin-specific STIL overexpression were reduced, an effect that was not rescued by concomitant p53 inactivation. These results suggest that supernumerary centrosomes impair proliferation in vitro as well as in vivo, resulting in reduced lifespan and spontaneous as well as carcinogen-induced tumor formation.

cancer biology↗

bioRxiv2023

The evolutionary age-range size relationship is modulated by insularity and dispersal in plants and animals

Earth is home to millions of plant and animal species, with more than 40 thousand species facing extinction worldwide (Diaz et al. 2019). Species range size is particularly important in this context because it influences extinction risk (Purvis et al. 2000, Gaston & Fuller 2009), but the causes underlying the wide natural variation in range size remain poorly known. Here, we investigate how evolutionary age is related to present-day range size for over 25,000 species of mammals, birds, reptiles, amphibians, reef fishes, and plants. We show that, on average, older species have significantly larger ranges, but the effect of age on range size is modulated by clade, geographical context and dispersal ability. Specifically, age does not affect range size for island species, because islands limit dispersal and hence range size, regardless of species age. Furthermore, species from clades with high dispersal capabilities obtain large ranges faster, thereby further neutralizing the relationship between age and range size. Our results can help supporting global conservation priorities, by showing that species that are young, occupy islands, and/or are dispersal limited often have small ranges and therefore increased extinction risk.

ecology↗

bioRxiv2023

Genetically engineering endothelial niche in human kidney organoids enables multilineage maturation, vascularization, and de novo cell types

Vascularization plays a critical role in organ maturation and cell type development. Drug discovery, organ mimicry, and ultimately transplantation in a clinical setting thereby hinges on achieving robust vascularization of in vitro engineered organs. Here, focusing on human kidney organoids, we overcome this hurdle by combining an inducible ETS translocation variant 2 (ETV2) human induced pluripotent stem cell (iPSC) line, which directs endothelial fate, with a non-transgenic iPSC line in suspension organoid culture. The resulting human kidney organoids show extensive vascularization by endothelial cells with an identity most closely related to endogenous kidney endothelia. Vascularized organoids also show increased maturation of nephron structures including more mature podocytes with improved marker expression, foot process interdigitation, an associated fenestrated endothelium, and the presence of renin+ cells. The creation of an engineered vascular niche capable of improving kidney organoid maturation and cell type complexity is a significant step forward in the path to clinical translation. Furthermore, this approach is orthogonal to native tissue differentiation paths, hence readily adaptable to other organoid systems and thus has the potential for a broad impact on basic and translational organoid studies. Translational StatementDeveloping therapies for patients with kidney diseases relies on a morphologically and physiologically representative in vitro model. Human kidney organoids are an attractive model to recapitulate kidney physiology, however, they are limited by the absence of a vascular network and mature cell populations. In this work, we have generated a genetically inducible endothelial niche that, when combined with an established kidney organoid protocol, induces the maturation of a robust endothelial cell network, induces a more mature podocyte population, and induces the emergence a functional renin population. This advance significantly increases the clinical relevance of human kidney organoids for etiological studies of kidney disease and future regenerative medicine strategies. Graphical AbstractGenetically engineered endothelial niche induces mature cell populations in human kidney organoids O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/542848v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1b129d4org.highwire.dtl.DTLVardef@313ae3org.highwire.dtl.DTLVardef@111c91org.highwire.dtl.DTLVardef@16a8d45_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Corticosterone enhances formation of non-fear but not fear memory during infectious illness

Survivors of critical illness are at high risk of developing post-traumatic stress disorder (PTSD) but administration of glucocorticoids during the illness can lower that risk. The mechanism is not known but may involve glucocorticoid modulation of hippocampal- and amygdalar-dependent memory formation. In this study, we sought to determine whether glucocorticoids given during an acute illness influence the formation and persistence of fear and non-fear memories from the time of the illness. We performed cecal ligation and puncture in male and female mice to induce an acute infectious illness. During the illness, mice were introduced to a neutral object in their home cage and separately underwent contextual fear conditioning. We then tested the persistence of object and fear memories after recovery. Glucocorticoid treatment enhanced object discrimination but did not alter the expression of contextual fear memory. During context re-exposure, neural activity was elevated in the dentate gyrus irrespective of fear conditioning. Our results suggest that glucocorticoids given during illness enhance hippocampal-dependent non-fear memory processes. This indicates that PTSD outcomes in critically ill patients may be improved by enhancing non-fear memories from the time of their illness.

neuroscience↗