The Kinase mTORC1 Promotes the Generation and Suppressive Function of Follicular Regulatory T Cells.

Follicular regulatory T (Tfr) cells differentiate from conventional regulatory T (Treg) cells and suppress excessive germinal center (GC) responses by acting on both GC B cells and T follicular helper (Tfh) cells. Here, we examined the impact of mTOR, a serine/threonine protein kinase that senses and integrates diverse environmental cues, on the differentiation and functional competency of Tfr cells in response to protein immunization or viral infection. By genetically deleting Rptor or Rictor, essential components for mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2), respectively, we found that mTORC1 but not mTORC2 is essential for Tfr differentiation. Mechanistically, mTORC1-mediated phosphorylation of the transcription factor STAT3 induced the expression of the transcription factor TCF-1 by promoting STAT3 binding to the Tcf7 5'-regulatory region. Subsequently, TCF-1 bound to the Bcl6 promoter to induce Bcl6 expression, which launched the Tfr cell differentiation program. Thus, mTORC1 initiates Tfr cell differentiation by activating the TCF-1-Bcl-6 axis during immunization or infection.

Log odds of positive lymph nodes as a novel prognostic predictor for gastric cancer: a systematic review and meta-analysis.

BACKGROUND: We conducted a systematic review and meta-analysis to summarize the predictive and prognostic ability of the log odds of positive lymph nodes (LODDS) staging system and compare it with pathological N (pN) classification and the ratio-based lymph node system (rN) for the overall survival (OS) of gastric cancer (GC). METHODS: Through a systematic review till March 7, 2022, we identified population-based studies that reported the prognostic effects of LODDS in patients with GC. We compare the predictive effectiveness of the LODDS staging system with that of the rN and pN classification systems for the OS of GC. RESULTS: Twelve studies comprising 20,312 patients were included in this systematic review and meta-analysis. The results showed that LODDS1, LODDS2, LODDS3, and LODDS4 in GC patients were correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.62, 95% CI (1.42, 1.85); LODDS2 vs. LODDS0: HR = 2.47, 95% CI (2.02, 3.03); LODDS3 vs. LODDS0: HR = 3.15, 95% CI (2.50, 3.97); LODDS4 vs. LODDS0: HR = 4.55, 95% CI (3.29, 6.29)). Additionally, significant differences in survival were observed among patients with different LODDS classifications (all P-values were < 0.001) with the same rN and pN classifications. Meanwhile, for patients with different pN or rN classifications with the same LODDS classification, prognosis was highly similar. CONCLUSION: The findings show that LODDS is correlated with the prognosis of GC patients and is superior to the pN and rN classifications for prognostic assessment.

Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA.

BACKGROUND: RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. However, the potential value of RBPs as prognostic indicators and therapeutic targets in colorectal cancer (CRC) requires further investigation. METHODS: Four thousand eighty two RBPs were collected from literature. The weighted gene co-expression network analysis (WGCNA) was performed to identify prognosis-related RBP gene modules based on the data attained from the TCGA cohorts. LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR. RESULTS: One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues. CONCLUSION: Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.

Developing Insoluble Polyoxometalate Clusters to Bridge Homogeneous and Heterogeneous Water Oxidation Photocatalysis.

Cluster catalysts are attractive for their atomically precise structures, defined compositions, tunable coordination environments, uniform active sites, and their ability to transfer multiple electrons, but they suffer from poor stability and recyclability. Here, we report a general approach to the direct insolubilization of a water soluble polyoxometalate (POM) [{(B-α-PW9 O34 )Co3 (OH)(H2 O)2 (O3 PC(O)-(C3 H6 NH3 )PO3 )}2 Co]14- (Co7 ) and formation of a series of POM-based solid catalysts with the counter-cations Ag+ , Cs+ , Sr2+ , Ba2+ , Pb2+ , Y3+ , and Ce3+ . They exhibit improved catalytic activities for visible-light-driven water oxidation following the trend CsCo7 >SrCo7 >AgCo7 >CeIII Co7 >BaCo7 >YCo7 >PbCo7 . While CsCo7 exhibits mainly homogeneous catalysis, the others are predominantly heterogeneous catalysts. An optimal oxygen yield of 41.3 % and a high apparent quantum yield (AQY) of 30.6 % for SrCo7 is obtained, which is comparable to that of the parent homogeneous POM. Band gap structures, UV/Vis spectra, and real-time laser flash photolysis experiments collectively suggest that easier electron transfer from the solid POM catalyst to the photosensitizer promotes photocatalytic water oxidation performance. These solid POM catalysts exhibit good stability, which is directly confirmed by a combination of Fourier-transform infrared spectroscopy, electron microscopy, X-ray diffraction patterns, Raman spectroscopy, X-ray photoelectron spectroscopy, five cycles of tests, and poisoning experiments.

Log odds of positive lymph nodes as a novel prognostic predictor for colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) is the third most prevalent cancer in the world, which remains one of the leading causes of cancer-related deaths. Accurate prognosis prediction of CRC is pivotal to reduce the mortality and disease burden. Lymph node (LN) metastasis is one of the most commonly used criteria to predict prognosis in CRC patients. However, inaccurate surgical dissection and pathological evaluation may lead to inaccurate nodal staging, affecting the effectiveness of pathological N (pN) classification in survival prediction among patients with CRC. In this meta-analysis, we aimed to estimate the prognostic value of the log odds of positive lymph nodes (LODDS) in patients with CRC. METHODS: PubMed, Medline, Embase, Web of Science and the Cochrane Library were systematically searched for relevant studies from inception to July 3, 2021. Statistical analyses were performed on Stata statistical software Version 16.0 software. To statistically assess the prognostic effects of LODDS, we extracted the hazard ratio (HR) and 95% confidence interval (CI) of overall survival (OS) and disease-free survival (DFS) from the included studies. RESULTS: Ten eligible articles published in English involving 3523 cases were analyzed in this study. The results showed that LODDS1 and LODDS2 in CRC patients was correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.77, 95% CI (1.38, 2.28); LODDS2 vs. LODDS0: HR = 3.49, 95% CI (2.88, 4.23)). Meanwhile, LODDS1 and LODDS2 in CRC patients was correlated with poor DFS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.82, 95% CI (1.23, 2.68); LODDS2 vs. LODDS0: HR =3.30, 95% CI (1.74, 6.27)). CONCLUSIONS: The results demonstrated that the LODDS stage was associated with prognosis of CRC patients and could accurately predict the prognosis of patients with CRC.

Development of a model to predict the prognosis of esophageal carcinoma based on autophagy-related genes.

Aim: To identify a potential prognostic signature of esophageal carcinoma based on autophagy-related genes (ARGs). Methods: RNA sequencing and clinical data were downloaded from the Cancer Genome Atlas. Significantly different ARGs were identified by Wilcoxon signed-rank test. A prognostic model was established employing Cox regression analysis. The model was evaluated by receiver operating characteristic and Kaplan-Meier curve. Results: A total of 28 significantly different ARGs were identified. Seven ARGs were screened to construct the prognostic model. The efficacy of the model was verified. A nomogram also validated the role of risk score in predicting prognosis. Enrichment analyses showed the possible underlying mechanisms. Conclusion: The seven-ARGs prognostic model was validated to be promising for predicting the prognosis of patients with esophageal carcinoma.

Plain language summary Autophagy is an important metabolic process in cells. Also known as type II cell death, it is a process in which cells degrade their damaged organelles and macromolecular substances by lysosomes. Autophagy is reported to be involved in the development of multiple tumor types, including esophageal carcinoma (ESCA). Autophagy-related genes (ARGs) are those genes proved to be closely related to, or in control of, autophagy. We aimed to identify a model for predicting prognosis based on ARGs, using gene expression profiles and clinical data of ESCA patients from an online database. We identified 28 ARGs as having significantly different activity in ESCA cells compared with normal cells. Among them, four genes were less active, and 24 genes were more active in cancer. Seven ARGs were screened to construct the prognostic model. The effectiveness of the model in predicting the prognosis of ESCA patients was confirmed by standard statistical methods. This study is valuable for finding possible therapeutic targets and predicting prognosis in ESCA patients based on ARGs.

Prognostic biomarkers and therapeutic targets in oral squamous cell carcinoma: a study based on cross-database analysis.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is a malignant cancer, the survival rate of patients is disappointing. Therefore, it is necessary to identify the driven-genes and prognostic biomarkers in OSCC. METHODS: Four Gene Expression Omnibus (GEO) datasets were integratedly analyzed using bioinformatics approaches, including identification of differentially expressed genes (DEGs), GO and KEGG analysis, construction of protein-protein interaction (PPI) network, selection of hub genes, analysis of prognostic information and genetic alterations of hub genes. ONCOMINE, The Cancer Genome Atlas (TCGA) and Human Protein Atlas databases were used to evaluate the expression and prognostic value of hub genes. Tumor immunity was assessed to investigate the functions of hub genes. Finally, Cox regression model was performed to construct a multiple-gene prognostic signature. RESULTS: Totally 261 genes were found to be dysregulated. 10 genes were considered to be the hub genes. The Kaplan-Meier analysis showed that upregulated SPP1, FN1, CXCL8, BIRC5, PLAUR, and AURKA were related to poor outcomes in OSCC patients. FOXM1 and TPX2 were considered as the potential immunotherapeutic targets with future clinical significance. Moreover, we constructed a nine-gene signature (TEX101, DSG2, SCG5, ADA, BOC, SCARA5, FST, SOCS1, and STC2), which can be utilized to predict prognosis of OSCC patients effectively. CONCLUSION: These findings may provide new clues for exploring the molecular mechanisms and targeted therapy in OSCC. The hub genes and risk gene signature are helpful to the personalized treatment and prognostic judgement.

Depth-dependent soil organic carbon dynamics of croplands across the Chengdu Plain of China from the 1980s to the 2010s.

Agricultural soils have tremendous potential to sequester soil organic carbon (SOC) and mitigate global climate change. However, agricultural land use has a profound impact on SOC dynamics, and few studies have explored how agricultural land use combined with soil conditions affect SOC changes throughout the soil profile. Based on a paired soil resampling campaign in the 1980s and 2010s, this study investigated the SOC changes of the soil profile caused by agricultural land use and the correlations with parent material and topography across the Chengdu Plain of China. The results showed that the SOC content increased by 3.78 g C/kg in the topsoil (0-20 cm), but decreased in the 20-40 cm and 40-60 cm soil layers by 0.90 and 1.26 g C/kg respectively. SOC increases in topsoil were observed for all types of agricultural land. Afforestation on former agricultural land also caused SOC decreases in the 20-60 cm soil layers, while SOC decreases only occurred in the 40-60 cm soil layer for agricultural land using a traditional crop rotation (i.e. traditional rice-wheat/rapeseed rotation) and with rice-vegetable rotations converted from the traditional rotations. For each agricultural land use, SOC decreases in deep soils only occurred in high relief areas and in soils formed from Q4 (Quaternary Holocene) grey-brown alluvium and Q4 grey alluvium that had a relatively low soil bulk density and clay content. The results indicated that SOC change caused by agricultural land use was depth dependent and that the effects of agricultural land use on soil profile SOC dynamics varied with soil characteristics and topography. Subsoil SOC decreases were more likely to occur in high relief areas and in soils with low soil bulk density and low clay content.

Prognostic value of circulating tumor cells detected with the CellSearch system in esophageal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Esophageal carcinoma (EC) is the seventh-most prevalent tumor in the world, which is still one of the primary causes of tumor-related death. Identifying noteworthy biomarkers for EC is particularly significant in guiding effective treatment. Recently, circulating tumor cells (CTCs) in peripheral blood (PB) were intensively discussed as prognostic markers in patients with EC. However, an ongoing controversy still exists regarding the prognostic significance of CTCs determined by the CellSearch system in EC sufferers. This meta-analysis was designed to approach this topic. METHODS: We systematically conducted searches using PubMed, Medline, Web of Science and the Cochrane Library for relevant studies, which were published through February 20, 2020. Using the random-effects model, our study was performed in Review Manager software, with odds ratios (ORs), risk ratios (RRs), hazard ratios (HRs) and 95% confidence intervals (CIs) as the effect values. RESULTS: Totally 7 articles were finally included in this study. For clinicopathological characteristics, the pooled results on TNM stage indicated that the III/IV group had higher rate of CTCs compared with the I/II group (OR = 1.36, 95% CI: 0.68-2.71, I2 = 0%). Incidence of CTCs was higher in patients with T3/T4 stage (OR = 2.92, 95% CI: 1.31-6.51, I2 = 0%) and distant metastasis group (OR = 5.18, 95% CI: 2.38-11.25, I2 = 0%) compared to patients with T1/T2 stage or non-metastatic group. The pooled analysis revealed that CTC positivity detected in EC patients was correlated with poor overall survival (OS) (HR = 2.83, 95% CI:1.99-4.03, I2 = 0%) and relapse-free survival (RFS) (HR = 4.71, 95% CI:2.73-8.13, I2 = 0%). When pooling the estimated RR, a poor therapeutic response to chemoradiotherapy was discovered in patients with CTC positivity (RR = 1.99, 95% CI:1.73-2.29, I2 = 60%). CONCLUSIONS: In summary, our meta-analysis demonstrated that CTCs positivity determined by the CellSearch system are correlated with the prognosis of EC patients and might indicate a poor therapeutic response to chemotherapy in EC patients.

The dynamic-static dual-branch deep neural network for urban speeding hotspot identification using street view image data.

The visual information regarding the road environment can influence drivers' perception and judgment, often resulting in frequent speeding incidents. Identifying speeding hotspots in cities can prevent potential speeding incidents, thereby improving traffic safety levels. We propose the Dual-Branch Contextual Dynamic-Static Feature Fusion Network based on static panoramic images and dynamically changing sequence data, aiming to capture global features in the macro scene of the area and dynamically changing information in the micro view for a more accurate urban speeding hotspot area identification. For the static branch, we propose the Multi-scale Contextual Feature Aggregation Network for learning global spatial contextual association information. In the dynamic branch, we construct the Multi-view Dynamic Feature Fusion Network to capture the dynamically changing features of a scene from a continuous sequence of street view images. Additionally, we designed the Dynamic-Static Feature Correlation Fusion Structure to correlate and fuse dynamic and static features. The experimental results show that the model has good performance, and the overall recognition accuracy reaches 99.4%. The ablation experiments show that the recognition effect after the fusion of dynamic and static features is better than that of static and dynamic branches. The proposed model also shows better performance than other deep learning models. In addition, we combine image processing methods and different Class Activation Mapping (CAM) methods to extract speeding frequency visual features from the model perception results. The results show that more accurate speeding frequency features can be obtained by using LayerCAM and GradCAM-Plus for static global scenes and dynamic local sequences, respectively. In the static global scene, the speeding frequency features are mainly concentrated on the buildings and green layout on both sides of the road, while in the dynamic scene, the speeding frequency features shift with the scene changes and are mainly concentrated on the dynamically changing transition areas of greenery, roads, and surrounding buildings. The code and model used for identifying hotspots of urban traffic accidents in this study are available for access: https://github.com/gwt-ZJU/DCDSFF-Net.

Experimental study of the fast scintillating behavior of ZnO:Ga crystal under MeV electron beam.

An experimental study on the scintillating behavior of ZnO:Ga crystals was conducted using a 7-MeV electron accelerator. The ZnO:Ga crystals were grown using both hydrothermal and chemical vapor transport methods. One of the ZnO:Ga crystals grown via the hydrothermal method exhibited a 1.5-ns afterglow time when excited by an MeV electron beam. The ultra-short scintillation was captured using both an ultrafast streak camera and a framed camera. The experimental results also confirm its potential for diagnosing electron beam trains with a repetition rate of hundreds of MHz.

Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries.

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist. Now the battery is still a "black box", thus requiring a deep understanding of its internal state. The battery should "sense its internal physical/chemical conditions", which puts strict requirements on embedded sensing parts. This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed, focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition, electrolyte degradation, electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution. The paper contributes to understanding how to use optical fiber sensors to achieve "real" and "embedded" monitoring. Through the inherent advantages of the advanced optical fiber sensor, it helps clarify the battery internal state and reaction mechanism, aiding in the establishment of more detailed models. These advancements can promote the development of smart batteries, with significant importance lying in essentially promoting the improvement of system consistency. Furthermore, with the help of smart batteries in the future, the importance of consistency can be weakened or even eliminated. The application of advanced optical fiber sensors helps comprehensively improve the battery quality, reliability, and life.

Effects of grazing exclusion on soil microbial diversity and its functionality in grasslands: a meta-analysis.

Grazing exclusion (GE) is considered an effective strategy for restoring the degradation of overgrazed grasslands on the global scale. Soil microbial diversity plays a crucial role in supporting multiple ecosystem functions (multifunctionality) in grassland ecosystems. However, the impact of grazing exclusion on soil microbial diversity remains uncertain. Here, we conducted a meta-analysis using a dataset comprising 246 paired observations from 46 peer-reviewed papers to estimate how GE affects microbial diversity and how these effects vary with climatic regions, grassland types, and GE duration ranging from 1 to 64 years. Meanwhile, we explored the relationship between microbial diversity and its functionality under grazing exclusion. Overall, grazing exclusion significantly increased microbial Shannon (1.9%) and microbial richness (4.9%) compared to grazing group. For microbial groups, GE significantly increased fungal richness (8.6%) and bacterial richness (5.3%), but decreased specific microbial richness (-11.9%). The responses of microbial Shannon to GE varied among climatic regions, grassland types, and GE duration. Specifically, GE increased microbial diversity in in arid, semi-arid, and dry sub-humid regions, but decreased it in humid regions. Moreover, GE significantly increased microbial Shannon in semidesert grasslands (5.9%) and alpine grasslands (3.0%), but not in temperate grasslands. Long-term (>20 year) GE had greater effects on microbial diversity (8.0% for Shannon and 6.7% for richness) compared to short-term (<10 year) GE (-0.8% and 2.4%). Furthermore, grazing exclusion significantly increased multifunctionality, and both microbial and plant Shannon positively correlated with multifunctionality. Overall, our findings emphasize the importance of considering climate, GE duration, and grassland type for biodiversity conservation and sustainable grassland ecosystem functions.

Small extracellular vesicles-mediated cellular interactions between tumor cells and tumor-associated macrophages: Implication for immunotherapy.

The tumor microenvironment consists of cancer cells and various stromal cells, including macrophages, which exhibit diverse phenotypes with either pro-inflammatory (M1) or anti-inflammatory (M2) effects. The interaction between cancer cells and macrophages plays a crucial role in tumor progression. Small extracellular vesicles (sEVs), which facilitate intercellular communication, are known to play a vital role in this process. This review provides a comprehensive summary of how sEVs derived from cancer cells, containing miRNAs, lncRNAs, proteins, and lipids, can influence macrophage polarization. Additionally, we discuss the impact of macrophage-secreted sEVs on tumor malignant transformation, including effects on proliferation, metastasis, angiogenesis, chemoresistance, and immune escape. Furthermore, we address the therapeutic advancements and current challenges associated with macrophage-associated sEVs, along with potential solutions.

Akkermansia muciniphila ameliorates colonic injury in mice with DSS-induced acute colitis by blocking macrophage pro-inflammatory phenotype switching via the HDAC5/DAB2 axis.

Akkermansia muciniphila (A. muciniphila), a probiotic, has been linked to macrophage phenotypic polarization in different diseases. However, the role and mechanisms of A. muciniphila in regulating macrophage during ulcerative colitis (UC) are not clear. This research aimed to examine the impact of A. muciniphila on dextran sulfate sodium (DSS)-induced acute colitis and elucidate the underlying mechanism related to macrophage phenotypic polarization. A. muciniphila inhibited weight loss, increased disease activity index, and ameliorated inflammatory injury in colonic tissues in mice induced with DSS. Furthermore, A. muciniphila reduced macrophage M1 polarization and ameliorated epithelial barrier damage in colonic tissues of DSS-induced mice through inhibition of histone deacetylase 5 (HDAC5). In contrast, the effect of A. muciniphila was compromised by HDAC5 overexpression. HDAC5 deacetylated H3K9ac modification of the disabled homolog 2 (DAB2) promoter, which led to repressed DAB2 expression. DAB2 overexpression blocked HDAC5-induced pro-inflammatory polarization of macrophages, whereas knockdown of DAB2 resulted in the loss of effects of A. muciniphila against colonic injury in DSS-induced mice. Taken together, A. muciniphila-induced loss of HDAC5 hampered the deacetylation of DAB2 and enhanced the expression of DAB2. Our findings propose that A. muciniphila may be a possible probiotic agent for alleviating DSS-induced acute colitis.

A critical role for CaMKII in behavioral timescale synaptic plasticity in hippocampal CA1 pyramidal neurons.

Behavioral timescale synaptic plasticity (BTSP) is a type of non-Hebbian synaptic plasticity reported to underlie place field formation. Despite this important function, the molecular mechanisms underlying BTSP are poorly understood. The α-calcium-calmodulin-dependent protein kinase II (αCaMKII) is activated by synaptic transmission-mediated calcium influx, and its subsequent phosphorylation is central to synaptic plasticity. Because the activity of αCaMKII is known to outlast the event triggering phosphorylation, we hypothesized that it could mediate the extended timescale of BTSP. To examine the role of αCaMKII in BTSP, we performed whole-cell in vivo and in vitro recordings in CA1 pyramidal neurons from mice engineered with a point mutation at the autophosphorylation site (T286A) causing accelerated signaling kinetics. Here, we demonstrate a profound deficit in synaptic plasticity, strongly suggesting that αCaMKII signaling is required for BTSP. This study elucidates part of the molecular mechanism of BTSP and provides insight into the function of αCaMKII in place cell formation and ultimately learning and memory.

Effects of marital status on survival of retroperitoneal liposarcomas stratified by age and sex: A population-based study.

BACKGROUND: Previous studies have shown that marital status is associated with survival in patients with a variety of cancer types, including lung cancer, prostate cancer, and bladder cancer. However, to date, the impact of marital status on the survival of patients with retroperitoneal liposarcomas (RPLs) has not been established. METHODS: A total of 1211 eligible patients diagnosed with RPLs were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The relationships between marital status and survival in patients with RPLs were assessed. Patients were stratified by age to determine whether an association exists between marital status and age. We also probed the association between marital status and survival in males and females. RESULTS: Our findings suggest that divorced, separated, or widowed patients have more advanced cancer stages, and more of these patients do not undergo surgery. Meanwhile, divorced, separated, or widowed patients have worse survival outcomes than married patients (overall survival (OS): HR = 1.66 (95% CI, 1.12, 2.46)); cancer-specific survival (CSS): HR = 1.90 (95% CI, 1.13, 3.19)). OS does not differ between single patients and married patients (HR = 1.21 [95% CI, 0.81, 1.81]) or CSS (HR = 1.36 [95% CI, 0.80, 2.29]). In addition, these results demonstrate that being divorced, separated, or widowed can play a significant detrimental role in mortality in older and female patients. CONCLUSION: Married patients have earlier disease stages at diagnosis and better survival outcomes than divorced, separated, or widowed patients with RPLs. In addition, this effect is especially pronounced in older people and females.

Positive Effects of Organic Amendments on Soil Microbes and Their Functionality in Agro-Ecosystems.

Soil microbial characteristics are considered to be an index for soil quality evaluation. It is generally believed that organic amendments replacing chemical fertilizers have positive effects on changing microbial activity and community structure. However, their effects on different agro-ecosystems on a global scale and their differences in different environmental conditions and experimental durations are unclear. This study performed a meta-analysis based on 94 studies with 204 observations to evaluate the overall effects and their differences in different experimental conditions and duration. The results indicated that compared to chemical fertilizer, organic amendments significantly increased total microbial biomass, bacterial biomass, fungal biomass, Gram-positive bacterial biomass and Gram-negative bacterial biomass, and had no effect on the ratio of fungi to bacteria and ratio of Gram-positive bacteria to Gram-negative bacteria. Meanwhile, land use type, mean annual precipitation and soil initial pH are essential factors affecting microbial activity response. Organic-amendment-induced shifts in microbial biomass can be predominantly explained by soil C and nutrient availability changes. Additionally, we observed positive relationships between microbial functionality and microbial biomass, suggesting that organic-amendment-induced changes in microbial activities improved soil microbial functionality.

Meta-Analysis of Organic Fertilization Effects on Soil Bacterial Diversity and Community Composition in Agroecosystems.

Application of organic fertilizers or their combination with chemical fertilizers is a feasible practice for improving soil fertility and reducing soil degradation in agroecosystems, and these regulations are mainly mediated though soil microbial communities. Despite bacteria ranking among the most abundant and diverse groups of soil microorganisms, the effects of long-term organic fertilization (OF) and chemical-organic fertilization (COF) on soil bacterial diversity and community composition remain unclear. In this study, we conducted a meta-analysis and demonstrated that OF had no significant effect on bacterial alpha diversity. Application of chemical fertilizer and crop residue significantly decreased bacterial Richness index. Both OF and COF significantly altered bacterial community structure, with these changes being predominately attributed to shifts in soil pH. For bacterial phyla, both OF and COF significantly increased the relative abundance of Proteobacteria and Bacteroidetes, suggesting that OF and COF may cause the enrichment of copiotrophic taxa. In addition, COF significantly increased the relative abundance of Gammaproteobacteria but decreased the relative abundance of Acidobacteria. Overall, our results suggest that organic and chemical-organic fertilization can effectively maintain bacterial diversity and enhance soil fertility in agroecosystems, and the alteration of soil bacterial community structure is closely intertwined with soil pH.

Development and validation of a ligand-receptor pairs signature to predict outcome and provide a therapeutic strategy in gastric cancer.

BACKGROUND: An important factor in tumor development and progression is the tumor microenvironment (TME), which is heterogeneous. Previous studies have mainly investigated the expression profile and prognostic values of genes in gastric cancer (GC) at the cell population level but neglected the interactions and heterogeneity between cells. METHODS: The pattern of ligand-receptor (LR) interactions was delineated on a scRNA-seq dataset containing 44,953 cells from nine GC patients and a fourth bulk RNA-seq dataset including data from 1159 GC patients. We then constructed an LR.Score scoring model to comprehensively evaluate the influence of LR-pairs on the TME, overall survival, and immunotherapy response in GC patients from several cohorts. RESULTS: Cell communication network among 13 cell types was constructed based on the LR-pairs. We proposed a new molecular subtyping model for GC based on the LR-pairs and revealed the differences in prognosis, pathophysiologic features, mutation characteristics, function enrichment, and immunological characteristics among the three subtypes. Finally, an LR.Score model based on LR-pairs was developed and validated on several datasets. CONCLUSIONS: Based on the selected LR-pairs, we successfully constructed a novel prediction model and observed its well performance on molecular subtyping, target and pathway screening, prognosis judging, and immunotherapy response predicting.