Evaluating the spatiotemporal land ecological changes in the Yangtze-to-Huaihe Water Diversion Project area.

As a fundamental component of human existence, land is inextricably linked to human development, and its ecological functions are closely associated with multiple sustainable development goals. This paper presents a framework for constructing and optimizing ecological function space, with the Yangtze-to-Huaihe Water Diversion Project area serving as a case study. A comprehensive land ecological index system is established, encompassing natural foundation, land degradation, land production, ecological structure, and ecological protection. An identity-discrepancy-contrary connection method is employed to investigate changes in regional land ecological functions before (2013) and during (2017, 2020, and 2022) the project's construction based on remote sensing data. The results indicated that the mean values of the land ecological index for each period were 0.1883, 0.1981, 0.2253, and 0.1370, respectively. The study calculated the connection, differences, and contradictions in the land ecological impacts across the counties, revealing a gradual decrease in differences and a growing prominence of contradictions. The land ecology of the Yangtze-to-Huaihe Water Diversion Project area is affected by the project construction, particularly within the construction area, showing an overall improvement. Most counties exhibited a trend of ecological improvement compared to the land ecology before the project's construction. However, after the project implementation, most districts demonstrated a trend of ecological deterioration. As the distance from the construction canal increases, the characteristics of each section and stage vary, generally exhibiting an exponential decrease in the land ecological index. The study highlighted the significance of enhancing the land ecological pattern, improving water quality, increasing water supply along the project, and alleviating groundwater overexploitation. The study can serve as a reference for land ecological protection and restoration in water transfer areas and river basins worldwide.

IFN-γ induces acute graft-versus-host disease by promoting HMGB1-mediated nuclear-to-cytoplasm translocation and autophagic degradation of p53.

Acute graft-versus-host disease (aGVHD) poses a significant impediment to achieving a more favourable therapeutic outcome in allogeneic hematopoietic stem cell transplantation (allo-HSCT). Our prior investigations disclosed a correlation between p53 downregulation in CD4+ T cells and the occurrence of aGVHD. Notably, the insufficiency of the CCCTC-binding factor (CTCF) emerged as a pivotal factor in repressing p53 expression. However, the existence of additional mechanisms contributing to the reduction in p53 expression remains unclear. Interferon (IFN)-γ, a pivotal proinflammatory cytokine, assumes a crucial role in regulating alloreactive T cell responses and plays a complex part in aGVHD development. IFN-γ has the capacity to induce autophagy, a vital catabolic process facilitating protein degradation, in various cell types. Presently, whether IFN-γ participates in the development of aGVHD by instigating the autophagic degradation of p53 in CD4+ T cells remains an unresolved question. In this study, we demonstrated that heightened levels of IFN-γ in the plasma during aGVHD promoted the activation, proliferation, and autophagic activity of CD4+ T cells. Furthermore, IFN-γ induced the nuclear-to-cytoplasm translocation and autophagy-dependent degradation of p53 in CD4+ T cells. The translocation and autophagic degradation of p53 were contingent upon HMGB1, which underwent upregulation and translocation from the nucleus to the cytoplasm following IFN-γ stimulation. In conclusion, our data unveil a novel mechanism underlying p53 deficiency in CD4+ T cells among aGVHD patients. This deficiency is induced by IFN-γ and relies on autophagy, establishing a link between IFN-γ, HMGB1-mediated translocation, and the autophagic degradation of p53.

A network pharmacology and transcriptome analysis of the therapeutic effects of tea tree oil on the lungs of chicks exposed to hydrogen sulfide.

This study investigated the use of tea tree oil (TTO) in the treatment of H2S-induced lung injury in chickens, focusing on the detoxification mechanism. H2S can damage the respiratory system and reduce growth performance. TTO can improve immune inflammation and growth performance. The mechanism by which TTO mitigates the harmful effects of H2S on chicken lungs remains unclear. Therefore, the experimental model was established by H2S exposure and TTO addition in drinking water. The 240 one-day-old Roman pink chicks were selected for the experiment. The trial was divided into control group (CON), treatment group (TTG, 0.02 mL/L TTO+H2S) and H2S exposure group (AVG, H2S). There were 4 replicates in each group and the trial lasted for 42 d. The therapeutic effect of TTO on lung injury in chickens were determined by growth performance evaluation, transcription sequencing and network pharmacology analysis. The results showed that in the test's third week, the body weights of the chickens in the CON were higher than those in the AVG and TTG (P < 0.05). Pathological sections showed that TTO alleviated the symptoms of lung inflammation and bleeding caused by ROS. As showed by transcriptional sequencing, the mRNA expression of apoptosis-related genes Caspase-9, BAK-1, BCL-2 and BAX were significantly altered (P < 0.05). Meanwhile, the mRNA expression of inflammation-related genes IL-2, IL-6, and IL-17 were downregulated (P < 0.05). Network pharmacological analysis showed that CA2, CA4, GABRA5 and ADH1C were the key targets of TTO. The TTO treatment significantly altered these targets (P < 0.05). Molecular docking confirmed the strong binding ability between the active component and the targets. This study showed that TTO inhibits H2S-induced oxidative damage to the lungs, thereby improving their health status. This provides a new solution for the prevention of harmful gas in the poultry industry.

Rationally designed hierarchical hollow CuS/CdIn2S4 heterostructure nanoboxes for boosted photoreduction of CO2.

A novel double-shelled CuS/CdIn2S4 photocatalyst was rationally designed using CdIn2S4 sheets in situ grown upon the exterior of hollow CuS nanocubes. The unique hierarchical hollow structure of CuS/CdIn2S4 provides numerous active sites and reduces carrier diffusion length. Surface sulfur vacancies mitigate the detachment of the intermediate, which is favorable for a multi-electron reaction path such as that in the production of CH4. Meanwhile, a suitable band-structure alignment between p-type CuS and n-type CdIn2S4 leads to the formation of a type-II heterostructure, thus resulting in effective light-harvesting and spatial separation of electron-hole pairs for CO2 photoreduction. The CuS/CdIn2S4 heterostructure exhibits significantly enhanced performance with a boosted CO yield of 40.73 µmol g-1 h-1 as well as a noticeably improved CH4 selectivity (36.5%, 23.41 µmol g-1 h-1). This work introduces innovative concepts in designing photocatalytic systems with unique morphologies and rational band structures, promising advancements in CO2 photoreduction at reduced costs.

Assembly of protein-directed fluorescent gold nanoclusters for high-sensitivity detection of uranyl ions.

Uranium is a key element in the nuclear industry, whose accidental release causes health and environmental problems. In this paper, a protein-directed fluorescent sensor with aggregation-induced emission characteristics (gold nanoclusters@ovalbumin, AuNCs@OVA) was synthesized for the detection of UO22+ with high sensitivity and selectivity. The sensor exhibited good fluorescence stability, and its fluorescence intensity could be selectively enhanced by UO22+. Based on FT-IR and XPS analyses, the increase in fluorescence intensity of AuNCs@OVA after the addition of UO22+ was attributed to aggregation induced by the complexation between UO22+ and the amino, carboxyl, hydroxyl, and phosphate groups of ovalbumin. The detection limit was determined to be 34.4 nM, and the sensor showed excellent ion selectivity for UO22+. In combination with a smartphone program, the sensor could realize the real-time detection of UO22+ in a quantitative and portable way.

Suppression of P53 Pathway is an Important Factor Inducing Acute Graft-versus-Host Disease Through T Cell Activation Based on Bioinformatics Analysis.

Purpose: Acute graft-versus-host disease (aGVHD) poses a significant impediment to achieving a more favourable therapeutic outcome in allogeneic hematopoietic stem cell transplantation (allo-HSCT). The tumour suppressor p53 plays a pivotal role in preventing aGVHD development. However, whether P53 pathway which contains p53 family members and other related genes participates in aGVHD development remains an unsolved question. Patients and Methods: Transcriptomic data was obtained from Gene Expression Omnibus (GEO) database. Gene set enrichment analysis was applied to determine the enrichment degree of signaling pathways. CIBERSORT and ssGSVA were used to evaluate immune cell compositions. Univariate and multivariate logistic regression analysis were performed to examine the independent diagnostic variables. qRT-PCR was utilized to validate the genes expression levels in our cohort. Results: A total number of 102 patients (42 aGVHD patients vs 60 non-aGVHD patients) were obtained after integrating two datasets in GEO database (GSE73809 and GSE4624). P53 pathway was remarkably suppressed in T cells from aGVHD patients and negatively associated with activated T cells as well as T cells activation related signaling pathways, including T-cell receptor (TCR), mTORC1, MYC and E2F target pathways. A risk model for aGVHD built by four genes (DDIT3, FBXW7, TPRKB and TOB1) in P53 pathway, exhibiting high differentiate and predictive value. DDIT3 and FBXW7 mRNA expression levels significantly decreased in peripheral blood mononuclear cells (PBMCs) from aGVHD patients compared with non-aGVHD group in our patient cohort, consisting with bioinformatics analysis. Conclusion: P53 pathway plays a potential role in impeding T cell activation through suppressing its related signaling pathways, thereby preventing aGVHD development. P53 pathway may emerge as a promising therapeutic target in aGVHD treatment.

YTHDF2 regulates MSS51 expression contributing to mitochondria dysfunction of granulosa cells in polycystic ovarian syndrome patients.

RESEARCH QUESTION: Granulosa cells (GCs) dysfunction plays a crucial role in the pathogenesis of polycystic ovary syndrome (PCOS). It is reported that YTH domain-containing family protein 2 (YTHDF2) is upregulated in mural GCs of PCOS patients. What effect does the differential expression of YTHDF2 have in PCOS patients? DESIGN: Mural GCs and cumulus GCs from 15 patients with PCOS and 15 ovulatory controls and 4 cases of pathological sections in each group were collected. Real-time PCR, Western Blot, immunohistochemistry, and immunofluorescence experiments were conducted to detect gene and protein expression. RNA immunoprecipitation assay was performed to evaluate the binding relationship between YTHDF2 and MSS51. Mitochondrial morphology, cellular ATP and ROS levels and glycolysis-related gene expression were detected after YTHDF2 overexpression or MSS51 inhibition. RESULTS: In the present study, we found that YTHDF2 was upregulated in GCs of PCOS patients while MSS51 was downregulated. YTHDF2 protein can bind to MSS51 mRNA and affect MSS51 expression. The reduction of MSS51 expression or the increase in YTHDF2 expression can lead to mitochondrial damage, reduced ATP levels, increased ROS levels and reduced expression of LDHA, PFKP and PKM. CONCLUSIONS: YTHDF2 may regulate the expression of MSS51, affecting the structure and function of mitochondria in GCs and interfering with cellular glycolysis, which may disturb the normal biological processes of GCs and follicle development in PCOS patients.

Development of an mRNA-based therapeutic vaccine mHTV-03E2 for high-risk HPV-related malignancies.

Human papillomavirus (HPV) 16 and 18 infections are related to many human cancers. Despite several preventive vaccines for high-risk (hr) HPVs, there is still an urgent need to develop therapeutic HPV vaccines for targeting pre-existing hrHPV infections and lesions. In this study, we developed a lipid nanoparticle (LNP)-formulated mRNA-based HPV therapeutic vaccine (mHTV)-03E2, simultaneously targeting the E2/E6/E7 of both HPV16 and HPV18. mHTV-03E2 dramatically induced antigen-specific cellular immune responses, leading to significant CD8+ T cell infiltration and cytotoxicity in TC-1 tumors derived from primary lung epithelial cells of C57BL/6 mice expressing HPV E6/E7 antigens, mediated significant tumor regression, and prolonged animal survival, in a dose-dependent manner. We further demonstrated significant T cell immunity against HPV16/18 E6/E7 antigens for up to 4 months post-vaccination in immunological and distant tumor rechallenging experiments, suggesting robust memory T cell immunity against relapse. Finally, mHTV-03E2 synergized with immune checkpoint blockade to inhibit tumor growth and extend animal survival, indicating the potential in combination therapy. We conclude that mHTV-03E2 is an excellent candidate therapeutic mRNA vaccine for treating malignancies caused by HPV16 or HPV18 infections.

Tea tree oil inhibits hydrogen sulfide-induced oxidative damage in chicken lungs through CYP450s/ROS pathway.

A large amount of hydrogen sulfide (H2S) is produced in the process of chicken breeding, which can cause serious inflammation and oxidative damage to the respiratory system of chickens. Tea tree oil (TTO) has antioxidant and anti-inflammatory properties. No studies have been reported on the use of TTO in H2S-induced lung injury in chickens. Therefore, in this study, 240 one-day-old Roman pink laying hens were randomly and equally divided into 3 groups: control group (CON), H2S exposure group (AVG, containing H2S), and TTO treatment group (TTG, containing H2S and 0.02 mL/L TTO) to establish an experimental model of TTO treatment with H2S exposure for a period of 42 d. Hematoxylin and eosin (H&E) staining was used to detect lung histopathology. Gene expression profiles were analyzed using transcriptomics. The underlying mechanism of the amelioration of lung injury by TTO was further revealed by antioxidant enzyme assays and qRT-PCR. The results showed that H2S exposure induced significant gene expression of CYP450s (CYP1B1 and CYP1C1) (P < 0.05), and caused intense oxidative stress, apoptosis and inflammation compared with CON. TTO could reduce ROS production and enhance antioxidant capacity (SOD, CAT, T-AOC, and GSH-PX) by regulating the CYP450s/ROS pathway (P < 0.05). Compared with the control group, the treatment group showed significantly decreased expression of apoptotic (Caspase-8, Caspase-3, Bid and Fas) (P < 0.05) and inflammatory (IL-4, IL-16, NF-κB, TNF-α and IFN-γ) (P < 0.05) factors in the lung. This study revealed that TTO regulated CYP450s/ROS pathway to alleviate H2S-induced lung injury in chickens. These results enrich the theory of the action mechanism of TTO on H2S-exposed chicken lungs and are of great value for the treatment of H2S-exposed animals.

Construction of a diagnostic model based on random forest and artificial neural network for peri-implantitis.

OBJECTIVES: This study aimed to reveal critical genes regulating peri-implantitis during its development and construct a diagnostic model by using random forest (RF) and artificial neural network (ANN). METHODS: GSE-33774, GSE106090, and GSE57631 datasets were obtained from the GEO database. The GSE33774 and GSE106090 datasets were analyzed for differential expression and functional enrichment. The protein-protein interaction networks (PPI) and RF screened vital genes. A diagnostic model for peri-implantitis was established using ANN and validated on the GSE33774 and GSE57631 datasets. A transcription factor-gene interaction network and a transcription factor-micro-RNA (miRNA) regulatory network were also established. RESULTS: A total of 124 differentially expressed genes (DEGs) involved in the regulation of peri-implantitis were screened. Enrichment analysis showed that DEGs were mainly associated with immune receptor activity and cytokine receptor activity and were mainly involved in processes such as leukocyte and neutrophil migration. The PPI and RF screened six essential genes, namely, CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8. The receiver operating characteristic curve (ROC) indicated that the ANN model had an excellent diagnostic performance. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 may be a key miRNA. CONCLUSIONS: The diagnostic model of peri-implantitis constructed by RF and ANN has high confidence, and CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8 are potential diagnostic markers. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 plays a vital role as a critical miRNA.

The antagonism mechanism of astilbin against cadmium-induced injury in chicken lungs via Treg/Th1 balance signaling pathway.

The purpose of this study was to investigate the effect of Treg/Th1 imbalance in cadmium-induced lung injury and the potential protective effect of astilbin against cadmium-induced lung injury in chicken. Cadmium exposure significantly decreased T-AOC and GSH-Px levels and SOD activity in the chicken lung tissues. In contrast, it significantly increased the MDA and NO levels. These results indicate that cadmium triggers oxidative stress in lungs. Histopathological analysis revealed that cadmium exposure further induced infiltration of lymphocytes in the chicken lungs, indicating that cadmium causes pulmonary damage. Further analysis revealed that cadmium decreased the expression of IL-4 and IL-10 but increased those of IL-17, Foxp3, TNF-α, and TGF-ß, indicating that the exposure of cadmium induced the imbalance of Treg/Th1. Moreover, cadmium adversely affected chicken lung function by activating the NF-kB pathway and inducing expression of genes downstream to these pathways (COX-2, iNOS), associated with inflammatory injury in the lung tissue. Astilbin reduced cadmium-induced oxidative stress and inflammation in the lungs by increasing antioxidant enzyme activities and restoring Treg/Th1 balance. In conclusion, our results suggest that astilbin treatment alleviated the effects of cadmium-mediated lung injury in chickens by restoring the Treg/Th1 balance.

A novel approach for estimating lung tumor motion based on dynamic features in 4D-CT.

Due to the high expenses involved, 4D-CT data for certain patients may only include five respiratory phases (0%, 20%, 40%, 60%, and 80%). This limitation can affect the subsequent planning of radiotherapy due to the absence of lung tumor information for the remaining five respiratory phases (10%, 30%, 50%, 70%, and 90%). This study aims to develop an interpolation method that can automatically derive tumor boundary contours for the five omitted phases using the available 5-phase 4D-CT data. The dynamic mode decomposition (DMD) method is a data-driven and model-free technique that can extract dynamic information from high-dimensional data. It enables the reconstruction of long-term dynamic patterns using only a limited number of time snapshots. The quasi-periodic motion of a deformable lung tumor caused by respiratory motion makes it suitable for treatment using DMD. The direct application of the DMD method to analyze the respiratory motion of the tumor is impractical because the tumor is three-dimensional and spans multiple CT slices. To predict the respiratory movement of lung tumors, a method called uniform angular interval (UAI) sampling was developed to generate snapshot vectors of equal length, which are suitable for DMD analysis. The effectiveness of this approach was confirmed by applying the UAI-DMD method to the 4D-CT data of ten patients with lung cancer. The results indicate that the UAI-DMD method effectively approximates the lung tumor's deformable boundary surface and nonlinear motion trajectories. The estimated tumor centroid is within 2 mm of the manually delineated centroid, a smaller margin of error compared to the traditional BSpline interpolation method, which has a margin of 3 mm. This methodology has the potential to be extended to reconstruct the 20-phase respiratory movement of a lung tumor based on dynamic features from 10-phase 4D-CT data, thereby enabling more accurate estimation of the planned target volume (PTV).

Unraveling the distinction between depression and anxiety: A machine learning exploration of causal relationships.

OBJECTIVE: Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective healthcare interventions. This research addressed this gap by employing a streamlined Symptom Checklist 90 (SCL-90) designed to minimize patient response burden. Utilizing machine learning algorithms, the study sought to construct classification models capable of distinguishing between depression and anxiety. METHODS: The study included 4262 individuals currently experiencing depression alone (n = 2998), anxiety alone (n = 716), or both depression and anxiety (n = 548). Counterfactual diagnosis was used to construct a causal network on the dataset. Employing a causal network, the SCL-90 was simplified. Items that have causality with only depression, only anxiety and both depression and anxiety were selected, and these streamlined items served as input features for four distinct machine learning algorithms, facilitating the creation of classification models for distinguishing depression and anxiety. RESULTS: Cross-validation demonstrated the performance of the classification models with the following metrics: (1) K-nearest neighbors (AUC = 0.924, Acc = 92.81 %); (2) support vector machine (AUC = 0.937, Acc = 94.38 %); (3) random forest (AUC = 0.918, Acc = 94.38 %); and (4) adaptive boosting (AUC = 0.882, Acc = 94.38 %). Notably, the support vector machine excelled, with the highest AUC and superior accuracy. CONCLUSION: Incorporating the simplified SCL-90 and machine learning presents a promising, efficient, and cost-effective tool for the precise identification of depression and anxiety.

Implantable Neural Microelectrodes: How to Reduce Immune Response.

Implantable neural microelectrodes exhibit the great ability to accurately capture the electrophysiological signals from individual neurons with exceptional submillisecond precision, holding tremendous potential for advancing brain science research, as well as offering promising avenues for neurological disease therapy. Although significant advancements have been made in the channel and density of implantable neural microelectrodes, challenges persist in extending the stable recording duration of these microelectrodes. The enduring stability of implanted electrode signals is primarily influenced by the chronic immune response triggered by the slight movement of the electrode within the neural tissue. The intensity of this immune response increases with a higher bending stiffness of the electrode. This Review thoroughly analyzes the sequential reactions evoked by implanted electrodes in the brain and highlights strategies aimed at mitigating chronic immune responses. Minimizing immune response mainly includes designing the microelectrode structure, selecting flexible materials, surface modification, and controlling drug release. The purpose of this paper is to provide valuable references and ideas for reducing the immune response of implantable neural microelectrodes and stimulate their further exploration in the field of brain science.

Effects of Continuous Quality Improvement on Complication Rate and Treatment Outcome of Extremely Premature Infants.

Background: Extremely premature infants (EPIs) are those less than 32 weeks of gestational age. Preterm birth is the leading cause of neonatal death and poor prognosis, accounting for 25% of neonatal deaths, with extremely premature births accounting for 50% of all premature deaths. Continuous quality improvement (CQI) improves patient outcomes by changing and optimizing clinical practice including increasing participation of neonatologists in prenatal consultation, maintenance of normal body temperature in preterm infants, early use of pulmonary surfactant, reduction of mechanical ventilation time and intensive breastfeeding to reduce clinically avoidable adverse events. Objective: The risk of death and disability is high for very preterm infants, with a mortality rate of 30-50% and a risk of at least 20-50% for survivors. This study aimed to investigate the effect of CQI on the incidence of complications and treatment outcomes in very preterm infants. Design: This was a retrospective study. Setting: This study was conducted in the Maternal and Child Health Hospital of Hubei Province. Participants: A total of 140 EPIs born in our hospital and transferred to the neonatal intensive care unit between August 1, 2020, and July 31, 2022, were enrolled. The EPIs were divided into two groups: before improvement (n=79, 56.4%) and after improvement (n=61, 43.6%) according to the week of birth, and the gestational age ranged from 26 weeks to 26 weeks 6 days into the 26 weeks group. Interventions: From August 2021, the hospital implemented the CQI method, which included neonatologists' participation in consultations before birth, the care of a professionally trained resuscitation team after birth, and the introduction of transport heating tanks and ventilators during transport. Primary Outcome Measures: (1) Apgar score (2) body weight (3) duration of invasive ventilation (4) length of stay (5) treatment expense (6) incidence of complications and (7) survival rate of EPIs. Results: The application of CQI methods resulted in significant improvements in body weight (1305 g vs 1404 g) and duration of invasive ventilation (4.64 d vs 7.40 d) in EPIs (P = .036 and P = .040), reduced the time of invasive mechanical ventilation decreased significantly, from 7.4 days to 4.64 days (P < .01), increased the median temperature of newborn infants (36.2°C vs 35.7°C) (P = 0), increased the proportion of newborn infants with a temperature greater than 36°C (67.2% vs 35.4%) (P < .001), reduced the incidence of complications in EPIs (32.79% vs 45.57%) (P < .05). Conclusion: The application of the CQI approach significantly increases the body temperature, improves the incidence of complications of EPIs, and is conducive to the survival of EPIs. Our study may provide a clinical reference for management of EPIs.

Transcriptomic and Metabolomic Analyses Reveal the Response Mechanism of Ophiopogon japonicus to Waterlogging Stress.

Ophiopogon japonicus, a plant that thrives in river alluvial dams, often faces waterlogging stress due to sustained rainfall and flood seasons, which significantly impacts its growth and development. Currently, the mechanisms of waterlogging tolerance in Ophiopogon japonicus are still unclear. This study analyzed the transcriptome and metabolome data for Ophiopogon japonicus in the Sichuan region (referred to as CMD) under varying degrees of waterlogging stress: mild, moderate, and severe. The results indicate that the group exposed to flooding stress exhibited a higher number of differentially expressed genes (DEGs) compared to the control group. Notably, most DEGs were downregulated and primarily enriched in phenylpropanoid biosynthesis, starch and sucrose metabolism, and plant hormone signal transduction pathways. A total of 5151 differentially accumulated metabolites (DAMs) were identified, with significantly upregulated DAMs annotated to two clusters, namely flavonoids such as apiin, pelargonin, and others. Furthermore, our study revealed significant upregulation in the expression of C2H2 (C2H2 zinc finger proteins) and AP2/ERF-ERF (the subfamily ERF proteins of APETALA2/ethylene-responsive element binding factors) transcription factors in CMD under flooding stress, suggesting their critical roles in enabling CMD to adapt to these conditions. In conclusion, this research provides insights into the intricate molecular mechanisms underlying CMD's response to flooding stress and reports valuable genetic data for the development of transgenic plants with improved waterlogging tolerance.

Exploring the potential link between MitoEVs and the immune microenvironment of periodontitis based on machine learning and bioinformatics methods.

BACKGROUND: Periodontitis is a chronic inflammatory condition triggered by immune system malfunction. Mitochondrial extracellular vesicles (MitoEVs) are a group of highly heterogeneous extracellular vesicles (EVs) enriched in mitochondrial fractions. The objective of this research was to examine the correlation between MitoEVs and the immune microenvironment of periodontitis. METHODS: Data from MitoCarta 3.0, GeneCards, and GEO databases were utilized to identify differentially expressed MitoEV-related genes (MERGs) and conduct functional enrichment and pathway analyses. The random forest and LASSO algorithms were employed to identify hub MERGs. Infiltration levels of immune cells in periodontitis and healthy groups were estimated using the CIBERSORT algorithm, and phenotypic subgroups of periodontitis based on hub MERG expression levels were explored using a consensus clustering method. RESULTS: A total of 44 differentially expressed MERGs were identified. The random forest and LASSO algorithms identified 9 hub MERGs (BCL2L11, GLDC, CYP24A1, COQ2, MTPAP, NIPSNAP3A, FAM162A, MYO19, and NDUFS1). ROC curve analysis showed that the hub gene and logistic regression model presented excellent diagnostic and discriminating abilities. Immune infiltration and consensus clustering analysis indicated that hub MERGs were highly correlated with various types of immune cells, and there were significant differences in immune cells and hub MERGs among different periodontitis subtypes. CONCLUSION: The periodontitis classification model based on MERGs shows excellent performance and can offer novel perspectives into the pathogenesis of periodontitis. The high correlation between MERGs and various immune cells and the significant differences between immune cells and MERGs in different periodontitis subtypes can clarify the regulatory roles of MitoEVs in the immune microenvironment of periodontitis. Future research should focus on elucidating the functional mechanisms of hub MERGs and exploring potential therapeutic interventions based on these findings.

Dual consistency regularization with subjective logic for semi-supervised medical image segmentation.

Semi-supervised learning plays a vital role in computer vision tasks, particularly in medical image analysis. It significantly reduces the time and cost involved in labeling data. Current methods primarily focus on consistency regularization and the generation of pseudo labels. However, due to the model's poor awareness of unlabeled data, aforementioned methods may misguide the model. To alleviate this problem, we propose a dual consistency regularization with subjective logic for semi-supervised medical image segmentation. Specifically, we introduce subjective logic into our semi-supervised medical image segmentation task to estimate uncertainty, and based on the consistency hypothesis, we construct dual consistency regularization under weak and strong perturbations to guide the model's learning from unlabeled data. To evaluate the performance of the proposed method, we performed experiments on three widely used datasets: ACDC, LA, and Pancreas. Experiments show that the proposed method achieved improvement compared with other state-of-the-art (SOTA) methods.

Development and external validation of a nomogram predicting overall survival for Gastric adenocarcinoma patients with radical gastrectomy.

PURPOSE: The aim of this study was to develop and externally validate a nomogram to accurately predict the overall survival (OS) of patients with gastric adenocarcinoma who underwent radical gastrectomy. MATERIALS AND METHODS: A total of 3492 patients with gastric adenocarcinoma who underwent radical gastrectomy from 2012 to 2017 were included as the training cohort. Survival analysis was performed via Kaplan Meier method and log-rank test. Independent postoperative prognostic factors in patients with gastric adenocarcinoma were analyzed using univariate and multifactorial COX analysis methods. The prognosis nomogram was established in the training cohort and verified externally in the Surveillance, Epidemiology and End Results (SEER) database. RESULTS: According to the univariate and multifactorial COX analyses, metastatic lymph node ratio (MLNR) and five other independent prognostic factors (age at surgery, type of gastrectomy, tumor size, T stage, and pathological grade) were included in the prognostic nomogram. The nomogram had better prognostic predictive ability than the American Joint Committee on Cancer (AJCC) TNM staging in both the training (C-index: 0.736 VS. 0.668) and external validation cohort (C-index: 0.712 VS. 0.627). The calibration plots showed that the predicted survival rate was in good agreement with the actual survival rate. And the decision curve analysis (DCA) curves revealed that nomogram showed stronger ability in predicting 1-year, 3-year, and 5-year OS. CONCLUSION: This study estimated the excellent prognostic predictive power and clinical application potential of the MLNR-based nomogram, which may be used to facilitate postoperative clinical treatment decisions and potentially improve patient survival outcomes.