GSH exhaustion via inhibition of xCT-GSH-GPX4 pathway synergistically enhanced DSF/Cu-induced cuproptosis in myelodysplastic syndromes.

The clinical application of the therapeutic approach in myelodysplastic syndromes (MDS) remains an insurmountable challenge for the high propensity for progressing to acute myeloid leukemia and predominantly affecting elderly individuals. Thus, the discovery of molecular mechanisms underlying the regulatory network of different programmed cell death holds great promise for the identification of therapeutic targets and provides insights into new therapeutic avenues. Herein, we found that disulfiram/copper (DSF/Cu) significantly repressed the cell viability, increased reactive oxygen species (ROS) accumulation, destroyed mitochondrial morphology, and altered oxygen consumption rate. Further studies verified that DSF/Cu induces cuproptosis, as evidenced by the depletion of glutathione (GSH), aggregation of lipoylated DLAT, and induced loss of Fe-S cluster-containing proteins, which could be rescued by tetrathiomolybdate and knockdown of ferredoxin 1 (FDX1). Additionally, GSH contributed to the tolerance of DSF/Cu-mediated cuproptosis, while pharmacological chelation of GSH triggered ROS accumulation and sensitized cell death. The xCT-GSH-GPX4 axis is the ideal downstream component of ferroptosis that exerts a powerful protective mechanism. Notably, classical xCT inhibitors were capable of leading to the catastrophic accumulation of ROS and exerting synergistic cell death, while xCT overexpression restored these phenomena. Simvastatin, an inhibitor of HMG-CoA (3-hydroxy-3-methylglutaryl-coenzyme A) reductase, has beneficial effects in repurposing for inhibiting GPX4. Similarly, the combination treatment of DSF/Cu and simvastatin dramatically decreased the expression of GPX4 and Fe-S proteins, ultimately accelerating cell death. Moreover, we identified that the combination treatment of DSF/Cu and simvastatin also had a synergistic antitumor effect in the MDS mouse model, with the reduced GPX4, increased COX-2 and accumulated lipid peroxides. Overall, our study provided insight into developing a novel synergistic strategy to sensitize MDS therapy by targeting ferroptosis and cuproptosis.

Genome-wide Association Study of Exercise-induced Skeletal Muscle Hypertrophy and the Construction of Predictive Model.

To investigate inter-individual differences in muscle thickness of Rectus Femoris (MTRF) following 12 weeks of Resistance Training (RT) or High-Intensity Interval Training (HIIT) to explore the genetic architecture underlying skeletal muscle hypertrophy and to construct predictive models. We conducted musculoskeletal ultrasound assessments of the MTRF response in 440 physically inactive adults after the 12-week exercise period. A Genome-wide Association study (GWAS) was employed to identify variants associated with MTRF response, separately for RT and HIIT. Utilizing polygenic predictor score (PPS), we estimated the genetic contribution to exercise-induced hypertrophy. Predictive models for MTRF response were constructed using Random Forest (RF), Support Vector Mac (SVM), and Generalized Linear Model (GLM) in 10 cross-validated approach. MTRF increased significantly after both RT (8.8%, P<0.05) and HIIT (5.3%, P<0.05), but with considerable inter-individual differences (RT: -13.5~38.4%, HIIT: -14.2%~30.7%). Eleven lead SNPs in RT and eight lead SNPs in HIIT were identified at a significance level of P<1×10-5. The PPS was associated with MTRF response, explaining 47.2% of the variation in response to RT and 38.3% of the variation in response to HIIT. Notably, the GLM and SVM predictive models exhibited superior performance in comparison to RF models (p<0.05), and the GLM demonstrated optimal performance with an AUC of 0.809 (95%CI:0.669-0.949). Factors such as PPS, baseline MTRF, and exercise protocol exerted influence on the MTRF response to exercise, with PPS being the primary contributor. The GLM and SVM predictive model, incorporating both genetic and phenotypic factors, emerged as promising tools for predicting exercise-induced skeletal muscle hypertrophy.

Discovery of novel pyrrolo[2,1-c][1,4]benzodiazepine-3,11-dione (PBD) derivatives as selective HDAC6 inhibitors for the efficient treatment of idiopathic pulmonary fibrosis (IPF) in vitro and in vivo.

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease characterized by a progressive fibrotic phenotype. Immunohistochemical studies on HDAC6 overexpression in IPF lung tissues confirmed that IPF is associated with aberrant HDAC6 activity. We herein developed a series of novel HDAC6 inhibitors that can be used as potential pharmacological tools for IPF treatment. The best-performing derivative H10 showed good selectivity for multiple isoforms of the HDAC family. The structural analysis and structure-activity relationship studies of H10 will contribute to optimizing the binding mode of the new molecules. The pharmacological mechanism of H10 to inhibit pulmonary fibrosis was validated, and its ability to inhibit the IPF phenotype was also demonstrated. Moreover, H10 showed satisfactory metabolic stability. The efficacy of H10 was also determined in a mouse model of bleomycin-induced pulmonary fibrosis. The results highlighted in this paper may provide a reference for the identification of new drug molecules for the treatment of IPF.

Deep learning-based multi-modal data integration enhancing breast cancer disease-free survival prediction.

Background: The prognosis of breast cancer is often unfavorable, emphasizing the need for early metastasis risk detection and accurate treatment predictions. This study aimed to develop a novel multi-modal deep learning model using preoperative data to predict disease-free survival (DFS). Methods: We retrospectively collected pathology imaging, molecular and clinical data from The Cancer Genome Atlas and one independent institution in China. We developed a novel Deep Learning Clinical Medicine Based Pathological Gene Multi-modal (DeepClinMed-PGM) model for DFS prediction, integrating clinicopathological data with molecular insights. The patients included the training cohort (n = 741), internal validation cohort (n = 184), and external testing cohort (n = 95). Result: Integrating multi-modal data into the DeepClinMed-PGM model significantly improved area under the receiver operating characteristic curve (AUC) values. In the training cohort, AUC values for 1-, 3-, and 5-year DFS predictions increased to 0.979, 0.957, and 0.871, while in the external testing cohort, the values reached 0.851, 0.878, and 0.938 for 1-, 2-, and 3-year DFS predictions, respectively. The DeepClinMed-PGM's robust discriminative capabilities were consistently evident across various cohorts, including the training cohort [hazard ratio (HR) 0.027, 95% confidence interval (CI) 0.0016-0.046, P < 0.0001], the internal validation cohort (HR 0.117, 95% CI 0.041-0.334, P < 0.0001), and the external cohort (HR 0.061, 95% CI 0.017-0.218, P < 0.0001). Additionally, the DeepClinMed-PGM model demonstrated C-index values of 0.925, 0.823, and 0.864 within the three cohorts, respectively. Conclusion: This study introduces an approach to breast cancer prognosis, integrating imaging and molecular and clinical data for enhanced predictive accuracy, offering promise for personalized treatment strategies.

Flow cytometry-based peripheral blood analysis as an easily friendly tool for prognostic monitoring of acute ischemic stroke: a multicenter study.

Background and objective: Acute ischemic stroke (AIS) is a leading cause of mortality, severe neurological and long-term disability world-wide. Blood-based indicators may provide valuable information on identified prognostic factors. However, currently, there is still a lack of peripheral blood indicators for the prognosis of AIS. We aimed to identify the most promising prognostic indicators and establish prognostic models for AIS. Methods: 484 subjects enrolled from four centers were analyzed immunophenotypic indicators of peripheral blood by flow cytometry. Least absolute shrinkage and selection operator (LASSO) regression was applied to minimize the potential collinearity and over-fitting of variables measured from the same subject and over-fitting of variables. Univariate and multivariable Cox survival analysis of differences between and within cohorts was performed by log-rank test. The areas under the receiving operating characteristic (ROC) curves were used to evaluate the selection accuracy of immunophenotypic indicators in identifying AIS subjects with survival risk. The prognostic model was constructed using a multivariate Cox model, consisting of 402 subjects as a training cohort and 82 subjects as a testing cohort. Results: In the prospective study, 7 immunophenotypic indicators of distinct significance were screened out of 72 peripheral blood immunophenotypic indicators by LASSO. In multivariate cox regression, CTL (%) [HR: 1.18, 95% CI: 1.03-1.33], monocytes/µl [HR: 1.13, 95% CI: 1.05-1.21], non-classical monocytes/µl [HR: 1.09, 95% CI: 1.02-1.16] and CD56high NK cells/µl [HR: 1.13, 95% CI: 1.05-1.21] were detected to decrease the survival probability of AIS, while Tregs/µl [HR:0.97, 95% CI: 0.95-0.99, p=0.004], BM/µl [HR:0.90, 95% CI: 0.85-0.95, p=0.023] and CD16+NK cells/µl [HR:0.93, 95% CI: 0.88-0.98, p=0.034] may have the protective effect. As for indicators' discriminative ability, the AUC for CD56highNK cells/µl attained the highest of 0.912. In stratification analysis, the survival probability for AIS subjects with a higher level of Tregs/µl, BM/µl, CD16+NK cells/µl, or lower levels of CD56highNK cells/µl, CTL (%), non-classical monocytes/µl, Monocytes/µl were more likely to survive after AIS. The multivariate Cox model showed an area under the curve (AUC) of 0.805, 0.781 and 0.819 and 0.961, 0.924 and 0.982 in the training and testing cohort, respectively. Conclusion: Our study identified 7 immunophenotypic indicators in peripheral blood may have great clinical significance in monitoring the prognosis of AIS and provide a convenient and valuable predictive model for AIS.

ChatGPT achieves comparable accuracy to specialist physicians in predicting the efficacy of high-flow oxygen therapy.

Background: The failure of high-flow nasal cannula (HFNC) oxygen therapy can necessitate endotracheal intubation in patients, making timely prediction of the intubation risk following HFNC therapy crucial for reducing mortality due to delays in intubation. Objectives: To investigate the accuracy of ChatGPT in predicting the endotracheal intubation risk within 48 h following HFNC therapy and compare it with the predictive accuracy of specialist and non-specialist physicians. Methods: We conducted a prospective multicenter cohort study based on the data of 71 adult patients who received HFNC therapy. For each patient, their baseline data and physiological parameters after 6-h HFNC therapy were recorded to create a 6-alternative-forced-choice questionnaire that asked participants to predict the 48-h endotracheal intubation risk using scale options ranging from 1 to 6, with higher scores indicating a greater risk. GPT-3.5, GPT-4.0, respiratory and critical care specialist physicians and non-specialist physicians completed the same questionnaires (N = 71) respectively. We then determined the optimal diagnostic cutoff point, using the Youden index, for each predictor and 6-h ROX index, and compared their predictive performance using receiver operating characteristic (ROC) analysis. Results: The optimal diagnostic cutoff points were determined to be ≥ 4 for both GPT-4.0 and specialist physicians. GPT-4.0 demonstrated a precision of 76.1 %, with a specificity of 78.6 % (95%CI = 52.4-92.4 %) and sensitivity of 75.4 % (95%CI = 62.9-84.8 %). In comparison, the precision of specialist physicians was 80.3 %, with a specificity of 71.4 % (95%CI = 45.4-88.3 %) and sensitivity of 82.5 % (95%CI = 70.6-90.2 %). For GPT-3.5 and non-specialist physicians, the optimal diagnostic cutoff points were ≥5, with precisions of 73.2 % and 64.8 %, respectively. The area under the curve (AUC) in ROC analysis for GPT-4.0 was 0.821 (95%CI = 0.698-0.943), which was the highest among the predictors and significantly higher than that of non-specialist physicians [0.662 (95%CI = 0.518-0.805), P = 0.011]. Conclusion: GPT-4.0 achieves an accuracy level comparable to specialist physicians in predicting the 48-h endotracheal intubation risk following HFNC therapy, based on patient baseline data and physiological parameters after 6-h HFNC therapy.

Photoredox-Catalyzed Decarboxylative Cross-Coupling Reaction to Synthesis Unsymmetrical Diarylmethanes.

The photoredox-catalyzed decarboxylative cross-coupling reaction of aryl acetic acids and aryl nitriles has been achieved under an argon atmosphere in high yields. This method provides a fast way to obtain prevalent aryl acetic acids from an abundant natural source. A tentative radical mechanism has been proposed.

Screening approach by a combination of computational and in vitro experiments: identification of fluvastatin sodium as a potential SIRT2 inhibitor.

BACKGROUND: Sirtuins (SIRTs) are NAD+-dependent deacetylases that play various roles in numerous pathophysiological processes, holding promise as therapeutic targets worthy of further investigation. Among them, the SIRT2 subtype is closely associated with tumorigenesis and malignancies. Dysregulation of SIRT2 activation can regulate the expression levels of related genes in cancer cells, leading to tumor occurrence and metastasis. METHODS: In this study, we used computer simulations to screen for novel SIRT2 inhibitors from the FDA database, based on which 10 compounds with high docking scores and good interactions were selected for in vitro anti-pancreatic cancer metastasis testing and enzyme binding inhibition experiments. The results showed that fluvastatin sodium may possess inhibitory activity against SIRT2. Subsequently, fluvastatin sodium was subjected to molecular docking experiments with various SIRT isoforms, and the combined results from Western blotting experiments indicated its potential as a SIRT2 inhibitor. Next, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were performed, revealing the binding mode of fluvastatin sodium at the SIRT2 active site, further validating the stability and interaction of the ligand-protein complex under physiological conditions. RESULTS: Overall, this study provides a systematic virtual screening workflow for the discovery of SIRT2 activity inhibitors, identifies the potential inhibitory effect of fluvastatin sodium as a lead compound on SIRT2, and opens up a new direction for developing highly active and selectively targeted SIRT2 inhibitors.

Hypoxia treatment and resistance training alters microRNA profiling in rats skeletal muscle.

MicroRNAs (miRNAs) may play a crucial regulatory role in the process of muscle atrophy induced by high-altitude hypoxia and its amelioration through resistance training. However, research in this aspect is still lacking. Therefore, this study aimed to employ miRNA microarray analysis to investigate the expression profile of miRNAs in skeletal muscle from an animal model of hypoxia-induced muscle atrophy and resistance training aimed at mitigating muscle atrophy. The study utilized a simulated hypoxic environment (oxygen concentration at 11.2%) to induce muscle atrophy and established a rat model of resistance training using ladder climbing, with a total intervention period of 4 weeks. The miRNA expression profile revealed 9 differentially expressed miRNAs influenced by hypoxia (e.g., miR-341, miR-32-5p, miR-465-5p) and 14 differentially expressed miRNAs influenced by resistance training under hypoxic conditions (e.g., miR-338-5p, miR-203a-3p, miR-92b-3p) (∣log2(FC)∣ ≥ 1.5, p < 0.05). The differentially expressed miRNAs were found to target genes involved in muscle protein synthesis and degradation (such as Utrn, mdm2, eIF4E), biological processes (such as negative regulation of transcription from RNA polymerase II promoter, regulation of transcription, DNA-dependent), and signaling pathways (such as Wnt signaling pathway, MAPK signaling pathway, ubiquitin-mediated proteolysis, mTOR signaling pathway). This study provides a foundation for understanding and further exploring the molecular mechanisms underlying hypoxia-induced rats muscle atrophy and the mitigation of atrophy through resistance training.

Role of reactive oxygen species in myelodysplastic syndromes.

Reactive oxygen species (ROS) serve as typical metabolic byproducts of aerobic life and play a pivotal role in redox reactions and signal transduction pathways. Contingent upon their concentration, ROS production not only initiates or stimulates tumorigenesis but also causes oxidative stress (OS) and triggers cellular apoptosis. Mounting literature supports the view that ROS are closely interwoven with the pathogenesis of a cluster of diseases, particularly those involving cell proliferation and differentiation, such as myelodysplastic syndromes (MDS) and chronic/acute myeloid leukemia (CML/AML). OS caused by excessive ROS at physiological levels is likely to affect the functions of hematopoietic stem cells, such as cell growth and self-renewal, which may contribute to defective hematopoiesis. We review herein the eminent role of ROS in the hematological niche and their profound influence on the progress of MDS. We also highlight that targeting ROS is a practical and reliable tactic for MDS therapy.

Powder Synthesis and Characterization of Al0.5CoCrFeNi High-Entropy Alloy for Additive Manufacturing Prepared by the Plasma Rotating Electrode Process.

The Al0.5CoCrFeNi high-entropy alloy powder was produced by using a plasma rotating electrode process. The morphology, microstructure, and physical properties of the powder were characterized. The powder exhibited a smooth surface and a narrow particle size distribution with a single peak. The relationships between particle size and secondary dendrite arm space as well as cooling rate were evaluated as follows: λ = 0.0105d + 0.062 and vc = 4.34 × 10-5d-2 + 2.62 × 10-2d-3/2, respectively. The Al0.5CoCrFeNi powder mainly consisted of fcc + bcc phases. As the powder particle size decreased, the microstructure of the powder changed from dendritic to columnar or equiaxed, along with a decrease in the fcc content and an increase in the bcc content. The tap density (4.76 g cm-3), flowability (15.01 s × 50 g-1), oxygen content (<300 ppm), and sphericity (>94%) of the powder indicated suitability for additive manufacturing.

Analysis of m6A-regulated genes and subtype classification in lupus nephritis.

BACKGROUND: Lupus nephritis (LN) is the most common and severe clinical manifestation of systemic lupus erythematosus (SLE). N6-methyladenosine (m6A) is a reversible RNA modification and has been implicated in various biological processes. However, the roles of m6A regulators in LN are not fully demonstrated. METHODS: We downloaded the kidney tissue transcriptome dataset of LN patients and normal controls from the GEO database and extracted the expression levels of m6A regulators. We constructed and compared Random Forest (RF) and Support Vector Machine (SVM) models, and subsequently selected featured genes to develop nomogram models. The m6A subtypes were identified based on significantly differentially expressed m6A regulators, and the m6A gene subtypes were identified based on m6A-associated differential genes, and the two m6A modification patterns were comprehensively evaluated. RESULTS: We obtained the GSE32591 and GSE112943 datasets from the GEO database, including 78 LN samples and 36 normal control samples. We extracted the expression levels of 20 m6A regulators. By RF analysis we identified 7 characteristic m6A regulators and constructed nomogramh models with these 7 genes. We identified two m6A subtypes based on these seven important m6A regulators, and the immune cell infiltration levels of the two subtype clusters were significantly different. We identified two more m6A gene subtypes based on m6A-associated DEGs. We calculated the m6A scores using the principal component analysis (PCA) algorithm and found that the m6A scores of m6A cluster A and gene cluster A were lower than those of m6A cluster B and gene cluster B. In addition, we found that the levels of inflammatory factors were also significantly different between m6A clusters and gene clusters. CONCLUSION: This study confirms that m6A regulators are involved in the LN process through different modes of action and provide new diagnostic and therapeutic targets for LN.

Four New Species and One New Record of Thelephora from China.

Species of the genus Thelephora (Thelephorales, Thelephoraceae) are ectomycorrhizal symbionts of coniferous and broad-leaved plants, and some of them are well-known edible mushrooms, making it an exceptionally important group ecologically and economically. However, the diversity of the species from China has not been fully elucidated. In this study, we conducted a phylogenetic analysis based on the internal transcribed spacer (ITS) regions, using Maximum Likelihood and Bayesian analyses, along with morphological observations of this genus. Four new species from China are proposed, viz., T. dactyliophora, T. lacunosa, T. petaloides, and T. pinnatifida. In addition, T. sikkimensis originally described from India is reported for the first time from China. Thelephora dactyliophora, T. pinnatifida, and T. sikkimensis are distributed in subtropical forests and mainly associated with plants of the families Fagaceae and Pinaceae. Thelephora lacunosa and T. petaloides are distributed in tropical to subtropical forests. Thelephora lacunosa is mainly associated with plants of the families Fagaceae and Pinaceae, while T. petaloides is mainly associated with plants of the family Fagaceae. Line drawings of microstructures, color pictures of fresh basidiomes, and detailed descriptions of these five species are provided.

Spatiotemporal heterogeneity in meteorological and hydrological drought patterns and propagations influenced by climatic variability, LULC change, and human regulations.

This study aims to quantify meteorological-hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide.

Inhibitory Effects of the Polyphenols from the Root of Rhizophora apiculata Blume on Fatty Acid Synthase Activity and Human Colon Cancer Cells.

Marine mangrove vegetation has been traditionally employed in folk medicine to address various ailments. Notably, Rhizophora apiculata Blume has exhibited noteworthy properties, demonstrating efficacy against cancer, viruses, and bacteria. The enzyme fatty acid synthase (FAS) plays a pivotal role in de novo fatty acid synthesis, making it a promising target for combating colon cancer. Our study focused on evaluating the FAS inhibitory effects of both the crude extract and three isolated compounds from R. apiculata. The n-butanol fraction of R. apiculata extract (BFR) demonstrated a significant inhibition of FAS, with an IC50 value of 93.0 µg/mL. For inhibition via lyoniresinol-3α-O-ß-rhamnopyranoside (LR), the corresponding IC50 value was 20.1 µg/mL (35.5 µM). LR competitively inhibited the FAS reaction with acetyl-CoA, noncompetitively with malonyl-CoA, and in a mixed manner with NADPH. Our results also suggest that both BFR and LR reversibly bind to the KR domain of FAS, hindering the reduction of saturated acyl groups in fatty acid synthesis. Furthermore, BFR and LR displayed time-dependent inhibition for FAS, with kobs values of 0.0045 min-1 and 0.026 min-1, respectively. LR also exhibited time-dependent inhibition on the KR domain, with a kobs value of 0.019 min-1. In human colon cancer cells, LR demonstrated the ability to reduce viability and inhibit intracellular FAS activity. Notably, the effects of LR on human colon cancer cells could be reversed with the end product of FAS-catalyzed chemical reactions, affirming the specificity of LR on FAS. These findings underscore the potential of BFR and LR as potent FAS inhibitors, presenting novel avenues for the treatment of human colon cancer.

Riboflavin protects against pancreatic cancer metastasis by targeting TGF-ß receptor 1.

The inhibition of transforming growth factor-ß1 (TGF-ß1) signaling by targeting TGF-ß receptor 1 (TßR1) has been considered as an ideal approach for the prevention of pancreatic cancer metastasis. Utilizing a pharmacophore model for TßR1 inhibitors, candidate compounds with the potential TßR1 binding ability were screened from the U.S. Food and Drug Administration (FDA) database, and riboflavin (RF) with a highest fit value was chosen to investigate its binding ability to TßR1 and effect on TGF-ß1 signaling in pancreatic cancer cells. Molecular docking and cellular thermal shift assay (CETSA) proved that RF at pharmacological concentrations could directly bind to TßR1. Further studies showed that pharmacological concentrations of RF in vitro could block TGF-ß1 signaling, suppress the migration and invasion, and prevent epithelial-mesenchymal transition (EMT) process of pancreatic cancer cells in the absence or presence of TGF-ß1 stimulation, indicating that RF presented anti-metastatic effect in pancreatic cancer cells. Knockdown of TßR1 could significantly attenuate the effects of RF on the migration and EMT process in pancreatic cancer cells, further confirming that the anti-metastatic effect of RF was achieved by blocking TGF-ß1 signaling after binding to TßR1. Moreover, in a mouse model of pancreatic cancer metastasis, it was certified that RF administration could block lung and liver metastases, TGF-ß1 signaling and EMT process of pancreatic cancer in vivo. In summary, our findings showed that RF could block TGF-ß1 signaling by directly binding to TßR1, thereby suppressing the metastasis of pancreatic cancer cells by inhibiting EMT process both in vitro and in vivo.

Norcantharidin inhibits the malignant progression of cervical cancer by inducing endoplasmic reticulum stress.

The antitumor effect of norcantharidin (NCTD) has been widely reported. However, whether NCTD can inhibit cervical cancer remains unknown. In the present study, it was shown that NCTD inhibited the viability of cervical cancer cells and caused cell cycle arrest in a concentration­dependent manner. Further analysis revealed that the NCTD­induced reduction in cell viability could be reversed by the inhibitor of apoptosis z­VAD­FMK and by the inhibitor of endoplasmic reticulum (ER) stress, 4­phenylbutyric acid (4­PBA). Additionally, NCTD led to the accumulation of reactive oxygen species as well as a decrease in the mitochondrial membrane potential in cervical cancer cells, whereas 4­PBA pre­treatment attenuated these alterations. In addition, NCTD increased the expression of the apoptosis­related proteins Bip, activating transcription factor (ATF) 4 and C/EBP homologous protein in a concentration­dependent manner. Moreover, NCTD significantly increased the expression of the ER stress­related signaling molecules protein kinase R­like ER kinase, inositol­requiring enzyme 1 and ATF6, but 4­PBA abolished these effects. In vivo experiments showed that NCTD significantly inhibited the growth of subcutaneous tumors in mice. Additionally, the expression of ER stress­related molecules and apoptosis­related proteins increased significantly after NCTD treatment. In conclusion, NCTD induces apoptosis by activating ER stress and ultimately curtails the progression of cervical cancer.

Safety and efficacy evaluation of personalized exercise prescription during chemotherapy for lung cancer patients.

BACKGROUND: To explore the safety and effectiveness of personalized exercise intervention during chemotherapy for lung cancer patients who were relatively weak and with compromised cardiopulmonary function. METHODS: Thirty-eight lung cancer patients treated with chemotherapy at Peking University Third Hospital were enrolled in this prospective study. The exercise group (N = 21) received individualized exercise guidance based on personal test results and exercised regularly, while the control group (N = 17) only received exercise education and planed exercise methods according to their own preferences. Both groups underwent three fitness tests and clinical indicator assessments at 0, 6, and 12 weeks after starting the exercise, and the differences in trends of various indicators between the two groups were compared. RESULTS: No exercise-related adverse events occurred during the 12-week exercise period. After 12 weeks of exercise training, in terms of fitness, the exercise group showed significant improvements in 6-min walk test (6MWT) (p < 0.001), peak oxygen consumption (VO2peak) (p = 0.005), muscle content (p < 0.001), muscle percentage (p < 0.001), and grip strength (p = 0.008) compared to the control group. In terms of clinical indicators, the exercise group showed significant improvements in vital capacity (p = 0.018), D-dimer (p = 0.031), and C-reactive protein (CRP) (p = 0.01), uric acid (p = 0.003), triglycerides (p < 0.001), functional average score (p < 0.001), and main symptom average score (p = 0.004) compared to the control group in trends over time. CONCLUSION: Rehabilitation exercises using individualized exercise prescriptions tailored by exercise prescription specialists during chemotherapy are safe for lung cancer patients. Adhering to exercise can achieve comprehensive improvements in physical fitness and quality of life at 12 weeks.

Ferroptosis mechanisms and its novel potential therapeutic targets for DLBCL.

Diffuse large B-cell lymphoma (DLBCL), a heterogeneous lymphoid malignancy, poses a significant threat to human health. The standard therapeutic regimen for patients with DLBCL is rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), with a typical cure rate of 50-70%. However, some patients either relapse after complete remission (CR) or exhibit resistance to R-CHOP treatment. Therefore, novel therapeutic approaches are imperative for managing high-risk or refractory DLBCL. Ferroptosis is driven by iron-dependent phospholipid peroxidation, a process that relies on the transition metal iron, reactive oxygen species (ROS), and phospholipids containing polyunsaturated fatty acids-containing phospholipids (PUFA-PLs). Research indicates that ferroptosis is implicated in various carcinogenic and anticancer pathways. Several hematological disorders exhibit heightened sensitivity to cell death induced by ferroptosis. DLBCL cells, in particular, demonstrate an increased demand for iron and an upregulation in the expression of fatty acid synthase. Additionally, there exists a correlation between ferroptosis-associated genes and the prognosis of DLBCL. Therefore, ferroptosis may be a promising novel target for DLBCL therapy. In this review, we elucidate ferroptosis mechanisms, its role in DLBCL, and the potential therapeutic targets in DLBCL. This review offers novel insights into the application of ferroptosis in treatment strategies for DLBCL.

Machine learning assisted biosensing technology: An emerging powerful tool for improving the intelligence of food safety detection.

Recently, the application of biosensors in food safety assessment has gained considerable research attention. Nevertheless, the evaluation of biosensors' sensitivity, accuracy, and efficiency is still ongoing. The advent of machine learning has enhanced the application of biosensors in food security assessment, yielding improved results. Machine learning has been preliminarily applied in combination with different biosensors in food safety assessment, with positive results. This review offers a comprehensive summary of the diverse machine learning methods employed in biosensors for food safety. Initially, the primary machine learning methods were outlined, and the integrated application of biosensors and machine learning in food safety was thoroughly examined. Lastly, the challenges and limitations of machine learning and biosensors in the realm of food safety were underscored, and potential solutions were explored. The review's findings demonstrated that algorithms grounded in machine learning can aid in the early detection of food safety issues. Furthermore, preliminary research suggests that biosensors could be optimized through machine learning for real-time, multifaceted analyses of food safety variables and their interactions. The potential of machine learning and biosensors in real-time monitoring of food quality has been discussed.