Therapeutic Potential of Terpenoids in Cancer Treatment: Targeting Mitochondrial Pathways.

BACKGROUND: In recent decades, natural compounds have been considered a significant source of new antitumor medicines due to their unique advantages. Several in vitro and in vivo studies have focused on the effect of terpenoids on apoptosis mediated by mitochondria in malignant cells. RECENT FINDINGS: In this review article, we focused on six extensively studied terpenoids, including sesquiterpenes (dihydroartemisinin and parthenolide), diterpenes (oridonin and triptolide), and triterpenes (betulinic acid and oleanolic acid), and their efficacy in targeting mitochondria to induce cell death. Terpenoid-induced mitochondria-related cell death includes apoptosis, pyroptosis, necroptosis, ferroptosis, autophagy, and necrosis caused by mitochondrial permeability transition. Apoptosis and autophagy interact in meaningful ways. In addition, in view of several disadvantages of terpenoids, such as low stability and bioavailability, advances in research on combination chemotherapy and chemical modification were surveyed. CONCLUSION: This article deepens our understanding of the association between terpenoids and mitochondrial cell death, presenting a hypothetical basis for the use of terpenoids in anticancer management.

Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study.

BACKGROUND: Acute kidney injury (AKI) is a common adverse outcome following nephrectomy. The progression from AKI to acute kidney disease (AKD) and subsequently to chronic kidney disease (CKD) remains a concern; yet, the predictive mechanisms for these transitions are not fully understood. Interpretable machine learning (ML) models offer insights into how clinical features influence long-term renal function outcomes after nephrectomy, providing a more precise framework for identifying patients at risk and supporting improved clinical decision-making processes. OBJECTIVE: This study aimed to (1) evaluate postnephrectomy rates of AKI, AKD, and CKD, analyzing long-term renal outcomes along different trajectories; (2) interpret AKD and CKD models using Shapley Additive Explanations values and Local Interpretable Model-Agnostic Explanations algorithm; and (3) develop a web-based tool for estimating AKD or CKD risk after nephrectomy. METHODS: We conducted a retrospective cohort study involving patients who underwent nephrectomy between July 2012 and June 2019. Patient data were randomly split into training, validation, and test sets, maintaining a ratio of 76.5:8.5:15. Eight ML algorithms were used to construct predictive models for postoperative AKD and CKD. The performance of the best-performing models was assessed using various metrics. We used various Shapley Additive Explanations plots and Local Interpretable Model-Agnostic Explanations bar plots to interpret the model and generated directed acyclic graphs to explore the potential causal relationships between features. Additionally, we developed a web-based prediction tool using the top 10 features for AKD prediction and the top 5 features for CKD prediction. RESULTS: The study cohort comprised 1559 patients. Incidence rates for AKI, AKD, and CKD were 21.7% (n=330), 15.3% (n=238), and 10.6% (n=165), respectively. Among the evaluated ML models, the Light Gradient-Boosting Machine (LightGBM) model demonstrated superior performance, with an area under the receiver operating characteristic curve of 0.97 for AKD prediction and 0.96 for CKD prediction. Performance metrics and plots highlighted the model's competence in discrimination, calibration, and clinical applicability. Operative duration, hemoglobin, blood loss, urine protein, and hematocrit were identified as the top 5 features associated with predicted AKD. Baseline estimated glomerular filtration rate, pathology, trajectories of renal function, age, and total bilirubin were the top 5 features associated with predicted CKD. Additionally, we developed a web application using the LightGBM model to estimate AKD and CKD risks. CONCLUSIONS: An interpretable ML model effectively elucidated its decision-making process in identifying patients at risk of AKD and CKD following nephrectomy by enumerating critical features. The web-based calculator, found on the LightGBM model, can assist in formulating more personalized and evidence-based clinical strategies.

Multilevel factors associated with HIV-related stigma among women living with HIV in Guangdong Province, China: a social-ecological model-informed study.

BACKGROUND: HIV-related stigma continues to hinder optimal HIV care, and its determinants should be understood at multiple levels. Based on the social-ecological model, this study aimed to explore factors associated with HIV-related stigma among women living with HIV in Guangdong Province, China. METHODS: A cross-sectional study was conducted from July to August 2022 to recruit newly reported women living with HIV with a history of pregnancy or current pregnancy in 2021 in 21 cities in Guangdong Province. HIV-related stigma was assessed using an abbreviated Chinese version of Berger's HIV Stigma Scale. Univariate and multivariable hierarchical regression analyses based on the social-ecological model were conducted to explore factors associated with HIV-related stigma and its four dimensions (personalized stigma, disclosure concerns, negative self-image and concerns about public attitudes) at the community/hospital, interpersonal, and individual levels. RESULTS: A moderate level of HIV-related stigma was found among the 360 participants included, with a mean score of 45.26. Multivariable hierarchical regression analysis showed that at the community/hospital-level, individuals were more likely to experience high levels of HIV-related stigma if they had experienced the discriminatory behaviors from health care workers (aOR = 2.34, 95%CI: 1.48-3.70) and if they rated serostatus disclosure services as less helpful (aOR = 0.69, 95%CI: 0.48-0.98). At the interpersonal-level, individuals with an HIV-positive partner (aOR = 1.71, 95%CI: 1.01-2.90) were more likely to experience high levels of HIV-related stigma than those with an HIV-negative or unknown partner. Individuals with high resilience (aOR = 0.22, 95%CI: 0.13-0.35) had lower levels of HIV-related stigma at the individual-level. In addition, ever experiencing discriminatory behaviors from health care workers, thinking serostatus disclosure services helpful, having ever seen publicity about personal interest protection services and complaint channels for people living with HIV(PLHIV), knowing about care and support services for PLHIV from social organizations at the community/hospital-level, partner notification and support at the interpersonal-level, and violations of personal interests, resilience at the individual-level were also associated with different dimensions of HIV-related stigma. CONCLUSIONS: HIV-related stigma was moderate among women living with HIV. The social-ecological model can facilitate a better understanding of factors associated with HIV-related stigma. Multilevel intervention strategies need to be tailored to reduce HIV-related stigma.

The risk of thromboembolic events in patients with nephrotic syndrome and relatively high albumin levels: a study over 10 years.

BACKGROUND: Low albumin level is a risk factor for thromboembolic events in patients with NS (nephrotic syndrome). However, little is known about the proportion and characteristics of patients with NS who experience thromboembolic events with relatively high albumin levels (≥ 25 g/L). Therefore, we explored the features of this specific group of patients. METHODS: This study included all hospitalized patients in our center for the past 10 years who had diagnoses of NS and relevant thromboembolic events. We divided them into 2 groups based on their serum albumin level when the thromboembolic event occurred. The clinical data were analyzed with SPSS software. RESULTS: There were 312 patients enrolled in our study. Eighty-four (26.9%) of them had relatively high albumin levels (≥ 25 g/L). Patients with NS with high albumin levels had significantly lower levels of 24-h proteinuria (P < 0.01) and a higher rate of autoimmune disease (P = 0.03) than the low-albumin group. Membranous nephropathy (MN) was the most frequent pathological type of NS in patients with thromboembolic events, regardless of their albumin level. There were significantly fewer patients with anti-PLA2R (M-type phospholipase A2 receptor)-positive MN in the high-albumin group than in the low-albumin group (P < 0.01). CONCLUSIONS: Our study found that there was still a high risk for patients with NS and relatively high albumin levels to develop thromboembolic events.

Cpd861 Targeting BCL2 to Alleviate Hepatic Fibrosis: Network Pharmacology, Mendelian Randomization, and Molecular Docking Mechanisms.

BACKGROUND: Compound 861 (Cpd861) is a traditional Chinese herbal compound for the treatment of hepatic fibrosis (HF). In the current investigation, Cpd861 has been demonstrated to have an underlying molecular mechanism and material foundation for the treatment of HF through network pharmacology, Mendelian randomization (MR), and molecular docking. METHODS: Public databases were consulted for Cpd861 constituents and HF targets. Protein-protein interactions (PPIs) were established using STRING software, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. To elucidate the causal relationship between potential targets and liver injury, MR was used as a methodological tool. Finally, a molecular docking analysis was conducted between the active compound and the key target. RESULTS: We obtained 174 active ingredients and 113 intersecting genes. Through the PPI network, high-degree targets were identified, namely CTNNB1, ESR1, FOS, MDM2, CCND1, TP53, RELA, and BCL2. As shown by GO and KEGG pathway enrichment analyses, Cpd861 functions through xenobiotic stimulus and oxidative stress-related genes, as well as the PI3K-AKT and non-alcoholic fatty liver disease (NAFLD) signaling pathways. The results of MR showed that MDM2 and BCL2 had a causal relationship with liver injury. Molecular docking results showed that several active compounds in Cpd861 were stably bound to BCL2. CONCLUSION: This study made predictions regarding the efficacious components, as well as potential targets and pathways of Cpd861 in the therapy of HF. This will open up a new perspective for further investigation of the molecular mechanism of Cpd861 in the treatment of HF.

Comprehensive Assessment of Immune Phenotype and Its Effects on Survival Outcomes in HER2-Low versus HER2-Zero Breast Cancer.

Background: The understanding of molecular characteristics of HER2-low breast cancer is evolving since the establishment of trastuzumab deruxtecan. Here, we explore the differences in expression patterns of immune-related genes in the tumor immune microenvironment (TME) and survival between HER2-low and HER2-zero breast cancers. Methods: Comprehensive genomic and immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on FFPE samples from 129 patients with advanced HER2-negative (immunohistochemistry (IHC) 0, 1+ or 2+ with negative ERBB2 amplification by in-situ hybridization) breast cancer. Both estrogen receptor (ER) and HER2 statuses were obtained from available pathology reports. mRNA expressions of immune biomarkers, except for PD-L1 IHC and TMB, were derived from RNA-seq. Statistical comparisons were performed using the Kruskal-Wallis or Wilcoxon Rank-Sum test or the two-sample test for equality of proportions with continuity correction (p≤0.05 for significance). Survival differences were calculated using Kaplan-Meier analysis (p≤0.05 for significance). Results: There were no significant differences in mRNA expressions of immune-related genes between HER2-low and HER2-zero breast cancers. However, HER2-low breast cancers were associated with a higher proportion of ER-positivity. When ER was analyzed along with HER2, we observed a significantly higher tumor immunogenic signature (TIGS) expression in HER2-zero/ER-negative tumors than in HER2-low/ER-positive tumors (p=0.0088). Similarly, lower expression of PD-L1 and T cell immunoglobulin and ITIM domain (TIGIT) mRNA was observed in HER2-low/ER-positive tumors when compared to HER2-zero/ER-negative tumors (p=0.014 and 0.012, respectively). Patients with HER2-low tumors had a longer median OS than those with HER2-zero tumors (94 months vs 42 months, p=0.0044). Conclusion: Patients with HER2-low breast cancer have longer survivals yet display no differences in immune-related gene expression when compared to those with HER2-zero cancers. The differences in survival can be attributed to the higher rate of ER-positivity seen in HER2-low breast cancers, compared to HER2-zero tumors.

One-Stone-For-Three-Birds Strategy Using a Fullerene Modifier for Efficient and Stable Inverted Perovskite Solar Cells.

The electron extraction from perovskite/C60 interface plays a crucial role in influencing the photovoltaic performance of inverted perovskite solar cells (PSCs). Here, we develop a one-stone-for-three-birds strategy via employing a novel fullerene derivative bearing triple methyl acrylate groups (denoted as C60-TMA) as a multifunctional interfacial layer to optimize electron extraction at the perovskite/C60 interface. It is found that the C60-TMA not only passivates surface defects of perovskite via coordination interactions between C=O groups and Pb2+ cations but also bridge electron transfer between perovskite and C60. Moreover, it effectively induces the secondary grain growth of the perovskite film through strong bonding effect, and this phenomenon has never been observed in prior art reports on fullerene related studies. The combination of the above three upgrades enables improved perovskite film quality with increased grain size and enhanced crystallinity. With these advantages, C60-TMA treated PSC devices exhibit a much higher power conversion efficiency (PCE) of 24.89% than the control devices (23.66%). Besides, C60-TMA benefits improved thermal stability of PSC devices, retaining over 90% of its initial efficiency after aging at 85 °C for 1200 h, primarily due to the reinforced interfacial interactions and improved perovskite film quality.

The mechanism of cancer-depression comorbidity.

Cancer and depression are closely interrelated, particularly in patients with advanced cancer, who often present with comorbid anxiety and depression for various reasons. Recently, there has been a growing interest in the study of depression in cancer patients, with the aim of assessing the possible triggers, predictors, adverse events, and possible treatment options for depression in several common cancers. The objective of this narrative review is to synthesize the extant literature on the relationship between the occurrence and progression of depression in several common patient categories. The authors conducted a comprehensive review of 75 articles published in PubMed over the past five years. This review was further evaluated in the present paper. Ultimately, it was determined that depression is a prevalent and detrimental phenomenon among cancer patients, particularly those with advanced disease. Consequently, there is a pressing need to prioritize research and interventions aimed at improving the quality of life and psychosocial well-being of cancer patients, including those with advanced disease. The relationship between cancer and depression has been evolving dynamically in recent times. The current research findings indicate a strong association between cancer and depression. However, the direction of causality remains unclear. Focusing on depression in cancer patients may, therefore, be beneficial for these patients.

International Trade Reshapes the Decoupling of Emissions from Economic Growth.

Efforts to stabilize the global climate change while also continuing human development depend upon "decoupling" economic growth from fossil fuel CO2 emissions. However, evaluations of such decoupling have typically relied on production-based emissions, which do not account for emissions embodied in international trade. Yet international trade can greatly change emissions accounting and reshape the decoupling between emissions and economic growth. Here, we evaluate decoupling of economic growth from different accounts of emissions in each of the 159 countries and analyze the drivers of decoupling. We find that between 1995 and 2015, although 29 countries exhibited strong decoupling of territorial emissions (growing economies and decreasing emissions), only 19 countries achieved economic growth while their consumption-based emissions decreased. Most developed countries have achieved decoupling of emissions related to domestic goods and services, but have not achieved decoupling of emissions related to imported goods and services. The U-test confirms that the domestic component of consumption-based emissions exhibits a stronger decoupling trend from gross domestic product (GDP) growth than consumption-based emissions, and emissions from imports continue to rise with GDP per capita without a corresponding decline, providing a statistical validation of the decoupling analysis. Moreover, in the countries where economic growth and consumption-based emissions are most decoupled, a key driver is decreasing emissions intensity due to technological progress─and especially reductions in the intensity of imported goods and services. Our results reveal the importance of assessing decoupling using consumption-based emissions; successful decoupling may require international cooperation and coordinated mitigation efforts of trading partners.

Spatial source, simulating improvement, and short-term health effect of high PM2.5 exposure during mutation event in the key urban agglomeration regions in China.

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM2.5 in urban agglomeration regions continue to occur frequently. Identifying the spatial sources and influencing factors, as well as improving the prediction accuracy of high PM2.5 during mutation events, are crucial for public health. In this study, we firstly introduced discrete wavelet transform (DWT) to identify the mutation events with high PM2.5 concentration in the four key urban agglomerations, and evaluated the spatial sources for the polluted scenario using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Additionally, DWT was combined with a widely used artificial neural network (ANN) to improve the prediction accuracy of PM2.5 concentration seven days in advance (seven-day forecast). Results indicated that mutation events commonly occurred in the northern regions during winter time, which were under the control of both short-range transportation of dirty airmass as well as negative meteorology conditions. Compared with the ANN model alone, the average band errors decreased by 9% when using DWT-ANN model. The average correlation coefficient (R) and root mean square error (RMSE) obtained using the DWT-ANN improved by 10% and 12% compared to those obtained using the ANN, indicating the efficiency and accuracy of simulating PM2.5, by combining the DWT and ANN. The short-term mortality during mutation events was then calculated, with the total averted all-cause, cardiovascular, and respiratory deaths in the four regions, being 4751, 2554, and 582 persons, respectively. A declining trend in prevented deaths from 2018 to 2020 demonstrated that the pollution intensity during mutation events gradually decreased owing to the implementation of the Three-Year Action Plan to Win the Blue Sky Defense War. The method proposed in this study can be used by policymakers to take preventive measures in response to a sudden increase in PM2.5, thereby ensuring public health.

Changes in source composition of wet nitrate deposition after air pollution control in a typical area of Southeast China.

In recent years, China has adopted numerous policies and regulations to control NOx emissions to further alleviate the adverse impacts of NO3--N deposition. However, the variation in wet NO3--N deposition under such policies is not clear. In this study, the southeastern area, with highly developed industries and traditional agriculture, was selected to explore the variation in NO3--N deposition and its sources changes after such air pollution control through field observation and isotope tracing. Results showed that the annual mean concentrations of NO3--N in precipitation were 0.67 mg L-1 and 0.54 mg L-1 in 2014-2015 and 2021-2022, respectively. The average wet NO3--N depositions in 2014-2015 and 2021-2022 was 7.76 kg N ha-1 yr-1 and 5.03 kg N ha-1 yr-1, respectively, indicating a 35% decrease. The δ15N-NO3- and δ18O-NO3- values were lower in warm seasons and higher in cold seasons, and both showed a lower trend in 2021-2022 compared with 2014-2015. The Bayesian model results showed that the NOx emitted from coal-powered plants contributed 53.6% to wet NO3--N deposition, followed by vehicle exhaust (22.9%), other sources (17.1%), and soil emissions (6.4%) during 2014-2015. However, the contribution of vehicle exhaust (33.3%) overpassed the coal combustion (32.3%) and followed by other sources (25.4%) and soil emissions (9.0%) in 2021-2022. Apart from the control of air pollution, meteorological factors such as temperature, precipitation, and solar radiation are closely related to the changes in atmospheric N transformation and deposition. The results suggest phased achievements in air pollution control and that more attention should be paid to the control of motor vehicle exhaust pollution in the future, at the same time maintaining current actions and supervision of coal-powered plants.

[Establishment and evaluation of a premenstrual syndrome rat model induced by progesterone-withdrawal and emotional-stimulation].

Premenstrual syndrome(PMS) lacks a highly consistent and feasible animal model that aligns with diagnostic and therapeutic standards in both traditional Chinese medicine(TCM) and western medicine, resulting in a lack of reliable experimental carriers for studying its pathogenesis and pharmacological effects. This study aims to systematically analyze the biological implications of PMS from the perspective of the "disease-syndrome-symptom" correlation and establish preparation and evaluation methods for an improved animal model of this disease. Firstly, clinical symptom gene sets related to the Qi stagnation syndromes due to liver depression and blood stasis in PMS in both modern medicine and TCM diagnostic standards were collected through GeneCards, DisGeNET, Mala-Cards, and the System of Foundational Diagnostic Association(SoFDA) database, as well as published literature. Based on the interaction information between genes, a "disease-syndrome-symptom" correlation network of PMS was established. Based on data mining results, an improved rat model of PMS was prepared by combining chronic restraint stress with the classical progesterone-withdrawal mo-del to simulate emotional depression caused by external environmental stimuli during the clinical onset process, inducing pathological damage from both physiological and emotional dimensions. The evaluation of the improved model before and after modification included open field experiment scores, organ indices, ovarian pathological changes, serum levels of estradiol(E_2), follicle-stimulating hormone/luteinizing hormone(FSH/LH), 5-hydroxytryptamine(5-HT), dopamine(DA), norepinephrine(NE), as well as coagulation parameters and hemorheology indexes. By calculating the degree, betweenness, and closeness centrality of nodes in the "disease-syndrome-symptom" correlation network, 163 core genes with topological importance were identified. Further biological function mining results indicated that core genes in PMS mainly participated in the regulation of the "nervous-endocrine-immune" system and pathways related to circulatory disorders. Mapping analysis of clinical phenotype symptom gene sets suggested significant correlations between core genes in PMS and depressive symptoms and pain symptoms caused by blood stasis. Compared with the simple progesterone withdrawal model, rats subjected to combined injections and restraint stress showed more significant abnormalities in open field experiment scores, ovarian tissue pathology, serum neurotransmitter levels of 5-HT and DA, as well as serum hormone levels of E_2 and FSH/LH. The modified modeling conditions exacerbated the pathological changes in blood rheology, coagulation function, and red blood cell morphology in model rats, confirming that the improved rat model could characterize the "nervous-endocrine-immune" system disorder and circulatory system disorders in the occurrence and progression of PMS, consistent with the clinical diagnostic and therapeutic standards of both TCM and western medicine. The establishment of the improved rat model of PMS can provide a reliable experimental carrier for elucidating the pathogenesis of PMS and discovering and evaluating therapeutic drugs. It also provides references for objectively reflecting the clinical characteristics of PMS in TCM and western medicine and precision treatment.

Identification of novel dual-target 4-hydroxyphenylpyruvate dioxygenase & phytoene dehydrogenase inhibitors via multiple virtual screening.

Two important plant enzymes are 4-hydroxyphenylpyruvate dioxygenase (HPPD; EC 1.13.11.27), which is necessary for biosynthesis of plastoquinone and tocopherols, and phytoene dehydrogenase (PDS; EC 1.3.99.26), which plays an important role in colour rendering. Dual-target proteins that inhibit pigment synthesis will prevent resistant weeds and improve the spectral characteristics of herbicides. This study introduces virtual screening of pharmacophores based on the complex structure of the two targets. A three-dimensional database was established by screening 1,492,858 compounds based on the Lipinski principle. HPPD&PDS dual-target receptor-ligand pharmacophore models were then constructed, and nine potential dual-target inhibitors were obtained through pharmacophore modeling, molecular docking, and molecular dynamics simulations. Ultimately, ADMET prediction software yielded three compounds with high potential as dual-target herbicides. The obtained nine inhibitors were stable when combined with both HPPD and PDS proteins. This study offers guidance for the development of HPPD&PDS dual-target inhibitors with novel skeletons.

4-Hydroxyphenylpyruvate Dioxygenase Inhibitors: From Molecular Design to Synthesis.

Weed resistance is a critical issue in crop production. Among the known herbicides, 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors are crucial for addressing weed resistance. HPPD inhibitors constitute a pivotal aspect of contemporary crop protection strategies. The advantages of these herbicides are their broad weed spectrum, flexible application, and excellent compatibility with other herbicides. They also exhibit satisfactory crop selectivity and low toxicity and are environmentally friendly. An increasing number of new HPPD inhibitors have been designed by combining computer-aided drug design with conventional design approaches. Herein, the molecular design and structural features of innovative HPPD inhibitors are reviewed to guide the development of new HPPD inhibitors possessing an enhanced biological efficacy.

Bacteroidetes promotes esophageal squamous carcinoma invasion and metastasis through LPS-mediated TLR4/Myd88/NF-κB pathway and inflammatory changes.

Gut microbiota plays a crucial role in gastrointestinal tumors. Additionally, gut microbes influence the progression of esophageal cancer. However, the major bacterial genera that affect the invasion and metastasis of esophageal cancer remain unknown, and the underlying mechanisms remain unclear. Here, we investigated the gut flora and metabolites of patients with esophageal squamous cell carcinoma and found abundant Bacteroides and increased secretion and entry of the surface antigen lipopolysaccharide (LPS) into the blood, causing inflammatory changes in the body. We confirmed these results in a mouse model of 4NQO-induced esophageal carcinoma in situ and further identified epithelial-mesenchymal transition (EMT) occurrence and TLR4/Myd88/NF-κB pathway activation in mouse esophageal tumors. Additionally, in vitro experiments revealed that LPS from Bacteroides fragile promoted esophageal cancer cell proliferation, migration, and invasion, and induced EMT by activating the TLR4/Myd88/NF-κB pathway. These results reveal that Bacteroides are closely associated with esophageal cancer progression through a higher inflammatory response level and signaling pathway activation that are both common to inflammation and tumors induced by LPS, providing a new biological target for esophageal cancer prevention or treatment.

Ethanol exposure exacerbates 4-nitroquinoline-1-oxide induced esophageal carcinogenesis and induces invasive carcinoma with muscularis propria infiltration in a mouse model.

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal cancers worldwide. Most ESCC patients are diagnosed at an advanced stage; however, current research on in vivo animal models accurately reflecting their clinical presentation is lacking. Alcohol consumption is a major risk factor for ESCC and has been used in several disease models for disease induction. In this study, we used 4-nitroquinoline-1-oxide in combination with ethanol to induce an in vivo ESCC mouse model. Esophageal tissues were stained with hematoxylin and eosin for histopathological examination and lesion scoring. In cellular experiments, cell adhesion and migration invasion ability were observed using phalloidin staining, cell scratch and transwell assays, respectively, and the expression of epithelial-mesenchymal transition-related markers was detected using quantitative reverse transcription polymerase chain reaction and western blotting. The results showed that ethanol-exposed mice lost more weight and had an increased number of esophageal nodules. Histological examination revealed that the lesion scores of the ethanol-exposed esophageal samples were significantly higher than those of the unexposed esophageal samples. Furthermore, ethanol-exposed esophageal cancer samples had more severe lesions with infiltration of tumor cells into the muscularis propria. In vitro cellular experiments showed that ethanol exposure induced cytoskeletal microfilament formation, promoted cell migration invasion elevated the expression of N-cadherin and Snail, and decreased the expression of E-cadherin. In conclusion, ethanol exposure exacerbates ESCC, promotes tumor cell infiltration into the muscularis propria, and could be an effective agent for establishing innovative models of invasive carcinoma.

Mechanistic insights into super-enhancer-related genes as prognostic signatures in colon cancer.

BACKGROUND: Colon cancer (CC) is the most frequently occurring digestive system malignancy and is associated with a dismal prognosis. While super-enhancer (SE) genes have been identified as prognostic markers in several cancers, their potential as practical prognostic markers for CC patients remains unexplored. METHODS: We obtained super-enhancer-related genes (SERGs) from the Human Super-Enhancer Database (SEdb). Transcriptome and relevant clinical data for colon cancer (CC) were sourced from the Gene Expression Omnibus (GEO) database. Subsequently, we identified up-regulated SERGs by the Weighted Gene Co-expression Network Analysis (WGCNA). Prognostic signatures were constructed via univariate and multivariate Cox regression analysis. We then delved into the mechanisms of these predictive genes by examining immune infiltration. We also assessed differential sensitivities to chemotherapeutic drugs between high- and low-SERGs risk patients. The critical gene was further validated using external datasets and finally confirmed by qRT PCR. RESULTS: We established a ten-gene risk score prognostic model (S100A11, LZTS2, CYP2S1, ZNF552, PSMG1, GJC1, NXN, and DCBLD2), which can effectively predict patient survival rates. This model demonstrated effective prediction capabilities in survival rates at 1, 3, and 5 years and was successfully validated using external datasets. Furthermore, we detected significant differences in immune cell infiltration between high- and low-SERGs risk groups. Notably, high-risk patients exhibited heightened sensitivity to four chemotherapeutic agents, suggesting potential benefits for precision therapy in CC patients. Finally, qRT-PCR validation revealed a significant upregulation of LZTS2 mRNA expression in CC cells. CONCLUSION: These findings reveal that the SERGs model could effectively predict the prognosis of CC.

Direct electrospinning for producing multiple activity nanofibers consisting of aggregated luteolin/hydroxypropyl-gamma-cyclodextrin inclusion complex.

Hydroxypropyl-gamma-cyclodextrin (HPγCD) inclusion complex nanofibers (Lut/HPγCD-IC-NF) containing Luteolin (Lut) were prepared by electrospinning technology. Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) spectra confirmed the formation of Lut/HPγCD-IC-NF. Scanning electron microscopy (SEM) images showed that the morphology of Lut/HPγCD-IC-NF was uniform and bead-free, suggesting that self-assembled aggregates, macromolecules with higher molecular weights, were formed by strong hydrogen bonding interactions between the cyclodextrin inclusion complexes. Confocal laser scanning microscopy (CLSM) images showed that Lut was distributed in Lut/HPγCD-IC-NF. Proton nuclear magnetic resonance (1H NMR) spectroscopy revealed the change in chemical shift of the proton peak between Lut and HPγCD, confirming the formation of inclusion complex. Thermogravimetric analysis (TGA) proved that Lut/HPγCD-IC-NF had good thermal stability. The phase solubility test confirmed that HPγCD had a solubilizing effect on Lut. When the solubility of HPγCD reached 10 mM, the solubility of Lut increased by 15-fold. The drug loading test showed that the content of Lut in fibers reached 8.57 ± 0.02 %. The rapid dissolution experiment showed that Lut/HPγCD-IC-NF dissolved within 3 s. The molecular simulation provides three-dimensional evidence for the formation of inclusion complexes between Lut and HPγCD. Antibacterial experiments showed that Lut/HPγCD-IC-NF had enhanced antibacterial activity against S. aureus. Lut/HPγCD-IC-NF exhibited excellent antioxidant properties with a free radical scavenging ability of 89.5 ± 1.1 %. In vitro release experiments showed Lut/HPγCD-IC-NF had a higher release amount of Lut. In conclusion, Lut/HPγCD-IC-NF improved the physicochemical properties and bioavailability of Lut, providing potential applications of Lut in the pharmaceutical field.

Knockdown of thioredoxin interacting protein in Müller cells attenuates photoreceptor apoptosis in streptozotocin-induced diabetic mouse model.

We explored the effect of inhibition of thioredoxin interacting protein (Txnip) on neuroprotection in Müller cells under high glucose. Wild-type (WT) and Txnip knockout (Txnip-/-) mice were used to establish a streptozotocin (STZ)-induced diabetes model and a Müller cells high glucose model. We detected BDNF expression and PI3K/AKT/CREB pathway activation levels in the retina and Müller cells of each group in vivo and in vitro experiments. The Txnip-/- STZ group showed higher expression of BDNF and phosphorylation of PI3K/AKT/CREB in retina, and less retinal photoreceptor apoptosis was observed in Txnip-/- diabetic group than in WT. After using an inhibitor of PI3K signaling pathway, BDNF expression was reduced; In vitro co-cultured with Müller cells in different groups, 661 W cells showed different situations, Txnip-/- Müller cells maximum downregulated Cleaved-caspase 3 expression in 661 W, accompanied by an increase in Bcl-2/Bax ratio. These findings indicate that inhibiting endogenous Txnip in mouse Müller cells can promote their expression and secretion of BDNF, thereby reducing HG induced photoreceptor apoptosis and having important neuroprotective effects on DR. The regulation of BDNF expression by Txnip may be achieved by activating the PI3K/AKT/CREB pathway. This study suggests that regulating Txnip may be a potential target for DR treatment.

Mapping annual 10-m soybean cropland with spatiotemporal sample migration.

China, as the world's biggest soybean importer and fourth-largest producer, needs accurate mapping of its planting areas for global food supply stability. The challenge lies in gathering and collating ground survey data for different crops. We proposed a spatiotemporal migration method leveraging vegetation indices' temporal characteristics. This method uses a feature space of six integrals from the crops' phenological curves and a concavity-convexity index to distinguish soybean and non-soybean samples in cropland. Using a limited number of actual samples and our method, we extracted features from optical time-series images throughout the soybean growing season. The cloud and rain-affected data were supplemented with SAR data. We then used the random forest algorithm for classification. Consequently, we developed the 10-meter resolution ChinaSoybean10 maps for the ten primary soybean-producing provinces from 2019 to 2022. The map showed an overall accuracy of about 93%, aligning significantly with the statistical yearbook data, confirming its reliability. This research aids soybean growth monitoring, yield estimation, strategy development, resource management, and food scarcity mitigation, and promotes sustainable agriculture.