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A healthy immune system is pivotal for the hosts to resist external pathogens and maintain homeostasis; however, the immunosuppressive tumor microenvironment (TME) damages the anti-tumor immunity and promotes tumor progression, invasion, and metastasis. Recently, many studies have found that Foxp3+ regulatory T (Treg) cells are the major immunosuppressive cells that facilitate the formation of TME by promoting the development of various tumor-associated cells and suppressing the activity of effector immune cells. Considering the role of Tregs in tumor progression, it is pivotal to identify new therapeutic drugs to target and deplete Tregs in tumors. Although several studies have developed strategies for targeted deletion of Treg to reduce the TME and support the accumulation of effector T cells in tumors, Treg-targeted therapy systematically affects the Treg population and may lead to the progression of autoimmune diseases. It has been understood that, nevertheless, in disease conditions, Foxp3 undergoes several definite post-translational modifications (PTMs), including acetylation, glycosylation, phosphorylation, ubiquitylation, and methylation. These PTMs not only elevate or mitigate the transcriptional activity of Foxp3 but also affect the stability and immunosuppressive function of Tregs. Various studies have shown that pharmacological targeting of enzymes involved in PTMs can significantly influence the PTMs of Foxp3; thus, it may influence the progression of cancers and/or autoimmune diseases. Overall, this review will help researchers to understand the advances in the immune-suppressive mechanisms of Tregs, the post-translational regulations of Foxp3, and the potential therapeutic targets and strategies to target the Tregs in TME to improve anti-tumor immunity.

Ferroptosis, a new form of programmed cell death, not only promotes the pathological process of various human diseases, but also regulates cancer progression. Current perspectives on the underlying mechanisms remain largely unknown. Herein, we report a member of the NEET protein family, CISD3, exerts a regulatory role in cancer progression and ferroptosis both in vivo and in vitro. Pan-cancer analysis from TCGA reveals that expression of CISD3 is generally elevated in various human cancers which are consequently associated with a higher hazard ratio and poorer overall survival. Moreover, knockdown of CISD3 significantly accelerates lipid peroxidation and accentuates free iron accumulation triggered by Xc – inhibition or cystine-deprivation, thus causing ferroptotic cell death. Conversely, ectopic expression of the shRNA-resistant form of CISD3 (CISD3res) efficiently ameliorates the ferroptotic cell death. Mechanistically, CISD3 depletion presents a metabolic reprogramming toward glutaminolysis, which is required for the fuel of mitochondrial oxidative phosphorylation. Both the inhibitors of glutaminolysis and the ETC process were capable of blocking the lipid peroxidation and ferroptotic cell death in the shCISD3 cells. Besides, genetic and pharmacological activation of mitophagy can rescue the CISD3 knockdown-induced ferroptosis by eliminating the damaged mitochondria. Noteworthily, GPX4 acts downstream of CISD3 mediated ferroptosis, which fails to reverse the homeostasis of mitochondria. Collectively, the present work provides novel insights into the regulatory role of CISD3 in ferroptotic cell death and presents a potential target for advanced antitumor activity through ferroptosis.

Background Fresh embryo transfer reduces waiting time and minimizes embryo cryodamage for endometriosis (EM) patients. The current prediction models for fresh embryo transfer outcomes in EM primarily rely on logistic regression, with limited application of machine learning (ML) approaches. This study aimed to develop an ML-based predictive model for clinical pregnancy in EM patients undergoing fresh embryo transfer. Methods A retrospective analysis included 1752 EM patients undergoing IVF/ICSI with fresh embryo transfer (2014–2024). Twenty-four clinical and embryonic characteristics were predictors; clinical pregnancy was the outcome. Six ML models—Naïve Bayes, Logistic Regression, Random Forest, k-Nearest Neighbors, Neural Network, and eXtreme Gradient Boosting (XGBoost)—were developed and compared. Feature selection involved logistic regression and Random Forest recursive feature elimination, with tenfold cross-validation. Results Male age (OR = 0.96, 95% CI 0.93–0.98, p < 0.001), normal fertilization count (OR = 1.07, 95% CI 1.03–1.11, p = 0.001), and transferred embryo count (OR = 1.61, 95% CI 1.24–2.08, p < 0.001) significantly predicted clinical pregnancy. The XGBoost model demonstrated optimal performance (training AUC: 0.764; testing AUC: 0.622). Shapley Additive Explanations (SHAP) provided model interpretability. Conclusions An XGBoost-based model effectively predicts clinical pregnancy in EM patients after fresh embryo transfer, showing acceptable performance and interpretability.

Temperature tolerance is an important trait from both an economic and evolutionary perspective in fish. Because of difficulties with measurements, genome-wide selection using quantitative trait loci (QTLs) affecting Upper temperature tolerance may be an alternative for genetic improvement. Turbot Scophthalmus maximus (L.) is a cold-water marine fish with high economic value in Europe and Asia. The genetic bases of upper temperature tolerance (UTTs) traits have been rarely studied. In this study, we constructed a genetic linkage map of turbot using simple sequence repeats (SSRs) and single nucleotide polymorphism (SNP) markers. A total of 190 SSR and 8,123 SNP were assigned to 22 linkage groups (LGs) of a consensus map, which spanned 3,648.29 cM of the turbot genome, with an average interval of 0.44 cM. Moreover, we re-anchored genome sequences, allowing 93.8% physical sequences to be clustered into 22 turbot pseudo-chromosomes. A high synteny was observed between two assemblies from the literature. QTL mapping and validation analysis identified thirteen QLTs which are major effect QTLs, of these, 206 linked SNP loci, and two linked SSR loci were considered to have significant QTL effects. Association analysis for UTTs with 129 QTL markers was performed for different families, results showed that eight SNP loci were significantly correlated with UTT, which markers could be helpful in selecting thermal tolerant breeds of turbot. 1,363 gene sequences were genomically annotated, and 26 QTL markers were annotated. We believe these genes could be valuable candidates affecting high temperatures, providing valuable genomic resources for the study of genetic mechanisms regulating thermal stress. Similarly, they may be used in marker-assisted selection (MAS) programs to improve turbot performance.

Background Double crush syndrome (DCS) is a relatively rare nerve compression syndrome among peripheral nerve compression diseases. However, ulnar nerve double entrapment caused by peri-cubital tunnel ganglion cysts has been rarely reported. Case presentation Here, we present a case of a 54-year-old woman who experienced occasional pain, numbness and paralysis in her right half hand for 1 year. A B-ultrasound of the right elbow initially revealed cubital tunnel syndrome only. Further Magnetic Resonance Imaging (MRI) showed a ganglion cyst near the cubital tunnel. After evaluation, we performed open surgery to excise the cyst and incise the cubital tunnel, completely decompressing the ulnar nerve entrapment. Ulnar nerve anterior transposition was also performed simultaneously. Conclusions The patient was followed up for 1 month, and she experienced a complete recovery with no functional limitations. Clinical trial number Not applicable.

Turbot Scophthalmus maximus is an economically important species extensively aquacultured in China. The genetic selection program is necessary and urgent for the sustainable development of this industry, requiring more and more genome background knowledge. Transcriptome sequencing is an excellent alternative way to identify transcripts involved in specific biological processes and exploit a considerable quantity of molecular makers when no genome sequences are available. In this study, a comprehensive transcript dataset for major tissues of S. maximus was produced on basis of an Illumina platform. Total RNA was isolated from liver, spleen, kidney, cerebrum, gonad (testis and ovary) and muscle. Equal quantities of RNA from each type of tissues were pooled to construct two cDNA libraries (male and female). Using the Illumina paired-end sequencing technology, nearly 44.22 million clean reads in length of 100 bp were generated and then assembled into 106,643 contigs, of which 71,107 were named unigenes with an average length of 892 bp after the elimination of redundancies. Of these, 24,052 unigenes (33.83% of the total) were successfully annotated. GO, KEGG pathway mapping and COG analysis were performed to predict potential genes and their functions. Based on our sequence analysis and published documents, many candidate genes with fundamental roles in sex determination and gonad differentiation (dmrt1), growth (ghrh, myf5, prl/prlr) and immune response (TLR1/TLR21/TLR22, IL-15/IL-34), were identified for the first time in this species. In addition, a large number of credible genetic markers, including 21,192 SSRs and 8,642 SNPs, were identified in the present dataset. This informative transcriptome provides valuable new data to increase genomic resources of Scophthalmus maximus. The future studies of corresponding gene functions will be very useful for the management of reproduction, growth and disease control in turbot aquaculture breeding programs. The molecular markers identified in this database will aid in genetic linkage analyses, mapping of quantitative trait loci, and acceleration of marker assisted selection programs.

Accurate traffic flow prediction is highly important for relieving road congestion. Due to the intricate spatial–temporal dependence of traffic flows, especially the hidden dynamic correlations among road nodes, and the dynamic spatial–temporal characteristics of traffic flows, a traffic flow prediction model based on an interactive dynamic spatial–temporal graph convolutional probabilistic sparse attention mechanism (IDG-PSAtt) is proposed. Specifically, the IDG-PSAtt model consists of an interactive dynamic graph convolutional network (IL-DGCN) with a spatial–temporal convolution (ST-Conv) block and a probabilistic sparse self-attention (ProbSSAtt) mechanism. The IL-DGCN divides the time series of a traffic flow into intervals and synchronously and interactively shares the captured dynamic spatiotemporal features. The ST-Conv block is utilized to capture the complex dynamic spatial–temporal characteristics of the traffic flow, and the ProbSSAtt block is utilized for medium-to-long-term forecasting. In addition, a dynamic GCN is generated by fusing adaptive and learnable adjacency matrices to learn the hidden dynamic associations among road network nodes. Experimental results demonstrate that the IDG-PSAtt model outperforms the baseline methods in terms of prediction accuracy. Specifically, on METR-LA, the mean absolute error (MAE) and root mean square error (RMSE) induced by IDG-PSAtt for a 60 min forecasting scenario are reduced by 0.75 and 1.31, respectively, compared to those of the state-of-the-art models. This traffic flow prediction improvement will lead to more precise estimates of the emissions produced by mobile sources, resulting in more accurate air quality forecasts. Consequently, this research will greatly support local environmental management efforts.

Purpose To study the relationship between blastomere number and pregnancy outcomes of day 3 embryo transfers. Methods This retrospective cohort study included 2237 fresh single day 3 embryo transfer cycles from October 2013 to November 2020. Patients were divided into six groups according to the blastomere number on day 3: ≤ 6-cell ( n  = 100), 7-cell ( n  = 207), 8-cell ( n  = 1522), 9-cell ( n  = 187), 10-cell ( n  = 91) and ≥ 11-cell ( n  = 130). Generalized estimating equation analysis based on multivariate logistic regression model was performed to adjust for potential confounders. Results The live birth rate (LBR) was 19.0%, 27.1%, 38.9%, 32.1%, 44.0% and 53.8% for the ≤ 6-cell, 7-cell, 8-cell, 9-cell, 10-cell and ≥ 11-cell groups, respectively ( P  < 0.001). Specifically, the ≤ 6-cell group was associated with reduced LBR compared with the 8-cell group (aOR 0.50, 95% CI 0.29–0.86; P  = 0.013). Conversely, the odds of live birth were significantly increased in patients transferred with 10-cell embryos (aOR 1.62, 95% CI 1.03–2.53; P  = 0.035) and ≥ 11-cell embryos (aOR 2.14, 95% CI 1.47–3.11; P  < 0.001) when using the 8-cell embryo group as reference. Similar trends were also observed in the rates of positive hCG test and clinical pregnancy, while no significant differences were detected in miscarriage risk. Conclusion Increased blastomere number was associated with higher LBR in fresh single day 3 embryo transfer cycles. This finding questions the consensus on the reduced developmental potential of fast-cleaving embryos. Further large prospective studies are warranted for confirmation.

Functional constipation (FC) is a common functional gastrointestinal disorder thought to arise from the brain–gut axis dysfunction, yet direct human neurophysiological evidence is lacking. We recorded high-density electroencephalography (EEG) data in 21 FC patients and 37 healthy controls across resting, cognitive, and defecation-related tasks. We observed that FC patients displayed a consistent, task-dependent signature compared with healthy controls. At the regional level, FC patients exhibited increased alpha during both resting and defecation-related tasks, reduced temporal gamma during defecation-related tasks, as well as elevated temporal theta during the cognitive task. At the global level, we found altered network properties, such as global efficiency in the delta and beta band networks during resting and defecation-related tasks. These findings establish a direct neurophysiological link between specific, condition-dependent perturbations in cortical rhythm activity and FC pathophysiology. Our work implicates the brain–gut axis in symptom generation and opens a path toward EEG-based biomarkers and targeted neuromodulatory therapies.