Vehicle Behavior Discovery and Three-Dimensional Object Detection and Tracking Based on Spatio-Temporal Dependency Knowledge and Artificial Fish Swarm Algorithm.

In complex traffic environments, 3D target tracking and detection are often occluded by various stationary and moving objects. When the target is occluded, its apparent characteristics change, resulting in a decrease in the accuracy of tracking and detection. In order to solve this problem, we propose to learn the vehicle behavior from the driving data, predict and calibrate the vehicle trajectory, and finally use the artificial fish swarm algorithm to optimize the tracking results. The experiments show that compared with the CenterTrack method, the proposed method improves the key indicators of MOTA (Multi-Object Tracking Accuracy) in 3D object detection and tracking on the nuScenes dataset, and the frame rate is 26 fps.

Fabrication of TiN Coatings Deposited on Laser Shock Micro-Textured Substrates for Improving the Interface Adhesion Properties of Coatings.

This paper aims to investigate the strengthening mechanism of laser shock peening on the interfacial bonding properties between TiN coatings and TC4 titanium alloy substrates. The different surface textures were induced by LSP on a TC4 titanium alloy substrate. Subsequently, titanium nitride (TiN) coatings were deposited on the surface texture. A scratch test and reciprocating sliding wear assessment were conducted to evaluate the impact of LSP on the interfacial bonding properties and wear performance of the coatings. The experimental results demonstrated that the adhesion of TiN coatings deposited on the surface texture formed by laser shock peening was significantly enhanced. The efficacy of laser shock treatment in reducing wear rates was found to be significantly enhanced in cases of both increased spot overlapping rate and increased laser power density. The surface texture created using laser parameters of 6.43 GW/cm2 and a 50% overlapping rate was found to have the most significant effect on improving the adhesion and anti-wear properties of the coating. The laser shock texture was identified as the main contributor to this improvement, providing a large interfacial contact area and a mechanical bond between the coating and the substrate. This bond inhibited the initiation and propagation of micro-cracks caused by the concentration of internal stress and interfacial stress of the coating.

Social vulnerability and surgery outcomes: a cross-sectional analysis.

BACKGROUND: Post-operative complications present a challenge to the healthcare system due to the high unpredictability of their incidence. Socioeconomic conditions have been established as social determinants of health. However, their contribution relating to postoperative complications is still unclear as it can be heterogeneous based on community, type of surgical services, and sex and gender. Uncovering these relations can enable improved public health policy to reduce such complications. METHODS: In this study, we conducted a large population cross-sectional analysis of social vulnerability and the odds of various post-surgical complications. We collected electronic health records data from over 50,000 surgeries that happened between 2012 and 2018 at a quaternary health center in St. Louis, Missouri, United States and the corresponding zip code of the patients. We built statistical logistic regression models of postsurgical complications with the social vulnerability index of the tract consisting of the zip codes of the patient as the independent variable along with sex and race interaction. RESULTS: Our sample from the St. Louis area exhibited high variance in social vulnerability with notable rapid increase in vulnerability from the south west to the north of the Mississippi river indicating high levels of inequality. Our sample had more females than males, and females had slightly higher social vulnerability index. Postoperative complication incidence ranged from 0.75% to 41% with lower incidence rate among females. We found that social vulnerability was associated with abnormal heart rhythm with socioeconomic status and housing status being the main association factors. We also found associations of the interaction of social vulnerability and female sex with an increase in odds of heart attack and surgical wound infection. Those associations disappeared when controlling for general health and comorbidities. CONCLUSIONS: Our results indicate that social vulnerability measures such as socioeconomic status and housing conditions could affect postsurgical outcomes through preoperative health. This suggests that the domains of preventive medicine and public health should place social vulnerability as a priority to achieve better health outcomes of surgical interventions.

Inhibition of Ferroptosis by Mesenchymal Stem Cell-Derived Exosomes in Acute Spinal Cord Injury: Role of Nrf2/GCH1/BH4 Axis.

OBJECTIVE: The therapeutic benefits of exosomes obtained from mesenchymal stem cells (MSCs) in acute spinal cord injury (SCI) have been demonstrated in recent years, but the precise mechanisms remain unknown. In this study, the efficacy and mechanisms of MSC-derived exosomes (MSC-Exo) in acute SCI were investigated. METHODS: By utilizing a BV2 ferroptosis cellular model and an SCI rat model, we investigated the effects of MSC-Exo on iron death related indicators and NF-E2 related factor 2 (Nrf2)/GTP cyclolase I (GCH1)/5,6,7,8-tetrahydrobiopterin (BH4) signaling axis, as well as their therapeutic effects on SCI rats. RESULTS: The results revealed that MSC-Exo effectively inhibited the production of ferrous iron, lipid peroxidation products malonaldehyde and reactive oxygen species, and ferroptosis-promoting factor prostaglandin-endoperoxide synthase 2. Concurrently, they upregulated ferroptosis suppressors FTH-1 (ferritin heavy chain 1), SLC7A11 (solute carrier family 7 member 11), FSP1 (ferroptosis suppressor protein 1), and GPX4 (glutathione peroxidase 4), contributing to enhanced neurological recovery in SCI rats. Further analysis showed the Nrf2/GTP/BH4 signaling pathway's critical role in suppressing ferroptosis. Additionally, MSC-Exo was found to inhibit lipopolysaccharide-induced ferroptosis in BV2 cells and SCI rats by activating the Nrf2/GCH1/BH4 axis. CONCLUSION: In summary, the study demonstrates that MSC-Exo mitigates microglial cell ferroptosis via the Nrf2/GCH1/BH4 axis, showing potential for preserving and restoring neurological function post-SCI.

Nanozyme-Inhibited SERS Multichannel Paper-Based Sensor Array for the Quantification and Identification of Biothiols and Cancer Cells Based on Three Ag-Based Nanomaterials.

Biothiols play essential roles in maintaining normal physiological functions, resisting oxidative stress, and protecting cell health. Establishing an effective and reliable sensor array for the accurate quantification and discrimination of diverse biothiols is extremely meaningful. In this work, Ag/Mn3O4, Ag3PO4, and Ag3Cit with excellent oxidase-mimetic activity and surface-enhanced Raman scattering (SERS)-enhanced features have been prepared and loaded onto Whatman filter paper (WFP) to build SERS paper chips as three sensing channels, which can induce 3,3',5,5'-tetramethylbenzidine (TMB) oxidation to SERS-active reporters (TMBox) and concurrently generate prominent SERS signals. Nevertheless, the addition of biothiols can suppress conversion from TMB to TMBox, which can cause the reduction of the SERS signal from TMBox. Interestingly, each SERS sensing channel can generate different TMBox signals' variations due to differences in the oxidative inhibition abilities of diverse biothiols and exclusive properties of each paper chip, which can be plotted as specific fingerprint patterns of each biothiol and further translated into intuitive two-dimensional (2D) clustering profiles through linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) techniques for precise identification of these six biothiols with the minimum concentration of 1 µM. More importantly, this SERS sensor array is exploited for the precise quantification of intracellular glutathione (GSH), and can differentiate between normal and cancer cells based on different intracellular GSH contents and even identify different types of tumor cells, demonstrating its powerful application prospects in disease diagnosis.

The YY1-CPT1C signaling axis modulates the proliferation and metabolism of pancreatic tumor cells under hypoxia.

Carnitine palmitoyltransferase 1C (CPT1C) is an enzyme that regulates tumor cell proliferation and metabolism by modulating mitochondrial function and lipid metabolism. Hypoxia, commonly observed in solid tumors, promotes the proliferation and progression of pancreatic cancer by regulating the metabolic reprogramming of tumor cells. So far, the metabolic regulation of hypoxic tumor cells by CPT1C and the upstream mechanisms of CPT1C remain poorly understood. Yin Yang 1 (YY1) is a crucial oncogene for pancreatic tumorigenesis and acts as a transcription factor that is involved in multiple metabolic processes. This study aimed to elucidate the relationship between YY1 and CPT1C under hypoxic conditions and explore their roles in hypoxia-induced proliferation and metabolic alterations of tumor cells. The results showed enhancements in the proliferation and metabolism of PANC-1 cells under hypoxia, as evidenced by increased cell growth, cellular ATP levels, up-regulation of mitochondrial membrane potential, and decreased lipid content. Interestingly, knockdown of YY1 or CPT1C inhibited hypoxia-induced rapid cell proliferation and vigorous cell metabolism. Importantly, for the first time, we reported that YY1 directly activated the transcription of CPT1C and clarified that CPT1C was a novel target gene of YY1. Moreover, the YY1 and CPT1C were found to synergistically regulate the proliferation and metabolism of hypoxic cells through transfection with YY1 siRNA to CRISPR/Cas9-CPT1C knockout PANC-1 cells. Taken together, these results indicated that the YY1-CPT1C axis could be a new target for the intervention of pancreatic cancer proliferation and metabolism.

Estimation of optimal adherence threshold for tumor necrosis factor inhibitors in rheumatoid arthritis.

INTRODUCTION: Optimal adherence thresholds can vary across medications and disease states. The objective of the study was to determine the optimal threshold of the proportion of days covered (PDC) for tumor necrosis factor (TNF) inhibitors in patients with rheumatoid arthritis (RA). METHODS: Patients with RA initiating self-administered TNF inhibitors were identified using 2012-18 Medicare fee-for-service claims. Time-varying PDC was calculated every day for the preceding 90 days during follow-up. Oral and injected glucocorticoid use, hospitalizations, emergency room (ER) visits, serious infections, and a composite of these were measured as outcomes. Time to first occurrence of each outcome as a function of time-varying PDC for TNF inhibitors was evaluated using Cox regression. Incident/dynamic time-dependent receiver operating characteristic curves and Youden's J index were used to obtain the optimal PDC threshold for outcomes at 365 days. RESULTS: Of the 1190 patients who met the study inclusion criteria, almost 75% (865 patients) experienced at least one of the outcomes. Increasing PDC by 10% was significantly associated with decreased risks of the composite outcome (HR 0.98, 95% CI 0.96-1.00), oral glucocorticoid use (HR 0.93, 95% CI 0.91-0.96), and hospitalization (HR 0.96, 95% CI 0.94-0.99) but an increased risk of ER visits (HR 1.04, 95% 1.01-1.07). Optimal PDC thresholds for the composite outcome, oral glucocorticoid use, and hospitalization were 0.64, 0.59, and 0.56, respectively. CONCLUSIONS: Increased PDC was associated with a decreased risk of adverse outcomes, except ER visits. The optimal PDC for TNF inhibitors in Medicare patients with RA based on clinical outcomes was about 60%. Key Points • The optimal proportion of days covered threshold for tumor necrosis factor inhibitors at 365 days based on clinical outcomes was found to be about 60%, which is lower than the traditional 80% used to define adherence. • Increased adherence was associated with decreased risks of oral glucocorticoid use, hospitalization, and the composite outcome. However, it was also associated with an increased risk of emergency room visits. • The mean time-varying 90-day proportion of days covered decreased throughout the study starting 92% at day 1 of follow-up to 62% at day 365.

Study on the risk assessment of Pedestrian-Vehicle conflicts in channelized Right-Turn lanes based on the Hierarchical-Grey Entropy-Cloud model.

Channelized right-turn lanes (CRTLs) in urban areas have been effective in improving the efficiency of right-turning vehicles but have also presented negative impacts on pedestrian movement. Pedestrians experience confusion regarding the allocation of road space when crossing crosswalks within these areas, leading to frequent conflicts between pedestrians and motor vehicles. In this paper, considering the characteristics of pedestrian-vehicle conflicts at channelized right-turn lanes as well as the ambiguity and uncertainty of the causes, a comprehensive assignment combined with a cloud model is proposed as a risk evaluation model for pedestrian-vehicle conflicts. The study established a risk indicator system based on three aspects of the transportation system: pedestrians, motor vehicles, and the road environment. Combining the analytic hierarchy process (AHP), grey relational analysis (GRA), and entropy weighting method (EWM) to get the weights of indicator combinations, and then using the cloud model to realize quantitative and qualitative language transformation to complete the risk evaluation. This study employs specific road segments in Qingdao as a validation case for model analysis. The results indicate that the model's evaluation outcomes exhibited a significant level of agreement with the findings from field investigations during both peak and off-peak periods. It is demonstrated that the model has good performance for the safety assessment of pedestrian-vehicle conflicts at CRTL, and it also reflects the ability of the model to assess fuzzy randomness problems. It provides participation value for urban pedestrian-vehicle safety problems as well as applications in other fields.

PathFinder: a novel graph transformer model to infer multi-cell intra- and inter-cellular signaling pathways and communications.

Recently, large-scale scRNA-seq datasets have been generated to understand the complex signaling mechanisms within the microenvironment of Alzheimer's Disease (AD), which are critical for identifying novel therapeutic targets and precision medicine. However, the background signaling networks are highly complex and interactive. It remains challenging to infer the core intra- and inter-multi-cell signaling communication networks using scRNA-seq data. In this study, we introduced a novel graph transformer model, PathFinder, to infer multi-cell intra- and inter-cellular signaling pathways and communications among multi-cell types. Compared with existing models, the novel and unique design of PathFinder is based on the divide-and-conquer strategy. This model divides complex signaling networks into signaling paths, which are then scored and ranked using a novel graph transformer architecture to infer intra- and inter-cell signaling communications. We evaluated the performance of PathFinder using two scRNA-seq data cohorts. The first cohort is an APOE4 genotype-specific AD, and the second is a human cirrhosis cohort. The evaluation confirms the promising potential of using PathFinder as a general signaling network inference model.

On Transforming Reinforcement Learning With Transformers: The Development Trajectory.

Transformers, originally devised for natural language processing (NLP), have also produced significant successes in computer vision (CV). Due to their strong expression power, researchers are investigating ways to deploy transformers for reinforcement learning (RL), and transformer-based models have manifested their potential in representative RL benchmarks. In this paper, we collect and dissect recent advances concerning the transformation of RL with transformers (transformer-based RL (TRL)) to explore the development trajectory and future trends of this field. We group the existing developments into two categories: architecture enhancements and trajectory optimizations, and examine the main applications of TRL in robotic manipulation, text-based games (TBGs), navigation, and autonomous driving. Architecture enhancement methods consider how to apply the powerful transformer structure to RL problems under the traditional RL framework, facilitating more precise modeling of agents and environments compared to traditional deep RL techniques. However, these methods are still limited by the inherent defects of traditional RL algorithms, such as bootstrapping and the "deadly triad". Trajectory optimization methods treat RL problems as sequence modeling problems and train a joint state-action model over entire trajectories under the behavior cloning framework; such approaches are able to extract policies from static datasets and fully use the long-sequence modeling capabilities of transformers. Given these advancements, the limitations and challenges in TRL are reviewed and proposals regarding future research directions are discussed. We hope that this survey can provide a detailed introduction to TRL and motivate future research in this rapidly developing field.

Maternal exposure to heavy metals from industrial sources during pregnancy and childhood cancer risk in California.

OBJECTIVE: The study investigated maternal exposure to heavy metals from industrial sources during pregnancy as potential risk factors for childhood cancer. METHODS: Cases ages 0-19 were identified from California Cancer Registry. Controls (20:1 ratio) were randomly selected from California Birth Registry, frequency-matched by birth year (1998-2016). We estimated maternal exposure to lead, nickel and cobalt in ambient air from the Toxic Release Inventory. We examined "ever/never", and "high/low" exposures, categorized by median exposure. Models were adjusted for maternal age, race/ethnicity, method of payment for prenatal care, neighborhood socioeconomic status, and urban/rural residence. RESULTS: Among highly-exposed persons, lead was associated with an increased teratoma risk (aOR: 1.52; 95% CI: 0.97, 2.37), while nickel was associated with an increased rhabdomyosarcoma risk (aOR: 1.45; 95% CI: 1.03, 2.04). Cobalt was associated with an increased glioma risk (aOR: 2.25, 95% CI 1.39, 3.65) among ever-exposed persons. Inverse associations were found between Wilms tumor and nickel among the ever exposed and highly exposed (ever: aOR: 0.75; 95% CI: 0.59, 0.96; high: aOR: 0.64; 95% CI: 0.45, 0.93). CONCLUSIONS: Findings suggest air pollution from heavy metals released by industrial sources may elevate childhood cancer risk.

IDEAL-IQ measurement can distinguish dysplastic nodule from early hepatocellular carcinoma: a case-control study.

Background: Previous studies have confirmed that malignant transformation of dysplastic nodule (DN) into hepatocellular carcinoma (HCC) is accompanied by reduction of iron content in nodules. This pathological abnormality can serve as the basis for magnetic resonance imaging (MRI). This study was designed to identify the feasibility of iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantitative (IDEAL-IQ) measurement to distinguish early hepatocellular carcinoma (eHCC) from DN. Methods: We reviewed MRI studies of 35 eHCC and 23 DN lesions (46 participants with 58 lesions total, 37 males, 9 females, 31-80 years old). The exams include IDEAL-IQ sequence and 3.0T MR conventional scan [including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and Gadopentic acid (Gd-GDPA)-enhanced]. Then, 3 readers independently diagnosed eHCC, DN, or were unable to distinguish eHCC from DN using conventional MRI (CMRI), and then assessed R2* value of nodules [R2* value represents the nodule iron content (NIC)] and R2* value of liver background [R2* value represents the liver background iron content (LBIC)] with IDEAL-IQ. Statistical analysis was conducted using the t-test for comparison of means, the Mann-Whitney test for comparison of medians, the chi-square test for comparison of frequencies, and diagnostic efficacy was evaluated by using receiver operating characteristic (ROC) curve. Results: This study evaluated 35 eHCC participants (17 males, 6 females, 34-81 years old, nodule size: 10.5-27.6 mm, median 18.0 mm) and 23 DN participants (20 males, 3 females, 31-76 years old, nodule size: 16.30±4.095 mm). The NIC and ratio of NIC to LIBC (NIC/LBIC) of the eHCC group (35.926±12.806 sec-1, 0.327±0.107) was lower than that of the DN group (176.635±87.686 sec-1, 1.799±0.629) (P<0.001). Using NIC and NIC/LBIC to distinguish eHCC from DN, the true positive/false positive rates were 91.3%/94.3% and 87.0%/97.1%, respectively. The rates of CMRI, NIC and NIC/LBIC in diagnosis of eHCC were 77.1%, and 94.3%, 97.1%, respectively, and those of DN were 65.2%, 91.3%, and 87.0%, respectively. The diagnosis rate of eHCC and DN by CMRI was lower than that of NIC and NIC/LBIC (eHCC: P=0.03, 0.04, DN: P=0.02, 0.04). Conclusions: Using IDEAL-IQ measurement can distinguish DN from eHCC.

Online chasing action recruits both mirror neuron and mentalizing systems: A pilot fNIRS study.

Engaging in chasing, where an actor actively pursues a target, is considered a crucial activity for the development of social skills. Previous studies have focused predominantly on understanding the neural correlates of chasing from an observer's perspective, but the neural mechanisms underlying the real-time implementation of chasing action remain poorly understood. To gain deeper insights into this phenomenon, the current study employed functional near-infrared spectroscopy (fNIRS) techniques and a novel interactive game. In this interactive game, participants (N = 29) were tasked to engage in chasing behavior by controlling an on-screen character using a gamepad, with the goal of catching a virtual partner. To specifically examine the brain activations associated with the interactive nature of chasing, we included two additional interactive actions: following action of following the path of a virtual partner and free action of moving without a specific pursuit goal. The results revealed that chasing and following actions elicited activation in a broad and overlapping network of brain regions, including the temporoparietal junction (TPJ), medial prefrontal cortex (mPFC), premotor cortex (PMC), primary somatosensory cortex (SI), and primary motor cortex (M1). Crucially, these regions were found to be modulated by the type of interaction, with greater activation and functional connectivity during the chasing interaction than during the following and free interactions. These findings suggested that both the MNS, encompassing regions such as the PMC, M1 and SI, and the mentalizing system (MS), involving the TPJ and mPFC, contribute to the execution of online chasing actions. Thus, the present study represents an initial step toward future investigations into the roles of MNS and MS in real-time chasing interactions.

Effect of Machine Learning on Anaesthesiology Clinician Prediction of Postoperative Complications: The Perioperative ORACLE Randomised Clinical Trial.

Background: Anaesthesiology clinicians can implement risk mitigation strategies if they know which patients are at greatest risk for postoperative complications. Although machine learning models predicting complications exist, their impact on clinician risk assessment is unknown. Methods: This single-centre randomised clinical trial enrolled patients age ≥18 undergoing surgery with anaesthesiology services. Anaesthesiology clinicians providing remote intraoperative telemedicine support reviewed electronic health records with (assisted group) or without (unassisted group) also reviewing machine learning predictions. Clinicians predicted the likelihood of postoperative 30-day all-cause mortality and postoperative acute kidney injury within 7 days. Area under the receiver operating characteristic curve (AUROC) for the clinician predictions was determined. Results: Among 5,071 patient cases reviewed by 89 clinicians, the observed incidence was 2% for postoperative death and 11% for acute kidney injury. Clinician predictions agreed with the models more strongly in the assisted versus unassisted group (weighted kappa 0.75 versus 0.62 for death [difference 0.13, 95%CI 0.10-0.17] and 0.79 versus 0.54 for kidney injury [difference 0.25, 95%CI 0.21-0.29]). Clinicians predicted death with AUROC of 0.793 in the assisted group and 0.780 in the unassisted group (difference 0.013, 95%CI -0.070 to 0.097). Clinicians predicted kidney injury with AUROC of 0.734 in the assisted group and 0.688 in the unassisted group (difference 0.046, 95%CI -0.003 to 0.091). Conclusions: Although there was evidence that the models influenced clinician predictions, clinician performance was not statistically significantly different with and without machine learning assistance. Further work is needed to clarify the role of machine learning in real-time perioperative risk stratification. Trial Registration: ClinicalTrials.gov NCT05042804.

MiR-106a-5p targets PFKFB3 and improves sepsis through regulating macrophage pyroptosis and inflammatory response.

The enzyme 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase isoform 3 (PFKFB3) is a critical regulator of glycolysis and plays a key role in modulating the inflammatory response, thereby contributing to the development of inflammatory diseases such as sepsis. Despite its importance, the development of strategies to target PFKFB3 in the context of sepsis remains challenging. In this study, we employed a miRNA-based approach to decrease PFKFB3 expression. Through multiple meta-analyses, we observed a downregulation of miR-106a-5p expression and an upregulation of PFKFB3 expression in clinical sepsis samples. These changes were also confirmed in blood monocytes from patients with early sepsis and from a mouse model of lipopolysaccharide (LPS)-induced sepsis. Overexpression of miR-106a-5p significantly decreased the LPS-induced increase in glycolytic capacity, inflammatory response, and pyroptosis in macrophages. Mechanistically, we identified PFKFB3 as a direct target protein of miR-106a-5p and demonstrated its essential role in LPS-induced pyroptosis and inflammatory response in macrophages. Furthermore, treatment with agomir-miR-106a-5p conferred a protective effect in an LPS mouse model of sepsis, but this effect was attenuated in myeloid-specific Pfkfb3 KO mice. These findings indicate that miR-106a-5p inhibits macrophage pyroptosis and inflammatory response in sepsis by regulating PFKFB3-mediated glucose metabolism, representing a potential therapeutic option for the treatment of sepsis.

Directional thermal emission and display using pixelated non-imaging micro-optics.

Thermal radiation is intrinsically broadband, incoherent and non-directional. The ability to beam thermal energy preferentially in one direction is not only of fundamental importance, but it will enable high radiative efficiency critical for many thermal sensing, imaging, and energy devices. Over the years, different photonic materials and structures have been designed utilizing resonant and propagating modes to generate directional thermal emission. However, such thermal emission is narrowband and polarised, leading to limited thermal transfer efficiency. Here we experimentally demonstrate ultrabroadband polarisation-independent directional control of thermal radiation with a pixelated directional micro-emitter. Our compact pixelated directional micro-emitter facilitates tunable angular control of thermal radiation through non-imaging optical principles, producing a large emissivity contrast at different view angles. Using this platform, we further create a pixelated infrared display, where information is only observable at certain directions. Our pixelated non-imaging micro-optics approach can enable efficient radiative cooling, infrared spectroscopy, thermophotovoltaics, and thermal camouflaging.

Hemorrhagic Fever with Renal Syndrome Complicated by Acute Pancreatitis, High Intraocular Pressure, and Pulmonary Involvement: a Case Report.

Hemorrhagic fever with renal syndrome (HFRS), a naturally occurring epidemic disease, is primarily caused by hantaviruses. It frequently involves the lungs and is characterized by symptoms such as fever, hemorrhage, and renal failure. However, the occurrence of acute pancreatitis (AP) in HFRS patients can be neglected, and high intraocular pressure (IOP) is exceedingly uncommon. In this report, we discuss the case of a 30-year-old male who presented with fever, nausea, vomiting, and abdominal pain. Physical examination revealed extremity petechiae rashes and elevated IOP. Laboratory tests indicated coagulopathy and renal failure. A computed tomography scan confirmed AP. Further testing revealed a positive anti-hantavirus IgM antibody. The patient received supportive care, fluid hydration, hemofiltration, mannitol, brinzolamide, and brimonidine to reduce IOP. Three days post-admission, the patient developed shortness of breath and chest pain. Subsequent chest computed tomography revealed pulmonary edema and bilateral pleural effusion. Treatment included oxygen supply, respiratory support, and thoracentesis, with continued hemofiltration. The patient recovered, regaining normal pulmonary and renal functions and normalized IOP. This case underscores the importance of comprehensive evaluations and vigilant monitoring in HFRS patients, particularly measuring IOP in those with visual complaints, to save lives and reduce morbidity.

Combination therapy with oncolytic virus and T cells or mRNA vaccine amplifies antitumor effects.

Antitumor therapies based on adoptively transferred T cells or oncolytic viruses have made significant progress in recent years, but the limited efficiency of their infiltration into solid tumors makes it difficult to achieve desired antitumor effects when used alone. In this study, an oncolytic virus (rVSV-LCMVG) that is not prone to induce virus-neutralizing antibodies was designed and combined with adoptively transferred T cells. By transforming the immunosuppressive tumor microenvironment into an immunosensitive one, in B16 tumor-bearing mice, combination therapy showed superior antitumor effects than monotherapy. This occurred whether the OV was administered intratumorally or intravenously. Combination therapy significantly increased cytokine and chemokine levels within tumors and recruited CD8+ T cells to the TME to trigger antitumor immune responses. Pretreatment with adoptively transferred T cells and subsequent oncolytic virotherapy sensitizes refractory tumors by boosting T-cell recruitment, down-regulating the expression of PD-1, and restoring effector T-cell function. To offer a combination therapy with greater translational value, mRNA vaccines were introduced to induce tumor-specific T cells instead of adoptively transferred T cells. The combination of OVs and mRNA vaccine also displays a significant reduction in tumor burden and prolonged survival. This study proposed a rational combination therapy of OVs with adoptive T-cell transfer or mRNA vaccines encoding tumor-associated antigens, in terms of synergistic efficacy and mechanism.

Scalable decarboxylative trifluoromethylation by ion-shielding heterogeneous photoelectrocatalysis.

Electrochemistry offers a sustainable synthesis route to value-added fine chemicals but is often constrained by competing electron transfer between the electrode and redox-sensitive functionalities distinct from the target site. Here, we describe an ion-shielding heterogeneous photoelectrocatalysis strategy to impose mass-transfer limitations that invert the thermodynamically determined order of electron transfer. This strategy is showcased to enable decarboxylative trifluoromethylation of sensitive (hetero)arenes by using trifluoroacetate, an inexpensive yet relatively inert trifluoromethyl group (CF3) source. An ion-shielding layer, formed by trifluoroacetate anions electrostatically adsorbed on a positive molybdenum-doped tungsten trioxide (WO3) photoanode, prevents undesired electron transfer between substrates and photogenerated holes. The practicality of the developed method was demonstrated with robust photoanode stability (approximately 380 hours), a good substrate scope, and scaling capability to achieve 100-gram synthesis by using photoelectrochemical flow cells.

Genome-Wide Identification of GAST Family Members and Their Potential Roles in Epicotyl Dormancy in Chinese Cork Oak (Quercus variabilis).

Chinese cork oak (Quercus variabilis Blume) is a widespread tree species with high economic and ecological values. Chinese cork oak exhibits epicotyl dormancy, causing emergence heterogeneity and affecting the quality of seedling cultivation. Gibberellic acid-stimulated transcript (GAST) is a plant-specific protein family that plays a crucial regulatory role in plant growth, development, and seed germination. However, their evolution in Chinese cork oak and roles in epicotyl dormancy are still unclear. Here, a genome-wide identification of the GAST gene family was conducted in Chinese cork oak. Ten QvGAST genes were identified, and nine of them were expressed in seed. The physicochemical properties and promoter cis-acting elements of the selected Chinese cork oak GAST family genes indicated that the cis-acting elements in the GAST promoter are involved in plant development, hormone response, and stress response. Germinated seeds were subjected to gibberellins (GAs), abscisic acid (ABA), and fluridone treatments to show their response during epicotyl dormancy release. Significant changes in the expression of certain QvGAST genes were observed under different hormone treatments. QvGAST1, QvGAST2, QvGAST3, and QvGAST6 exhibited upregulation in response to gibberellin. QvGAST2 was markedly upregulated during the release of epicotyl dormancy in response to GA. These findings suggested that QvGAST2 might play an important role in epicotyl dormancy release. This study provides a basis for further analysis of the mechanisms underlying the alleviation of epicotyl dormancy in Chinese cork oak by QvGASTs genes.