Geochemical characteristics, source analysis, influencing factors, and reserves of soil Selenium in Wuming, Guangxi, China.

Although selenium (Se) reserves are crucial for the development and exploitation of Se-rich resources in karst soil areas, research on these reserves is still limited. A comprehensive study was conducted in a typical karst region known for its Se richness. A total of 12,547 surface soil samples, 134 deep soil samples, and 60 soil profiles from various locations were systematically collected. The findings showed that the Se content in the surface soil ranged from 0.073 to 9.04 mg/kg, with a baseline level of 0.84 mg/kg. This underscores the high background level and moderate variability in the region. Surface soil Se exhibited a notable positive correlation with deep soil Se, and an inverse correlation with pH (p < 0.01). One-way analysis of variance indicated that land formations and soil structure were the primary determinants affecting the concentration of Se in the topsoil (p = 0.000), with parent rock type and land-use type following closely (p = 0.003). In addition, the study included an investigation of soil Se variations with depth using 60 soil profiles. Through this analysis, it was revealed that Se content exhibited an exponential change with depth. Multiple integrations were employed to derive formulas for calculating Se reserves in the 0-200 cm depth range. Following these calculations, the estimations of Se stockpile across diverse types of source materials, varieties of soils, and land management methods were determined, highlighting the findings using a passive construction. This paper lays the groundwork for advancing the extraction and application of Se.

Disease burden of breast cancer and risk factors in Europe 44 countries, 1990-2019: findings of the global burden of disease study 2019.

Background: Breast cancer (BC) represents a significant health challenge in Europe due to its elevated prevalence and heterogeneity. Despite notable progress in diagnostic and treatment methods, the region continues to grapple with rising BC burdens, with comprehensive investigations into this matter notably lacking. This study explores BC burden and potential contributing risk factors in 44 European countries from 1990 to 2019. The aim is to furnish evidence supporting the development of strategies for managing BC effectively. Methods: Disease burden estimates related to breast cancer from the Global Burden of Disease 2019(GBD2019) across Eastern, Central, and Western Europe were examined using Joinpoint regression for trends from 1990 to 2019. Linear regression models examined relationships between BC burden and Socio-demographic Index (SDI), healthcare access and quality (HAQ), and BC prevalence. We utilized disability-adjusted life year(DALY) proportions for each risk factor to depict BC risks. Results: In Europe, the BC burden was 463.2 cases per 100,000 people in 2019, 1.7 times the global burden. BC burden in women was significantly higher and increased with age. Age-standardized mortality and DALY rates of BC in Europe in 2019 decreased by 23.1%(average annual percent change: AAPC -0.92) and 25.9%(AAPC -1.02), respectively, compared to 1990, in line with global trends. From 1990 to 2019, age-standardized DALY declined faster in Western Europe (-34.8%, AAPC -1.49) than in Eastern Europe (-9.4%, AAPC -0.25) and Central Europe (-15.0%, AAPC -0.56). Monaco, Serbia, and Montenegro had the highest BC burden in Europe in 2019. BC burden was negatively correlated with HAQ. In addition, Alcohol use and Tobacco were significant risk factors for DALY. High fasting plasma glucose and obesity were also crucial risk factors that cannot be ignored in DALY. Conclusion: The burden of BC in Europe remains a significant health challenge, with regional variations despite an overall downward trend. Addressing the burden of BC in different regions of Europe and the increase of DALY caused by different risk factors, targeted prevention measures should be taken, especially the management of alcohol and tobacco should be strengthened, and screening services for BC should be popularized, and medical resources and technology allocation should be optimized.

Analysis on congestion mechanism of CAVs around traffic accident zones.

Unexpected traffic accidents cause traffic congestion and aggravate the unsafe situation on the roadways. Reducing the impact of such congestion by introducing Connected and Autonomous Vehicles (CAVs) into the traditional traffic flow is possible. It requires estimating the incident's duration and analyzing the incident's impact area to determine the appropriate strategy. To guide the driver in making efficient and accurate judgments and avoiding secondary traffic congestion, the Cooperative Adaptive Cruise Control (CACC) model with dynamic safety distance and the Intelligent Driver Model (IDM) based on the safety potential field theory are introduced to build the evolution model of accidental traffic congestion under diversion interference and non-interference. The Huatao Interchange section of the Inner Ring Highway in the Banan District of Chongqing, China, was selected as the test section for simulating mixed traffic flow under different CAVs permeability (Pc). The relationship between the evacuation time, evacuation traffic volume, and the accident impact degree index (including the farthest queue length and accident duration) under the diversion intervention scenario was analyzed, respectively. The results of the study indicate that the higher the penetration of CAVs, the more significant the improvement in traffic flow occupancy, flow, and speed. Diversion interventions reduce congestion, about 50 % of the duration without interventions, when Pc ≤ 80 %. The traffic volume of diversion interference is non-linearly positively correlated with the maximum queue length, and the earlier the interference time, the stronger the positive correlation. The negative correlation between the interference time and queue length is weak at low evacuation traffic volume. With the increase in evacuation traffic volume, the influence of evacuation time on queue length becomes stronger. The maximum queue length value interval under different conditions is [348 m, 3140 m], and the shortest evacuation time is [1649 s, 2834 s]. The traffic flow data obtained from the simulation are imported into the episodic traffic congestion evolution model. The congestion evaluation indexes are calculated under non-interference and interference measures and compared with the simulation results. The maximum relative error is within 5.38 %. The results can be of great significance in relieving congestion caused by traffic accidents and promptly restoring road capacity.

Moderate regulation of wheat B-starch ratio: Improvement of molecular structure, spatial conformation, aggregation behavior of reconstituted fermented doughs and its processing suitability.

Aiming to investigate the changes and effects of different particle sizes of wheat A/B starch during dough fermentation, the present study reconstituted A/B starch fractions in ratios of 100:0, 75:25, 50:50, 25:75, and 0:100, further blended with gluten and subjected to slight (20 min), medium (30 min), and high (60 min) fermentation processes by yeasts. Results showed that fermentation gas production promoted gluten network extension, inducing starch granule exposure and dough surface roughness. Also, fermentation fractured protein intermolecular disulfide bonds and decreased α-helix and ß-folded structure content, contributing to GMP, LPP, and SPP content decreases. Moreover, moderately increasing the B-starch ratio in the dough can improve gluten network stability, continuity, and air-holding capacity. The 25A-75B steam bread exhibited optimal processing suitability (better morphology, texture, and quality) due to its higher GMP and polymer protein content with lower free sulfhydryl and monomeric protein content. Further, conformational relationships indicated the key indicators influencing dough products' properties were free sulfhydryl content, GMP content, protein molecular weight distribution, and secondary structure. The obtained findings contributed to understanding the effect of wheat starch granule size distribution on dough processing behavior, and future targeted breeding for wheat cultivars with high B-starch content for improved fermentation pasta product qualities.

Cardiovascular toxic effects of nanoparticles and corresponding molecular mechanisms.

Rapid advancements in nanotechnology have been integrated into various disciplines, leading to an increased prevalence of nanoparticle exposure. The widespread utilization of nanomaterials and heightened levels of particulate pollution have prompted government departments to intensify their focus on assessing the safety of nanoparticles (NPs). The cardiovascular system, crucial for maintaining human health, has emerged as vulnerable to damage from nanoparticle exposure. A mounting body of evidence indicates that interactions can occur when NPs come into contact with components of the cardiovascular system, contributing to adverse cardiovascular disease (CVD). However, the underlying molecular mechanisms driving these events remain elusive. This work provides a comprehensive review of recent advance on nanoparticle-induced adverse cardiovascular events and offers insight into the associated molecular mechanisms. Finally, the influencing factors of NPs-induced cardiovascular toxicity are discussed.

Dual-Responsive Microsphere Based on Natural Sunflower Pollen for Hemostasis and Repair in Inflammatory Bowel Disease.

Noninvasive treatment of inflammatory bowel disease with lower gastrointestinal bleeding is a major clinical challenge. In this study, we designed an orally targeted microsphere based on sunflower pollen microcapsules to localize the site of inflammatory injury and promote hemostasis and tissue repair. Due to the Eudragit and ascorbate palmitate coatings, EL/AP@PS(t+Dex) demonstrates pH- and enzyme-responsive release of loaded drugs and helps to resist the harsh environment of the gastrointestinal tract. Both in vitro and in vivo experiments show the characteristics of inflammation targeting and mucosal adhesion, which reduce the systematic exposure and increase the local drug concentration. In the DSS model, orally administered EL/AP@PS(t+Dex) significantly alleviates hematochezia, inhabits intestinal inflammation, and remarkably promotes the recovery of the intestinal epithelial barrier to reduce the exposure of intestinal microvessels. Furthermore, EL/AP@PS(t+Dex) optimized the composition of intestinal microbiota, which benefits intestinal homeostasis. This finding provides a fundamental solution for the treatment of intestinal bleeding caused by inflammatory bowel disease (IBD).

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. METHODS: This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. RESULTS: The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-ß-D-glucan test (G test). CONCLUSION: We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

Conformal and conductive biofilm-bridged artificial Z-scheme system for visible light-driven overall water splitting.

Semi-artificial Z-scheme systems offer promising potential toward efficient solar-to-chemical conversion, yet sustainable and stable designs are currently lacking. Here, we developed a sustainable hybrid Z-scheme system capable for visible light-driven overall water splitting by integrating the durability of inorganic photocatalysts with the interfacial adhesion and regenerative property of bacterial biofilms. The Z-scheme configuration is fabricated by drop casting a mixture of photocatalysts onto a glass plate, followed by the growth of biofilms for conformal conductive paste through oxidative polymerization of pyrrole molecules. Notably, the system exhibited scalability indicated by consistent catalytic efficiency across various sheet areas, resistance observed by remarkable maintaining of photocatalytic efficiency across a range of background pressures, and high stability as evidenced by minimal decay of photocatalytic efficiency after 100-hour reaction. Our work thus provides a promising avenue toward sustainable and high-efficiency artificial photosynthesis, contributing to the broader goal of sustainable energy solutions.

Ion migration and dark current suppression in quasi-2D perovskite-based X-ray detectors.

Cesium-based lead-free double perovskite materials (Cs2AgBiBr6) have garnered significant attention in the X-ray detection field due to their environment friendly characteristics. However, their substantial ion migration properties lead to large dark currents and detection limits in Cs2AgBiBr6-based X-ray detectors, restricting the detection performance of the device. In terms of process technology, ultrasonic spraying is more suitable than a spin-coating method for fabricating large-area, micron-scale perovskite thick films, with higher cost-effectiveness, which is crucial for X-ray detection. This work introduces a BA+ (BA+ = CH3CH2CH2CH2NH3 +, n-butyl) source into the precursor solution and employs ultrasonic spraying to fabricate quasi-two-dimensional structured polycrystalline (BA)2Cs9Ag5Bi5Br31 perovskite thick films, developing a low-cost, eco-friendly X-ray detector with low dark current density and low detection limit. Characterization results reveal that the ion migration activation energy of (BA)2Cs9Ag5Bi5Br31 reaches 419 meV, approximately 17% higher than that of traditional three-dimensional perovskites, effectively suppressing perovskite ion migration and subsequently reducing the dark current. The (BA)2Cs9Ag5Bi5Br31-based X-ray detectors exhibit high resistivity (about 1.75 × 1010 Ω cm), low dark current density (66 nA cm-2), minimal dark current drift (0.016 pA cm-1 s-1 V-1), and detection limit (138 nGyair s-1), holding considerable promise for applications in low-noise, low-dose X-ray detection.

Correction of plasma fat-soluble vitamin levels by blood lipids in elderly patients with coronary heart disease.

This study aims to investigate the correlation between plasma fat-soluble vitamin levels and blood lipid in elderly patients with coronary heart disease (CHD). A total of 120 participants were enrolled, including 60 CHD patients and 60 controls without CHD. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify plasma levels of vitamins A, D3, E, and K. Data analysis was conducted using the statistical analysis system module of MetaboAnalyst 5.0. The CHD group showed significantly higher levels of plasma total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) but not high-density lipoprotein cholesterol (HDL-C) compared to controls. The CHD group exhibited significantly higher plasma levels of VA and VE, positively correlating with TC, TG, and LDL-C. After adjusted by TG levels, the CHD group had significantly lower plasma levels of VA and VE, negatively correlating with TC, TG, and LDL-C. The CHD group also had significantly lower concentrations of VD3, independent of TG modification, compared to controls. VD3 negatively correlated with TC, TG, and LDL-C. Elderly individuals with CHD display abnormal blood lipid metabolism, and fat-soluble vitamins adjusted by TG levels can more accurately and timely response to implicit fat-soluble vitamins deficiency in CHD patients.

Epidemiological characteristics and hospitalization burden analysis of pediatric inpatients with melanocytic nevi in China from 2016 to 2021: A nationwide retrospective study of 13,396 cases.

BACKGROUND: Melanocytic nevi typically appear in early childhood, and their removal is a common plastic surgery procedure performed on children. However, the epidemiological characteristics and hospitalization burden of children with melanocytic nevi have rarely been described in detail. METHODS: Medical records of pediatric inpatients with melanocytic nevi from January 1, 2016, to December 31, 2021, were collected from the Futang Research Center of Pediatric Development database in China. We then extracted and statistically analyzed the relevant information, including demographic characteristics, clinical information, hospitalization burden, and other basic information for each inpatient. RESULTS: Among the 13,396 inpatients with melanocytic nevi, the highest number of cases was found in East China, and most patients were residents of urban areas. Most hospitalized patients consisted of boys aged 7-12 years with melanocytic nevi. Lesion sites in the buttocks and lower limbs were most common among pediatric inpatients with melanocytic nevi. Compound nevi were the most common (38.50 %) histological subtype and the rate of conversion into melanoma was 1.02 % (137 inpatients) among pediatric inpatients with melanocytic nevi. The hospitalization burden for patients varied significantly based on factors such as the age of the patients undergoing surgery, year of hospitalization, site of the lesion, histological subtype, and surgical method. In general, if the patients' age was under 1 year, lesion site was located in face, and there was a need for excision combined with tissue expander can significantly increase the treatment fees for pediatric inpatients with melanocytic nevi. CONCLUSION: Given the increasing number and relatively large hospitalization burden among children with melanocytic nevi hospitalized in China, the government needs to pay more attention to this group and provide corresponding economic and policy support.

Association between circulatory complement activation and hypertensive renal damage: a case-control study.

OBJECTIVE: The aim of this study was to investigate the potential importance of complement system activation, with particular emphasis on the complement alternative pathway (AP), in the pathogenesis of hypertensive renal damage. METHODS: Serum complement C3, complement Factor H (CFH) and AP activation were assessed in 66 participants with established essential hypertension with renal damage (RD). Fifty-nine patients with age- and sex-matched essential hypertension without renal damage (NRD) and 58 healthy participants (normal) were selected. RESULTS: Our study revealed that C3 and AP50 continuously increased from normal to NRD to RD (p < 0.05, respectively), while CFH was significantly lower than that in NRD and healthy participants (p < 0.05, respectively). After multifactorial logistic regression analysis corrected for confounders, elevated serum C3 (p = 0.001) and decreased CFH (p < 0.001) were found to be independent risk factors for hypertension in healthy participants; elevated serum C3 (p = 0.034), elevated AP50 (p < 0.001), decreased CFH (p < 0.001), increased age (p = 0.011) and increased BMI (p = 0.013) were found to be independent risk factors for the progression of hypertension to hypertensive renal damage; elevated serum C3 (p = 0.017), elevated AP50 (p = 0.023), decreased CFH (p = 0.005) and increased age (p = 0.041) were found to be independent risk factors for the development of hypertensive renal damage in healthy participants. CONCLUSION: Abnormal activation of complement, particularly complement AP, may be a risk factor for the development and progression of hypertensive renal damage.

Discriminative analysis of schizophrenia and major depressive disorder using fNIRS.

BACKGROUND: Research into the shared and distinct brain dysfunctions in patients with schizophrenia (SCZ) and major depressive disorder (MDD) has been increasing. However, few studies have explored the application of functional near-infrared spectroscopy (fNIRS) in investigating brain dysfunction and enhancing diagnostic methodologies in these two conditions. METHODS: A general linear model was used for analysis of brain activation following task-state fNIRS from 131 patients with SCZ, 132 patients with MDD and 130 healthy controls (HCs). Subsequently, seventy-seven time-frequency analysis methods were used to construct new features of fNIRS, followed by the implementation of five machine learning algorithms to develop a differential diagnosis model for the three groups. This model was evaluated by comparing it to both a diagnostic model relying on traditional fNIRS features and assessments made by two psychiatrists. RESULTS: Brain activation analysis revealed significantly lower activation in Broca's area, the dorsolateral prefrontal cortex, and the middle temporal gyrus for both the SCZ and MDD groups compared to HCs. Additionally, the SCZ group exhibited notably lower activation in the superior temporal gyrus and the subcentral gyrus compared to the MDD group. When distinguishing among the three groups using independent validation datasets, the models utilizing new fNIRS features achieved an accuracy of 85.90 % (AUC = 0.95). In contrast, models based on traditional fNIRS features reached an accuracy of 52.56 % (AUC = 0.66). The accuracies of the two psychiatrists were 42.00 % (AUC = 0.60) and 38.00 % (AUC = 0.50), respectively. CONCLUSION: This investigation brings to light the shared and distinct neurobiological abnormalities present in SCZ and MDD, offering potential enhancements for extant diagnostic systems.

Identification and validation of a novel Parkinson-Glioma feature gene signature in glioma and Parkinson's disease.

Introduction: The prognosis for glioma is generally poor, and the 5-year survival rate for patients with this disease has not shown significant improvement over the past few decades. Parkinson's disease (PD) is a prevalent movement disorder, ranking as the second most common neurodegenerative disease after Alzheimer's disease. Although Parkinson's disease and glioma are distinct diseases, they may share certain underlying biological pathways that contribute to their development. Objective: This study aims to investigate the involvement of genes associated with Parkinson's disease in the development and prognosis of glioma. Methods: We obtained datasets from the TCGA, CGGA, and GEO databases, which included RNA sequencing data and clinical information of glioma and Parkinson's patients. Eight machine learning algorithms were used to identify Parkinson-Glioma feature genes (PGFGs). PGFGs associated with glioma prognosis were identified through univariate Cox analysis. A risk signature was constructed based on PGFGs using Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) method. We subsequently validated its predictive ability using various methods, including ROC curves, calibration curves, KM survival analysis, C-index, DCA, independent prognostic analysis, and stratified analysis. To validate the reproducibility of the results, similar work was performed on three external test datasets. Additionally, a meta-analysis was employed to observe the heterogeneity and consistency of the signature across different datasets. We also compared the differences in genomic variations, functional enrichment, immune infiltration, and drug sensitivity analysis based on risk scores. This exploration aimed to uncover potential mechanisms of glioma occurrence and prognosis. Results: We identified 30 PGFGs, of which 25 were found to be significantly associated with glioma survival. The prognostic signature, consisting of 19 genes, demonstrated excellent predictive performance for 1-, 2-, and 3-year overall survival (OS) of glioma. The signature emerged as an independent prognostic factor for glioma overall survival (OS), surpassing the predictive performance of traditional clinical variables. Notably, we observed differences in the tumor microenvironment (TME), levels of immune cell infiltration, immune gene expression, and drug resistance analysis among distinct risk groups. These findings may have significant implications for the clinical treatment of glioma patients. Conclusion: The expression of genes related to Parkinson's disease is closely associated with the immune status and prognosis of glioma patients, potentially regulating glioma pathogenesis through multiple mechanisms. The interaction between genes associated with Parkinson's disease and the immune system during glioma development provides novel insights into the molecular mechanisms and targeted therapies for glioma.

Antitumor Therapy through Photothermal Performance Synergized with Catalytic Activity Based on the Boron Cluster Supramolecular Frameworks.

Chemodynamic therapy (CDT) has received widespread attention as a tumor optical treatment strategy in the field of malignant tumor therapy. Nonmetallic multifunctional nanomaterials as CDT agents, due to their low toxicity, long-lasting effects, and safety characteristics, have promising applications in the integrated diagnosis and treatment of cancer. Here, we modified the supramolecular framework of boron clusters, coupled with a variety of dyes to develop a series of metal-free agent compounds, and demonstrated that these nonmetallic compounds have excellent CDT activities through experiments. Subsequently, the best performing Methylene Blue/[closo-B12H12]2- (MB@B12H12) was used as an example. Through theoretical calculations, electron paramagnetic resonance spectroscopy, and 808 nm light irradiation, we confirmed that MB@B12H12 exhibited photothermal performance and CDT activity further. More importantly, we applied MB@B12H12 to melanoma cells and subcutaneous tumor, demonstrating its effective suppression of melanoma growth in vitro and in vivo through the synergistic effects of photothermal performance and CDT activity. This study emphasizes the generalizability of the coupling of dyes to [closo-B12H12]2- with important clinical translational potential for CDT reagents. Among them, MB@B12H12 may have a brighter future, paving the way for the rapid development of metal-free CDT reagents.

Revisiting Solar Energy Flow in Nanomaterial-Microorganism Hybrid Systems.

Nanomaterial-microorganism hybrid systems (NMHSs), integrating semiconductor nanomaterials with microorganisms, present a promising platform for broadband solar energy harvesting, high-efficiency carbon reduction, and sustainable chemical production. While studies underscore its potential in diverse solar-to-chemical energy conversions, prevailing NMHSs grapple with suboptimal energy conversion efficiency. Such limitations stem predominantly from an insufficient systematic exploration of the mechanisms dictating solar energy flow. This review provides a systematic overview of the notable advancements in this nascent field, with a particular focus on the discussion of three pivotal steps of energy flow: solar energy capture, cross-membrane energy transport, and energy conversion into chemicals. While key challenges faced in each stage are independently identified and discussed, viable solutions are correspondingly postulated. In view of the interplay of the three steps in affecting the overall efficiency of solar-to-chemical energy conversion, subsequent discussions thus take an integrative and systematic viewpoint to comprehend, analyze and improve the solar energy flow in the current NMHSs of different configurations, and highlighting the contemporary techniques that can be employed to investigate various aspects of energy flow within NMHSs. Finally, a concluding section summarizes opportunities for future research, providing a roadmap for the continued development and optimization of NMHSs.

Biological Activity of Lactic Acid Bacteria Exopolysaccharides and Their Applications in the Food and Pharmaceutical Industries.

Exopolysaccharides are natural macromolecular bioactive substances produced by lactic acid bacteria. With their unique physiological activity and structural characteristics, they are gradually showing broad application prospects in the food and pharmaceutical industries. Exopolysaccharides have various biological functions, such as exerting antioxidant and anti-tumor activities and regulating gut microbiota. Meanwhile, as a food additive, exopolysaccharides can significantly enhance the taste and quality of food, bringing consumers a better eating experience. In the field of medicine, exopolysaccharides have been widely used as drug carriers due to their non-toxic properties and good biocompatibility. This article summarizes the biological activities of exopolysaccharides produced by lactic acid bacteria, their synthesis, and their applications in food and pharmaceutical industries, aiming to promote further research and development in this field.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets.

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Unveiling the metabolic and coagulation disruptions in SARS-CoV-2-associated acute macular neuroretinopathy: A case-control study.

SARS-CoV-2 infection has been associated with the increased incidence of acute macular neuroretinopathy (AMN), an infrequent ocular disorder. However, the precise mechanisms underpinning AMN in the context of SARS-CoV-2 infection (AMN-SARS-CoV-2) remain elusive. In this case-control study, 14 patients diagnosed with AMN-SARS-CoV-2 between 2022/12 and 2023/3 were enrolled and compared with 14 SARS-CoV-2-infected individuals without AMN, who served as controls (SARS-CoV-2-no AMN). Metabolomic profiling using ultrahigh-performance liquid chromatography-online electrospray mass spectrometry revealed significant alterations in serum metabolites in AMN-SARS-CoV-2 patients. Coagulation abnormalities were observed in AMN-SARS-CoV-2 patients, and their relationship with metabolic disorders was studied. Finally, a predictive model for AMN-SARS-CoV-2 was established. Seventy-six upregulated and 42 downregulated metabolites were identified in AMN-SARS-CoV-2 cases. Notably, arginine metabolism within the urea cycle was significantly altered, evidenced by variations in ornithine, citrulline,  l-proline, and ADAM levels, correlating with abnormal coagulation markers like platelet crit, fibrinogen degradation product, and fibrinogen. Additionally, increased arginase 1 (AGR1) activity within the urea cycle and reduced nitric oxide synthase activity were observed in AMN-SARS-CoV-2. The integration of urea cycle metabolite levels with coagulation parameters yielded a robust discriminatory model for AMN-SARS-CoV-2, as evidenced by an area under the curve of 0.96. The findings of the present study enhance our comprehension of the underlying metabolic mechanisms associated with AMN-SARS-CoV-2 and offer potential diagnostic markers for this uncommon ocular disorder within the context of SARS-CoV-2 infection.