Browse Articles

High-latitude teleconnections drive subtropical marine bioproductivity at the dawn of the Antarctic ice sheet

The inception of the Antarctic ice sheet (AIS) marked a major global climatic reorganization of the Cenozoic, but the response of the subtropical marine biosphere remains poorly constrained. A new sediment archive from the subtropical South Atlantic (IODP Exp. 390 and 393) reveals a sevenfold increase in surface ocean bioproductivity proxy accumulation (biogenic barium) commensurate with the initial expansion of the AIS 34 Mya, and the emergence of an amplified astronomical forcing of subtropical bioproductivity that mirrors the subsequent evolution of the AIS in the early Oligocene. We find that a strong 40-kyr obliquity response characterizes subtropical bioproductivity following the initial establishment of an expansive marine-based AIS. Portions of the AIS in contact with the marine environment are sensitive to meridional heat delivery controlled by obliquity-forced interactions between the atmosphere and ocean, which can propagate to the lower latitudes via Southern Ocean overturning circulation. The surprising emergence of obliquity forcing of low-latitude bioproductivity enhances our understanding of global teleconnections and feedbacks that regulate global climate, and points to mechanisms driving global marine bioproductivity on astronomical timescales—and their intricate connections to the evolution of the cryosphere.

A lightweight deep learning framework for reliable microscopy-based diagnosis of cutaneous leishmaniasis

Cutaneous leishmaniasis (CL) is a neglected tropical and zoonotic disease affecting both human and animal health, for which microscopic examination of Giemsa-stained slides remains the diagnostic reference standard despite being time-consuming and operator-dependent. In this study, we developed a lightweight, calibration-aware deep learning framework for automated amastigote detection and slide-level diagnostic probability estimation from microscopy images. A U-Net architecture with a MobileNetV2 encoder was employed for pixel-level parasite segmentation using a weakly supervised pseudo-labeling strategy on a single-center dataset comprising 292 field-of-view images. Slide-level diagnostic probabilities were derived via probability pooling and subsequently refined using post-hoc calibration techniques, including isotonic regression, Platt scaling, and temperature scaling. Model performance was evaluated on an independent test set using segmentation metrics (Dice coefficient and Intersection-over-Union) and diagnostic reliability metrics (AUROC, Brier score, and Expected Calibration Error). The proposed framework achieved a Dice coefficient of 0.901 and an IoU of 0.820 for segmentation against pseudo-label references, with strong discriminative performance at the slide level (AUROC = 0.978). Isotonic regression markedly improved probability reliability, reducing the Brier score from 0.089 to 0.030 and the Expected Calibration Error from 0.120 to 0.023 without significantly affecting discrimination. Statistical analyses confirmed the robustness of the calibration improvements. Overall, the results demonstrate that isotonic calibration enhances the interpretability and reliability of deep-learning-based CL diagnostics. The proposed lightweight framework provides a robust foundation for microscopy-based screening and supports future validation across broader datasets and One Health–oriented diagnostic applications.

Identification and characterization of a wet adhesive protein extracted from <i>Dreissena bugensis</i> , the freshwater quagga mussel

Mechanisms of wet adhesion have evolved in several aquatic organisms over millions of years. Yet, the repertoire of synthetic biocompatible wet adhesive materials is still limited. The byssus is a well-studied proteinaceous bioadhesive structure utilized by several bivalves to support sessile lifestyles in turbulent conditions. The quagga mussel ( Dreissena bugensis ) is a freshwater byssate and a notorious invasive species in the Great Lakes region. To identify adhesive proteins in the quagga mussel byssus, we utilized quantitative proteomics and found several proteins enriched at the byssus–substrate interface. Among the identified proteins was the Dbfp7 protein family. Dbfp7 is a small, polymorphic, and mostly disordered protein that lacks significant amounts of 3,4-dihydroxyphenylalanine (DOPA), a modified amino acid found in several marine mussel byssal proteins. Atomic force microscopy nanomechanical mapping of Dbfp7 films demonstrates that this protein exhibits adhesive ability in aqueous conditions. While DOPA is critical for marine mussel adhesion, interfacial electrochemistry of freshwater adhesive plaques suggests that freshwater byssates circumvent catechol-based adhesion. The functional characterization of Dbfp7 as a freshwater mussel adhesive protein advances the understanding of fundamental requirements for biocompatible wet adhesion, a crucial step for the development of bioinspired wet adhesive materials, such as improved medical adhesives.

Prevalence and influencing factors of dry eye syndrome among pilots: A survey study

Background Dry eye syndrome (DES) is a prevalent ocular condition that significantly impacts affected individuals’ quality of life and occupational performance. This study investigates the prevalence and contributing factors of DES among pilots, which is a group particularly susceptible to environmental and occupational stressors. Methods A descriptive, observational study was conducted, which involved 794 pilots. Based on the severity of DES, these pilots were assigned into mild, moderate and severe groups. Data was collected through surveys, and analyzed using multiple linear regression, in order to determine the relationship between the DES scores and potential influencing factors. Results The study revealed that all pilots included in the present study were affected by DES, in which 88.40% of pilots experienced moderate DES and 11.60% of pilots reported severe DES. After adjusting for other covariates in the model, the multivariate analysis revealed that eyelid diseases, ocular surface disease, poor sleep quality, and fatigue were statistically significant and positively correlated to higher DES scores ( p  &lt; 0.05), while residing in the southern region and engaging in physical activities were statistically significant and negatively correlated to the DES scores ( p  &lt; 0.05). Conclusion The high prevalence of DES in pilots highlights the urgent need for tailored occupational health interventions. Strategies to mitigate DES risk should include promoting regular physical exercise, improving sleep quality, and addressing fatigue. Future research should prioritize longitudinal studies to establish causal relationships and develop targeted management approaches for this high-risk occupational group.

Opioid-specific brain connectivity dynamics distinguish analgesia from secondary effects: Studies in male mice

The µ-opioid receptor (MOP) is a critical pharmaceutical target that mediates both the therapeutic benefits and adverse effects of opioid drugs. However, the large-scale neural circuit dynamics underlying key opioid effects, such as analgesia and respiratory depression, remain poorly understood, hindering the development of safer analgesics. Here, we present a multimodal experimental framework that integrates functional ultrasound imaging through the intact skull with behavioral and molecular analyses to investigate opioid-induced large-scale functional responses and their physiological relevance in awake, behaving male mice. Administration of major opioids—morphine, fentanyl, methadone, and buprenorphine—elicited robust, dose- and time-dependent reorganization of functional brain connectivity (FC) patterns, with magnitude scaling according to MOP agonist efficacy. This opioid-specific functional fingerprint is marked by decreased FC between the somatosensory cortex and hippocampal/thalamic regions and increased bilateral FC within the somatosensory cortex. Notably, this fingerprint was attenuated following tolerance induction and abolished by pharmacological or genetic MOP inactivation. Through power Doppler spectral analysis and lagged correlation measurements, we show that morphine perturbs temporal FC dynamics and the propagation of brain-wide oscillatory activity, disrupting critical-state dynamics. Importantly, we identify a dissociation between fast, transient processes—such as cerebral blood volume changes, locomotion, and respiratory depression—and slower processes driving FC reorganization, analgesia, and sustained MOP activation. This study provides mechanistic insights into opioid-induced network reorganization, establishes FC alterations as a reliable biomarker of opioid efficacy, and offers a framework for advancing the development of analgesic compounds with improved therapeutic windows and reduced side effects.

The effect of grade retention on secondary school performance: Evidence from a natural experiment

We study the effects of grade retention on secondary school performance using a change in legislation in Colombia. In 2010, the rule that allowed schools to retain a maximum of 5 percent of their students was abolished. We exploit variation in changes in schools’ retention rates across time in a difference-in-differences framework, and find that higher school retention rates improved performance on high-school exit tests scores. While gains in learning did not differ between STEM and non-STEM subjects, increased retention disproportionately benefited non-retained students, students from higher socioeconomic backgrounds, private schools, and schools operating under a full day shift.

When collagen fails: Zinc isotopes unlock Sumerian lifeways in southern Mesopotamia

Reconstructing past lifeways and diets is essential to understanding the emergence of urban societies. However, in what are now arid environments like southern Mesopotamia, poor collagen preservation has long hampered direct isotopic analysis of trophic levels. This limitation has left key gaps in our understanding of subsistence in one of the world’s earliest urban heartlands. Here, we apply zinc isotope analysis to human and faunal dental enamel from the third-millennium BCE site of Abu Tbeirah (Iraq), integrating δ 13 C, δ 18 O, and trace element ratios (Ba/Ca and Sr/Ca). This multiproxy approach reveals an omnivorous diet based on C 3 cereals, terrestrial animal products (likely including pigs), and limited freshwater resources, with no or little evidence of marine fish consumption, despite the site’s proximity to the ancient shoreline. Dietary patterns do not vary by sex, suggesting broad access to similar food sources within this nonelite population. Moreover, zinc and carbon isotopes proved valuable in identifying animal feeding practices. Our results provide direct dietary evidence from southern Mesopotamia, overcoming long-standing preservation challenges. The results allow us to evaluate specific expectations about diet and animal management in a collagen-poor context, also highlighting early-life feeding behaviors. They demonstrate the power of zinc isotopes to reconstruct trophic level in collagen-poor contexts, opening broad avenues for bioarchaeological research in early complex societies.

Human body dynamics simulation and comfort evaluation of interhospital transport patients with different road conditions

Road unevenness has a significant impact on the comfort of patients during interhospital transport. Vibration is easy to cause dizziness, palpitation, tension, restlessness and other symptoms, and even cause secondary injuries to patients. Therefore, it is very important to analyze the vibration characteristics of human body and take care of vibration reduction. In this paper, the finite element technology, dynamic theory and experimental method are used to establish a “human-vehicle-road” coupling dynamic model, and the human dynamic response under different road conditions is simulated and analyzed. The results show that the human comfort is poor on bumpy road and continuous speed bumps; The vibration of different parts of human body is very different, and the head and sacrococcygeal vibration are the most obvious. Therefore, for patients with interhospital transport, vibration reduction nursing should be focused on the head and sacrococcygeal region. And a variable stiffness damping device is proposed, which has the functions of damping and limiting position. The simulation results show that the vibration reduction of head is more than 35%, and that of sacrococcygeal region is more than 30%. Therefore, the device is of great significance for improving the comfort of patients with interhospital transport.

Bacterial reporter–paired scRNA sequencing reveals cross talk between zinc starvation and zinc toxicity in macrophage antibacterial defense

Mechanisms by which macrophages deploy antibacterial zinc toxicity are poorly understood. To gain insight into this antimicrobial pathway, we developed bacterial reporter–paired single-cell RNA sequencing of human monocyte-derived macrophages (HMDM) infected with an Escherichia coli zinc-stress reporter strain. We identified HMDM subpopulations harboring zinc-stressed E. coli and corresponding mammalian genes predicted to be associated with either zinc toxicity or survival of zinc-stressed bacteria. Consistent with the latter, SLC30A4 that encodes zinc exporter ZNT4 was enriched in one subpopulation of HMDM containing zinc-stressed E. coli and its overexpression in human macrophages increased intracellular E. coli survival. At a population level, SLC30A4 expression was rapidly downregulated in human macrophages responding to E. coli and its ectopic expression in macrophages attenuated zinc starvation of intracellular E. coli . This is consistent with a model in which macrophages switch off SLC30A4 to engage zinc starvation, while also deploying zinc toxicity against bacteria adapting to a low-zinc environment. Consistent with this, intramacrophage E. coli rapidly upregulated znuA messenger RNA (mRNA) that is induced during zinc limitation, with zntA mRNA that is induced during zinc stress peaking later. Moreover, E. coli cultured under conditions of zinc limitation displayed greatly enhanced zinc sensitivity. Susceptibility of zinc-sensitive E. coli to killing by macrophages was also attenuated when zinc uptake by E. coli was inactivated, confirming the coordinated actions of zinc starvation and zinc toxicity in macrophage antibacterial responses. Strategies that enhance zinc starvation of intracellular bacteria could be exploited in the design of host-directed therapeutics that amplify macrophage-mediated antibacterial zinc toxicity.

Correction: Blockade of mTOR ameliorates IgA nephropathy by correcting CD89 and CD71 dysfunctions in humanized mice

Ambient ammonia synthesis from air via tandem water microdroplets–driven oxidation and pulsed photoelectrochemical reduction

Artificial N 2 reduction offers a sustainable approach to green NH 3 synthesis, but the practical implementation is challenged by N 2 activation and competing hydrogen evolution. Photoelectrochemical nitrate and nitrite (NO x – , x = 2 and 3) reduction with favorable thermodynamics represents a promising alternative for NH 3 production, provided that NO x – can be supplied from the atmosphere. Here, through leveraging water microdroplet chemistry and dynamic photoelectrode–electrolyte interface engineering, we report a tandem air–NO x – –NH 3 conversion system that integrates catalyst-free N 2 oxidation with pulsed photoelectrochemical NO x − reduction (mNOR-pPNO x R). The system achieves efficient and selective NH 3 production with a yield rate of 24.5 μmol cm −2 h −1 at −0.2 V RHE , which are two to three orders of magnitude higher than conventional photo/electrocatalytic N 2 fixation. This study introduces insights for decentralized, on-demand ammonia production from air and water and broadens horizons of microdroplet chemistry and pulse strategy for sustainable chemical manufacturing.

Development and validation of a health education module for parents of schoolchildren with overweight and obesity in the UAE

Background Childhood overweight and obesity continue to rise globally and in the United Arab Emirates (UAE), underscoring the need for accessible, evidence-based parental education tools. Objective This study aims to develop and validate a health educational module (HEM) tailored for parents of schoolchildren with overweight and obesity in the UAE. Methods The study was conducted in two phases: module development, and content and face validation. The module development involved an extensive review of national and international guidelines and previous research, followed by the design of infographic-based educational messages. Content and Face Validity were performed by six nutrition experts and 16 parents, respectively, using the Content Validity Index (CVI) and Face Validity Index (FVI). Results The final HEM consisted of 25 infographic messages covering dietary intake, physical activity, behavior change, and family engagement. The module achieved excellent content validity (S-CVI/Ave = 0.97) and face validity (S-FVI/Ave = 0.99). Participant feedback resulted in language refinement, improved illustrations, and removal of outdated elements such as the Food Pyramid. Conclusion The validated HEM is culturally relevant, parent-friendly, and scientifically grounded. It offers a structured, high-quality educational tool suitable for use in research, school-based initiatives, and public-health programs aimed at reducing childhood obesity in the UAE.

Direct and indirect benefits of cooperation in collective defense against predation

The evolution and maintenance of public goods cooperation, despite cheating, remains a key interest in social biology. Identifying how ecological factors determine the direct and indirect benefits that maintain cooperation has proven challenging, as these can vary significantly across species and environments. Here, we study this problem using the social pine sawfly Neodiprion sertifer (Hymenoptera) as a model system. During their larval stage, N. sertifer live in groups and collectively secrete a defensive fluid against predators. This behavior comprises a public good as it is costly to exhibit and beneficial to others, and individuals vary in their contribution to group defense. We experimentally manipulated individual contributions to defense to assess how these influence survival under natural insect predation. Our results indicate that defense has a group-level benefit as individuals were more likely to survive in cooperative groups with a higher proportion of defending larvae. Moreover, being able to deploy defensive fluid confers direct survival benefits. Genetic and phenotypic analyses of natural populations further show that kin selection promotes collective defense, as groups of larvae are often composed of full siblings. We also find that the contribution to defense is female-biased and diminishes in larger, more male-biased groups, and to some extent with decreased kinship, indicating that individuals adjust their contributions based on social context. Overall, we find that contribution to the collective defense provides both direct and indirect benefits and that individuals regulate their contributions mainly based on the social environment, resulting in variation within and among natural populations.

Enhancing cropping intensity and system productivity through early-bulking potato genotypes in potato-based cropping systems

Increasing cropping intensity is a key strategy for enhancing food production in regions facing shrinking arable land and rising population pressure. Early-bulking potato genotypes offer opportunities to redesign potato-based cropping systems by creating temporal space for additional crops. This study evaluated the agronomic performance, system productivity, economic returns, and land use efficiency of early-bulking potato genotypes (7 Alu and Sagitta ) within intensified potato-based cropping patterns at the Regional Agricultural Research Station (RARS), Burirhat, Rangpur, Bangladesh during the 2017–2018 cropping year. Thirteen cropping systems, including the conventional potato– boro rice–T. aman rice system, were assessed using a randomized complete block design with three replications. Results showed that incorporation of early-bulking potato genotypes enabled the inclusion of four to five crops per year, substantially increasing system productivity. Potato equivalent yield increased by 43.8–111.5% in the improved patterns compared with the conventional system. The highest land use efficiency (95.61%), whole pattern gross margin (Tk. 538775 ha −1 ), and marginal benefit-cost ratio (8.17) were achieved in the 7 Alu – garden pea – red amaranth – T. aus rice – T. aman rice pattern, while the highest potato equivalent yield (95.37 t ha −1 ) was recorded in the 7 Alu – cardinal – Mungbean – red amaranth – T. aman rice pattern. This study indicates that inclusion of early bulking potato varieties has the potential to serve as effective entry-point crops for intensifying potato-based cropping systems, improving land use efficiency and farm profitability. These findings represent promising outcomes from a single-season trial and highlight the potential of flexible cropping system designs that warrant further multi-year and multi-location validation.

Elevated phthalate exposure and metabolic susceptibility increased breast cancer risk: A 20-y follow-up study in Taiwan

Widely used phthalates, especially di-(2-ethylhexyl) phthalate (DEHP), increase breast cancer risk in experimental animals and humans, but long-term follow-up evidence of its human breast carcinogenicity remains inconclusive. This nested case–control study included 119 invasive breast cancer cases and 245 matched controls from a longitudinal cohort of 11,923 women recruited in 1991–1992 and followed to 2010 in Taiwan. Urine samples at baseline and follow-up visit were tested for 11 metabolites of seven phthalates using LC-ESI-MS/MS. DEHP metabolism susceptibility was evaluated by the percentage of mono-2-ethylhexyl phthalate (MEHP%) in the sum of five DEHP metabolites (∑DEHP). Odds ratios (ORs) with 95% CI from conditional logistic regression were used to examine risk predictors. DEHP was the only phthalate significantly associated with breast cancer risk. Risk increased significantly with elevated urinary levels of ∑DEHP (&gt; 0.381 μmol/g creatinine, OR = 1.71, 95% CI = 1.02 to 2.43), MEHP (&gt; 0.022 μmol/g creatinine, OR = 1.87, 95% CI = 1.07 to 3.25), and MEHP% (&gt; 6.7%, OR = 1.65, 95% CI = 0.96 to 2.82). Elevated ∑DEHP and MEHP% combined with early menarche (≤ 14 years) was associated with further increased risk (OR = 7.52, 95% CI = 2.68 to 21.05). The intraclass correlation coefficient between paired baseline and follow-up samples of 152 women was 0.06 for ∑DEHP and 0.31 for MEHP%. High DEHP exposure, high MEHP%, and early menarche were associated with increased breast cancer risk. MEHP% was a better biomarker for DEHP metabolism.

Hybrid deep learning and optimized variational mode decomposition for point-interval runoff prediction

Runoff prediction is crucial for water resource allocation and hydropower planning. To address low accuracy and uncertainty in runoff forecasting, this study proposes a framework integrating the Information Acquisition Optimizer (IAO), Variational Mode Decomposition (VMD), Convolutional Neural Network-Support Vector Machine (CNN-SVM), and Kernel Density Estimation (KDE) for interval prediction. An IAO-based optimized VMD (IVMD) is employed to decompose non-stationary runoff series and enhance feature extraction, with the resulting components used as inputs to the CNN-SVM model for point prediction. To quantify predictive uncertainty, KDE is applied to model the prediction error distribution, where a B-spline-based least squares cross-validation bandwidth selection method (LSCV-B) is adopted. By combining B-spline basis functions with data-driven cross-validation, LSCV-B overcomes the limited local adaptability of conventional AMISE-based bandwidth selection, enabling more accurate error density estimation and narrower prediction intervals with reliable coverage. Experiments in the Yangtze River Basin show that the IVMD-CNN-SVM framework reduces RMSE and MAPE by approximately 40–50% on the testing dataset compared with VMD-based counterparts, while producing highly reliable and compact 90% interval predictions.

RGS-YOLO: A lightweight solution for surface defect detection in wind turbines

The defects in wind turbines not only affect energy generation efficiency but can also lead to significant damage if not repaired promptly. To address the challenges of low detection efficiency and high costs in the real-world industrial scenario of wind turbine defect detection, we have designed a lightweight detection model. First, this study introduces Receptive-Field Attention Convolution(RFAConv) and develops the Cross Stage Partial with 2 convolutions and feature fusion-Receptive-Field Attention Convolution(C2f-RFAConv) module, integrating it into the backbone network. This approach allows the model to focus on spatial features while accurately capturing local information in each region through its receptive field, significantly enhancing its feature extraction capabilities. Additionally, we incorporate Group Shuffle Convolution(GSConv) in the neck network to ensure that the model remains lightweight while maintaining a high level of accuracy. In the design of the detection head, we leverage the low redundant computation capability of Spatial and Channel reconstruction Convolution(SCConv), along with its ability to promote the learning of representative features, to develop a detection head-SCConv Head-that integrates classification and detection with low computational cost and parameters. All experimental results are reported as the average of no fewer than three independent runs to ensure the stability and reliability of the results. Experimental results show that, compared to the original You Only Look Once version 8 nano(YOLOv8n), our model reduces its size by 1.16 MB and decreases the floating-point operations by 3.5 G while improving the mean Average Precision (mAP) by 3.7%. These results demonstrate the effectiveness of our model in achieving lightweight performance.

Bayesian hierarchical modelling of academic orientation and advising effects on student retention and progression: Multi-cohort evidence

Student retention and academic progression remain central concerns in higher education, particularly within contexts characterised by widening access and structural inequality. This study examines the independent and interactive effects of academic orientation performance and academic advising utilisation on first-year student retention and progression at a South African public university. Using administrative data from 8,300 undergraduate students across three entry cohorts spanning the 2023–2024 academic periods, we employ Bayesian hierarchical multivariate modelling to account for cohort-level variation and the interdependence between retention and progression outcomes. Retention is operationalised as enrolment in the subsequent academic year and is analysed only for cohorts with observable follow-up data (based on confirmed registration records), while academic progression is examined for all cohorts. Results indicate that stronger performance in academic orientation is positively associated with both retention and progression, while engagement with academic advising is associated with improved outcomes, particularly when combined with higher orientation performance. The observed interaction effects suggest complementary engagement between orientation and advising rather than differential treatment effectiveness, and all estimated relationships are interpreted as associative rather than causal. Model comparison results indicate statistically indistinguishable predictive performance between joint and univariate specifications, with the joint model offering additional inferential advantages by capturing correlations between outcomes. Overall, the findings highlight the value of integrated first-year support interventions and demonstrate the utility of Bayesian hierarchical approaches for analysing complex, multi-cohort educational data in Global South higher education contexts.

Divergent BLA engram circuits orchestrate social preference dynamics in bystander male mice with self-experienced stress

Personal experiences are encoded and stored in memory engram cells and are crucial for social preference dynamics in future social contexts, yet the neural circuit mechanisms involved are still poorly understood. Here, we develop a mouse model that combines self-experienced single social defeat stress with vicarious social defeat stress, demonstrating a social preference with defeat stress-experienced cagemate and social avoidance toward an aggressor. Basolateral amygdala engram cells (BLA EC ) exhibit significant activation, and chemogenetic manipulations confirm their sufficiency and necessity for both social preference and social avoidance behaviors. Virus-based cell-type-specific brain mapping suggests BLA EC project to anterior cingulate cortex (ACC) and these projections are also responsible for modulating social preference dynamics. Distinct projections from BLA-ACC circuit, including ventral/dorsal hippocampus and zona incerta, exert the diverse effects on these behaviors in male mice. Our findings reveal regulation of social preference dynamics by divergent circuits originating from BLA EC , which may contribute to the neurobiological mechanism of social psychopathologies.

Beyond direct-acting antiviral therapy: Characterizing mental health conditions and depressive symptoms among patients recently treated for hepatitis C

The uptake of hepatitis C virus (HCV) treatment, including among under-served populations, has improved significantly in the Direct Acting Antiviral (DAA) era. However, it is unclear whether patients undergoing HCV treatment are receiving adequate support to engage in healthcare for other concurrent conditions. We sought to characterize psychiatric disorders and depressive symptomatology among a cohort of patients recently treated for HCV. We conducted a secondary analysis using data from the Preservation of Sustained Virologic Response (Per-SVR) study, a prospective cohort of individuals who achieved sustained virologic response (SVR) following DAA treatment in British Columbia, Canada. After confirming SVR through receipt of an undetectable HCV viral load test within three months post-treatment, participants were enrolled in the study and completed interviewer-administered surveys. Logistic regression was used to characterize depressive symptoms and psychiatric diagnoses. Among 256 participants, 122 (48%) had significant depressive symptoms and 142 (55%) reported ever having been diagnosed with a psychiatric disorder. Less than half (44%) of those with depressive symptoms had ever been diagnosed with depressive disorder. Participants with depressive symptoms were more likely to report experiencing recent healthcare barriers (adjusted odds ratio: 2.27; 95% confidence interval: 1.02, 5.03). We observed a high prevalence of psychiatric comorbidity among a cohort of patients recently treated for HCV, highlighting an opportunity to engage HCV patients in mental health care. The integration of mental health screening and treatment alongside HCV care may improve health outcomes among HCV-affected populations.