Plasma SMOC2 Predicts Prognosis in Patients with Heart Failure: A Prospective Cohort.

Background: Heart failure (HF) is a chronic disease with a poor prognosis, making it extremely important to assess the prognosis of patients with HF for accurate treatment. Secreted modular calcium-binding protein 2 (SMOC2) is a cysteine-rich acidic secreted protein that plays a pathophysiological role in many diseases, including regulation of vascular growth factor activity. It has previously been found that SMOC2 plays an essential role in cardiac fibrosis in our previous preclinical study, but whether it can be used as a clinical marker in heart failure patients remains unclear. The purpose of this research was to evaluate the correlation between plasma levels of SMOC2 and the prognosis for individuals with HF. Methods: HF patients diagnosed with ischemic cardiomyopathy were enrolled from January to December 2021. Baseline plasma levels of SMOC2 were measured after demographic and clinical features were collected. Linear and nonlinear multivariate Cox regression models were used to determine the association between plasma SMOC2 and patient outcomes during follow-up. All analysis was performed using SPSS, EmpowerStats, and R software. Results: The study included 188 patients, and the average follow-up time was 489.5±88.3 days. The plasma SMOC2 concentrations were positively correlated with N-terminal pro-B-type Natriuretic Peptide (NT-proBNP), left ventricular end-diastolic diameter (LVEDd), and length of hospital stay and were negatively correlated with left ventricular ejection fraction (LVEF) at baseline. A total of 53 patients (28.2%) were rehospitalized due to cardiac deterioration, 14 (7.4%) died, and 37 (19.7%) developed malignant arrhythmias. A fully adjusted multivariate COX regression model showed that SMOC2 is associated with readmission (HR = 1.02, 95% CI:1.012-1.655). A significant increase in rehospitalization risk was observed in group Q2 (HR =1.064, 95% CI: 1.037, 3.662, p=0.005) and group Q3 (HR =1.085, 95% CI:1.086, 3.792, p=0.009) in comparison with group Q1. The p for trend also shows a linear correlation across the three models (P < 0.001). SMOC2 was associated with the severity of HF in patients, but not with all-cause deaths and arrhythmias during follow-up. Conclusion: Plasma SMOC2 is associated with the severity of HF and readmission rate, and is a good predictor of the risk of readmission in patients.

Enhancing astaxanthin accumulation through the expression of the plant-derived astaxanthin biosynthetic pathway in Dunaliella salina.

Dunaliella salina, a microalga that thrives under high-saline conditions, is notable for its high ß-carotene content and the absence of a polysaccharide cell wall. These unique characteristics render it a prime candidate as a cellular platform for astaxanthin production. In this study, our initial tests in an E. coli revealed that ß-ring-4-dehydrogenase (CBFD) and 4-hydroxy-ß-ring-4-dehydrogenase (HBFD) genes from Adonis aestivalis outperformed ß-carotene hydroxylase (BCH) and ß-carotene ketolase (BKT) from Haematococcus pluvialis counterparts by two-fold in terms of astaxanthin biosynthesis efficiency. Subsequently, we utilized electroporation to integrate either the BKT gene or the CBFD and HBFD genes into the genome of D. salina. In comparison to wild-type D. salina, strains transformed with BKT or CBFD and HBFD exhibited inhibited growth, underwent color changes to shades of red and yellow, and saw a nearly 50% decline in cell density. HPLC analysis confirmed astaxanthin synthesis in engineered D. salina strains, with CBFD + HBFD-D. salina yielding 134.88 ± 9.12 µg/g of dry cell weight (DCW), significantly higher than BKT-D. salina (83.58 ± 2.40 µg/g). This represents the largest amount of astaxanthin extracted from transgenic D. salina, as reported to date. These findings have significant implications, opening up new avenues for the development of specialized D. salina-based microcell factories for efficient astaxanthin production.

Synergistic effects of hydrophilic function group and micropores on water evaporation in a novel carbon hydrogels for efficient solar steam generation.

Solar steam generation (SSG) using hydrogels is emerging as a promising technology for clean water production. Herein, a novel oxygen-doped microporous carbon hydrogel (OPCH), rich in hydrophilic groups and micropores, has been synthesized from microalgae to optimize SSG. OPCH outperforms hydrogels with hydrophobic porous carbon or nonporous hydrophilic biochar, significantly reducing water's evaporation enthalpy from 2216.06 to 1107.88 J g-1 and activating 42.3 g of water per 100 g for evaporation, resulting in an impressive evaporation rate of 2.44 kg m-2 h-1 under one sun. A detailed investigation into the synergistic effects of hydrophilic groups and micropores on evaporation via a second derivative thermogravimetry method revealed two types of bonded water contributing to enthalpy reduction. Molecular dynamics simulations provided further insights, revealing that the hydrophilic micropores considerably decrease both the number and the lifetime of hydrogen bonds among water molecules. This dual effect not only reduces the energy barrier for evaporation but also enhances the kinetic energy needed for the phase transition, significantly boosting the water evaporation process. The sustained high evaporation rates of OPCH, observed across multiple cycles and under varying salinity conditions, underscore its potential as a highly efficient and sustainable solution for SSG applications.

Cluster-Cluster Co-Nucleation Induced Defective Polyoxometalate-Based Metal-Organic Frameworks for Efficient Tandem Catalysis.

The construction of defective sites is one of the effective strategies to create high-activity Metal-Organic frameworks (MOFs) catalysts. However, traditional synthesis methods usually suffer from cumbersome synthesis steps and disordered defect structures. Herein, a cluster-cluster co-nucleation (CCCN) strategy is presented that involves the in situ introduction of size-matched functional polyoxometalates (H6P2W18O62, {P2W18}) to intervene the nucleation process of cluster-based MOFs (UiO-66), achieving one-step inducement of exposed defective sites without redundant post-processing. POM-induced UiO-66 ({P2W18}-0.1@UiO-66) exhibits a classical reo topology for well-defined cluster defects. Moreover, the defective sites and the interaction between POM and skeletal cluster nodes are directly observed by Integrated Differential Phase Contrast in Scanning Transmission Electron Microscopy (iDPC-STEM). Owing to the molecular-level proximity between defective sites and POM in the same nano-reaction space, {P2W18}-0.1@UiO-66 exhibits efficient tandem catalysis in the preparation of γ-valerolactone (γ-GVL) from laevulinic acid (LA) by the combination of Lewis and Brønsted acids with 11 times higher performance than defective UiO-66 formed by conventional coordination modulation strategy. The CCCN strategy is applicable to different POM and has the potential to be extended to other cluster-based MOFs, which will pave a new way for the construction of functional MOFs with multi-centered synergistic catalysis.

Evaluating a river's ecological health: A multidimensional approach.

Evaluating the health of river surface water is essential, as rivers support significant biological resources and serve as vital drinking water sources. While the Water Quality Index (WQI) is commonly employed to evaluate surface water quality, it fails to consider biodiversity and does not fully capture the ecological health of rivers. Here we show a comprehensive assessment of the ecological health of surface water in the lower Yangtze River (LYR), integrating chemical and biological metrics. According to traditional WQI metrics, the LYR's surface water generally meets China's Class II standards. However, it also contains 43 high-risk emerging contaminants; nitrobenzenes are found at the highest concentrations, representing 25-90% of total detections, while polycyclic aromatic hydrocarbons present the most substantial environmental risks, accounting for 81-93% of the total risk quotient. Notably, the plankton-based index of biological integrity (P-IBI) rates the ecological health of the majority of LYR water samples (59.7%) as 'fair', with significantly better health observed in autumn compared to other seasons (p < 0.01). Our findings suggest that including emerging contaminants and P-IBI as additional metrics can enhance the traditional WQI analysis in evaluating surface water's ecological health. These results highlight the need for a multidimensional assessment approach and call for improvements to LYR's ecological health, focusing on emerging contaminants and biodiversity rather than solely on reducing conventional indicators.

A ubiquitous tire rubber additive induced serious eye injury in zebrafish (Danio rerio).

Previous studies have indicated that tire wear particles (TWPs) leachate exposure induced serious eye injury in fish through inhibiting the thyroid peroxidase (TPO) enzyme activity. However, the main TPO inhibitors in the leachate were still unknown. In this study, we identified 2-Mercaptobenzothiazole (MBT) as the potential TPO inhibitor in the TWPs leachate through references search, model prediction based on Danish QSAR and ToxCast database, molecular docking, and in vivo assay. We further explored the toxic mechanism of MBT under environmentally relevant concentrations. The decreased eye size of zebrafish larvae was mainly caused by the decreased lens diameter and cell density in the inner nuclear layer (INL) and outer nuclear layer (ONL) of the retina. Transcriptomics analysis demonstrated that the eye phototransduction function was significantly suppressed by inhibiting the photoreceptor cell proliferation process after MBT exposure. The altered opsin gene expression and decreased opsin protein levels were induced by weakening thyroid hormone signaling after MBT treatment. These results were comparable to those obtained from a known TPO inhibitor, methimazole. This study has identified MBT as the primary TPO inhibitor responsible for inducing eye impairment in zebrafish larvae exposed to TWPs leachate. It is crucial for reducing the toxicity of TWPs leachate in fish.

Impact of healthy lifestyle on the incidence and progression trajectory of mental disorders: A prospective study in the UK Biobank.

BACKGROUND: Healthier lifestyle decreased the risk of mental disorders (MDs) such as depression and anxiety. However, research on the effects of a comprehensive healthy lifestyle on their progression is lacking. METHODS: 385,704 individuals without baseline MDs from the UK Biobank cohort were included. A composite healthy lifestyle score was computed by assessing alcohol intake, smoking status, television viewing time, physical activity, sleep duration, fruit and vegetable intake, oily fish intake, red meat intake, and processed meat intake. Follow-up utilized hospital and death register records. Multistate model was used to examine the role of healthy lifestyle on the progression of specific MDs, while a piecewise Cox regression model was utilized to assess the influence of healthy lifestyle across various phases of disease progression. RESULTS: Higher lifestyle score reduced risks of transitions from baseline to anxiety and depression, as well as from anxiety and depression to comorbidity, with corresponding hazard ratios (HR) and 95 % confidence intervals (CI) of 0.94 (0.93, 0.95), 0.90 (0.89, 0.91), 0.94 (0.91, 0.98), and 0.95 (0.92, 0.98), respectively. Healthier lifestyle decreased the risk of transitioning from anxiety to comorbidity within 2 years post-diagnosis, with HR 0.93 (0.88, 0.98). Higher lifestyle scores at 2-4 years and 4-6 years post-depression onset were associated with reduced risk of comorbidity, with HR 0.93 (0.87, 0.99) and 0.92 (0.86, 0.99), respectively. LIMITATION: The generalizability to other ethnic groups is limited. CONCLUSION: This study observed a protective role of holistic healthy lifestyle in the trajectory of MDs and contributed to identifying critical progression windows.

REV-ERBα negatively regulates NLRP6 transcription and reduces the severity of Salmonella infection in mice.

Non-typhoidal Salmonella infection is among the most frequent foodborne diseases threatening human health worldwide. The host circadian clock orchestrates daily rhythms to adapt to environmental changes, including coordinating immune function in response to potential infections. However, the molecular mechanisms underlying the interplay between the circadian clock and the immune system in modulating infection processes are incompletely understood. Here, we demonstrate that NLRP6, a novel nucleotide-oligomerization domain (NOD)-like receptor (NLR) family member highly expressed in the intestine, is closely associated with the differential day-night response to Salmonella infection. The core clock component REV-ERBα negatively regulates NLRP6 transcription, leading to the rhythmic expression of NLRP6 and the secretion of IL-18 in intestinal epithelial cells, playing a crucial role in mediating the differential day-night response to Salmonella infection. Activating REV-ERBα with agonist SR9009 in wild-type mice attenuated the severity of infection by decreasing the NLRP6 level in intestinal epithelial cells. Our findings provide new insights into the association between the host circadian clock and the immune response to enteric infections by revealing the regulation of Salmonella infection via the inhibitory effect of REV-ERBα on NLRP6 transcription. Targeting REV-ERBα to modulate NLRP6 activation may be a potential therapeutic strategy for bacterial infections.

Clinical outcomes of treatment-naïve HBeAg-negative patients with chronic hepatitis B virus infection with low serum HBsAg and undetectable HBV DNA.

Serum hepatitis B surface antigen (HBsAg) level < 100 IU/ml and undetectable hepatitis B virus (HBV) DNA have been recently proposed as an alternate endpoint of "partial cure" in chronic hepatitis B (CHB). We investigated clinical outcomes of hepatitis B e antigen (HBeAg)-negative CHB patients with HBsAg <100 IU/ml and undetectable HBV DNA. Treatment-naïve HBeAg-negative CHB patients with undetectable HBV DNA and normal alanine aminotransferase were retrospectively included from three institutions. Patients were classified into the low HBsAg group (<100 IU/ml) and the high HBsAg group (≥100 IU/ml). Liver fibrosis was evaluated by noninvasive tests (NITs). A total of 1218 patients were included and the median age was 41.5 years. Patients with low HBsAg were older (45.0 vs. 40.0 years, P < 0.001) than those in the high HBsAg group, while the NIT parameters were comparable between groups. During a median follow-up of 25.7 months, patients with low HBsAg achieved a higher HBsAg clearance rate (13.0% vs. 0%, P < 0.001) and a lower rate of significant fibrosis development (2.2% vs. 7.0%, P = 0.049) compared to patients with high HBsAg. No patient developed HCC in either group. HBsAg level was negatively associated with HBsAg clearance (HR 0.213, P < 0.001) and patients with HBsAg < 100 IU/ml had a low risk of significant fibrosis development (HR 0.010, P = 0.002). The optimal cutoff value of HBsAg for predicting HBsAg clearance was 1.1 Log10 IU/ml. Treatment-naïve HBeAg-negative CHB patients with HBsAg <100 IU/ml and undetectable HBV DNA had favourable outcomes with a high rate of HBsAg clearance and a low risk of fibrosis progression.

A deep multi-task learning approach to identifying mummy berry infection sites, the disease stage, and severity.

Introduction: Mummy berry is a serious disease that may result in up to 70 percent of yield loss for lowbush blueberries. Practical mummy berry disease detection, stage classification and severity estimation remain great challenges for computer vision-based approaches because images taken in lowbush blueberry fields are usually a mixture of different plant parts (leaves, bud, flowers and fruits) with a very complex background. Specifically, typical problems hindering this effort included data scarcity due to high manual labelling cost, tiny and low contrast disease features interfered and occluded by healthy plant parts, and over-complicated deep neural networks which made deployment of a predictive system difficult. Methods: Using real and raw blueberry field images, this research proposed a deep multi-task learning (MTL) approach to simultaneously accomplish three disease detection tasks: identification of infection sites, classification of disease stage, and severity estimation. By further incorporating novel superimposed attention mechanism modules and grouped convolutions to the deep neural network, enabled disease feature extraction from both channel and spatial perspectives, achieving better detection performance in open and complex environments, while having lower computational cost and faster convergence rate. Results: Experimental results demonstrated that our approach achieved higher detection efficiency compared with the state-of-the-art deep learning models in terms of detection accuracy, while having three main advantages: 1) field images mixed with various types of lowbush blueberry plant organs under a complex background can be used for disease detection; 2) parameter sharing among different tasks greatly reduced the size of training samples and saved 60% training time than when the three tasks (data preparation, model development and exploration) were trained separately; and 3) only one-sixth of the network parameter size (23.98M vs. 138.36M) and one-fifteenth of the computational cost (1.13G vs. 15.48G FLOPs) were used when compared with the most popular Convolutional Neural Network VGG16. Discussion: These features make our solution very promising for future mobile deployment such as a drone carried task unit for real-time field surveillance. As an automatic approach to fast disease diagnosis, it can be a useful technical tool to provide growers real time disease information that can prevent further disease transmission and more severe effects on yield due to fruit mummification.

Exposure to Molybdate Results in Metabolic Disorder: An Integrated Study of the Urine Elementome and Serum Metabolome in Mice.

The increasing use of molybdate has raised concerns about its potential toxicity in humans. However, the potential toxicity of molybdate under the current level of human exposure remains largely unknown. Endogenous metabolic alterations that are caused in humans by environmental exposure to pollutants are associated with the occurrence and progression of many diseases. This study exposed eight-week-old male C57 mice to sodium molybdate at doses relevant to humans (0.01 and 1 mg/kg/day) for eight weeks. Inductively coupled plasma mass spectrometry (ICP-MS) and ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS) were utilized to assess changes in urine element levels and serum metabolites in mice, respectively. A total of 838 subjects from the NHANES 2017-2018 population database were also included in our study to verify the associations between molybdenum and cadmium found in mice. Analysis of the metabolome in mice revealed that four metabolites in blood serum exhibited significant changes, including 5-aminolevulinic acid, glycolic acid, l-acetylcarnitine, and 2,3-dihydroxypropyl octanoate. Analysis of the elementome revealed a significant increase in urine levels of cadmium after molybdate exposure in mice. Notably, molybdenum also showed a positive correlation with cadmium in humans from the NHANES database. Further analysis identified a positive correlation between cadmium and 2,3-dihydroxypropyl octanoate in mice. In conclusion, these findings suggest that molybdate exposure disrupted amino acid and lipid metabolism, which may be partially mediated by molybdate-altered cadmium levels. The integration of elementome and metabolome data provides sensitive information on molybdate-induced metabolic disorders and associated toxicities at levels relevant to human exposure.

Unveiling Low Temperature Assembly of Dense Fe-N4 Active Sites via Hydrogenation in Advanced Oxygen Reduction Catalysts.

The single-atom Fe-N-C is a prominent material with exceptional reactivity in areas of sustainable energy and catalysis research. It is challenging to obtain the dense Fe-N4 site without the Fe nanoparticles (NPs) sintering during the Fe-N-C synthesis via high-temperature pyrolysis. Thus, a novel approach is devised for the Fe-N-C synthesis at low temperatures. Taking FeCl2 as Fe source, a hydrogen environment can facilitate oxygen removal and dichlorination processes in the synthesis, efficiently favouring Fe-N4 site formation without Fe NPs clustering at as low as 360 °C. We shed light on the reaction mechanism about hydrogen promoting Fe-N4 formation in the synthesis. By adjusting the temperature and duration, the Fe-N4 structural evolution and site density can be precisely tuned to directly influence the catalytic behaviour of the Fe-N-C material. The FeNC-H2-360 catalyst demonstrates a remarkable Fe dispersion (8.3 wt %) and superior acid ORR activity with a half-wave potential of 0.85 V and a peak power density of 1.21 W cm-2 in fuel cell. This method also generally facilitates the synthesis of various high-performance M-N-C materials (M=Fe, Co, Mn, Ni, Zn, Ru) with elevated single-atom loadings.

Association of liver function and prognosis in patients with severe fever with thrombocytopenia syndrome.

OBJECTIVES: Severe fever with thrombocytopenia syndrome (SFTS) is an epidemic emerging infectious disease with high mortality rate. We investigated the association between liver injury and clinical outcomes in patients with SFTS. METHODS: A total of 291 hospitalized SFTS patients were retrospectively included. Cox proportional hazards model was adopted to identify risk factors of fatal outcome and Kaplan-Meier curves were used to estimate cumulative risks. RESULTS: 60.1% of patients had liver injury at admission, and the median alanine transaminase, aspartate aminotransferase (AST), alkaline phosphatase (ALP), and total bilirubin (TBil) levels were 76.4 U/L, 152.3 U/L, 69.8 U/L and 9.9 µmol/L, respectively. Compared to survivors, non-survivors had higher levels of AST (253.0 U/L vs. 131.1 U/L, P < 0.001) and ALP (86.2 U/L vs. 67.9 U/L, P = 0.006), higher proportion of elevated ALP (20.0% vs. 4.4%, P < 0.001) and liver injury (78.5% vs. 54.9%, P = 0.001) at admission. The presence of liver injury (HR 2.049, P = 0.033) at admission was an independent risk factor of fatal outcome. CONCLUSIONS: Liver injury was a common complication and was strongly associated with poor prognosis in SFTS patients. Liver function indicators should be closely monitored for SFTS patients.

Soluble Programmed Cell Death 1 Protein Is a Promising Biomarker to Predict Severe Liver Inflammation in Chronic Hepatitis B Patients.

Background and Aims: Liver inflammation is important in guiding the initiation of antiviral treatment and affects the progression of chronic hepatitis B(CHB). The soluble programmed cell death 1 protein (sPD-1) was upregulated in inflammatory and infectious diseases and correlated with disease severity. We aimed to investigate the correlation between serum sPD-1 levels and liver inflammation in CHB patients and their role in indicating liver inflammation. Methods: 241 CHB patients who underwent liver biopsy were enrolled. The correlation between sPD-1 levels and the degree of liver inflammation was analyzed. Univariate and multivariate logistic regression analyses were performed to analyze independent variables of severe liver inflammation. Binary logistic regression analysis was conducted to construct a predictive model for severe liver inflammation, and the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic accuracy of the predictive model. Results: sPD-1 was highest in CHB patients with severe liver inflammation, which was higher than that in CHB patients with mild or moderate liver inflammation (P < 0.001). Besides, sPD-1 was weakly correlated with AST (r = 0.278, P < 0.001). Multivariable analysis showed that sPD-1 was an independent predictor of severe liver inflammation. The predictive model containing sPD-1 had areas under the ROC (AUROCs) of 0.917 and 0.921 in predicting severe liver inflammation in CHB patients and CHB patients with ALT ≤ 1× upper limit of normal (ULN), respectively. Conclusions: Serum sPD-1 level is associated with liver inflammation in CHB patients, and high levels of sPD-1 reflect severe liver inflammation. Serum sPD-1 is an independent predictor of severe liver inflammation and shows improved diagnostic accuracy when combined with other clinical indicators.

Relationship between leaf vein traits of three dominant Quercus species and ecological factors in the Qinling Mountains, China.

We investigated the inter- and intra-species differences of leaf vein traits of three dominant Quercus species, Q. wutaishanica, Q. aliena var. acutiserrata, and Q. variabilis of Niubeiling (subtropical humid climate) and Taohuagou (warm temperate semi-humid climate), located in the eastern and western Qinling Mountains. The nine examined leaf vein traits included primary leaf vein width, secondary leaf vein width, mean fine vein width, primary vein density, fine vein density, vein areole diameter, areole density, 3D fine vein surface area, and fine vein volume. We further elucidated the influencing mechanisms and regulatory pathways of biotic and abiotic factors on leaf vein traits. The results showed that species identity had significant effects on eight out of nine leaf vein traits except 3D fine vein surface area, while habitat had significant effects on primary leaf vein width, secondary leaf vein width, vein areole diameter, fine vein density, and areole density. Altitude had significant effects on primary vein density, mean fine vein width, vein areole diameter, fine vein density and areole density. Habitat, tree species identity, and altitude had significantly interactive effects on primary leaf vein density, 3D fine vein surface area, and fine vein volume. There were significant differences in primary leaf vein width, mean fine vein width, areole density, 3D fine vein surface area, fine vein volume, primary vein density of Q. wutaishanica between the two studied habitats, but the differences were only found in secondary leaf vein width and areole density of Q. aliena var. acutiserrata and Q. variabilis. The examined leaf vein traits were influenced both by biotic and abiotic factors, with varying effect sizes. Among the biotic factors, petiole length, leaf length and width ratio had strong effect on leaf vein traits. Among the abiotic factors, climatic and soil factors had high effect size on vein traits, with the former being higher than the latter. Leaf vein traits were affected directly by biotic factors, but indirectly by abiotic factors (soil and climatic factors) via regulating biotic factors (leaf stoichiometry and leaf phenotypic traits).

Targeting PARG induces tumor cell growth inhibition and antitumor immune response by reducing phosphorylated STAT3 in ovarian cancer.

BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy, with limited treatment options after failure of standard therapies. Despite the potential of poly(ADP-ribose) polymerase inhibitors in treating DNA damage response (DDR)-deficient ovarian cancer, the development of resistance and immunosuppression limit their efficacy, necessitating alternative therapeutic strategies. Inhibitors of poly(ADP-ribose) glycohydrolase (PARG) represent a novel class of inhibitors that are currently being assessed in preclinical and clinical studies for cancer treatment. METHODS: By using a PARG small-molecule inhibitor, COH34, and a cell-penetrating antibody targeting the PARG's catalytic domain, we investigated the effects of PARG inhibition on signal transducer and activator of transcription 3 (STAT3) in OVCAR8, PEO1, and Brca1-null ID8 ovarian cancer cell lines, as well as in immune cells. We examined PARG inhibition-induced effects on STAT3 phosphorylation, nuclear localization, target gene expression, and antitumor immune responses in vitro, in patient-derived tumor organoids, and in an immunocompetent Brca1-null ID8 ovarian mouse tumor model that mirrors DDR-deficient human high-grade serous ovarian cancer. We also tested the effects of overexpressing a constitutively activated STAT3 mutant on COH34-induced tumor cell growth inhibition. RESULTS: Our findings show that PARG inhibition downregulates STAT3 activity through dephosphorylation in ovarian cancer cells. Importantly, overexpression of a constitutively activated STAT3 mutant in tumor cells attenuates PARG inhibitor-induced growth inhibition. Additionally, PARG inhibition reduces STAT3 phosphorylation in immune cells, leading to the activation of antitumor immune responses, shown in immune cells cocultured with ovarian cancer patient tumor-derived organoids and in immune-competent mice-bearing mouse ovarian tumors. CONCLUSIONS: We have identified a novel antitumor mechanism underlying PARG inhibition beyond its primary antitumor effects through blocking DDR in ovarian cancer. Furthermore, targeting PARG activates antitumor immune responses, thereby potentially increasing response rates to immunotherapy in patients with ovarian cancer.

Effects of Patient-Controlled Transcutaneous Electrical Acupoint Stimulation on Cancer Induced Bone Pain Relief in Patients with Non-Small Cell Lung Cancer: Study Protocol for a Randomized Controlled Trial.

Background: Transcutaneous Electrical Acupoint Stimulation (TEAS) therapy opens up the possibility for individuals with Cancer-induced bone pain (CIBP) to receive a home-based, patient-controlled approach to pain management. The aim of this study is designed to evaluate the efficacy of patient-controlled TEAS (PC-TEAS) for relieving CIBP in patients with non-small cell lung cancer (NSCLC). Methods/Design: This is a study protocol for a prospective, triple-blind, randomized controlled trial. We anticipate enrolling 188 participants with NSCLC bone metastases who are also using potent opioid analgesics from 4 Chinese medical centers. These participants will be randomly assigned in a 1:1 ratio to either the true PC-TEAS or the sham PC-TEAS group. All participants will receive standard adjuvant oncology therapy. The true group will undergo patient-controlled TEAS intervention as needed, while the sham group will follow the same treatment schedule but with non-conductive gel patches. Each treatment course will span 7 days, with a total of 4 courses administered. There will be 4 assessment time points: baseline, the conclusion of weeks 4, 8, and 12. The primary outcome of this investigation is the response rate of the average pain on the Brief Pain Inventory (BPI) scale at week 4 after treatment. Secondary outcomes include pain related indicators, quality of life scale, mood scales, and routine blood counts on the assessment days. Any adverse events will be promptly addressed and reported if they occur. We will manage trial data using the EDC platform, with a data monitoring committee providing regular quality oversight. Discussion: PC-TEAS interventions offer an attempt to achieve home-based acupuncture treatment and the feasibility of achieving triple blinding in acupuncture research. This study is designed to provide more rigorous trial evidence for the adjuvant treatment of cancer-related pain by acupuncture and to explore a safe and effective integrative medicine scheme for CIBP. Trial Registration: ClinicalTrials.gov NCT05730972, registered February 16, 2023.

Development and validation of prediction models for papillary thyroid cancer structural recurrence using machine learning approaches.

BACKGROUND: Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial. Thus, we investigated whether machine learning (ML) approaches based on comprehensive predictors can predict the risk of structural recurrence for PTC patients. METHODS: A total of 2244 patients treated with thyroid surgery and radioiodine were included. Twenty-nine perioperative variables consisting of four dimensions (demographic characteristics and comorbidities, tumor-related variables, lymph node (LN)-related variables, and metabolic and inflammatory markers) were analyzed. We applied five ML algorithms-logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), and neural network (NN)-to develop the models. The area under the receiver operating characteristic (AUC-ROC) curve, calibration curve, and variable importance were used to evaluate the models' performance. RESULTS: During a median follow-up of 45.5 months, 179 patients (8.0%) experienced structural recurrence. The non-stimulated thyroglobulin, LN dissection, number of LNs dissected, lymph node metastasis ratio, N stage, comorbidity of hypertension, comorbidity of diabetes, body mass index, and low-density lipoprotein were used to develop the models. All models showed a greater AUC (AUC = 0.738 to 0.767) than did the ATA risk stratification (AUC = 0.620, DeLong test: P < 0.01). The SVM, XGBoost, and RF model showed greater sensitivity (0.568, 0.595, 0.676), specificity (0.903, 0.857, 0.784), accuracy (0.875, 0.835, 0.775), positive predictive value (PPV) (0.344, 0.272, 0.219), negative predictive value (NPV) (0.959, 0.959, 0.964), and F1 score (0.429, 0.373, 0.331) than did the ATA risk stratification (sensitivity = 0.432, specificity = 0.770, accuracy = 0.742, PPV = 0.144, NPV = 0.938, F1 score = 0.216). The RF model had generally consistent calibration compared with the other models. The Tg and the LNR were the top 2 important variables in all the models, the N stage was the top 5 important variables in all the models. CONCLUSIONS: The RF model achieved the expected prediction performance with generally good discrimination, calibration and interpretability in this study. This study sheds light on the potential of ML approaches for improving the accuracy of risk stratification for PTC patients. TRIAL REGISTRATION: Retrospectively registered at www.chictr.org.cn (trial registration number: ChiCTR2300075574, date of registration: 2023-09-08).