8-Cl-Ado and 8-NH2-Ado synergize with venetoclax to target the methionine-MAT2A-SAM axis in acute myeloid leukemia.

Targeting the metabolic dependencies of acute myeloid leukemia (AML) cells is a promising therapeutical strategy. In particular, the cysteine and methionine metabolism pathway (C/M) is significantly altered in AML cells compared to healthy blood cells. Moreover, methionine has been identified as one of the dominant amino acid dependencies of AML cells. Through RNA-seq, we found that the two nucleoside analogs 8-chloro-adenosine (8CA) and 8-amino-adenosine (8AA) significantly suppress the C/M pathway in AML cells, and methionine-adenosyltransferase-2A (MAT2A) is one of most significantly downregulated genes. Additionally, mass spectrometry analysis revealed that Venetoclax (VEN), a BCL-2 inhibitor recently approved by the FDA for AML treatment, significantly decreases the intracellular level of methionine in AML cells. Based on these findings, we hypothesized that combining 8CA or 8AA with VEN can efficiently target the Methionine-MAT2A-S-adenosyl-methionine (SAM) axis in AML. Our results demonstrate that VEN and 8CA/8AA synergistically decrease the SAM biosynthesis and effectively target AML cells both in vivo and in vitro. These findings suggest the promising potential of combining 8CA/8AA and VEN for AML treatment by inhibiting Methionine-MAT2A-SAM axis and provide a strong rationale for our recently activated clinical trial.

Preclinical Evaluation of Off-The-Shelf PD-L1+ Human Natural Killer Cells Secreting IL15 to Treat Non-Small Cell Lung Cancer.

We described previously a human natural killer (NK) cell population that upregulates PD-L1 expression upon recognizing and reacting to tumor cells or exposure to a combination of IL12, IL18 and IL15. Here, to investigate the safety and efficacy of tumor-reactive and cytokine-activated (TRACK) NK cells, human NK cells from umbilical cord blood were expanded, transduced with a retroviral vector encoding soluble (s) IL15, and further cytokine activated to induce PD-L1 expression. Our results show cryopreserved and thawed sIL15_TRACK NK cells had significantly improved cytotoxicity against non-small cell lung cancer (NSCLC) in vitro when compared to non-transduced (NT) NK cells, PD-L1+ NK cells lacking sIL15 expression (NT_TRACK NK), or NK cells expressing sIL15 without further cytokine activation (sIL15 NK cells). Intravenous injection of sIL15_TRACK NK cells into immunodeficient mice with NSCLC significantly slowed tumor growth and improved survival when compared to NT NK and sIL15 NK cells. The addition of the anti-PD-L1 atezolizumab further improved control of NSCLC growth by sIL15_TRACK NK cells in vivo. Moreover, a dose-dependent efficacy was assessed for sIL15_TRACK NK cells without observed toxicity. These experiments indicate that the administration of frozen, off-the-shelf allogeneic sIL15_TRACK NK cells is safe in preclinical models of human NSCLC and has potent antitumor activity without and with the administration of atezolizumab. A Phase I clinical trial modeled after this preclinical study using sIL15_TRACK NK cells alone or with atezolizumab for relapsed or refractory NSCLC is currently underway (NCT05334329).

Assessing the 2023 Canadian wildfire smoke impact in Northeastern US: Air quality, exposure and environmental justice.

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM2.5 exposure to fully understand the environmental justice implications remains underinvestigated. This study aims to enhance the accuracy of estimating ground-level fine particulate matter (PM2.5) concentrations by fusing chemical transport model outputs with empirical observations, estimating exposures using human mobility data, and evaluating the impact of environmental justice. Employing a novel data fusion technique, the study combines the Weather Research and Forecasting model with Chemistry (WRF-Chem) outputs and surface PM2.5 measurements, providing a more accurate estimation of PM2.5 distribution. The study addresses the gap in traditional exposure assessments by incorporating human mobility data and further investigates the spatial correlation of PM2.5 levels with various environmental and demographic factors from the US Environmental Protection Agency (EPA) Environmental Justice Screening and Mapping Tool (EJScreen). Results reveal that despite reduced mobility during high PM2.5 levels from wildfire smoke, exposure for both residents and individuals on the move remains high. Regions already burdened with high environmental pollution levels face amplified PM2.5 effects from wildfire smoke. Furthermore, we observed mixed correlations between PM2.5 concentrations and various demographic and socioeconomic factors, indicating complex exposure patterns across communities. Urban areas, in particular, experience persistent high exposure, while significant correlations in rural areas with EJScreen factors highlight the unique vulnerabilities of these populations to smoke exposure. These results advocate for a comprehensive approach to environmental health that leverages advanced models, integrates human mobility data, and addresses socio-demographic disparities, contributing to the development of equitable strategies against the growing threat of wildfires.

Lights at night mediate depression-like behavioral and molecular phenotypes in a glucocorticoid-dependent manner in male rats.

Nocturnal light pollution, an underappreciated mood manipulator, disturbs the circadian rhythms of individuals in modern society. Preclinical and clinical studies have suggested that exposure to lights at night (LANs) results in depression-like phenotypes. However, the mechanism underlying the action of LANs remains unclear. Therefore, this study explored the potential influence of LANs on depression-related brain regions by testing brain-derived neurotrophic factor (BDNF), synaptic transmission, and plasticity in male Sprague-Dawley rats. Depression-related behavioral tests, enzyme-linked immunosorbent assays, and intracellular and extracellular electrophysiological recordings were performed. Resultantly, rats exposed to either white or blue LAN for 5 or 21 days exhibited depression-like behaviors. Both white and blue LANs reduced BDNF expression in the medial prefrontal cortex (mPFC) and ventrolateral periaqueductal gray (vlPAG). Moreover, both lights at night (LANs) elevated the plasma corticosterone levels. Pharmacologically, the activation of glucocorticoid receptors mimics the LAN-mediated effects on depression-like behaviors and reduces BDNF levels, whereas the inhibition of glucocorticoid receptors blocks LAN-mediated behavioral and molecular actions. Electrophysiologically, both LANs attenuated the stimulation-response curve, increased the paired-pulse ratio, and decreased the frequency and amplitude of miniature excitatory postsynaptic currents in the vlPAG. In the mPFC, LANs attenuate long-term potentiation and long-term depression. Collectively, these results suggested that white and blue LANs disturbed BDNF expression, synaptic transmission, and plasticity in the vlPAG and mPFC in a glucocorticoid-dependent manner. The results of the present study provide a theoretical basis for understanding the effects of nocturnal light exposure on depression-like phenotypes.

Injectable Bioadhesive Photocrosslinkable Hydrogels with Sustained Release of Kartogenin to Promote Chondrogenic Differentiation and Partial-Thickness Cartilage Defects Repair.

Partial-thickness cartilage defect (PTCD) is a common and formidable clinical challenge without effective therapeutic approaches. The inherent anti-adhesive characteristics of the extracellular matrix within cartilage pose a significant impediment to the integration of cells or biomaterials with the native cartilage during cartilage repair. Here, an injectable photocrosslinked bioadhesive hydrogel, consisting of gelatin methacryloyl (GM), acryloyl-6-aminocaproic acid-g-N-hydroxysuccinimide (AN), and poly(lactic-co-glycolic acid) microspheres loaded with kartogenin (KGN) (abbreviated as GM/AN/KGN hydrogel), is designed to enhance interfacial integration and repair of PTCD. After injected in situ at the irregular defect, a stable and robust hydrogel network is rapidly formed by ultraviolet irradiation, and it can be quickly and tightly adhered to native cartilage through amide bonds. The hydrogel exhibits good adhesion strength up to 27.25 ± 1.22 kPa by lap shear strength experiments. The GM/AN/KGN hydrogel demonstrates good adhesion, low swelling, resistance to fatigue, biocompatibility, and chondrogenesis properties in vitro. A rat model with PTCD exhibits restoration of a smoother surface, stable seamless integration, and abundant aggrecan and type II collagen production. The injectable stable adhesive hydrogel with long-term chondrogenic differentiation capacity shows great potential to facilitate repair of PTCD.

Understanding the bias of mobile location data across spatial scales and over time: A comprehensive analysis of SafeGraph data in the United States.

Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Without a clear understanding of the data representativeness, the interpretations of research based on mobile location data may be questionable. This article presents a comprehensive examination of the potential biases associated with mobile location data using SafeGraph Patterns data in the United States as a case study. The research rigorously scrutinizes and documents the bias from multiple dimensions, including spatial, temporal, urbanization, demographic, and socioeconomic, over a five-year period from 2018 to 2022 across diverse geographic levels, including state, county, census tract, and census block group. Our analysis of the SafeGraph Patterns dataset revealed an average sampling rate of 7.5% with notable temporal dynamics, geographic disparities, and urban-rural differences. The number of sampled devices was strongly correlated with the census population at the county level over the five years for both urban (r > 0.97) and rural counties (r > 0.91), but less so at the census tract and block group levels. We observed minor sampling biases among groups such as gender, age, and moderate-income, with biases typically ranging from -0.05 to +0.05. However, minority groups such as Hispanic populations, low-income households, and individuals with low levels of education generally exhibited higher levels of underrepresentation bias that varied over space, time, urbanization, and across geographic levels. These findings provide important insights for future studies that utilize SafeGraph data or other mobile location datasets, highlighting the need to thoroughly evaluate the spatiotemporal dynamics of the bias across spatial scales when employing such data sources.

Blue light at night produces stress-evoked heightened aggression by enhancing brain-derived neurotrophic factor in the basolateral amygdala.

Light is an underappreciated mood manipulator. People are often exposed to electronic equipment, which results in nocturnal blue light exposure in modern society. Light pollution drastically shortens the night phase of the circadian rhythm. Preclinical and clinical studies have reported that nocturnal light exposure can influence mood, such as depressive-like phenotypes. However, the effects of blue light at night (BLAN) on other moods and how it alters mood remain unclear. Here, we explored the impact of BLAN on stress-provoked aggression in male Sprague‒Dawley rats, focusing on its influence on basolateral amygdala (BLA) activity. Resident-intruder tests, extracellular electrophysiological recordings, and enzyme-linked immunosorbent assays were performed. The results indicated that BLAN produces stress-induced heightened aggressive and anxiety-like phenotypes. Moreover, BLAN not only potentiates long-term potentiation and long-term depression in the BLA but also results in stress-induced elevation of brain-derived neurotrophic factor (BDNF), mature BDNF, and phosphorylation of tyrosine receptor kinase B expression in the BLA. Intra-BLA microinfusion of BDNF RNAi, BDNF neutralizing antibody, K252a, and rapamycin blocked stress-induced heightened aggressive behavior in BLAN rats. In addition, intra-BLA application of BDNF and 7,8-DHF caused stress-induced heightened aggressive behavior in naïve rats. Collectively, these results suggest that BLAN results in stress-evoked heightened aggressive phenotypes, which may work by enhancing BLA BDNF signaling and synaptic plasticity. This study reveals that nocturnal blue light exposure may have an impact on stress-provoked aggression. Moreover, this study provides novel insights into the BLA BDNF-dependent mechanism underlying the impact of the BLAN on mood.

Therapeutic application of human type 2 innate lymphoid cells via induction of granzyme B-mediated tumor cell death.

The therapeutic potential for human type 2 innate lymphoid cells (ILC2s) has been underexplored. Although not observed in mouse ILC2s, we found that human ILC2s secrete granzyme B (GZMB) and directly lyse tumor cells by inducing pyroptosis and/or apoptosis, which is governed by a DNAM-1-CD112/CD155 interaction that inactivates the negative regulator FOXO1. Over time, the high surface density expression of CD155 in acute myeloid leukemia cells impairs the expression of DNAM-1 and GZMB, thus allowing for immune evasion. We describe a reliable platform capable of up to 2,000-fold expansion of human ILC2s within 4 weeks, whose molecular and cellular ILC2 profiles were validated by single-cell RNA sequencing. In both leukemia and solid tumor models, exogenously administered expanded human ILC2s show significant antitumor effects in vivo. Collectively, we demonstrate previously unreported properties of human ILC2s and identify this innate immune cell subset as a member of the cytolytic immune effector cell family.

Residential Segregation and County-Level COVID-19 Booster Coverage in the Deep South: Surveillance Report and Ecological Study.

BACKGROUND: COVID-19 had a greater impact in the Deep South compared with other regions in the United States. While vaccination remains a top priority for all eligible individuals, data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age are sparse. Despite existing evidence of racial and ethnic disparities in COVID-19 vaccinations at the individual level, there is an urgent need for evidence at the population level. Such information could highlight vulnerable communities and guide future health care policy-making and resource allocation. OBJECTIVE: We aimed to evaluate county-level COVID-19 booster coverage by age group in the Deep South and explore its association with residential segregation. METHODS: An ecological study was conducted at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of 5 Deep South states from December 15, 2021, to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster uptake by age group (eg, 12 to 17 years, 18 to 64 years, and at least 65 years) by the end of the study period. The longitudinal relationships were examined between residential segregation, the interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson model. RESULTS: As of October 19, 2022, among the 418 counties, the median of booster uptake was 40% (IQR 37.8%-43%). Compared with older adults (ie, at least 65 years; median 63.1%, IQR 59.5%-66.5%), youth (ie, 12 to 17 years; median 14.1%, IQR 11.3%-17.4%) and adults (ie, 18 to 64 years; median 33.4%, IQR 30.5%-36.5%) had lower percentages of booster uptake. There was geospatial heterogeneity in the county-level COVID-19 booster coverage. We found that higher segregated counties had lower percentages of booster coverage. Such relationships attenuated as time increased. The findings were consistent across the age groups. CONCLUSIONS: The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccination strategies should focus on youth and adults. Health care facilities and resources are needed in racial and ethnic minority communities.

Patterns and predictors of racial/ethnic disparities in HIV care continuum in the Southern USA: protocol for a population-based cohort study.

INTRODUCTION: Health disparities exist at every step of the HIV care continuum (HCC) among racial/ethnic minority population. Such racial/ethnic disparities may have significantly delayed the progress in HCC in the Southern US states that are strongly represented among geographic focus areas in the 2019 federal initiative titled 'Ending the HIV Epidemic: A Plan for America'. However, limited efforts have been made to quantify the long-term spatiotemporal variations of HCC disparities and their contributing factors over time, particularly in the context of COVID-19 pandemic. This project aims to identify the spatiotemporal patterns of racial disparities of each HCC outcome and then determine the contribution of contextual features for temporal change of disparities in HCC. METHODS AND ANALYSIS: This cohort study will use statewide HIV cohort data in South Carolina, including all people living with HIV (PLWH) who were diagnosed with HIV in 2005-2020. The healthcare encounter data will be extracted from longitudinal EHR from six state agencies and then linked to aggregated county-level community and social structural-level data (eg, structural racism, COVID-19 pandemic) from multiple publicly available data sources. The South Carolina Revenue of Fiscal and Affairs will serve as the honest broker to link the patient-level and county-level information. We will first quantify the HCC-related disparities by creating a county-level racial/ethnic disparity index (RDI) for each key HCC outcomes (eg, HIV testing, timely diagnosis), examine the temporal patterns of each RDI over time and then using geographical weighted lasso model examine which contextual factors have significant impacts on the change of county-level RDI from 2005 to 2020. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board at the University of South Carolina (Pro00121718) as a Non-Human Subject study. The study's findings will be published in peer-reviewed journals and disseminated at national and international conferences and through social media.

Understanding social risk factors of county-level disparities in COVID-19 tests per confirmed case in South Carolina using statewide electronic health records data.

BACKGROUND: COVID-19 testing is essential for pandemic control, and insufficient testing in areas with high disease burdens could magnify the risk of poor health outcomes. However, few area-based studies on COVID-19 testing disparities have considered the disease burden (e.g., confirmed cases). The current study aims to investigate socioeconomic drivers of geospatial disparities in COVID-19 testing relative to disease burden across 46 counties in South Carolina (SC) in the early (from April 1, 2020, to June 30, 2020) and later (from July 1, 2020, to September 30, 2021) phases of the pandemic. METHODS: Using SC statewide COVID-19 testing data, the COVID-19 testing coverage was measured by monthly COVID-19 tests per confirmed case (hereafter CTPC) in each county. We used modified Lorenz curves to describe the unequal geographic distribution of CTPC and generalized linear mixed-effects regression models to assess the association of county-level social risk factors with CTPC in two phases of the pandemic in SC. RESULTS: As of September 30, 2021, a total of 641,201 out of 2,941,227 tests were positive in SC. The Lorenz curve showed that county-level disparities in CTPC were less apparent in the later phase of the pandemic. Counties with a larger percentage of Black had lower CTPC during the early phase (ß = -0.94, 95%CI: -1.80, -0.08), while such associations reversed in the later phase (ß = 0.28, 95%CI: 0.01, 0.55). The association of some other social risk factors diminished as the pandemic evolved, such as food insecurity (ß: -1.19 and -0.42; p-value is < 0.05 for both). CONCLUSIONS: County-level disparities in CTPC and their predictors are dynamic across the pandemic. These results highlight the systematic inequalities in COVID-19 testing resources and accessibility, especially in the early stage of the pandemic. Counties with greater social vulnerability and those with fewer health care resources should be paid extra attention in the early and later phases, respectively. The current study provided empirical evidence for public health agencies to conduct more targeted community-based testing campaigns to enhance access to testing in future public health crises.

Integrating human activity into food environments can better predict cardiometabolic diseases in the United States.

The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.

Using geospatial social media data for infectious disease studies: a systematic review.

Geospatial social media (GSM) data has been increasingly used in public health due to its rich, timely, and accessible spatial information, particularly in infectious disease research. This review synthesized 86 research articles that use GSM data in infectious diseases published between December 2013 and March 2022. These articles cover 12 infectious disease types ranging from respiratory infectious diseases to sexually transmitted diseases with spatial levels varying from the neighborhood, county, state, and country. We categorized these studies into three major infectious disease research domains: surveillance, explanation, and prediction. With the assistance of advanced statistical and spatial methods, GSM data has been widely and deeply applied to these domains, particularly in surveillance and explanation domains. We further identified four knowledge gaps in terms of contextual information use, application scopes, spatiotemporal dimension, and data limitations and proposed innovation opportunities for future research. Our findings will contribute to a better understanding of using GSM data in infectious diseases studies and provide insights into strategies for using GSM data more effectively in future research.

Injectable Self-Expanding/Self-Propelling Hydrogel Adhesive with Procoagulant Activity and Rapid Gelation for Lethal Massive Hemorrhage Management.

Developing hydrogels that can quickly reach deep bleeding sites, adhere to wounds, and expand to stop lethal and/or noncompressible bleeding in civil and battlefield environments remains a challenge. Herein, an injectable, antibacterial, self-expanding, and self-propelling hydrogel bioadhesive with procoagulant activity and rapid gelation is reported. This hydrogel combines spontaneous gas foaming and rapid Schiff base crosslinking for lethal massive hemorrhage. Hydrogels have rapid gelation and expansion rate, high self-expanding ratio, excellent antibacterial activity, antioxidant efficiency, and tissue adhesion capacity. In addition, hydrogels have good cytocompatibility, procoagulant ability, and higher blood cell/platelet adhesion activity than commercial combat gauze and gelatin sponge. The optimized hydrogel (OD-C/QGQL-A30) exhibits better hemostatic ability than combat gauze and gelatin sponge in rat liver and femoral artery bleeding models, rabbit volumetric liver loss massive bleeding models with/without anticoagulant, and rabbit liver and kidney incision bleeding models with bleeding site not visible. Especially, OD-C/QGQL-A30 rapidly stops the bleedings from pelvic area of rabbit, and swine subclavian artery vein transection. Furthermore, OD-C/QGQL-A30 has biodegradability and biocompatibility, and accelerates Methicillin-resistant S. aureus (MRSA)-infected skin wound healing. This injectable, antibacterial, self-expanding, and self-propelling hydrogel opens up a new avenue to develop hemostats for lethal massive bleeding, abdominal organ bleeding, and bleeding from coagulation lesions.

Place Visitation Data Reveals the Geographic and Racial Disparities of COVID-19 Impact on HIV Service Utilization in the Deep South.

BACKGROUND: The COVID-19 pandemic has posed unprecedented pressure to health care systems, and interrupted health care delivery and access including HIV care in the United States' Deep South, which endures a double epidemic of HIV and COVID-19. Ryan White programs cover HIV care services for over half of PLWH in the Deep South. Given the important role of Ryan White programs, examining the visitation changes to Ryan White facilities during the pandemic offers insights into the impact of the pandemic on HIV healthcare utilization. OBJECTIVES: Analyze the geographic distribution of HIV facility visitors at the county level before and during the pandemic in the nine US states of Deep South (Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Texas) to reveal the geographic and racial disparity in visitation disruption caused by the pandemic. METHODS: We first extracted mobile device-based visitation data for Ryan White HIV facilities in the Deep South during 2019 and 2020. To quantify the disruption in visitations during 2020, we calculated the visitation reduction rate (VRR) for each county, using 2019 data as the baseline. Next, we conducted a spatial analysis of the VRR values to uncover geographical disparities in visitation interruptions. To investigate racial disparities, we performed spatial regression analyses with VRR as the dependent variable, and the percentages of Black, Hispanic, and Asian populations as the independent variables. In this analysis, we controlled for potential confounders. RESULTS: Geographic disparities in visitation reduction were observed, with all nine Deep South states experiencing significant drops. Georgia experienced the highest visitation loss (VRR = -0.58), followed by Texas (-0.47), Alabama (0.47), and Tennessee (-0.46), while South Carolina had the smallest reductions (-0.11). All the regression models consistently revealed racial disparities in visitation interruption. That is, counties with a higher proportion of Black population tended to have higher RW facility visitation reductions. CONCLUSIONS: Our analysis revealed distinct geographic disparities in visitation interruptions at Ryan White HIV facilities in the Deep South during the COVID-19 pandemic in 2020. Furthermore, we found that the Black/African American population experienced a greater disruption at the county level in the Deep South during this period.

The Impacts of HIV-Related Service Interruptions During the COVID-19 Pandemic: Protocol of a Mixed Methodology Longitudinal Study.

The global COVID-19 pandemic has imposed unprecedented pressure on health systems and has interrupted public health efforts for other major health conditions, including HIV. It is critical to comprehensively understand how the pandemic has affected the delivery and utilization of HIV-related services and what are the effective strategies that may mitigate the negative impacts of COVID-19 and resultant interruptions. The current study thus aims to comprehensively investigate HIV service interruptions during the pandemic following a socioecological model, to assess their impacts on various outcomes of the HIV prevention and treatment cascade and to identify resilience resources for buffering impacts of interruptions on HIV treatment cascade outcomes. We will assess HIV service interruptions in South Carolina (SC) since 2020 using operational report data from Ryan White HIV clinics and HIV service utilization data (including telehealth use) based on statewide electronic health records (EHR) and cellphone-based place visitation data. We will further explore how HIV service interruptions affect HIV prevention and treatment cascade outcomes at appropriate geospatial units based on the integration of multi-type, multi-source datasets (e.g., EHR, geospatial data). Finally, we will identify institutional-, community-, and structural-level factors (e.g., resilience resources) that may mitigate the adverse impacts of HIV service interruptions based on the triangulation of quantitative (i.e., EHR data, geospatial data, online survey data) and qualitative (i.e., in-depth interviews with clinic leaders, healthcare providers, people living with HIV, and HIV clinic operational reports) data regarding health system infrastructure, social capital, and organizational preparedness. Our proposed research can lead to a better understanding of complicated HIV service interruptions in SC and resilience factors that can mitigate the negative effects of such interruptions on various HIV treatment cascade outcomes. The multilevel resilience resources identified through data triangulation will assist SC health departments and communities in developing strategic plans in response to this evolving pandemic and other future public health emergencies (e.g., monkeypox, disasters caused by climate change). The research findings can also inform public health policymaking and the practices of other Deep South states with similar sociocultural contexts in developing resilient healthcare systems and communities and advancing epidemic preparedness.

Implications of inflammatory cell death-related IFNG and co-expressed RNAs (AC006369.1 and CCR7) in breast carcinoma prognosis, and anti-tumor immunity.

Objective: Interferon-γ (IFN-γ) encoded by IFNG gene is a pleiotropic molecule linked with inflammatory cell death mechanisms. This work aimed to determine and characterize IFNG and co-expressed genes, and to define their implications in breast carcinoma (BRCA). Methods: Transcriptome profiles of BRCA were retrospectively acquired from public datasets. Combination of differential expression analysis with WGCNA was conducted for selecting IFNG-co-expressed genes. A prognostic signature was generated through Cox regression approaches. The tumor microenvironment populations were inferred utilizing CIBERSORT. Epigenetic and epitranscriptomic mechanisms were also probed. Results: IFNG was overexpressed in BRCA, and connected with prolonged overall survival and recurrence-free survival. Two IFNG-co-expressed RNAs (AC006369.1, and CCR7) constituted a prognostic model that acted as an independent risk factor. The nomogram composed of the model, TNM, stage, and new event owned the satisfying efficacy in BRCA prognostication. IFNG, AC006369.1, and CCR7 were closely linked with the tumor microenvironment components (e.g., macrophages, CD4/CD8 T cells, NK cells), and immune checkpoints (notably PD1/PD-L1). Somatic mutation frequencies were 6%, and 3% for CCR7, and IFNG, and high amplification potentially resulted in their overexpression in BRCA. Hypomethylated cg05224770 and cg07388018 were connected with IFNG and CCR7 upregulation, respectively. Additionally, transcription factors, RNA-binding proteins, and non-coding RNAs possibly regulated IFNG and co-expressed genes at the transcriptional and post-transcriptional levels. Conclusion: Collectively, our work identifies IFNG and co-expressed genes as prognostic markers for BRCA, and as possible therapeutic targets for improving the efficacy of immunotherapy.

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. OBJECTIVE: This study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. METHODS: This study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. RESULTS: Twitter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533; P<.001); this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 (P<.001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. CONCLUSIONS: Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.

BTRX-246040 Acts Through the Ventrolateral Periaqueductal Gray to Exert Antidepressant-Relevant Actions in Mice.

BACKGROUND: BTRX-246040, a nociceptin/orphanin FQ peptide receptor antagonist, is being developed for the treatment of depressive patients. However, the underlying mechanism of this potential antidepressant is still largely unclear. Here, we studied the antidepressant-related actions of BTRX-246040 in the ventrolateral periaqueductal gray (vlPAG). METHODS: The tail suspension test, forced swim test, female urine sniffing test, sucrose preference test, and learned helplessness (LH) combined with pharmacological approaches were employed to examine the antidepressant-like effects and drug effects on LH-induced depressive-like behavior in C57BL/6J mice. Electrophysiological recordings in vlPAG neurons were used to study synaptic activity. RESULTS: Intraperitoneal administration of BTRX-246040 produced antidepressant-like behavioral effects in a dose-dependent manner. Systemic BTRX-246040 (10 mg/kg) resulted in an increased frequency and amplitude of miniature excitatory postsynaptic currents (EPSCs) in the vlPAG. Moreover, slice perfusion of BTRX-246040 directly elevated the frequency and amplitude of miniature EPSCs and enhanced the evoked EPSCs in the vlPAG, which were blocked by pretreatment with the nociceptin/orphanin FQ peptide receptor agonist Ro 64-6198. In addition, intra-vlPAG application of BTRX-246040 produced antidepressant-like behavioral effects in a dose-dependent manner. Moreover, intra-vlPAG pretreatment with 6-cyano-7-nitroquinoxaline-2,3-dione reversed both systemic and local BTRX-246040-mediated antidepressant-like behavioral effects. Furthermore, both systemic and local BTRX-246040 decreased the LH phenotype and reduced LH-induced depressive-like behavior. CONCLUSIONS: The results suggested that BTRX-246040 may act through the vlPAG to exert antidepressant-relevant actions. The present study provides new insight into a vlPAG-dependent mechanism underlying the antidepressant-like actions of BTRX-246040.

Association between immigrant concentration and mental health service utilization in the United States over time: A geospatial big data analysis.

Immigrants (foreign-born United States [US] citizens) generally have lower utilization of mental health services compared with US-born counterparts, but extant studies have not investigated the disparities in mental health service utilization within immigrant population nationwide over time. Leveraging mobile phone-based visitation data, we estimated the average mental health utilization in contiguous US census tracts in 2019, 2020, and 2021 by employing two novel outcomes: mental health service visits and visit-to-need ratio (i.e., visits per depression diagnosis). We then investigated the tract-level association between immigration concentration and mental health service utilization outcomes using mixed-effects linear regression models that accounted for spatial lag effects, time effects, and covariates. This study reveals spatial and temporal disparities in mental health service visits and visit-to-need ratio among different levels of immigrant concentration across the US, both before and during the pandemic. Tracts with higher concentrations of Latin American immigrants showed significantly lower mental health service utilization visits and visit-to-need ratio, particularly in the US West. Tracts with Asian and European immigrant concentrations experienced a more significant decline in mental health service utilization visits and visit-to-need ratio from 2019 to 2020 than those with Latin American concentrations. Meanwhile, in 2021, tracts with Latin American concentrations had the least recovery in mental health service utilization visits. The study highlights the potential of geospatial big data for mental health research and informs public health interventions.