The Mutual Regulatory Role of Ferroptosis and Immunotherapy in Anti-tumor Therapy.

Ferroptosis is a form of cell death that is triggered by the presence of ferrous ions and is characterized by lipid peroxidation induced by these ions. The mechanism exhibits distinct morphological characteristics compared to apoptosis, autophagy, and necrosis. A notable aspect of ferroptosis is its ability to inhibit uncontrolled tumor replication and immortalization, especially in malignant, drug-resistant, and metastatic tumors. Additionally, immunotherapy, a novel therapeutic approach for tumors, has been found to have a reciprocal regulatory relationship with ferroptosis in the context of anti-tumor therapy. A comprehensive analysis of ferroptosis and immunotherapy in tumor therapy is presented in this paper, highlighting the potential for mutual adjuvant effects. Specifically, we discuss the mechanisms underlying ferroptosis and immunotherapy, emphasizing their ability to improve the tumor immune microenvironment and enhance immunotherapeutic effects. Furthermore, we investigate how immunotherapeutic factors may increase the sensitivity of tumor cells to ferroptosis. We aim to provide a prospective view of the promising value of combined ferroptosis and immunotherapy in anticancer therapy by elucidating the mutual regulatory network between each.

High-Performance Anode Material Based on Zinc Naphthalocyanine/Graphene Composite.

Transition metal oxides are a potential anode material owing to their high theoretical capacity. Nonetheless, their large volume changes and low electrical conductivities lead to poor cycling performance and rate capabilities. In this article, an effective strategy is proposed and developed for preparing a ZnO/N-doped graphene composite (ZnNc/GO-5). The key point of this strategy is to use zinc tetra tert-butyl-naphthalocyanine (ZnNc) as a codoped source of N atoms and zinc ions, and graphene oxide (GO) which is combined with ZnNc by π-π deposition as a carbon matrix. After calcination, ZnO microcrystals coated with N-doped graphene are obtained. The unique features of the composite and synergistic effect between N-doped reduced graphene oxide and ZnO microcrystals enable good electrochemical performance by the composites when used in lithium-ion batteries. As an anode material, the as-synthesized ZnNc/GO-5 composite delivers a high first capacity of 1942.9 mAh g-1 and excellent cyclic stability of 861.4 mAh g-1 after 150 cycles at 100 mA g-1. This strategy may offer a new method of designing the anode materials of lithium-ion batteries and promote the practical use of organic molecules in next-generation lithium-ion batteries.

Differences in Kondo Splitting of Surface Quantum Systems Induced by Two Distinct Magnetic Tips: A Joint Method of DFT and HEOM.

The interactions between a magnetic tip and local spin impurities initiate unconventional Kondo phenomena, such as asymmetric suppression or even splitting of the Kondo peak. However, a lack of realistic theoretical models and comprehensive explanations for this phenomenon persists due to the complexity of the interactions. This research employs a joint method of density functional theory (DFT) and hierarchical equation of motion (HEOM) to simulate and contrast the modulation of the spin state and Kondo behavior in the Fe/Cu(100) system with two distinct magnetic tips. A cobalt tip, possessing a larger magnetic moment, incites greater atomic displacement of the iron atom, more notable alterations in electronic structure, and enhanced charge transfer with the environment compared with the control process utilizing a nickel tip. Furthermore, the Kondo resonance undergoes asymmetric splitting as a result of the ferromagnetic correlation between the iron atom and the magnetic tip. The Co tip's higher spin polarization results in a wider spacing between the splitting peaks. This investigation underscores the precision of the DFT + HEOM approach in predicting complex quantum phenomena and explaining the underlying physical principles. This provides valuable theoretical support for developing more sophisticated quantum regulation experiments.

Novel STAT3 oligonucleotide compounds suppress tumor growth and overcome the acquired resistance to sorafenib in hepatocellular carcinoma.

Signal transducer and activator of transcription 3 (STAT3) plays an important role in the occurrence and progression of tumors, leading to resistance and poor prognosis. Activation of STAT3 signaling is frequently detected in hepatocellular carcinoma (HCC), but potent and less toxic STAT3 inhibitors have not been discovered. Here, based on antisense technology, we designed a series of stabilized modified antisense oligonucleotides targeting STAT3 mRNA (STAT3 ASOs). Treatment with STAT3 ASOs decreased the STAT3 mRNA and protein levels in HCC cells. STAT3 ASOs significantly inhibited the proliferation, survival, migration, and invasion of cancer cells by specifically perturbing STAT3 signaling. Treatment with STAT3 ASOs decreased the tumor burden in an HCC xenograft model. Moreover, aberrant STAT3 signaling activation is one of multiple signaling pathways involved in sorafenib resistance in HCC. STAT3 ASOs effectively sensitized resistant HCC cell lines to sorafenib in vitro and improved the inhibitory potency of sorafenib in a resistant HCC xenograft model. The developed STAT3 ASOs enrich the tools capable of targeting STAT3 and modulating STAT3 activity, serve as a promising strategy for treating HCC and other STAT3-addicted tumors, and alleviate the acquired resistance to sorafenib in HCC patients. A series of novel STAT3 antisense oligonucleotide were designed and showed potent anti-cancer efficacy in hepatocellular carcinoma in vitro and in vivo by targeting STAT3 signaling. Moreover, the selected STAT3 ASOs enhance sorafenib sensitivity in resistant cell model and xenograft model.

Ophthalmic Artery Morphology and Hemodynamics Associated with White Matter Hyperintensity.

Purpose: To investigate morphological and hemodynamic characteristics of the ophthalmic artery (OA) in patients with white matter hyperintensity (WMH), and the association of the presence and severity of WMH with OA characteristics. Methods: This cross-sectional study included 44 eyes of 25 patients with WMH and 38 eyes of 19 controls. The Fazekas scale was adopted as criteria for evaluating the severity of white matter hyperintensities. The morphological characteristics of the OA were measured on the basis of three-dimensional reconstruction. The hemodynamic parameters of the OA were calculated using computational fluid dynamics simulations. Results: Compared with the control group, the diameter (16.0±0.27 mm vs. 1.71±0.18 mm, P=0.029), median blood flow velocity (0.12 m/s vs. 0.22 m/s, P<0.001), mass flow ratio (2.16% vs. 3.94%, P=0.012) and wall shear stress (2.65 Pa vs. 9.31 Pa, P<0.001) of the OA in patients with WMH were significantly decreased. After adjusting for confounding factors, the diameter, blood flow velocity, wall shear stress, and mass flow ratio of the OA were significantly associated with the presence of WMH. Male sex and high low-density protein level were associated with moderate-to-severe total WMH, and smoking was associated with the moderate-to-severe periventricular WMH. Conclusions: The diameter, blood flow velocity, mass flow ratio, and wall shear stress of the OA were independently associated with the presence of WMH. Atherosclerosis might be involved in the common mechanism of the occurrence of WMH and the OA changes.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Deep learning in computed tomography to predict endotype in chronic rhinosinusitis with nasal polyps.

BACKGROUND: As treatment strategies differ according to endotype, rhinologists must accurately determine the endotype in patients affected by chronic rhinosinusitis with nasal polyps (CRSwNP) for the appropriate management. In this study, we aim to construct a novel deep learning model using paranasal sinus computed tomography (CT) to predict the endotype in patients with CRSwNP. METHODS: We included patients diagnosed with CRSwNP between January 1, 2020, and April 31, 2023. The endotype of patients with CRSwNP in this study was classified as eosinophilic or non-eosinophilic. Sinus CT images (29,993 images) were retrospectively collected, including the axial, coronal, and sagittal planes, and randomly divided into training, validation, and testing sets. A residual network-18 was used to construct the deep learning model based on these images. Loss functions, accuracy functions, confusion matrices, and receiver operating characteristic curves were used to assess the predictive performance of the model. Gradient-weighted class activation mapping was performed to visualize and interpret the operating principles of the model. RESULTS: Among 251 included patients, 86 and 165 had eosinophilic or non-eosinophilic CRSwNP, respectively. The median (interquartile range) patient age was 49 years (37-58 years), and 153 (61.0%) were male. The deep learning model showed good discriminative performance in the training and validation sets, with areas under the curves of 0.993 and 0.966, respectively. To confirm the model generalizability, the receiver operating characteristic curve in the testing set showed good discriminative performance, with an area under the curve of 0.963. The Kappa scores of the confusion matrices in the training, validation, and testing sets were 0.985, 0.928, and 0.922, respectively. Finally, the constructed deep learning model was used to predict the endotype of all patients, resulting in an area under the curve of 0.962. CONCLUSIONS: The deep learning model developed in this study may provide a novel noninvasive method for rhinologists to evaluate endotypes in patients with CRSwNP and help develop precise treatment strategies.

The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers.

BACKGROUND: This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. MATERIALS AND METHODS: 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. RESULTS: The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. CONCLUSIONS: The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model's classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat's impact on radiomic features in medical imaging.

A multi-view fusion lightweight network for CRSwNPs prediction on CT images.

Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS (non-eCRS) is an important topic in predicting postoperative outcomes and administering personalized treatment. To this end, we have constructed a sinus CT dataset, which comprises CT scan data and pathological biopsy results from 192 patients of chronic rhinosinusitis with nasal polyps (CRSwNP), treated at the Second Affiliated Hospital of Shantou University Medical College between 2020 and 2022. To differentiate CRSwNP endotype on preoperative CT and improve efficiency at the same time, we developed a multi-view fusion model that contains a mini-architecture with each network of 10 layers by modifying the deep residual neural network. The proposed model is trained on a training set and evaluated on a test set. The multi-view deep learning fusion model achieved the area under the receiver-operating characteristics curve (AUC) of 0.991, accuracy of 0.965 and F1-Score of 0.970 in test set. We compared the performance of the mini-architecture with other lightweight networks on the same Sinus CT dataset. The experimental results demonstrate that the developed ResMini architecture contribute to competitive CRSwNP endotype identification modeling in terms of accuracy and parameter number.

Association of the Verbal Rating Scale-Measured Dysmenorrhea with Nausea and Vomiting in Pregnancy: A Retrospective Cohort Study.

OBJECTIVES: Nausea and vomiting in pregnancy (NVP) is a common condition that reduces the quality of life by negatively affecting work and family life, physical and mental health, and economic well-being. However, its risk factors remain unclear. This study aimed to explore the association between NVP and verbal rating scale (VRS)-measured dysmenorrhea and to explore potential protective factors. METHODS: This retrospective cohort study was conducted from June 2018 to December 2020 at Tongji Hospital in Wuhan. Information on baseline characteristics, pregnancy-related history, periconceptional micronutrient supplementation, and obstetric outcomes were collected. The severity of dysmenorrhea was assessed using VRS. RESULTS: A total of 443 pregnant women were recruited and divided into the NVP group (n = 76) and the control group (n = 367). A significant association was observed between NVP and VRS-measured dysmenorrhea (c2=10.038, P = 0.007). After adjusting for covariates, the association between moderate/severe dysmenorrhea and NVP remained significant (OR 2.384; 95% CI 1.104-5.148, P = 0.004). First-trimester docosahexaenoic acid supplement (OR 0.443; 95% CI 0.205-0.960, P = 0.039) may be beneficial in reducing the risk of NVP. CONCLUSIONS: Women with moderate to severe dysmenorrhea have a higher risk of experiencing NVP during the first trimester. Periconceptional docosahexaenoic acid supplementation may play a protective role.

Visualization of Blood-Brain Barrier Disruption in Septic Mice with the New Method Based on in Vivo Imaging Technology.

BACKGROUND: Dynamic monitoring of the blood-brain barrier (BBB) functional status in septic mice can help to explore the pathological mechanisms. Therefore, we proposed a new method for monitoring BBB permeability and applied it to the detection of sepsis models. METHODS: The new method involves the construction of an optical cranial window and in vivo imaging. We performed dynamic monitoring of BBB permeability and cerebral blood flow (CBF) in cecal ligation puncture (CLP) and endotoxemia (lipopolysaccharide [LPS]) mice. RESULTS: The sensitivity and accuracy of this method were higher than those of Evans blue evaluation. The increase of BBB permeability in the group of CLP mice was relatively mild and correlated with overall survival, and the damage was irreversible. Contrarily, BBB damage in the LPS group was more acute and severe, unrelated to overall survival, but recoverable. The CBF decreased significantly in both model mouse groups 24 h after modeling, but only the CBF proportion decrease in the LPS group was significantly correlated with an increase in BBB permeability. Within 24 h after both models were established, the decrease in blood flow in the digestive organs occurred earlier than in the brain and kidneys, and the decrease in small intestine blood flow in the LPS group progressed faster. CONCLUSIONS: We have successfully demonstrated the feasibility of our novel method to detect BBB permeability in mice. Our results revealed a significant difference in the BBB permeability change trend between the CLP and LPS model mice when survival curves were consistent. Notably, the CLP-model mice demonstrated a closer resemblance to clinical patients. Our findings suggest that early-stage brain tissue hypoperfusion has a greater impact on BBB function damage in endotoxemia mice, which is related to the faster progression of blood flow redistribution.

[Seminal vesiculoscopy-assisted thulium laser ablation for the treatment of ejaculatory duct obstruction: An analysis of clinical outcomes].

OBJECTIVE: To evaluate the clinical outcomes of seminal vesiculoscopy-assisted thulium laser ablation (SVS-TLA) in the treatment of oligoasthenozoospermia or azoospermia induced by ejaculatory duct obstruction (EDO). METHODS: We retrospectively analyzed the clinical data on 42 cases of EDO-induced oligoasthenozoospermia or azoospermia in our Clinic of Andrology from April 2018 to January 2020, all definitely diagnosed and treated by SVS-TLA. We followed up the patients regularly after operation, obtained their routine semen parameters at 3, 6 and 9 months postoperatively, examined them by t-test and compared them with the baseline. RESULTS: Operations were successfully completed in all the 42 cases, with an average surgery time of 52.7 minutes. Compared with the routine semen parameters collected 2 weeks before surgery, the semen volume, sperm concentration and total sperm motility of the patients were all significantly improved at 3, 6 and 9 months postoperatively (P < 0.01). Sperm were found in 40 cases at 3 months and in the other 2 cases at 6 and 9 months after surgery. Postoperative complications were observed in 7 cases, including epididymitis, perineal or testicular pain, and hematuria, which all disappeared after corresponding symptomatic treatment. No such serious complications as retrograde ejaculation, rectal injury, urethral stricture or urinary incontinence occurred in any of the cases after operation. CONCLUSION: SVS-TLA is a safe and effective option for the treatment of EDO, which can significantly improve the semen quality of the patient without causing serious postoperative complications.

STAT4 targets KISS1 to inhibit the oxidative damage, inflammation and neuronal apoptosis in experimental PD models by inactivating the MAPK pathway.

BACKGROUND: Oxidative stress and neuroinflammation are proven to play critical roles in the pathogenesis of Parkinson's disease (PD). As reported, patients with PD have lower level of STAT4 compared with healthy subjects. However, the biological functions and mechanisms of STAT4 in PD pathogenesis remain uncertain. This study aimed to investigate the roles and related mechanisms of STAT4 in PD development. METHODS: The intraperitoneal injection of MPTP (20 mg/kg) dissolved in physiological saline was performed to mimic PD-like conditions in vivo. MPP + solution was prepared for cell model of PD. Cell viability was measured by CCK-8. Griess reaction was conducted to measure NO concentrations. The mRNA and protein levels were evaluated by RT-qPCR and western blotting. ROS generation was assessed by DCFH-DA. The levels of inflammatory cytokines were measured by ELISA. Cell apoptosis was examined by flow cytometry and western blotting. Moreover, the SH-SY5Y cells were treated with conditioned medium from LPS-stimulated microglia and subjected to CCK-8 assays and ELISA. Mechanistically, CHIP assays and luciferase reporter assays were performed to verify the binding relationship between KISS1 and STAT4. For in vivo analysis, the histological changes of midbrain tissues of mice were determined by hematoxylin and eosin staining. The expression of tyrosine hydroxylase (TH) was detected by immunohistochemistry staining. Iba-1 positive microglial cells in the striatum were assessed by immunofluorescence staining. RESULTS: For in vitro analysis, STAT4 level was downregulated after MPP+ treatment, and STAT4 upregulation inhibited the oxidative damage, inflammation and apoptosis in SH-SY5Y cells. STAT4 bound at +215-228 region of KISS1, and KISS1 upregulation counteracted the protection of STAT4 upregulation against cell damage. Moreover, STAT4 upregulation inhibited cell viability loss and inflammation induced by conditioned medium from LPS-treated microglia, whereas KISS1 upregulation had the opposite effect. For in vivo analysis, the protective effects of STAT4 upregulation against inflammatory response, oxidative stress, dopaminergic neuronal loss and microglia activation were attenuated by KISS1 upregulation. Moreover, the inactivation of MAPK pathway caused by STAT4 upregulation was reversed by KISS1 upregulation, and MAPK inhibition attenuated the MPP+-induced inflammation, oxidative stress and apoptosis in SH-SY5Y cells. CONCLUSION: STAT4 inhibits KISS1 to attenuate the oxidative damage, inflammation and neuronal apoptosis in PD by inactivating the MAPK pathway.

Association between dietary inflammatory index and all-cause mortality in patients with osteopenia or osteoporosis: A retrospective cohort study from the NHANES 2007-2018.

Objective: Osteoporosis is an inflammatory disease that causes a large disease burden worldwide. Dietary inflammation index (DII), a comprehensive assessment index that reflects the pro-inflammatory/anti-inflammatory level of diet was related to multiple inflammatory diseases. This study aimed to explore the association between DII and all-cause mortality in patients with osteoporosis or osteopenia. Methods: In this retrospective cohort study, data of patients aged ≥ 45 years diagnosed as osteopenia or osteoporosis and had complete dietary intake information were extracted from the National Health and Nutrition Examination Survey (NHANES 2007-2010, 2013-2014, 2017-2018). Dietary intake information was obtained from 24-h dietary recall interviews and was used to calculate the DII score. Weighted univariate and multivariate Cox proportional hazard models were utilized to explore the association between DII and all-cause mortality in patients with osteoporosis or osteopenia, with hazard ratios (HRs) and 95 % confidence intervals (CIs). Subgroup analyses based on different age, gender and complications were further assessed this association. Results: A total of 5,381 patients were included. Until December 31, 2019, 1,286 all-cause deaths occurred. After adjusting all covariates, high DII was associated with the high odds of all-cause mortality among patients with osteoporosis or osteopenia (HR=1.28, 95 %CI: 1.10-1.48), especially in the male (HR=1.38, 95 %CI: 1.06-1.78), aged < 65 years (HR=1.49, 95 %CI: 1.09-2.02), and without the history the cardiovascular disease (HR=1.30, 95 %CI: 1.03-1.65), diabetes mellitus (HR=1.27, 95 %CI: 1.06-1.52) and chronic kidney disease (HR=1.28, 95 %CI: 1.03-1.58). Conclusion: A pro-inflammatory diet may have an adverse effect on the prognosis of osteoporosis patients.

A transcutaneous acupoint electrical simulation glove for relieving the mental fatigue of crane drivers in real building environment.

In the field of construction, the lifting environment of precast parts is more complex, which leads to the driver's fatigue. When the tower crane driver appears driving fatigue, it will appear slow operation response, hoisting precast parts appear abnormal swing, which will endanger the safety of on-site operators. Therefore, this study developed a kind of transcutaneous acupoint electrical stimulation gloves. When the crane driver wears this kind of glove, the good contraction of the glove can make the stimulation electrode closely fit with the three points, so as to perform electrical stimulation on the Neìguan point (PC6), Láogóng point (PC8) and Hégu point (L14) of the palm to relieve the driver's driving fatigue. In this study, non-periodic transcutaneous acupoint electrical stimulation (NPTAES) was used to stimulate human acupuncture points. This is different from the traditional periodic transcutaneous acupoint electrical stimulation (PTAES) method for relieving mental fatigue. In addition, this study used hilbert marginal spectral entropy (HMSE) to calculate the heart rate variability (HRV) characteristics of the subjects, so as to detect and analyze the driving fatigue of the drivers. At the same time, the drivers' blinking frequency and electroencephalogram (EEG) characteristics were analyzed comprehensively. The results show that: The NPTAES method used in this study is superior to the PTAES method in alleviating driving fatigue and greatly improves the efficiency of tower crane drivers. Compared to other methods, the HMSE method proposed in this study, when analyzing signals, stronger ability to characterize signal characteristics.

Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma.

BACKGROUND: The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded. METHODS: A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays. RESULTS: The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays. CONCLUSION: The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.

Effects of Momordica charantia L. supplementation on glycemic control and lipid profile in type 2 diabetes mellitus patients: A systematic review and meta-analysis of randomized controlled trials.

Background and aims: Momordica charantia L. (M. charantia) has been traditionally utilized as a medicinal intervention for managing type 2 diabetes mellitus (T2DM). The current study was designed to offer a GRADE-assessed systematic review and meta-analysis of randomized controlled trials (RCTs) examining the impact of M. Charantia intake on glycemic indexes and the lipid profile of patients with T2DM. Methods: A comprehensive search was conducted across several databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, from the inception of each database until April 22, 2023. The Hartung-Knapp adjustment was applied to ensure conservative summary estimates with broad confidence intervals. Results: A total of eight trials involving 423 patients with T2DM were included in this study. Compared to the control group, the intake of M. charantia supplementation resulted in significant reductions in fasting blood glucose (FBG) (WMD: -0.85 mmol/L; 95%CI: -1.44, -0.26; p = 0.005; I2 = 73.4 %), postprandial glucose (PPG) (WMD: -2.28 mmol/L; 95%CI: -3.35, -1.21; p = 0.000; I2 = 66.9 %), glycosylated hemoglobin A1c (HbA1c) (WMD: -0.38 %; 95%CI: -0.53, -0.23; p = 0.000; I2 = 37.6 %), and total cholesterol (TC) (WMD: -0.38 mmol/L; 95%CI: -0.70, -0.07; p = 0.017; I2 = 63.6 %). These results remained statistically significant even after applying the Hartung-Knapp adjustment. However, no significant differences were observed in terms of triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). Conclusions: The findings of this study suggest that M. charantia could serve as a potential alternative for individuals with T2DM, particularly those with elevated total cholesterol levels. However, further high-quality studies are necessary to validate these results.

The manufacturing process provides green teas with differentiated nonvolatile profiles and influences the deterioration of flavor during storage at room temperature.

Hundreds of green tea products are available on the tea market and exhibit different characteristics. In the present study, seven types of green tea were processed, and their nonvolatile profiles were analyzed by liquid chromatography-mass spectrometry. Non-spreading green tea contained higher concentrations of catechins and flavonoid glycosides, but lower concentrations of amino acids, caffeine, and theaflavins. Non-rolling green teas with a straight appearance contained higher concentrations of flavonoid glycosides and theaflavins. In contrast, leaf-rolling green teas contained much lower concentrations of flavonoid glycosides and catechins. These seven green tea qualities all decreased following prolonged storage, concurrent with increasing concentrations of proanthocyanidins, catechins dimers, theaflavins, and organic acids. The leaf-rolling green teas exhibited reduced levels of deterioration during storage in terms of their nonvolatile profile and sensory quality. Findings show that moderate destruction on tea leaves during green tea processing is beneficial to both tea flavor and quality maintenance during storage.

Quantitative differentiation of toxicity contributions and predicted global risk of fipronil and its transformation products to aquatic invertebrates.

Biotransformation often alters chemical toxicity, yet its impacts on risk assessment are hardly quantified due to the challenges in acquiring internal exposure-based thresholds for chemicals that are readily metabolizable. Here, we integrated toxic unit and toxicokinetics to quantitatively assess toxicity contributions and potential risk of both parent compound and transformation products (TPs) to aquatic organisms, using fipronil (FIP) as a representative toxicant. In aquatic invertebrates Chironomus dilutus and Hyalella azteca, approximately 90 % of FIP was transformed to fipronil sulfone (SUL). FIP and SUL exhibited similar intrinsic toxicity to these organisms, which was contrary to conventional perception that SUL was more toxic than FIP. However, biotransformation was still important in risk assessment because the TP had 10-fold slower depuration rate than FIP. The amphipod H. azteca was found to be as sensitive to FIPs as the insect C. dilutus, which was previously considered ten times more sensitive based on external thresholds. This discrepancy has led to overlooking the toxicity of FIP to H. azteca in regional risk assessments. Lastly, we predicted the lethal risk of FIPs in global surface water. When using external thresholds for prediction, FIPs in 3.4 % of the water samples were lethally toxic to H. azteca, and the percentage of water samples at risk increased to 14 % when internal thresholds were used and SUF dominated the risk. This study presents an improved method for quantifying aquatic risk of readily metabolized toxicants. Our findings underscore the urgency of considering TPs in water quality assessments, especially for sensitive species that are at risk in the environment.