Myocardial strain is regulated by cardiac preload in the early stage of sepsis.

BACKGROUND: Owing to a lack of data, this study aimed to explore the effect of cardiac preload on myocardial strain in patients with sepsis. METHODS: A total of 70 patients with sepsis in intensive care unit (ICU) of a tertiary teaching hospital in China from January 2018 to July 2019 and underwent transthoracic echocardiography were enrolled. Echocardiographic data were recorded at ICU admission and 24 h later. Patients were assigned to low left ventricular end-diastolic volume index (LVEDVI) and normal LVEDVI groups. We assessed the impact of preload on myocardial strain between the groups and analyzed the correlation of echocardiographic parameters under different preload conditions. RESULTS: Thirty-seven patients (53%) had a low LVEDVI and 33 (47%) a normal LVEDVI. Those in the low LVEDVI group had a faster heart rate (121.7 vs. 95.3, p < 0.001) and required a greater degree of fluid infusion (3.67 L vs. 2.62 L, P = 0.019). The left ventricular global strain (LVGLS) (-8.60% vs. -10.80%, p = 0.001), left ventricular global circumferential strain (LVGCS) (-13.83% vs. -18.26%, p = 0.006), and right ventricular global longitudinal strain (RVGLS) (-6.9% vs. -10.60%, p = 0.001) showed significant improvements in the low LVEDVI group after fluid resuscitation. However, fluid resuscitation resulted in a significantly increased cardiac afterload value (1172.00 vs. 1487.00, p = 0.009) only in the normal LVEDVI group. Multivariate backward linear regression showed that LVEDVI changes were independently associated with myocardial strain-related improvements during fluid resuscitation. The baseline LVEDVI was significantly negatively correlated with the LVGLS and RVGLS (r = -0.44 and - 0.39, respectively) but not LVGCS. LVEDVI increases during fluid resuscitation were associated with improvements in the myocardial strain degree. CONCLUSIONS: Myocardial strain alterations were significantly influenced by the cardiac preload during fluid resuscitation in sepsis.

Identification of a cancer driver gene-associated lncRNA signature for prognostic prediction and immune response evaluation in clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) predominates among kidney cancer cases and is influenced by mutations in cancer driver genes (CDGs). However, significant obstacles persist in the early diagnosis and treatment of ccRCC. While various genetic models offer new hopes for improving ccRCC management, the relationship between CDG-related long non-coding RNAs (CDG-RlncRNAs) and ccRCC remains poorly understood. Therefore, this study aims to construct prognostic molecular features based on CDG-RlncRNAs to predict the prognosis of ccRCC patients, and aims to provide a new strategy to enhance clinical management of ccRCC patients. Methods: This study employed Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to comprehensively investigate the association between lncRNAs and CDGs in ccRCC. Leveraging The Cancer Genome Atlas (TCGA) dataset, we identified 97 prognostically significant CDG-RlncRNAs and developed a robust prognostic model based on these CDG-RlncRNAs. The performance of the model was rigorously validated using the TCGA dataset for training and the International Cancer Genome Consortium (ICGC) dataset for validation. Functional enrichment analysis elucidated the biological relevance of CDG-RlncRNA features in the model, particularly in tumor immunity. Experimental validation further confirmed the functional role of representative CDG-RlncRNA SNHG3 in ccRCC progression. Results: Our analysis revealed that 97 CDG-RlncRNAs are significantly associated with ccRCC prognosis, enabling patient stratification into different risk groups. Development of a prognostic model incorporating key lncRNAs such as HOXA11-AS, AP002807.1, APCDD1L-DT, AC124067.2, and SNHG3 demonstrated robust predictive accuracy in both training and validation datasets. Importantly, risk stratification based on the model revealed distinct immune-related gene expression patterns. Notably, SNHG3 emerged as a key regulator of the ccRCC cell cycle, highlighting its potential as a therapeutic target. Conclusions: Our study established a concise CDG-RlncRNA signature and underscored the pivotal role of SNHG3 in ccRCC progression. It emphasizes the clinical relevance of CDG-RlncRNAs in prognostic prediction and targeted therapy, offering potential avenues for personalized intervention in ccRCC.

Comparative long-term outcomes of pembrolizumab plus chemotherapy versus pembrolizumab monotherapy as first-line therapy for metastatic non-small-cell lung cancer: a systematic review and network meta-analysis.

Introduction: This systematic review and network meta-analysis(NMA) was designed to compare the long-term outcomes of pembrolizumab monotherapy and pembrolizumab plus chemotherapy as first-line therapy for metastatic non-small-cell lung cancer(NSCLC). Materials and Methods: Four databases(Medline, Embase, Web of Science and CENTRAL were searched published from establishment of database to August 17, 2023, for articles studying pembrolizumab monotherapy or pembrolizumab plus chemotherapy for non-small cell lung cancer (NSCLC). Network meta-analyses of progression-free survival(PFS), overall survival(OS), objective response rate(ORR), treatment-related adverse events(trAEs) and immune-related adverse events(irAEs) were performed. Results: A total of five studies were considered for NMA. This NMA includes a cohort of 2878 patients diagnosed with advanced NSCLC. Among them, 791 patients received pembrolizumab monotherapy, 1337 patients received chemotherapy, and 748 patients received pembrolizumab plus chemotherapy. The IPDformKM software was utilized to reconstruct Kaplan-Meier curves for OS and PFS, offering a lucid and intuitive depiction of oncological outcomes. For patients who have high levels of programmed death-ligand 1(PD-L1) expression (≥50%), pembrolizumab plus chemotherapy was more effective than using pembrolizumab alone as first-line therapy in terms of PFS (median survival time: 10.41 months versus 7.41 months, HR: 0.81, 95%CI 0.67 to 0.97, P=0.02) and ORR (RR:1.74, 95% CI: 1.25-2.43). Nevertheless, there was no statistically significant difference observed between the two groups in terms of OS (median survival time: 22.54 months versus 22.62 months, HR: 0.89, 95%CI 0.73 to 1.08, P=0.24). Furthermore, pembrolizumab plus chemotherapy provided a more advantageous long-term survival advantage in terms of OS (median survival time: 20.88 months versus 13.60 months, HR: 0.77, 95%CI: 0.62 to 0.95, P=0.015) compared to pembrolizumab monotherapy in patients with low PD-L1 expression levels (1% to 49%). With regards to safety, there was no statistically significant disparity between the two groups in relation to any irAEs (RD=0.02, 95% CI: -0.12 to 0.16) or Grade≥ 3 irAEs (RD=0.01, 95% CI: -0.10 to 0.12). Nevertheless, pembrolizumab plus chemotherapy exhibited a greater likelihood of encountering any trAEs (RD=0.23, 95% CI: 0.17 to 0.30) and Grade≥ 3 trAEs (RD=0.28, 95% CI: 0.21 to 0.35) in comparison to pembrolizumab monotherapy. Conclusions: The present network meta-analysis reported comparative long-term outcomes of pembrolizumab plus chemotherapy versus pembrolizumab monotherapy as first-line therapy for metastatic non-small-cell lung cancer. Pembrolizumab plus chemotherapy led to improved PFS and ORR in patients with advanced NSCLC who had a PD-L1 expression level of 50% or above. However, there was no noticeable benefit in terms of OS when pembrolizumab was paired with chemotherapy compared to utilizing pembrolizumab alone. In addition, pembrolizumab plus chemotherapy offered a greater long-term survival benefit in terms of OS when compared to utilizing pembrolizumab alone in patients with PD-L1 expression levels ranging from 1% to 49%. Furthermore, the increased effectiveness of pembrolizumab plus chemotherapy was accompanied by an increase in adverse side effects. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024501740.

Microbiome analysis in Asia's largest watershed reveals inconsistent biogeographic pattern and microbial assembly mechanisms in river and lake systems.

Microorganisms are critical to the stability of aquatic environments, and understanding the ecological mechanisms of microbial community is essential. However, the distinctions and linkages across biogeographic patterns, ecological processes, and formation mechanisms of microbes in rivers and lakes remain unknown. Accordingly, microbiome-centric analysis was conducted in rivers and lakes in the Yangtze River watershed. Results revealed significant differences in the structure and diversity of microbial communities between rivers and lakes, with rivers showing higher diversity. Lakes exhibited lower community stability, despite higher species interactions. Although deterministic processes dominated microbial community assembly both in rivers and lakes, higher stochastic processes of rare and abundant taxa exhibited in rivers. Spatial factors influenced river microbial community, while environmental factors drove differences in the lake bacterial community. This study deepened the understanding of microbial biogeography and formation mechanisms in large watershed rivers and lakes, highlighting distinct community aggregation patterns between river and lake microorganisms.

Palmitic acid induces ß-cell ferroptosis by activating ceramide signaling pathway.

Individuals with type 2 diabetes mellitus frequently display heightened levels of palmitic acid (PA) in their serum, which may lead to ß-cell damage. The involvement of ferroptosis, a form of oxidative cell death in lipotoxic ß-cell injury remains uncertain. Here, we have shown that PA induces intracellular lipid peroxidation, increases intracellular Fe2+ content and decreases intracellular glutathione peroxidase 4 (GPX4) expression. Furthermore, PA causes distinct changes in pancreatic islets and INS-1 cells, such as mitochondrial atrophy and increased membrane density. Furthermore, the presence of the ferroptosis inhibitor has a significant mitigating effect on PA-induced ß-cell damage. Mechanistically, PA increased ceramide content and c-Jun N-terminal kinase (JNK) phosphorylation. The ceramide synthase inhibitor effectively attenuated PA-induced ß-cell damage and GPX4/Fe2+ abnormalities, while inhibiting JNK phosphorylation. Additionally, the JNK inhibitor SP600125 improved PA-induced cell damage. In conclusion, by promoting ceramide synthesis, PA inhibited GPX4 expression and increased intracellular Fe2+ to induce ß-cell ferroptosis. Moreover, JNK may be a downstream mechanism of ceramide-triggered lipotoxic ferroptosis in ß-cells.

Surface Engineering of Cathode Materials: Enhancing the High Performance of Lithium-Ion Batteries.

The development and application of lithium-ion batteries present a dual global prospect of opportunity and challenge. With conventional energy sources facing reserve shortages and environmental issues, lithium-ion batteries have emerged as a transformative technology over the past decade, owing to their superior properties. They are poised for exponential growth in the realms of electric vehicles and energy storage. The cathode, a vital component of lithium-ion batteries, undergoes chemical and electrochemical reactions at its surface that directly impact the battery's energy density, lifespan, power output, and safety. Despite the increasing energy density of lithium-ion batteries, their cathodes commonly encounter surface-side reactions with the electrolyte and exhibit low conductivity, which hinder their utility in high-power and energy-storage applications. Surface engineering has emerged as a compelling strategy to address these challenges. This paper meticulously examines the principles and progress of surface engineering for cathode materials, providing insights into its potential advancements and charting its development trajectory for practical implementation.

The effect of behavioral activation play therapy in adolescents with depression: A study protocol for a randomized controlled trial.

BACKGROUND: Depression is a common psychological problem in adolescents worldwide. Although the World Health Organization recommends that members of this population engage in physical activity to reduce depressive symptoms, compliance with this recommendation is often low. Furthermore, although behavioral activation (BA) is recommended as a treatment for adolescents with depression, the reported effect size is small. Compared with traditional exercises, gamified physical activity (GPA) can be particularly appealing to adolescents because it is perceived as an enjoyable experience. In this study, we integrated BA and GPA to create behavioral activation play therapy (BAPT). We designed a clinical trial to investigate the feasibility, acceptability, and effectiveness of this treatment in adolescents with depression. METHODS: This study is a randomized controlled trial (RCT) with a three-arm, assessor-blinded design, conducted to validate the effectiveness and applicability of BAPT for treating adolescent with depression. We will recruit 258 participants and randomly assign them to a BAPT group, BA group, or GPA group using a ratio of 1:1:1. Based on conventional strategies for treatment and care, the three groups will receive nine BAPT sessions, nine BA sessions, or nine GPA sessions, respectively. We will compare the outcomes of the BAPT with those of the BA and GPA interventions. DISCUSSION: This is the first RCT to explore the effectiveness and applicability of BAPT in adolescents with depression. This study will provide evidence that may help to decrease depressive symptoms in adolescents, and will demonstrate the treatment effectiveness in terms of increasing levels of physical activity, reducing the rate of non-suicidal self-injury behaviors, and improving sleep quality. We will also assess the presence of side effects and the treatment adherence of patients receiving BAPT. TRIAL REGISTRATION: Trial registration: Chinese Clinical Trial Registry, ChiCTR2300072671. Registered on 20 June 2023.

Efficiency of therapeutic plasma exchange in critically ill systemic rheumatologic diseases: A single-center 9-year experience.

INTRODUCTION: Therapeutic plasma exchange (TPE), an effective method to eliminate harmful soluble mediators associated with tissue injury, serves as a crucial intervention for systemic rheumatologic diseases (SRDs). However, its value in critically ill SRDs remains uncertain. This retrospective study aims to evaluate the efficacy of TPE in SRDs. METHODS: Critically ill SRD patients admitted to the department of intensive care unit of a large tertiary hospital receiving TPE from January 2011 to December 2019 were included. RESULTS: A total of 91 critically ill SRD patients received TPE were enrolled. Their mean age was 47.67 ± 16.35 years with a female predominance (n = 68). Significant decrease in SOFA score post-TPE treatment was observed (p < 0.05). There were no TPE-related fatalities. Improvement was observed in 64 (70.32%) patients. CONCLUSION: This study shows favorable clinical outcomes. TPE may be an acceptable treatment option for critically ill SRD patients.

Visible-Light-Induced C-H Cyanoalkylation of Azauracils with Cycloketone Oxime Esters via Catalytic EDA Complex.

Photoexcitation electron donor-acceptor (EDA) complexes provide an effective approach to produce radicals under mild conditions, while the catalytic version of EDA complex photoactivation remains scarce. Herein, we report a visible-light-induced organophotocatalytic pathway for the cyanoalkylation of azauracils using inexpensive and readily available 1,4-diazabicyclo[2.2.2]octane (DABCO) as a catalytic electron donor. This synthetic method exhibits exceptional compatibility with various functional groups and presents 34 examples in high yields. The efficient cyanoalkylation offers an environmentally friendly and sustainable route toward enhancing the structural and functional diversity of azauracils.

Endogenous retroviral solo-LTRs in human genome.

Human endogenous retroviruses (HERVs) are derived from the infection and integration of exogenetic retroviruses. HERVs account for 8% of human genome, and the majority of HERVs are solitary LTRs (solo-LTRs) due to homologous recombination. Multiple findings have showed that solo-LTRs could provide an enormous reservoir of transcriptional regulatory sequences involved in diverse biological processes, especially carcinogenesis and cancer development. The link between solo-LTRs and human diseases still remains poorly understood. This review focuses on the regulatory modules of solo-LTRs, which contribute greatly to the diversification and evolution of human genes. More importantly, although inactivating mutations, insertions and deletions have been identified in solo-LTRs, the inherited regulatory elements of solo-LTRs initiate the expression of chimeric lncRNA transcripts, which have been reported to play crucial roles in human health and disease. These findings provide valuable insights into the evolutionary and functional mechanisms underlying the presence of HERVs in human genome. Taken together, in this review, we will present evidences showing the regulatory and encoding capacity of solo-LTRs as well as the significant impact on various aspects of human biology.

The potential mechanism of ursolic acid in the treatment of bladder cancer based on network pharmacology and molecular docking.

OBJECTIVE: This study explored the potential molecular mechanisms of ursolic acid (UA) in bladder cancer treatment using network pharmacology and molecular docking. METHODS: The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were used to screen potential targets of UA. Relevant bladder cancer target genes were extracted using the GeneCards database. All data were pooled and intercrossed to obtain common target genes of UA and bladder cancer. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Molecular docking was conducted to verify the possible binding conformation between UA and bladder cancer cells. Then, in vitro experiments were performed to further validate the predicted results. RESULTS: UA exerts anti-tumor effects on bladder cancer through multiple targets and pathways. Molecular docking indicated that UA undergoes stable binding with the proteins encoded by the top six core genes (STAT3, VEGFA, CASP3, TP53, IL1B, and CCND1). The in vitro experiments verified that UA can induce bladder cancer cell apoptosis by regulating the PI3K/Akt signaling pathway. CONCLUSIONS: Our study illustrated the potential mechanism of UA in bladder cancer based on network pharmacology and molecular docking. The results will provide scientific references for follow-up studies and clinical treatment.

Identification of keystone taxa in rhizosphere microbial communities using different methods and their effects on compounds of the host Cinnamomum migao.

Exploring keystone taxa affecting microbial community stability and host function is crucial for understanding ecosystem functions. However, identifying keystone taxa from humongous microbial communities remains challenging. We collected 344 rhizosphere and bulk soil samples from the endangered plant C. migao for 2 years consecutively. Used high-throughput sequencing 16S rDNA and ITS to obtain the composition of bacterial and fungal communities. We explored keystone taxa and the applicability and limitations of five methods (SPEC-OCCU, Zi-Pi, Subnetwork, Betweenness, and Module), as well as the impact of microbial community domain, time series, and rhizosphere boundary on the identification of keystone taxa in the communities. Our results showed that the five methods, identified abundant keystone taxa in rhizosphere and bulk soil microbial communities. However, the keystone taxa shared by the rhizosphere and bulk soil microbial communities over time decreased rapidly decrease in the five methods. Among five methods on the identification of keystone taxa in the rhizosphere community, Module identified 113 taxa, SPEC-OCCU identified 17 taxa, Betweenness identified 3 taxa, Subnetwork identified 3 taxa, and Zi-Pi identified 4 taxa. The keystone taxa are mainly conditionally rare taxa, and their ecological functions include chemoheterotrophy, aerobic chemoheterotrophy, nitrate reduction, and anaerobic photoautotrophy. The results of the random forest model and structural equation model predict that keystone taxa Mortierella and Ellin6513 may have an effects on the accumulation of 1, 4, 7, - Cycloundecatriene, 1, 5, 9, 9-tetramethyl-, Z, Z, Z-, beta-copaene, bicyclogermacrene, 1,8-Cineole in C. migao fruits, but their effects still need further evidence. Our study evidence an unstable microbial community in the bulk soil, and the definition of microbial boundary and ecologically functional affected the identification of keystone taxa in the community. Subnetwork and Module are more in line with the definition of keystone taxa in microbial ecosystems in terms of maintaining community stability and hosting function.

Bloodstream infection clusters for critically ill patients: analysis of two-center retrospective cohorts.

BACKGROUND: Bloodstream infections (BSI) are highly prevalent in hospitalized patients requiring intensive care. They are among the most serious infections and are highly associated with sepsis or septic shock, which can lead to prolonged hospital stays and high healthcare costs. This study aimed at establishing an easy-to-use nomogram for predicting the prognosis of patients with BSI. METHODS: In retrospective study, records of patients with BSI admitted to the intensive care unit (ICU) over the period from Jan 1st 2016 to Dec 31st 2021 were included. We used data from two different China hospitals as development cohort and validation cohort respectively. The demographic and clinical data of patients were collected. Based on all baseline data, k-means algorithm was applied to discover the groups of BSI phenotypes with different prognostic outcomes, which was confirmed by Kaplan-Meier analysis and compared using log-rank tests. Univariate Cox regression analyses were used to estimate the risk of clusters. Random forest was used to identified discriminative predictors in clusters, which were utilized to construct nomogram based on multivariable logistic regression in the discovery cohort. For easy clinical applications, we developed a bloodstream infections clustering (BSIC) score according to the nomogram. The results were validated in the validation cohort over a similar period. RESULTS: A total of 360 patients in the discovery cohort and 310 patients in the validation cohort were included in statistical analyses. Based on baseline variables, two distinct clusters with differing prognostic outcomes were identified in the discovery cohort. Population in cluster 1 was 211 with a ICU mortality of 17.1%, while population in cluster 2 was 149 with an ICU mortality of 41.6% (p < 0.001). The survival analysis also revealed a higher risk of death for cluster 2 when compared with cluster 1 (hazard ratio: 2.31 [95% CI, 1.53 to 3.51], p < 0.001), which was confirmed in validation cohort. Four independent predictors (vasoconstrictor use before BSI, mechanical ventilation (MV) before BSI, Deep vein catheterization (DVC) before BSI, and antibiotic use before BSI) were identified and used to develop a nomogram. The nomogram and BSIC score showed good discrimination with AUC of 0.96. CONCLUSION: The developed score has potential applications in the identification of high-risk critically ill BSI patients.

A Case Report of Concurrent Transplant Renal Artery Stenosis, Renal Cell Carcinoma, and Papillary Thyroid Cancer After Renal Transplantation: A Literature Review.

BACKGROUND: Kidney transplantation is the preferred treatment option for eligible patients with end-stage renal disease. With advanced transplantation technology and novel immunosuppressive agents, kidney transplant recipients survive significantly longer. However, the chance of developing malignant tumors has increased, posing a serious challenge to the survival of transplanted kidneys and patients. CASE PRESENTATION: We report a male patient (the patient's informed consent has been obtained) who underwent kidney transplantation 23 years ago. Subsequently, he developed transplant renal artery stenosis, primary renal clear cell carcinoma, and papillary thyroid cancer. The narrowed blood vessels were dilated through percutaneous transluminal angioplasty, and the malignant tumor was removed surgically. Currently, antirejection drugs are regularly taken, and the transplanted kidney function is good. The patient is satisfied with his living conditions. CONCLUSIONS: Hypertension that is difficult to control after kidney transplantation should be suspected as a possibility of graft vascular stenosis. When B-ultrasound cannot accurately diagnose it, magnetic resonance angiography should be used as early as possible to clarify the diagnosis and relieve the stenosis before graft dysfunction. Transplantation patients have a high incidence of malignant tumors after surgery, and the risk increases with the prolongation of the disease course. The focus should be on symptomatic treatment of related diseases, and antirejection drugs can be reduced or not reduced as appropriate.

Mathematical modeling of optimal coagulant dosage for tofu preparation using MgCl2.

To explore the association between the optimal coagulant for tofu and the components of soybeans,30 different kinds of soybeans were selected, and tested for their optimal coagulant MgCl2 content. The optimal amount of coagulant was taken as the dependent variable, and the soybean Composition were taken as independent variables for the correlation analysis. The results showed that there was a positive correlation between the optimal coagulant content and the content of histidine, 7S ß-conglycinin, B1aB1bB2B3B4 of 11 s glycincin, and α'-subunit of 7S ß-conglycinin, negative correlation with lysine. The regression formula is y = -1.186 + 3.457*B1aB1bB2B3B4 + 2.304*7S + 0.351*histidine - 0.084*lysine + 4.696*α', and the model is validated to be within 10 % of the error value and has a high degree of confidence. This study provides theoretical support for realizing the green production of traditional soybean products.

Analysis of winter diet in Guizhou golden monkey (Rhinopithecus brelichi) using DNA metabarcoding data.

The Guizhou golden monkey (Rhinopithecus brelichi) is a critically endangered wildlife species, and understanding its diet composition may be useful for assessing its feeding strategies. DNA metabarcoding was used to determine the dietary diversity of R. brelichi. DNA was extracted from 31 faecal samples and amplified chloroplast rbcL and mitochondrial COI DNA was sequenced using the Illumina NovaSeq platform. A comparative analysis of the sequences revealed that the five most abundant plant genera were Magnolia, Morinda, Viburnum, Tetradium and Eurya. In winter, R. brelichi mostly consumed shrubs, herbs and shrubs/trees according to the habit of plant genera with higher abundances comparatively. The five most abundant families in animal diet were Psychodidae, Trichinellidae, Staphylinidae, Scarabaeidae and Trichoceridae. This study is the first to show the composition of the winter animal diets of R. brelichi based on DNA metabarcoding. These results provide an important basis for understanding the diet of wild R. brelichi, which inhabits only the Fanjingshan National Nature Reserve, China.

Development of a TLR-Based Model That Can Predict Prognosis, Tumor Microenvironment, and Drug Response for Esophageal Squamous Cell Carcinoma.

The toll-like receptor (TLR) family is an important class of proteins involved in the immune response. However, little is known about the association between TLRs and Esophageal squamous cell cancer (ESCC). We explored differentially expressed genes (DEGs) between ESCC and esophagus tissues in TCGA and GTEx database. By taking the intersection with TLR gene set and using univariate Cox analysis and multivariate Cox regression analysis to discriminate the hub genes, we created a TLR-prognostic model. Our model separated patients with ESCC into high- and low-risk score (RS) groups. Prognostic analysis was performed with Kaplan-Meier curves. The two groups were also compared regarding tumor immune microenvironment and drug sensitivity. Six hub genes (including CD36, LGR4, MAP2K3, NINJ1, PIK3R1, and TRAF3) were screened to construct a TLR-prognostic model. High-RS group had a worse survival (p < 0.01), lower immune checkpoint expression (p < 0.05), immune cell abundance (p < 0.05) and decreased sensitivity to Epirubicin (p < 0.001), 5-fluorouracil (p < 0.0001), Sorafenib (p < 0.01) and Oxaliplatin (p < 0.05). We constructed a TLR-based model, which could be used to assess the prognosis of patients with ESCC, provide new insights into drug treatment for ESCC patients and investigate the TME and drug response.

EGFR mediates epithelial­mesenchymal transition through the Akt/GSK-3ß/Snail signaling pathway to promote liver cancer proliferation and migration.

Epidermal growth factor receptor (EGFR) is expressed in various types of cancer and is associated with the malignant biological behavior of cancer cells. In the present study, the expression of EGFR in hepatocellular carcinoma (HCC) tissues and liver cancer cells was detected by immunohistochemical staining, western blotting and immunofluorescence. Furthermore, a lentivirus was transduced into HepG2 liver cancer cells to knock down EGFR expression. Cell proliferation and migration, and the expression levels of epithelial-mesenchymal transition (EMT) markers were assessed by EdU staining, Cell Counting Kit-8, colony formation, wound healing and Transwell assays, and western blotting. The results revealed that EGF/EGFR can mediate EMT through the Akt/glycogen synthase kinase-3ß (GSK-3ß)/Snail signaling pathway to promote HepG2 cell proliferation and migration. Inhibition of the activation of the EGFR signaling pathway can help to partially reverse the EMT phenotype, and inhibit the proliferation and migration of HepG2 cells. In conclusion, the EGFR/Akt/GSK-3ß/Snail signaling pathway serves an important role in HCC progression, and inhibition of the activation of the EGFR signaling pathway may be a valuable strategy in liver cancer treatment.

Fine-tuning rice heading date through multiplex editing of the regulatory regions of key genes by CRISPR-Cas9.

Heading date (or flowering time) is a key agronomic trait that affects seasonal and regional adaption of rice cultivars. An unoptimized heading date can either not achieve a high yield or has a high risk of encountering abiotic stresses. There is a strong demand on the mild to moderate adjusting the heading date in breeding practice. Genome editing is a promising method which allows more precise and faster changing the heading date of rice. However, direct knock out of major genes involved in regulating heading date will not always achieve a new germplasm with expected heading date. It is still challenging to quantitatively adjust the heading date of elite cultivars with best adaption for broader region. In this study, we used a CRISPR-Cas9 based genome editing strategy called high-efficiency multiplex promoter-targeting (HMP) to generate novel alleles at cis-regulatory regions of three major heading date genes: Hd1, Ghd7 and DTH8. We achieved a series of germplasm with quantitative variations of heading date by editing promoter regions and adjusting the expression levels of these genes. We performed field trials to screen for the best adapted lines for different regions. We successfully expanded an elite cultivar Ningjing8 (NJ8) to a higher latitude region by selecting a line with a mild early heading phenotype that escaped from cold stress and achieved high yield potential. Our study demonstrates that HMP is a powerful tool for quantitatively regulating rice heading date and expanding elite cultivars to broader regions.

Embracing Large Natural Data: Enhancing Medical Image Analysis via Cross-Domain Fine-Tuning.

With the rapid advancements of Big Data and computer vision, many large-scale natural visual datasets are proposed, such as ImageNet-21K, LAION-400M, and LAION-2B. These large-scale datasets significantly improve the robustness and accuracy of models in the natural vision domain. However, the field of medical images continues to face limitations due to relatively small-scale datasets. In this article, we propose a novel method to enhance medical image analysis across domains by leveraging pre-trained models on large natural datasets. Specifically, a Cross-Domain Transfer Module (CDTM) is proposed to transfer natural vision domain features to the medical image domain, facilitating efficient fine-tuning of models pre-trained on large datasets. In addition, we design a Staged Fine-Tuning (SFT) strategy in conjunction with CDTM to further improve the model performance. Experimental results demonstrate that our method achieves state-of-the-art performance on multiple medical image datasets through efficient fine-tuning of models pre-trained on large natural datasets.