Artiles
Open Access
Article
10 October 2025Immunoprofiling of Alcohol-Activated Hepatic Stellate Cells Reveals Mechanisms of Immune Evasion through NK/T Lymphocyte Checkpoint Signaling
Chronic alcohol consumption induces the pathogenic activation of hepatic stellate cells (HSC) and their conversion into proliferative myofibroblasts (Myo), which together constitute a disease hub in alcohol-associated liver disease (AALD). While natural killer (NK) lymphocytes efficiently target early activated HSC and ameliorate liver fibrosis in mouse models of diet- and alcohol-induced liver disease, late-activated HSC evade immune surveillance. To gain insight into evasive resistance mechanisms, we profiled the expression of immunoregulatory ligands by HSC and showed that HSC dynamically express CD80, a B7-family ligand that suppresses NK and T cell responses. Using a mouse model of acute-on-chronic alcohol consumption, we show that combined blockade of the CTLA-4//TIGIT/PD-1 inhibitory checkpoints overcomes this resistance mechanism, promoting the selective elimination of activated HSC (aHSC)/Myo, yet fails to diminish fibrosis or ameliorate liver function. Single-cell transcriptome profiling of liver non-parenchymal cells revealed that checkpoint blockade promotes hepatic infiltration of pro-fibrotic Th1 and Th17 T cell subpopulations, while decreasing immunosuppressive Treg. Strikingly, antibody-directed engagement of the PD-1 and TIGIT checkpoints also fails to reduce fibrosis or improve liver function. Thus, selective targeting of aHSC/Myo may be necessary to achieve significant therapeutic benefit.
Open Access
Article
09 October 2025Identification of Pathways That Drive Myofibroblast Transformation in Hypertrophic Scars
Hypertrophic scars (HTS) are a common complication of burn injuries and are characterized by excessive dermal fibrosis driven by the transformation of resident dermal fibroblasts to profibrotic myofibroblasts. Although single cell and bulk RNA transcriptomics analysis of HTS and normal skin tissue samples were performed previously, transcriptomics of the transformation of fibroblasts to myofibroblasts has not been studied. Here, we report the data obtained from RNA sequencing of fibroblasts before and after exposure to transforming growth factor beta 1 (TGF-β1) and highlight the pathways that are up- and down-regulated during myofibroblast transformation. Our results suggest increased cellular signalling and rewiring, proliferative surge, immune-like and metabolic reprogramming, and delayed structural remodelling as four groups of events during the transformation of human primary dermal fibroblasts to myofibroblasts.
Open Access
Case Report
09 October 2025A Case Report of Telehealth Assessment for Adolescent Anxiety, Depression and COVID-Related Grief
Rates of anxiety and depression in children and adolescents have steadily risen over the past decade, and the arrival of COVID-19 exacerbated existing psychological problems for many youth. In the context of these increased rates and the pandemic lockdown, telepsychology, including virtual assessment, evolved as a cornerstone of mental health practice. There are salient benefits to telepsychology, most notably its convenience and accessibility, which have contributed to its expanded application across different types of problems and populations. At the same time, it can pose challenges in acquiring a comprehensive picture of client functioning. This article presents a case study of an adolescent with combined anxiety and depression who was referred for teletherapy during COVID-19, with an emphasis on the assessment intake. Results from a multi-method approach to the assessment are provided along with a brief discussion of treatment and future implications for the practice of telepsychology with youth and families.
Open Access
Article
09 October 2025Preparation of CdS-BaZrO3 Heterojunction for Enhanced Photocatalytic Water-Splitting Hydrogen Production
Photocatalytic water splitting using solar light, a promising technical approach for hydrogen production. However, the slow charge transfer and rapid recombination of photogenerated charge carriers in photocatalysis limit their practical application. To address these issues, in this work, we successfully prepared a novel CdS-BaZrO3 (CdS-BZO3) heterojunction via a simple chemical-bath deposition method. The as-prepared heterojunctions facilitate the separation and transportation of photogenerated charges, while also maintaining the high redox-oxid ation ability of the photocatalysts. As a result, CdS-BZO3 heterojunctions show enhanced photocatalytic water-splitting hydrogen production ability without a co-catalyst. Especially, the optimized CdS-BZO3 sample exhibits high photocatalytic activity with a hydrogen production rate of 44.77 μmol/h, which is 4.4 and 2.9 times higher than that of BZO3 and CdS, respectively. At the same time, the CdS-BZO3 heterojunction exhibits good stability in the photocatalytic hydrogen production cycle test. This work provides a reference for the heterostructure construction of perovskite-based photocatalysts to improve photocatalytic performance.
Open Access
Review
09 October 2025Sitagliptin in Type 2 Diabetes Mellitus and Cardiovascular Disease: A Public Health and Health Equity Perspective
Type 2 diabetes mellitus and cardiovascular disease are interrelated conditions that disproportionately affect underserved populations, with compounded risk in communities facing systemic barriers to care. This review synthesizes clinical trial evidence, preclinical research, and public health perspectives to evaluate sitagliptin’s pharmacologic profile, safety, and potential vascular effects, particularly in resource-limited settings. Sitagliptin, the first FDA-approved oral DPP-4 inhibitor, demonstrates weight neutrality, minimal hypoglycemia risk, and renal dosing flexibility. Large cardiovascular outcomes trials confirm cardiovascular neutrality, while preclinical and animal studies suggest possible microvascular benefits. Despite superior cardiovascular outcomes with newer agents like GLP-1 receptor agonists and SGLT2 inhibitors, sitagliptin remains a practical option for patients who cannot access or tolerate these therapies, supported by oral dosing, low side-effect burden, and anticipated generic availability in the US. Its continued value is evident in U.S. safety-net systems such as federally qualified health centers (FQHCs), and globally in low- and middle-income countries where newer drugs remain unaffordable. Achieving meaningful public health impact will require pairing pharmacologic safety with structural access improvements, including expanded insurance coverage, protection of safety-net drug pricing programs, culturally tailored interventions, and inclusive research practices. Sitagliptin illustrates a broader principle in chronic disease care: even safe therapies cannot close disparities until equitable access.
Open Access
Review
29 September 2025Review of Gallium Nitride Devices and Integrated Circuits at High Temperatures
In various industrial applications, including aviation, electric vehicles, and drilling, the demand for semiconductor devices and associated circuits with high thermal stability is progressively increasing. Wide-bandgap semiconductor Gallium Nitride (GaN) devices exhibit the advantages of fast switching capability, low on-resistance, and the ability to operate at high temperatures. These advantages have made them potential candidates for integrated circuits in high-temperature environments in recent years. Lateral GaN devices promote monolithic integration, which consequently increases power density and reduces cost of cooling systems. Hence, it is worthwhile to investigate the performance of GaN devices in high-temperature environments. This review aims to present a thorough review of high-temperature characteristics of GaN devices and integrated circuits. The performance of GaN devices at high temperatures, such as threshold voltage，saturation current and on-resistance, has been reviewed in response to different structures. The underlying degradation mechanisms related to the intrinsic properties of structures and fabrication technology are discussed at high temperatures. The thermal performance of GaN small signal integrated circuits and power converters was presented. This paper systematically examines the advantages and challenges of GaN devices and integrated circuits at high temperature environments.
Open Access
Article
29 September 2025Multivariant Time-Series Forecasting Methodology for Product Demand Using Deep Learning and Large Language Models
Accurate demand Soothsaying is a crucial element in force chain operation and business planning. Traditional statistical ways don’t consider the nonlinear, dynamic, and interdependent nature of variables that drive product demand, including deal history, prices, seasonality, elevations, request changes, and profitable pointers. This design presents a sophisticated soothsaying frame for guidance from an artificial intelligence system, integrating soothsaying using deep literacy models together with large language models(LLMs), that can negotiate both accurate soothsaying and give practicable intelligence. The deep literacy infrastructures used in this study include Long Short Term Memory(LSTM), Reopened intermittent Units(GRU), and other Motor models for timeseries soothsaying, which optimize temporal dependences and the complex cross-variable relations. To further increase interpretability of the vaticinations, LLMs are useful agents to convert the specialized cast affair into a completely automated and enhanced mortal-readable textbook and reports to develop intelligence for decision timber. Prophetic modeling and naturally generated reporting lead to better delicacy and practicable intelligence for their businesses. This intelligence empowers businesses to create better procurement processes, improve inventory management, and develop more resilient supply chains relevant to today’s business environment.
Open Access
Review
29 September 2025Robot Grinding: From Frontier Hotspots to Key Technologies and Applications
Robot grinding technology has shown broad application prospects in the field of machining complex curved parts due to its high flexibility, strong adaptability, and high automation. However, industrial robots are generally only suitable for rough machining, and for semi-finishing and finishing, improving the machining accuracy of robots and the surface quality of parts is a key issue. This paper summarizes the current research status of robot grinding and provides a reference for realizing robot precision grinding. At present, the research on robot grinding technology mainly focuses on robot pose control, force/position hybrid control strategy, intelligent machining path planning, vibration suppression technology, compliance control, and so on, aiming at solving the key bottleneck problems such as low machining accuracy, large grinding force fluctuation and poor surface quality consistency caused by insufficient robot stiffness. Firstly, the development history of the robot grinding system and the research status of process technology are summarized systematically. Secondly, the analysis focuses on grinding path planning, programming technology, and robot compliance force control technology. Finally, the current status of optimization research in robot grinding technology is summarized. The overarching purpose of this paper is to provide a systematic analysis and a comprehensive reference framework, aiming to address the core challenges hindering the achievement of high-precision, consistent surface quality in robotic grinding manufacturing. Based on the summarized state-of-the-art, robot grinding technology development trend is also predicted.
Open Access
Opinion
29 September 2025Modeling Cardiac Response to Transient Hemodynamic Changes: Beyond dp/dt Max and New Insights from IVCO and ES Point Analysis
Traditional indices such as dp/dt max remain widely used in assessing ventricular contractility, yet their load-dependence limits clinical precision, particularly during dynamic hemodynamic shifts. This letter to the Editor advocates for a more physiologically grounded approach using dual pressure catheters equipped with two high-fidelity sensors, one in the left ventricle (LV) and one in the aorta, to capture real-time pressure gradients and valve events with high temporal resolution. When combined with transient inferior vena cava occlusion (IVCO), this setup enables accurate identification of the true end-systolic (ES) point, typically marked by dp/dt min or the dicrotic notch on the aortic pressure waveform. This method allows for the construction of more physiologically valid end-systolic pressure-volume relationships (ESPVR). It introduces the novel peak pressure end-systolic pressure-volume relationship (PPESPVR) model, which links peak LV pressure to the ES point within a single cardiac cycle. The resulting volume intercept (Vint) and end-systolic fraction (ESF) offer new insights into myocardial performance under varying preload and afterload conditions, without requiring extensive hemodynamic manipulation. This dual-sensor approach not only enhances diagnostic accuracy but also opens the door to real-time, patient-specific contractility assessment in both research and clinical settings.
Open Access
Review
29 September 2025Generative Artificial Intelligence for Function-Driven De Novo Enzyme Design
The de novo design of artificial enzymes with customized catalytic functions represents a long-standing challenge in synthetic biology. Recent breakthroughs in deep learning, particularly the rise of Generative Artificial Intelligence (GAI), have transformed enzyme design from structure-centric strategies toward function-oriented paradigms. This review outlines the emerging computational frameworks that now span the entire design pipeline, including active site design, backbone generation, inverse folding, and virtual screening. Detailed description of active site, called a theozyme, is designed to stabilize transition states and can be guided by density functional theory (DFT) calculations that define the geometry of key catalytic components. Guided by the theozyme, GAI approaches such as diffusion and flow-matching models enable the generation of protein backbones pre-configured for catalysis. Inverse folding methods, exemplified by ProteinMPNN and LigandMPNN, further incorporate atomic-level constraints to optimize sequence–function compatibility. To assess and optimize catalytic performance, virtual screening platforms such as PLACER allow evaluation of protein–ligand conformational dynamics under catalytically relevant conditions. Through representative case studies, we illustrate how GAI-driven frameworks facilitate the rational creation of artificial enzymes with architectures distinct from natural homologs, thereby enabling catalytic activities not observed in nature. With the rapid progress and widespread adoption of GAI, we anticipate that de novo enzyme design with customized catalytic functions will soon evolve into a mature and broadly applicable methodology.
