Engineered nanovesicles from activated neutrophils with enriched bactericidal proteins have molecular debridement ability and promote infectious wound healing.

Background: Bacterial infections pose a considerable threat to skin wounds, particularly in the case of challenging-to-treat diabetic wounds. Systemic antibiotics often struggle to penetrate deep wound tissues and topically applied antibiotics may lead to sensitization, necessitating the development of novel approaches for effectively treating germs in deep wound tissues. Neutrophils, the predominant immune cells in the bloodstream, rapidly release an abundance of molecules via degranulation upon activation, which possess the ability to directly eliminate pathogens. This study was designed to develop novel neutrophil cell engineered nanovesicles (NVs) with high production and explore their bactericidal properties and application in promoting infectious wound healing. Methods: Neutrophils were isolated from peripheral blood and activated in vitro via phorbol myristate acetate (PMA) stimulation. Engineered NVs were prepared by sequentially extruding activated neutrophils followed by ultracentrifugation and were compared with neutrophil-derived exosomes in terms of morphology, size distribution and protein contents. The bactericidal effect of NVs in vitro was evaluated using the spread plate technique, LIVE/DEAD backlight bacteria assay and observation of bacterial morphology. The therapeutic effects of NVs in vivo were evaluated using wound contraction area measurements, histopathological examinations, assessments of inflammatory factors and immunochemical staining. Results: Activated neutrophils stimulated with PMA in vitro promptly release a substantial amount of bactericidal proteins. NVs are similar to exosomes in terms of morphology and particle size, but they exhibit a significantly higher enrichment of bactericidal proteins. In vitro, NVs demonstrated a significant bactericidal effect, presumably mediated by the enrichment of bactericidal proteins such as lysozyme. These NVs significantly accelerated wound healing, leading to a marked reduction in bacterial load, downregulation of inflammatory factors and enhanced collagen deposition in a full-thickness infectious skin defect model. Conclusions: We developed engineered NVs derived from activated neutrophils to serve as a novel debridement method targeting bacteria in deep tissues, ultimately promoting infectious wound healing.

Stabilized ε-Fe2C catalyst with Mn tuning to suppress C1 byproduct selectivity for high-temperature olefin synthesis.

Accurately controlling the product selectivity in syngas conversion, especially increasing the olefin selectivity while minimizing C1 byproducts, remains a significant challenge. Epsilon Fe2C is deemed a promising candidate catalyst due to its inherently low CO2 selectivity, but its use is hindered by its poor high-temperature stability. Herein, we report the successful synthesis of highly stable ε-Fe2C through a N-induced strategy utilizing pyrolysis of Prussian blue analogs (PBAs). This catalyst, with precisely controlled Mn promoter, not only achieved an olefin selectivity of up to 70.2% but also minimized the selectivity of C1 byproducts to 19.0%, including 11.9% CO2 and 7.1% CH4. The superior performance of our ε-Fe2C-xMn catalysts, particularly in minimizing CO2 formation, is largely attributed to the interface of dispersed MnO cluster and ε-Fe2C, which crucially limits CO to CO2 conversion. Here, we enhance the carbon efficiency and economic viability of the olefin production process while maintaining high catalytic activity.

Urea regulates soil nematode population by enhancing the nematode-trapping ability of nematode-trapping fungi.

As the most abundant animal in the soil, nematodes are directly or indirectly involved in almost all soil ecological processes. Studying soil nematode population regulation is essential to understanding soil ecological processes. This study found urea combines nematode-trapping fungi to regulate the population of soil nematodes. In soil, compared with no urea, adding 0.2 mg/mL urea after applying Arthrobotrys oligospora and Dactylellina ellipsospora reduced the number of nematodes by 34.7% and 31.7%. Further, the mechanism of urea couple nematode-trapping fungi to regulate the nematode population was explored in the medium environment. The results showed that the addition of 0.2 mg/ml urea accelerated the trap formation of A. oligospora and D. ellipsosporas by 50% and 46.5%, and increased the yield of traps of A. oligospora and D. ellipsosporas by 39.5% and 40.6%, thus, the predatory efficiency of A. oligospora and D. ellipsospora on nematodes was increased by 34.2% and 32.7%. In conclusion, urea regulates the predation ability of A. oligospora and D. ellipsosporas to regulate the soil nematode population. This study deepens the understanding of the regulatory pathways of the soil nematodes but also provides a potential new strategy for harmful nematode bio-control.

PRDX1 exerts a photoprotection effect by inhibiting oxidative stress and regulating MAPK signaling on retinal pigment epithelium.

BACKGROUND: The purpose of this study was to investigate the photoprotection effect of peroxiredoxin 1 (PRDX1) protein in ultraviolet B (UVB) irradiation-induced damage of retinal pigment epithelium (RPE) and its possible molecular mechanism. METHODS: ARPE-19 cell viability and apoptosis were assessed by MTT assay and flow cytometry, respectively. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the PRDX1 expression. The corresponding kits were employed to measure the levels or activities of lactate dehydrogenase (LDH), 8-hydroxy-2-deoxyguanosine (8-OHdG), reactive oxygen species (ROS), malondialdehyde (MDA), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD). Western blotting was applied to examine PRDX1 expression and mitogen-activated protein kinase (MAPK) signaling pathway-related proteins. RESULTS: After exposure to 20 mJ/cm2 intensity of UVB irradiation for 24 h, ARPE-19 cells viability was decreased, the leakage degree of LDH and 8-OHdG were increased, and cell apoptosis was elevated. The expression of PRDX1 was significantly down-regulated in UVB-induced ARPE-19 cells. The low expression of PRDX1 was involved in high irradiation intensity. Overexpression of PRDX1 increased cell activity, decreased cell apoptosis, and LDH as well as 8-OHdG leakage in UVB-induced ARPE-19 cells. In addition to alleviating UVB-induced cell damage, PRDX1 overexpression also inhibited UVB-induced oxidative stress (down-regulation of ROS and MDA levels, up-regulation of GSH-Px and SOD activities) and the activation of MAPK signaling pathway in ARPE-19 cells. CONCLUSION: PRDX1 exerts a photoprotection effect on RPE by attenuating UVB-induced cell damage and inhibiting oxidative stress, which can be attributed to the inhibition of MAPK signaling pathway activation.

Gastric-type endocervical adenocarcinoma: a case report and literature review.

Gastric-type endocervical adenocarcinoma (G-EAC) represents a rare variant of cervical mucinous adenocarcinoma that is typically unrelated to human papillomavirus (HPV) infection. G-EAC exhibits highly atypical clinical presentations and characteristics, and aggressive biological behavior often leads to challenges in timely diagnosis. Here, we present a case study involving a 74-year-old Chinese woman who experienced urinary incontinence for one month. Biopsy pathology confirmed the diagnosis of G-EAC, revealing stage IVa by imaging examinations. The patient subsequently underwent three cycles of chemotherapy, followed by adjuvant radiotherapy and surgical excision of residual tumor foci. This comprehensive treatment approach yielded a favorable survival outcome. For patients with advanced G-EAC, a multimodal therapeutic approach holds promise and warrants further exploration.

Establishment of an immortalized yak granulosa cell line: in vitro tool for understanding the molecular processes of ovarian follicle development.

The yak, a unique species of cattle found exclusively on the western plateau of China, is a valuable source of livelihood for local residents. However, their low fecundity restricts the expansion of yak farming, whereas regional factors limit studies on yak breeding. Granulosa cells (GCs), which provide essential steroid hormones and growth factors for oocytes, have been the focus of many studies on the mechanisms of follicular growth and atresia. This study aimed to establish an immortalized cell line model that could serve as a tool for future studies on the mechanisms of ovarian follicle development in yaks. First, we isolated primary yak granulosa cells (yGCs) and evaluated their replicative senescence after continuous in vitro subculturing. Subsequently, an immortalized culture method for primary yGC was explored, and a new cell line model was established to study the mechanism of follicular development in vitro. We used a mammalian gene expression lentivirus vector to transfer the simian virus 40 large T antigen (SV40T) into primary yGC to obtain an immortalized cell line. The immortalized yGCs were morphologically identical to the primary yGCs, and cell proliferation and growth were normal within a limited number of generations. Follicle-stimulating hormone receptor (FSHR), a specific marker for GCs, was positively expressed in immortalized yGCs. Furthermore, the immortalized yGCs retained the ability of GCs to synthesize estradiol and progesterone and expressed genes related to steroid synthesis. The establishment of immortalized yGC opens up a myriad of possibilities for advancing our understanding of yak reproductive biology and improving yak breeding strategies.

Multifunctional fluorescence/photoacoustic bimodal imaging of γ-glutamyltranspeptidase in liver disorders under different triggering conditions.

Hepatocellular carcinoma (HCC) seriously threatens the human health. Previous investigations revealed that γ-glutamyltranspeptidase (GGT) was tightly associated with the chronic injury, hepatic fibrosis, and the development of HCC, therefore might act as a potential indicator for monitoring the HCC-related processes. Herein, with the contribution of a structurally optimized probe ETYZE-GGT, the bimodal imaging in both far red fluorescence (FL) and photoacoustic (PA) modes has been achieved in multiple HCC-related models. To our knowledge, this work covered the most comprehensive models including the fibrosis and developed HCC processes as well as the premonitory induction stages (autoimmune hepatitis, drug-induced liver injury, non-alcoholic fatty liver disease). ETYZE-GGT exhibited steady and practical monitoring performances on reporting the HCC stages via visualizing the GGT dynamics. The two modes exhibited working consistency and complementarity with high spatial resolution, precise apparatus and desirable biocompatibility. In cooperation with the existing techniques including testing serum indexes and conducting pathological staining, ETYZE-GGT basically realized the universal application for the accurate pre-clinical diagnosis of as many HCC stages as possible. By deeply exploring the mechanically correlation between GGT and the HCC process, especially during the premonitory induction stages, we may further raise the efficacy for the early diagnosis and treatment of HCC.

Human papillomavirus infection and the risk of cancer at specific sites other than anogenital tract and oropharyngeal region: an umbrella review.

BACKGROUND: Despite numerous studies having evaluated the associations between human papillomavirus (HPV) infection and risk of specific cancers other than anogenital tract and oropharyngeal, the findings are inconsistent and the quality of evidence has not been systematically quantified. We aimed to summarise the existing evidence as well as to evaluate the strength and credibility of these associations. METHODS: We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, EMBASE, and Web of Science were searched from inception to March 2024. Studies with systematic reviews and meta-analyses that examined associations between HPV or HPV-associated genotypes infection and specific cancers were eligible for this review. The quality of the methodology was evaluated using A Measurement Tool to Assess systematic Reviews (AMSTAR). The credibility of the evidence was assessed using GRADE. The protocol was preregistered with PROSPERO (CRD42023439070). FINDINGS: The umbrella review identified 31 eligible studies reporting 87 associations with meta-analytic estimates, including 1191 individual studies with 336,195 participants. Of those, 29 (93.5%) studies were rated as over moderate quality by AMSTAR. Only one association indicating HPV-18 infection associated with an increased risk of breast cancer (odds ratio [OR] = 3.48, 95% confidence interval [CI] = 2.24-5.41) was graded as convincing evidence. There were five unique outcomes identified as highly suggestive evidence, including HPV infection increased the risk of oral squamous cell carcinoma (OR = 7.03, 95% CI = 3.87-12.76), oesophageal cancer (OR = 3.32, 95% CI = 2.54-4.34), oesophageal squamous cell carcinoma (OR = 2.69, 95% CI = 2.05-3.54), lung cancer (OR = 3.60, 95% CI = 2.59-5.01), and breast cancer (OR = 6.26, 95% CI = 4.35-9.00). According to GRADE, one association was classified as high, indicating that compared with the controls in normal tissues, HPV infection was associated with an increased risk of breast cancer. INTERPRETATION: The umbrella review synthesised up-to-date observational evidence on HPV infection with the risk of breast cancer, oral squamous cell carcinoma, oesophageal cancer, oesophageal squamous cell carcinoma, and lung cancer. Further larger prospective cohort studies are needed to verify the associations, providing public health recommendations for prevention of disease. FUNDING: National Key Research and Development Program of China, Natural Science Foundation of China, Outstanding Scientific Fund of Shengjing Hospital of China Medical University, and 345 Talent Project of Shengjing Hospital of China Medical University.

Automated characterization and analysis of expression compatibility between regulatory sequences and metabolic genes in Escherichia coli.

Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories. However, when regulatory sequence expression strengths are characterized using only a few reporter genes, they may not be applicable across diverse genes. This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels. To address this, our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels. We combined 41 commonly-used metabolic genes with 15 regulatory sequences, yielding an expression dataset encompassing 520 unique combinations. This dataset highlighted substantial variation in protein expression level under identical regulatory sequences, with relative expression levels ranging from 2.8 to 176-fold. It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins. Utilizing this dataset, we have developed various machine learning models and discovered that the integration of promoter regions, ribosome binding sites, and coding sequences significantly improves the accuracy of predicting protein expression levels, with a Spearman correlation coefficient of 0.72, where the promoter sequence exerts a predominant influence. Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.

Characterization of Sand and Dust Pollution Degradation Based on Sensitive Structure of Microelectromechanical System Flow Sensor.

The effect of sand and dust pollution on the sensitive structures of flow sensors in microelectromechanical systems (MEMS) is a hot issue in current MEMS reliability research. However, previous studies on sand and dust contamination have only searched for sensor accuracy degradation due to heat conduction in sand and dust cover and have yet to search for other failure-inducing factors. This paper aims to discover the other inducing factors for the accuracy failure of MEMS flow sensors under sand and dust pollution by using a combined model simulation and sample test method. The accuracy of a flow sensor is mainly reflected by the size of its thermistor, so in this study, the output value of the thermistor value was chosen as an electrical characterization parameter to verify the change in the sensor's accuracy side by side. The results show that after excluding the influence of heat conduction, when sand particles fall on the device, the mutual friction between the sand particles will produce an electrostatic current; through the principle of electrostatic dissipation into the thermistor, the principle of measurement leads to the resistance value becoming smaller, and when the sand dust is stationary for some time, the resistance value returns to the expected level. This finding provides theoretical guidance for finding failure-inducing factors in MEMS failure modes.

Case report: A rare case of omental extrarenal rhabdoid tumor and review of the literature.

Extrarenal rhabdoid tumor of the greater omentum is extremely rare, with only sporadic reports and limited documentation of its ultrasonographic findings. Here, we report a case of an extrarenal rhabdoid tumor of the greater omentum in a 16-year-old girl and review the relevant literature. It was found that the disease mainly occurred in female children and adolescents, and mainly manifested as lower abdominal pain and a large abdominal cystic or solid hemorrhagic mass. The clinical characteristics include a high degree of malignancy and mortality. Ultrasound shows some malignant features, but it is not specific; thus, it is easy to be misdiagnosed in the clinic.

Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.

OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing both the intratumoral and peritumoral-to predict the status of axillary lymph nodes in patients with early-stage breast cancer. METHODS: The study employed retrospective methods, collecting clinical information, ultrasound data, and postoperative pathological results from 321 breast cancer patients (including 224 in the training group and 97 in the validation group). Through correlation analysis, univariate analysis, and Lasso regression analysis, independent risk factors related to axillary lymph node metastasis in breast cancer were identified from conventional ultrasound and immunohistochemical indicators, and a clinical feature model was constructed. Additionally, features were extracted from ultrasound images of the intratumoral and its 1-5 mm peritumoral to establish a radiomics feature formula. Furthermore, by combining clinical features and ultrasound radiomics features, six machine learning models (Logistic Regression, Decision Tree, Support Vector Machine, Extreme Gradient Boosting, Random Forest, and K-Nearest Neighbors) were compared for diagnostic efficacy, and constructing a joint prediction model based on the optimal ML algorithm. The use of Shapley Additive Explanations (SHAP) enhanced the visualization and interpretability of the model during the diagnostic process. RESULTS: Among the 321 breast cancer patients, 121 had axillary lymph node metastasis, and 200 did not. The clinical feature model had an AUC of 0.779 and 0.777 in the training and validation groups, respectively. Radiomics model analysis showed that the model including the Intratumor +3 mm peritumor area had the best diagnostic performance, with AUCs of 0.847 and 0.844 in the training and validation groups, respectively. The joint prediction model based on the XGBoost algorithm reached AUCs of 0.917 and 0.905 in the training and validation groups, respectively. SHAP analysis indicated that the Rad Score had the highest weight in the prediction model, playing a significant role in predicting axillary lymph node metastasis in breast cancer. CONCLUSION: The predictive model, which integrates clinical features and radiomic characteristics using the XGBoost algorithm, demonstrates significant diagnostic value for axillary lymph node metastasis in breast cancer. This model can provide significant references for preoperative surgical strategy selection and prognosis evaluation for breast cancer patients, helping to reduce postoperative complications and improve long-term survival rates. Additionally, the utilization of SHAP enhancing the global and local interpretability of the model.

High-order rogue wave and mixed interaction patterns for the three-component Gross-Pitaevskii equations in F=1 spinor Bose-Einstein condensates.

Under investigation are the three-component Gross-Pitaevskii equations in F=1 spinor Bose-Einstein condensates. Various localized waves' generation mechanisms have been derived from plane wave solutions using modulation instability. The perturbed continuous waves produce a large number of rogue wave structures through the split-step Fourier numerical method. Based on the known Lax pair, we construct the generalized iterative (n,N-n)-fold Darboux transformation to generate various high-order solutions, including the bright-dark-bright structure of rogue waves, periodic waves, and their mixed interaction structures. Numerical simulations show that rogue waves with a two-peaked structure have robust noise resistance and stable dynamical behavior. The asymptotic states of high-order rogue waves as the parameter approaches infinity are also predicted using the large parameter asymptotic technique. In addition, the position of these localized wave patterns can be controlled by some special parameters. These results may help us understand the dynamic behavior of spinor condensates for the mean-field approximation.

Bird's-Eye View of the Activity Distribution on a Catalyst Surface via a Machine Learning-Driven Adequate Sampling Algorithm.

Rational design of catalysts relies on a deep understanding of the active centers. The structure and activity distribution of active centers on a surface are two of the central issues in catalysis and important targets of theoretical and experimental investigations. Herein, we report a machine learning-driven adequate sampling (MLAS) framework for obtaining a statistical understanding of the chemical environment near catalyst sites. Combined strategies were implemented to achieve highly efficient sampling, including the decomposition of degrees of freedom, stratified sampling, Gaussian process regression, and well-designed constraint optimization. The MLAS framework was applied to the rate-determining step in NH3 synthesis, namely the N2 activation process. We calculated the produced population function, PA, which provides a comprehensive and intuitive understanding of active centers. The MLAS framework can be broadly applied to other more complicated catalyst materials and reaction networks.

Effects of movement training based on rhythmic auditory stimulation in cognitive impairment: a meta-analysis of randomized controlled clinical trial.

Objective: According to the World Alzheimer's Disease Report in 2015,there were 9.9 million new cases of dementia in the world every year. At present, the number of patients suffering from dementia in China has exceeded 8 million, and it may exceed 26 million by 2040.Mild cognitive impairment (MCI) refers to the pathological state of pre-dementia with the manifestation of the progressive decline of memory or other cognitive functions but without decline of activities of daily life. It is particularly important to prevent or prolong the development of MCI into dementia. Research showing effects of rhythmic auditory stimulation based-movement training(RASMT) interventions on cognitive function is also emerging. Therefore, the present meta-analysis briefly summarize findings regarding the impacts of RASMT programs on cognitive impairment. Methods: Data from Pubmed, Embase, and Cochrane Library were utilized. The impact of RASMT on cognitive functions was evaluated using indicators such as overall cognitive status, memory, attention, and executive functions. The REVMAN5.3 software was employed to analyze bias risks integrated into the study and the meta-analysis results for each indicator. Results: A total of 1,596 studies were retrieved, of which 1,385 non-randomized controlled studies and 48 repetitive studies were excluded. After reviewing titles and abstracts of the remaining 163 articles, 133 irrelevant studies were excluded, 30 studies were downloaded and read the full text. Among 30 articles, 18 articles that did not meet the inclusion criteria were excluded, the other 12 studies were included in this meta-analysis. Utilizing the Cochrane Collaborative Network Bias Risk Assessment Scale, it was found that 11 studies explained the method of random sequence generation, nine studies did not describe allocation concealment, four were single-blinded to all researchers, and eight reported single-blinding in the evaluation of experimental results. In the meta-analysis, the main outcomes showed statistically significant differences in overall cognitive status [MD = 1.19, 95%CI (0.09, 2.29), (p < 0.05)], attention [MD = -1.86, 95%CI (-3.53, -0.19), (p < 0.05)], memory [MD = 0.71, 95%CI (0.33, 1.09), (p < 0.01)], and executive function [MD = -0.23, 95% CI (-0.44, -0.02), (p < 0.05)]. Secondary outcomes indicated no statistically significant differences in verbal fluency [MD = -0.51, 95%CI (-1.30, 0.27), (p = 0.20)], while depression [MD = -0.29, 95% CI (-0.42, -0.16), (p < 0.01)] and anxiety [MD = 0.19, 95% CI (0.06, 0.32), (p < 0.01)] exhibited statistically significant differences. The GRADEpro GDT online tool assessed the quality of evidence for the outcome measures, revealing one low-quality outcome, two moderate-quality outcomes, and one high-quality outcome in this review. Conclusion: This study shows that RASMT can improve the general cognitive status, memory, attention and executive function of patients with cognitive impairment. The quality of evidence revealed that MMSE was low, attention and memory were moderate, and executive function was high. The RAMST program (type of exercise: play percussion instruments; time of exercise: 30-60 min; frequency of exercise: 2-3 times/week; duration of exercise: more than 12 weeks) was proved to be more effective in improving cognitive function. However, the sample size is relatively insufficient, the future needs further study. Systematic review registration: PROSPERO, identifier: CRD42023483561.

Ruthenium-Cobalt Solid-Solution Alloy Nanoparticles for Enhanced Photopromoted Thermocatalytic CO2 Hydrogenation to Methane.

Bimetallic alloy nanoparticles have garnered substantial attention for diverse catalytic applications owing to their abundant active sites and tunable electronic structures, whereas the synthesis of ultrafine alloy nanoparticles with atomic-level homogeneity for bulk-state immiscible couples remains a formidable challenge. Herein, we present the synthesis of RuxCo1-x solid-solution alloy nanoparticles (ca. 2 nm) across the entire composition range, for highly efficient, durable, and selective CO2 hydrogenation to CH4 under mild conditions. Notably, Ru0.88Co0.12/TiO2 and Ru0.74Co0.26/TiO2 catalysts, with 12 and 26 atom % of Ru being substituted by Co, exhibit enhanced catalytic activity compared with the monometallic Ru/TiO2 counterparts both in dark and under light irradiation. The comprehensive experimental investigations and density functional theory calculations unveil that the electronic state of Ru is subtly modulated owing to the intimate interaction between Ru and Co in the alloy nanoparticles, and this effect results in the decline in the CO2 conversion energy barrier, thus ultimately culminating in an elevated catalytic performance relative to monometallic Ru and Co catalysts. In the photopromoted thermocatalytic process, the photoinduced charge carriers and localized photothermal effect play a pivotal role in facilitating the chemical reaction process, which accounts for the further boosted CO2 methanation performance.

Predictive Value of 5-Methoxytryptophan on Long-Term Clinical Outcome after PCI in Patients with Acute Myocardial Infarction-a Prospective Cohort Study.

BACKGROUND: In recent years, 5-Methoxytryptophan (5-MTP) has been identified as an endothelial factor with vaso-protective and anti-inflammatory properties. METHODS: In this prospective cohort study, a total of 407 patients with acute myocardial infarction (AMI) who underwent percutaneous coronary intervention (PCI) successfully were enrolled. A 1-year follow-up Kaplan-Meier survival analysis was used for evaluating the correlation between 5-MTP and major adverse cardiovascular event (MACE) while Cox proportional-hazards regression was used to identify predictive values of 5-MTP on MACE after AMI. RESULTS: Increased 5-MTP level led to a significant downtrend in the incidence of MACE (All Log-rank p < 0.05). Thus, a high baseline 5-MTP could reduce the 1-year incidence of MACE (HR = 0.33, 95%Cl 0.17-0.64, p = 0.001) and heart failure (HF) (HR = 0.28, 95% Cl 0.13-0.62, p = 0.002). Subgroup analysis indicated the predictive value of 5-MTP was more significant in patients aged ≤ 65 years and those with higher baseline NT-proBNP, T2DM, STEMI, and baseline HF with preserved LVEF (HFpEF) characteristics. CONCLUSIONS: Plasma 5-MTP is an independent and protective early biomarker for 1-year MACE and HF events in patients with AMI, especially in younger patients and those with T2DM, STEMI, and baseline HFpEF characteristics.

Immune cell-related prognostic risk model and tumor immune environment modulation in esophageal carcinoma based on single-cell and bulk RNA sequencing.

BACKGROUND: Immune cells play a pivotal role in the tumor microenvironment, exerting significant influence on tumor progression and patient outcomes, but the current biomarkers are insufficient to fully capture the complex and diverse tumor immune microenvironment and the impact of immunotherapy. METHODS: The advent of single-cell sequencing allows us to explore the tumor microenvironment at an unprecedented resolution, enabling the identification and characterization of distinct subsets of immune cells, thereby paving the way for the development of prognostic models using immune cells. Leveraging single-cell data, our study deeply investigated the intricacies of immune microenvironment heterogeneity in esophageal carcinoma. RESULTS: We elucidated the composition, functionality, evolution, and intercellular communication patterns of immune cells, culminating in the construction of an independent prognostic model at the single-cell level. Furthermore, we conducted a comprehensive analysis of disparities in immune infiltration and immune checkpoint expression between patients categorized into high- and low-risk groups, which may impact patient prognosis. CONCLUSION: In summary, our study harnessed multiomics data to delineate the immune profile of esophageal carcinoma patients, provide a method for leveraging molecular signatures of immune cells to identify potential biomarkers, while concurrently providing evidence for the potential benefits of immunotherapy.

The complete chloroplast genome of Lagochilus ilicifolius Bunge ex Bentham, Labiat. Gen. 1834 (Lamiaceae) and its phylogenetic analysis.

Lagochilus ilicifolius Bunge ex Bentham, Labiat. Gen is a perennial herb with much-branched stems native to Nei Mongol, Ningxia, Gansu, N Shaanxi. It can be used clinically as a hemostatic agent. The chloroplast genome length is 151,466 bp. It contained two inverted repeat regions of 25,660 bp each, a large single-copy region of length 82,504 bp, and a small single-copy region of length 17,642 bp. Also, the GC content is 38.6%. There were 133 genes annotated, including 88 known protein-coding genes, 37 tRNAs, and eight rRNAs. The phylogenetic tree was constructed using Bayesian method for plastome data of 29 species. The entire chloroplast genome of L. ilicifolius within the Lamiaceae is the first to reveal genetic taxonomy at the molecular level, and the new phylogenetic tree data can be used for future evolutionary studies.