New perspectives in prognostication of hepatocellular carcinoma: The role and clinical implications of transient receptor potential family genes.

The study titled "Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients" is a significant contribution to hepatocellular carcinoma (HCC) research, highlighting the role of transient receptor potential (TRP) family genes in the disease's progression and prognosis. Utilizing data from The Cancer Genome Atlas database, it establishes a new risk assessment model, emphasizing the interaction of TRP genes with tumor proliferation pathways, key metabolic reactions like retinol metabolism, and the tumor immune microenvironment. Notably, the overexpression of the TRPC1 gene in HCC correlates with poorer patient survival outcomes, suggesting its potential as a prognostic biomarker and a target for personalized therapy, particularly in strategies combining immunotherapy and anti-TRP agents.

Delay-Oriented Roadside Unit Deployment for Highway Intersections in Vehicular Ad Hoc Networks.

Optimizing the deployment of roadside units (RSUs) holds great potential for enhancing the delay performance of vehicular ad hoc networks. However, there has been limited focus on devising RSU deployment strategies tailored specifically for highway intersections. In this study, we introduce a novel probabilistic model to characterize events occurring around highway intersections. By leveraging this model, we analytically determine the expected event reporting delays for both highway segments and intersections. Subsequently, we propose an RSU deployment scheme specifically designed for highway intersections, aimed at minimizing the expected event reporting delay. To implement this scheme, we introduce an innovative algorithm named cooperative walking. Through illustrative examples, we demonstrate that our proposed RSU deployment strategy for highway intersections outperforms the commonly employed uniform RSU deployment scheme and the previously proposed balloon method in terms of delay performance.

Construction of a nomogram model to predict technical difficulty in performing laparoscopic sphincter-preserving radical resection for rectal cancer.

BACKGROUND: Colorectal surgeons are well aware that performing surgery for rectal cancer becomes more challenging in obese patients with narrow and deep pelvic cavities. Therefore, it is essential for colorectal surgeons to have a comprehensive understanding of pelvic structure prior to surgery and anticipate potential surgical difficulties. AIM: To evaluate predictive parameters for technical challenges encountered during laparoscopic radical sphincter-preserving surgery for rectal cancer. METHODS: We retrospectively gathered data from 162 consecutive patients who underwent laparoscopic radical sphincter-preserving surgery for rectal cancer. Three-dimensional reconstruction of pelvic bone and soft tissue parameters was conducted using computed tomography (CT) scans. Operative difficulty was categorized as either high or low, and multivariate logistic regression analysis was employed to identify predictors of operative difficulty, ultimately creating a nomogram. RESULTS: Out of 162 patients, 21 (13.0%) were classified in the high surgical difficulty group, while 141 (87.0%) were in the low surgical difficulty group. Multivariate logistic regression analysis showed that the surgical approach using laparoscopic intersphincteric dissection, intraoperative preventive ostomy, and the sacrococcygeal distance were independent risk factors for highly difficult laparoscopic radical sphincter-sparing surgery for rectal cancer (P < 0.05). Conversely, the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance was identified as a protective factor (P < 0.05). A nomogram was subsequently constructed, demonstrating good predictive accuracy (C-index = 0.834). CONCLUSION: The surgical approach, intraoperative preventive ostomy, the sacrococcygeal distance, and the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance could help to predict the difficulty of laparoscopic radical sphincter-preserving surgery.

Eugenol-loaded polyurethane gelatin dressing for efficient angiogenesis and antibacterial effects in refractory diabetic wound defect healing.

The amelioration of refractory diabetic ulcers presents a formidable conundrum on a global scale, attributable to the elevated peril of contagion and protracted convalescence durations. Within the purlieus of this reparative epoch, the deployment of efficacious wound coverings endowed with both angiogenesis and antibacterial attributes is of paramount significance. Hydrogel wound dressings are distinguished by their elevated biocompatibility, adhesive tenacity, and innate regenerative capacity. Eugenol, a substance distilled from the blossoms of the lilac, serves as a precursor to metformin and is known to impede the genesis of reactive oxygen species. Although its antibacterial effects have been extensively chronicled, the angiogenic ramifications of eugenol within the context of wound remediation remain under-investigated. This research aimed to evaluate the effectiveness of eugenol-infused hydrogel as a wound dressing material. In this context, polyurethane gelatin (PG) was combined with eugenol at concentrations of 0.5% and 1%, creating PG-eugenol hydrogel mixtures with specific mass ratios for both in vivo and in vitro assessments. The in vivo studies indicated that hydrogels infused with eugenol expedited diabetic wound healing by fostering angiogenesis. Enhanced healing was noted, attributed to improved antibacterial and angiogenic properties, increased cell proliferation, tissue regeneration, and re-epithelialization. The in vitro analyses revealed that eugenol-enriched hydrogels stimulated the growth of fibroblasts (HFF-1) and human umbilical vein endothelial cells (HUVECs) and exhibited antibacterial characteristics. This investigation confirms the potential of eugenol-laden hydrogels in effectively treating diabetic wound defects.

Interpretable machine learning for predicting chronic kidney disease progression risk.

Objective: Chronic kidney disease (CKD) poses a major global health burden. Early CKD risk prediction enables timely interventions, but conventional models have limited accuracy. Machine learning (ML) enhances prediction, but interpretability is needed to support clinical usage with both in diagnostic and decision-making. Methods: A cohort of 491 patients with clinical data was collected for this study. The dataset was randomly split into an 80% training set and a 20% testing set. To achieve the first objective, we developed four ML algorithms (logistic regression, random forests, neural networks, and eXtreme Gradient Boosting (XGBoost)) to classify patients into two classes-those who progressed to CKD stages 3-5 during follow-up (positive class) and those who did not (negative class). For the classification task, the area under the receiver operating characteristic curve (AUC-ROC) was used to evaluate model performance in discriminating between the two classes. For survival analysis, Cox proportional hazards regression (COX) and random survival forests (RSFs) were employed to predict CKD progression, and the concordance index (C-index) and integrated Brier score were used for model evaluation. Furthermore, variable importance, partial dependence plots, and restrict cubic splines were used to interpret the models' results. Results: XGBOOST demonstrated the best predictive performance for CKD progression in the classification task, with an AUC-ROC of 0.867 (95% confidence interval (CI): 0.728-0.100), outperforming the other ML algorithms. In survival analysis, RSF showed slightly better discrimination and calibration on the test set compared to COX, indicating better generalization to new data. Variable importance analysis identified estimated glomerular filtration rate, age, and creatinine as the most important predictors for CKD survival analysis. Further analysis revealed non-linear associations between age and CKD progression, suggesting higher risks in patients aged 52-55 and 65-66 years. The association between cholesterol levels and CKD progression was also non-linear, with lower risks observed when cholesterol levels were in the range of 5.8-6.4 mmol/L. Conclusions: Our study demonstrated the effectiveness of interpretable ML models for predicting CKD progression. The comparison between COX and RSF highlighted the advantages of ML in survival analysis, particularly in handling non-linearity and high-dimensional data. By leveraging interpretable ML for unraveling risk factor relationships, contrasting predictive techniques, and exposing non-linear associations, this study significantly advances CKD risk prediction to enable enhanced clinical decision-making.

Assessing the association between the circulating levels of inflammatory cytokines and the risk of tuberculosis: A bidirectional two-sample mendelian randomization study.

BACKGROUND: Numerous observational studies have previously reported an association between inflammatory cytokines and tuberculosis (TB). However, the causal relationship between these factors remains unclear. Consequently, we conducted two-sample Mendelian randomization (MR) analyses to ascertain the causal link between levels of inflammatory cytokines and the risk of TB. METHODS: Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene. SNP was obtained from genome-wide association studies (GWAS) of 8293 individuals of Finnish. TB data was obtained from the UK Biobank, which included 46,293 individuals of European ancestry (comprising 2277 TB cases and 46,056 controls). Two-sample, bi-directional MR analyses using inverse-variance weighted (IVW) method as the primary analysis. Followed by comprehensive sensitivity analyses to validate the robustness of results. RESULT: The study showed that the causal relationship between circulating levels of interleukin (IL)-7 and risk of TB (odds ratio [OR] = 1.001, 95% confidence intervals [CIs]: 1.000, 1.003. p = 0.047). No causal associations were observed between other influencing factors and the occurrence of TB. Furthermore, the analysis revealed that TB infection exhibited negative causal associations with macrophage inflammatory protein 1 alpha ([MIP-1α], OR = 0.007, 95% CI: 0.000, 0.192. p = 0.004), IL-2 (OR = 0.014, 95% CI: 0.010, 0.427. p = 0.014), interleukin-2 receptor alpha chain([IL-2rα], OR = 0.019, 95% CI: 0.001, 0.525. p = 0.019) and basic fibroblast growth factor ([bFGF], OR = 0.066, 95% CI: 0.006, 0.700. p = 0.024). CONCLUSION: The study has illuminated the causal link between inflammatory cytokines and TB, thereby enhancing our comprehension of the potential mechanisms underlying TB pathogenesis. This discovery offers promising avenues for the identification of novel therapeutic targets in TB treatment. These insights may ultimately pave the way for more effective treatment approaches, thereby improving patient outcomes.

Weighted gene coexpression network analysis and machine learning reveal oncogenome associated microbiome plays an important role in tumor immunity and prognosis in pan-cancer.

BACKGROUND: For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation. METHODS: The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations. RESULTS: We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer. CONCLUSION: There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research.

Genetically predicted circulating levels of cytokines and the risk of depression: a bidirectional Mendelian-randomization study.

Objective: Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Method: Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Result: A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1ß, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, p = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, p = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, p = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Conclusion: Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved.

Intratumour microbiome of pancreatic cancer.

Pancreatic cancer is a high mortality malignancy with almost equal mortality and morbidity rates. Both normal and tumour tissues of the pancreas were previously considered sterile. In recent years, with the development of technologies for high-throughput sequencing, a variety of studies have revealed that pancreatic cancer tissues contain small amounts of bacteria and fungi. The intratumour microbiome is being revealed as an influential contributor to carcinogenesis. The intratumour microbiome has been identified as a crucial factor for pancreatic cancer progression, diagnosis, and treatment, chemotherapy resistance, and immune response. A better understanding of the biology of the intratumour microbiome of pancreatic cancer contributes to the establishment of better early cancer screening and treatment strategies. This review focuses on the possible origins of the intratumour microbiome in pancreatic cancer, the intratumour localization, the interaction with the tumour microenvironment, and strategies for improving the outcome of pancreatic cancer treatment. Thus, this review offers new perspectives for improving the prognosis of pancreatic cancer.

Immuno-oncology-microbiome axis of gastrointestinal malignancy.

Research on the relationship between the microbiome and cancer has been controversial for centuries. Recent works have discovered that the intratumor microbiome is an important component of the tumor microenvironment (TME). Intratumor bacteria, the most studied intratumor microbiome, are mainly localized in tumor cells and immune cells. As the largest bacterial reservoir in human body, the gut microbiome may be one of the sources of the intratumor microbiome in gastrointestinal malignancies. An increasing number of studies have shown that the gut and intratumor microbiome play an important role in regulating the immune tone of tumors. Moreover, it has been recently proposed that the gut and intratumor microbiome can influence tumor progression by modulating host metabolism and the immune and immune tone of the TME, which is defined as the immuno-oncology-microbiome (IOM) axis. The proposal of the IOM axis provides a new target for the tumor microbiome and tumor immunity. This review aims to reveal the mechanism and progress of the gut and intratumor microbiome in gastrointestinal malignancies such as esophageal cancer, gastric cancer, liver cancer, colorectal cancer and pancreatic cancer by exploring the IOM axis. Providing new insights into the research related to gastrointestinal malignancies.

Global burden and risk factors of musculoskeletal disorders among adolescents and young adults in 204 countries and territories, 1990-2019.

BACKGROUND: Current studies on musculoskeletal (MSK) disorders mainly focus on the elderly, while adolescents and young adults (AYAs) are often neglected despite their unique epidemiology, healthcare needs and societal implications. To bridge this gap, we evaluated the global burden and temporal trends of MSK disorders among AYAs from 1990 to 2019, as well as their common categories and main risk factors. METHODS: Data on the global burden and risk factors of MSK disorders were obtained from the Global Burden of Diseases study 2019. Age standardized rates for incidence, prevalence and disability-adjusted life-years (DALYs) were calculated using the world population age standard, and their temporal trends were evaluated by estimated annual percentage changes (EAPC). Locally estimated scatterplot smoothing (LOESS) regression was used to explore the association between two variables. RESULTS: Over the past 30 years, MSK disorders have become the third leading cause of global DALYs among AYAs, with 36.2%, 39.3%, and 21.2% of increases in incident cases, prevalent cases and DALYs, respectively. In 2019, age standardized incidence, prevalence and DALY rates for MSK disorders were positivity associated with socio-demographic index (SDI) among AYAs in 204 countries and territories. The global age-standardized prevalence and DALY rates of MSK disorders began to increases among AYAs since 2000. In the last decade, countries with high SDI not only presented the only increase in age-standardized incidence rate across all SDI quintiles (EAPC = 0.40, 0.15 to 0.65), but also displayed the most rapid increases in age-standardized prevalence and DALY rates (EAPC = 0.41, 0.24 to 0.57; 0.39, 0.19 to 0.58, respectively). Low back pain (LBP) and neck pain (NP) were the most common MSK disorders among AYAs, accounting for 47.2% and 15.4% of global DALYs of MSK disorders in this population, respectively. Rheumatoid arthritis (RA), osteoarthritis (OA), and gout exhibited increasing trends in global age-standardized incidence, prevalence, and DALY rates among AYAs over the past 30 years (all EAPC >0), whereas LBP and NP showed declining trends (all EAPC <0). Occupational ergonomic factors, smoking and high BMI accounted for 13.9%, 4.3%, and 2.7% of global DALYs for MSK disorders among AYAs, respectively. The proportion of DALYs attributable to occupational ergonomic factors was negatively associated with SDI, whereas the proportions attributable to smoking and high BMI increased with SDI. Over the last 30 years, both the proportions of DALYs attributable to occupational ergonomic factors and smoking have consistently decreased globally and across all SDI quintiles, while the proportion attributable to high BMI has increased. CONCLUSIONS: MSK disorders have emerged as the third leading cause of global DALYs among AYAs over the past three decades. Countries with high SDI should make more efforts to tackle the dual challenges posed by the high levels and rapid increases in age standardized incidence, prevalence, and DALY rates in the last decade.

Cu-MOFs based photocatalyst triggered antibacterial platform for wound healing: 2D/2D Schottky junction and DFT calculation.

Herein, we developed a multimodal antibacterial nanoplatform via synergism effect including knife-effect, photothermal, photocatalytic induced reactive oxygen species (ROS), and Cu2+ inherent attribute. Typically, 0.8-TC/Cu-NS possesses higher photothermal property with the higher photothermal conversion efficiency of 24% and the moderate temperature up to 97 °C. Meanwhile, 0.8-TC/Cu-NS exhibits the more active ROS, 1O2 and ·O2-. Hence, 0.8-TC/Cu-NS possesses best antibacterial properties against S. aureus and E. coli in vitro with efficiency of 99.94%/99.97% under near-infrared (NIR) light, respectively. In the therapeutic practical use for wound healing of Kunming mice, this system exhibits outstanding curing capacity and good biocompatibility. Based on the electron configuration measurement and density functional theory (DFT) simulation, it is confirmed that the electrons on CB of Cu-TCPP flow fleetingly to MXene trough the interface, with redistribution of charge and band upward bending over Cu-TCPP. As a result, the self-assembled 2D/2D interfacial Schottky junction have made great favor to accelerate photogenerated charges mobility, hamper charge recombination, and increases the photothermal/photocatalytic activity. This work gives us a hint to mostly design the multimodal synergistic nanoplatform under NIR light in biological applications without drug resistance.

Euphejolkinolide A, a new ent-abietane lactone from Euphorbia peplus L. with promising biological activity in activating the autophagy-lysosomal pathway.

A new ent-abietane diterpenoid, named Euphejolkinolide A (1), was isolated from the whole plant of Euphorbia peplus L. Its structure, including absolute configurations, was determined by spectroscopic analyses and was corroborated by single-crystal X-ray diffraction analysis. This new compound was assessed for its activity to induce lysosome biogenesis through Lyso-Tracker Red staining, in which compound 1 could significantly induce lysosome biogenesis. In addition, quantitative real-time PCR (qRT-PCR) analysis demonstrated a direct correlation between the observed lysosome biogenesis and the transcriptional activation of the lysosomal genes after treatment with the compound 1. Moreover, compound 1 promoted autophagic flux by upregulating LC3-II and downregulating SQSTM1 in both human microglia cells and U251 cells, which is required for cellular homeostasis. Further results suggested 1 induced lysosome biogenesis and autophagy which was mediated by TFEB (transcription factor EB). The structure activity relationships (SAR) analysis suggested that the carbony1 at C-7 in 1 might be a key active group. Overall, the current data suggested that 1 could be a potential compound for lysosome disorder therapy by induction of autophagy.

Liver infiltration of multiple immune cells during the process of acute liver injury and repair.

BACKGROUND: Immune cells, including neutrophils, natural killer (NK) cells, T cells, NKT cells and macrophages, participate in the progression of acute liver injury and hepatic recovery. To date, there has been no systematic study on the quantitative changes in these different immune cells from initial injury to subsequent recovery. AIM: To investigate the infiltration changes of various immune cells in acute liver injury models over time, and to study the relationship between the changes in leukocyte cell-derived chemotaxin 2 (LECT2) and the infiltration of several immune cells. METHODS: Carbon tetrachloride- and concanavalin A-induced acute liver injury models were employed to mimic toxin-induced and autoimmune-mediated liver injury respectively. The quantitative changes in various immune cells were monitored at different time points. Serum samples were collected, and liver tissues were harvested. Ly6G, CD161, CD4, CD8 and F4/80 staining were used to indicate neutrophils, NK/NKT cells, CD4+ T cells, CD8+ T cells and macrophages, respectively. Lect2-KO mice were used to detect the function of LECT2. RESULTS: During the injury and repair process, different types of immune cells began to increase, reached their peaks and fell into decline at different time points. Furthermore, when the serum alanine transaminase (ALT) and aspartate transaminase (AST) indices reverted to normal levels 7 d after the injury, the infiltration of immune cells still existed even 14 d after the injury, showing an obvious lag effect. We found that the expression of LECT2 was upregulated in acute liver injury mouse models, and the liver injuries of Lect2-KO mice were less severe than those of wild-type mice. Compared with wild-type mice, Lect2-KO mice had different immune cell infiltration. CONCLUSION: The recovery time of immune cells was far behind that of serum ALT and AST during the process of liver repair. LECT2 could regulate monocyte/macrophage chemotaxis and might be used as a therapeutic target for acute liver injury.

Two novel mutations in the VPS33B gene in a Chinese patient with arthrogryposis, renal dysfunction and cholestasis syndrome 1: A case report.

BACKGROUND: The VPS33B (OMIM: 608552) gene is located on chromosome 15q26.1. We found a female infant with autosomal recessive arthrogryposis, renal dysfunction and cholestasis syndrome 1 (ARCS1) caused by mutation in VPS33B. The child was diagnosed with ARCS1 (OMIM: 208085) after the whole exome sequencing revealed two heterozygous mutations (c.96+1G>C, c.242delT) in the VPS33B gene. CASE SUMMARY: We report a Chinese female infant with neonatal cholestasis disorder, who was eventually diagnosed with ARCS1 by genetic analysis. Genetic testing revealed two new mutations (c.96+1G>C and c.242delT) in VPS33B, which is the causal gene. The patient was compound heterozygous, and her parents were both heterozygous. CONCLUSION: This study extends the mutational spectrum of the VPS33B gene to provide a molecular basis for the etiological diagnosis of ARCS1 and for genetic counseling of the family.

The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (B.1.1.529) variant is highly transmissible with potential immune escape. Hence, control measures are continuously being optimized to guard against large-scale coronavirus disease 2019 (COVID-19) outbreaks. This study aimed to explore the relationship between the intensity of control measures in response to different SARS-CoV-2 variants and the degree of outbreak control at city level. METHODS: A retrospective study was conducted in 49 cities with COVID-19 outbreaks between January 2020 and June 2022. Epidemiological data on COVID-19 were extracted from the National Health Commission, People's Republic of China, and the population flow data were sourced from the Baidu migration data provided by the Baidu platform. Outbreak control was quantified by calculating the degree of infection growth and the time-varying reproduction number ([Formula: see text]). The intensity of the outbreak response was quantified by calculating the reduction in population mobility during the outbreak period. Correlation and regression analyses of the intensity of the control measures and the degree of outbreak control for the Omicron variant and non-Omicron mutants were conducted, respectively. RESULTS: Overall, 65 outbreaks occurred in 49 cities in China from January 2020 to June 2022. Of them, 66.2% were Omicron outbreaks and 33.8% were non-Omicron outbreaks. The intensity of the control measures was positively correlated with the degree of outbreak control (r = 0.351, P = 0.03). The degree of reduction in population mobility was negatively correlated with the Rt value (r = - 0.612, P < 0.01). Therefore, under the same control measure intensity, the number of new daily Omicron infections was 6.04 times higher than those attributed to non-Omicron variants, and the Rt value of Omicron outbreaks was 2.6 times higher than that of non-Omicron variants. In addition, the duration of non-Omicron variant outbreaks was shorter than that of the outbreaks caused by the Omicron variant (23.0 ± 10.7, 32.9 ± 16.3, t = 2.243, P = 0.031). CONCLUSIONS: Greater intensity of control measures was associated with more effective outbreak control. Thus, in response to the Omicron variant, the management to restrict population movement should be used to control its spread quickly, especially in the case of community transmission occurs widely. Faster than is needed for non-Omicron variants, and decisive control measures should be imposed and dynamically adjusted in accordance with the evolving epidemic situation.

Development of an innovative nomogram of risk factors to predict postoperative recurrence of gastrointestinal stromal tumors.

BACKGROUND: There are many staging systems for gastrointestinal stromal tumors (GISTs), and the risk indicators selected are also different; thus, it is not possible to quantify the risk of recurrence among individual patients. AIM: To develop and internally validate a model to identify the risk factors for GIST recurrence after surgery. METHODS: The least absolute shrinkage and selection operator (LASSO) regression model was performed to identify the optimum clinical features for the GIST recurrence risk model. Multivariable logistic regression analysis was used to develop a prediction model that incorporated the possible factors selected by the LASSO regression model. The index of concordance (C-index), calibration curve, receiver operating characteristic curve (ROC), and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predictive model. Internal validation of the clinical predictive capability was also evaluated by bootstrapping validation. RESULTS: The nomogram included tumor site, lesion size, mitotic rate/50 high power fields, Ki-67 index, intracranial necrosis, and age as predictors. The model presented perfect discrimination with a reliable C-index of 0.836 (95%CI: 0.712-0.960), and a high C-index value of 0.714 was also confirmed by interval validation. The area under the curve value of this prediction nomogram was 0.704, and the ROC result indicated good predictive value. Decision curve analysis showed that the predicting recurrence nomogram was clinically feasible when the recurrence rate exceeded 5% after surgery. CONCLUSION: This recurrence nomogram combines tumor site, lesion size, mitotic rate, Ki-67 index, intracranial necrosis, and age and can easily predict patient prognosis.

Pyroptosis-related genes play a significant role in the prognosis of gastric cancer.

BACKGROUND: Pyroptosis is an inflammatory form of programmed cell death, which has been shown to be related to the prognosis of many tumors. However, its role in gastric cancer (GC) is not fully understood. AIM: To evaluate the expression of pyroptosis-related genes in GC and its correlation with prognosis. METHODS: We constructed prognostic multigene markers of differentially expressed genes associated with pyroptosis by least absolute contraction and selection operator Cox regression. The risk model was analyzed by Kaplan-Meier curve, two-sided log-rank test and functional enrichment analysis. RESULTS: Sixty-three pyroptosis-related genes were differentially expressed in tumor tissues and adjacent nontumor tissues. Based on these differentially expressed genes, 5 gene signature were constructed and all GC patients were classified into two risk groups. Kaplan-Meier survival curve showed that the overall survival (OS) of patients in the high-risk group was significantly lower than that of the low-risk group. Multivariate Cox regression analyses showed that the risk score was an independent risk factor for OS. Receiver operating characteristic curve analysis confirmed the predictive ability of the model. External validation indicated increased OS in the low-risk group. The immune function and immune cell scores of the high-risk group were generally higher than those of the low-risk group. CONCLUSION: Pyroptosis-related genes play a significant role in tumor immune microenvironment. This novel model, which contains 5 pyroptosis-related genes, is an independent predicting factor for OS in GC patients, and may help to evaluate the prognosis of GC.

The complete chloroplast genome sequence of Begonia arachnoidea (Begoniaceae).

There are more than 2035 Begonia species (Begoniaceae) reported currently in the world. Begonia arachnoidea was found as a new species within a small area in Southern China. In this study, we are reporting for the first time its chloroplast genome for the purpose to compare with the chloroplast genomic data from other plant taxa which were closely related to this new species. Our results show that the circular chloroplast genome of B. arachnoidea is 169,725 bp in length, with 35.49% GC content. The whole structure of the genome has 76,431 bp in a large single-copy (LSC) region, 18,146 bp in a small single-copy (SSC) region, and the two inverted repeat (IRs) regions are both 37,574 bp. There are 90 protein-coding genes, 8 rRNA genes, and 42 tRNA genes encoded in this genome. Final phylogenetic analysis revealed that B. arachnoidea is genetically closest to B. pulchrifolia and B. coptidifolia.

Increased Circulating Pentraxin 3 Levels in Patients with Rheumatoid Arthritis: A Meta-analysis.

BACKGROUND: Pentraxin 3 (PTX3), a soluble pattern recognition molecule, not only acts as a promising indicator reflecting the disease activity of rheumatoid arthritis (RA) patients but exerts essential pathogenic roles in the progression of RA and serves as a potential therapeutic target for RA patients. Our study intends to systematically evaluate the circulating PTX3 levels and their potential influencing factors in RA patients. METHODS: Articles regarding the circulating PTX3 levels of RA patients were identified in Pubmed, Embase, China National Knowledge Infrastructure (CNKI), and Cochrane databases. Standardized mean difference (SMD) and corresponding 95% confidence intervals (95% CI) were calculated and further illustrated by the forest plot. Egger's regression test and sensitivity analysis were conducted to assess the publication bias and stability of the results, respectively. RESULTS: Twenty articles with 21 individual studies were recruited in our meta-analysis. The overall results revealed that compared to healthy controls, RA patients had significantly higher circulating PTX3 levels (pooled SMD = 0.97, 95% CI: 0.48 to 1.45). Subgroup analyses further demonstrated that compared to healthy controls, RA patients of age ≤ 50 years, 2.6 < disease activity score in 28 joints (DAS28) ≤ 3.2, 3.2 < DAS28 ≤ 5.1, DAS28 > 5.1, C-reactive protein (CRP) levels > 10 mg/L, erythrocyte sedimentation rate (ESR) > 20 mm/h, and disease duration > 5 years had significantly higher circulating PTX3 levels, respectively; whereas RA patients of age > 50 years, DAS28 ≤ 2.6, CRP levels ≤ 10 mg/L, ESR ≤ 20 mm/h and disease duration ≤ 5 years had no significantly altered circulating PTX3 levels, respectively. Additionally, no matter whether the patients were of Caucasian ethnicity or not, circulating PTX3 levels were significantly increased in RA patients. CONCLUSION: Compared to healthy controls, circulating PTX3 levels are significantly increased in RA patients, which are influenced by age, disease activity, CRP levels, ESR, and disease duration.