Engineering Spatially Adjacent Redox Sites with Synergistic Spin Polarization Effect to Boost Photocatalytic CO2 Methanation.

The integration of oxidation and reduction half-reactions to amplify their synergy presents a considerable challenge in CO2 photoconversion. Addressing this challenge requires the construction of spatially adjacent redox sites while suppressing charge recombination at these sites. This study introduces an innovative approach that utilizes spatial synergy to enable synergistic redox reactions within atomic proximity and employs spin polarization to inhibit charge recombination. We incorporate Mn into Co3O4 as a catalyst, in which Mn sites tend to enrich holes as water activation sites, while adjacent Co sites preferentially capture electrons to activate CO2, forming a spatial synergy. The direct H transfer from H2O at Mn sites facilitates the formation of *COOH on adjacent Co sites with remarkably favorable thermodynamic energy. Notably, the incorporation of Mn induces spin polarization in the system, significantly suppressing the recombination of photogenerated charges at redox sites. This effect is further enhanced by applying an external magnetic field. By synergizing spatial synergy and spin polarization, Mn/Co3O4 exhibits a CH4 production rate of 23.4 µmol g-1 h-1 from CO2 photoreduction, showcasing a 28.8 times enhancement over Co3O4. This study first introduces spin polarization to address charge recombination issues at spatially adjacent redox sites, offering novel insights for synergistic redox photocatalytic systems.

Disentangling Thermal from Electronic Contributions in the Spectral Response of Photoexcited Perovskite Materials.

Disentangling electronic and thermal effects in photoexcited perovskite materials is crucial for photovoltaic and optoelectronic applications but remains a challenge due to their intertwined nature in both the time and energy domains. In this study, we employed temperature-dependent variable-angle spectroscopic ellipsometry, density functional theory calculations, and broadband transient absorption spectroscopy spanning the visible to mid-to-deep-ultraviolet (UV) ranges on MAPbBr3 thin films. The use of deep-UV detection opens a new spectral window that enables the exploration of high-energy excitations at various symmetry points within the Brillouin zone, facilitating an understanding of the ultrafast responses of the UV bands and the underlying mechanisms governing them. Our investigation reveals that the photoinduced spectral features remarkably resemble those generated by pure lattice heating, and we disentangle the relative thermal and electronic contributions and their evolutions at different delay times using combinations of decay-associated spectra and temperature-induced differential absorption. The results demonstrate that the photoinduced transients possess a significant thermal origin and cannot be attributed solely to electronic effects. Following photoexcitation, as carriers (electrons and holes) transfer their energy to the lattice, the thermal contribution increases from ∼15% at 1 ps to ∼55% at 500 ps and subsequently decreases to ∼35-50% at 1 ns. These findings elucidate the intricate energy exchange between charge carriers and the lattice in photoexcited perovskite materials and provide insights into the limited utilization efficiency of photogenerated charge carriers.

A Novel Inhibitor of Poly(ADP-Ribose) Polymerase-1 Inhibits Proliferation of a BRCA-Deficient Breast Cancer Cell Line via the DNA Damage-Activated cGAS-STING Pathway.

Loss-of-function mutations in the Breast Cancer Susceptibility Gene (BRCA1 and BRCA2) are often detected in patients with breast cancer. Poly(ADP-ribose) polymerase-1 (PARP1) plays a key role in the repair of DNA strand breaks, and PARP inhibitors have been shown to induce highly selective killing of BRCA1/2-deficient tumor cells, a mechanism termed synthetic lethality. In our previous study, a novel PARP1 inhibitor─(E)-2-(2,3-dibromo-4,5-dimethoxybenzylidene)-N-(4-fluorophenyl) hydrazine-1-carbothioamide (4F-DDC)─was synthesized, which significantly inhibited PARP1 activity with an IC50 value of 82 ± 9 nM. The current study aimed to explore the mechanism(s) underlying the antitumor activity of 4F-DDC under in vivo and in vitro conditions. 4F-DDC was found to selectively inhibit the proliferation of BRCA mutant cells, with highly potent effects on HCC-1937 (BRCA1-/-) cells. Furthermore, 4F-DDC was found to induce apoptosis and G2/M cell cycle arrest in HCC-1937 cells. Interestingly, immunofluorescence and Western blot results showed that 4F-DDC induced DNA double strand breaks and further activated the cGAS-STING pathway in HCC-1937 cells. In vivo analysis results revealed that 4F-DDC inhibited the growth of HCC-1937-derived tumor xenografts, possibly via the induction of DNA damage and activation of the cGAS-STING pathway. In summary, the current study provides a new perspective on the antitumor mechanism of PARP inhibitors and showcases the therapeutic potential of 4F-DDC in the treatment of breast cancer.

Personalized prediction for multiple chronic diseases by developing the multi-task Cox learning model.

Personalized prediction of chronic diseases is crucial for reducing the disease burden. However, previous studies on chronic diseases have not adequately considered the relationship between chronic diseases. To explore the patient-wise risk of multiple chronic diseases, we developed a multitask learning Cox (MTL-Cox) model for personalized prediction of nine typical chronic diseases on the UK Biobank dataset. MTL-Cox employs a multitask learning framework to train semiparametric multivariable Cox models. To comprehensively estimate the performance of the MTL-Cox model, we measured it via five commonly used survival analysis metrics: concordance index, area under the curve (AUC), specificity, sensitivity, and Youden index. In addition, we verified the validity of the MTL-Cox model framework in the Weihai physical examination dataset, from Shandong province, China. The MTL-Cox model achieved a statistically significant (p<0.05) improvement in results compared with competing methods in the evaluation metrics of the concordance index, AUC, sensitivity, and Youden index using the paired-sample Wilcoxon signed-rank test. In particular, the MTL-Cox model improved prediction accuracy by up to 12% compared to other models. We also applied the MTL-Cox model to rank the absolute risk of nine chronic diseases in patients on the UK Biobank dataset. This was the first known study to use the multitask learning-based Cox model to predict the personalized risk of the nine chronic diseases. The study can contribute to early screening, personalized risk ranking, and diagnosing of chronic diseases.

DDX24 Is Essential for Cell Cycle Regulation in Vascular Smooth Muscle Cells During Vascular Development via Binding to FANCA mRNA.

BACKGROUND: The DEAD-box family is essential for tumorigenesis and embryogenesis. Previously, we linked the malfunction of DDX (DEAD-box RNA helicase)-24 to a special type of vascular malformation. Here, we aim to investigate the function of DDX24 in vascular smooth muscle cells (VSMCs) and embryonic vascular development. METHODS: Cardiomyocyte (CMC) and VSMC-specific Ddx24 knockout mice were generated by crossing Tagln-Cre mice with Ddx24flox/flox transgenic mice. The development of blood vessels was explored by stereomicroscope photography and immunofluorescence staining. Flow cytometry and cell proliferation assays were used to verify the regulation of DDX24 on the function of VSMCs. RNA sequencing and RNA immunoprecipitation coupled with quantitative real-time polymerase chain reaction were combined to investigate DDX24 downstream regulatory molecules. RNA pull-down and RNA stability experiments were performed to explore the regulation mechanism of DDX24. RESULTS: CMC/VSMC-specific Ddx24 knockout mice died before embryonic day 13.5 with defects in vessel formation and abnormal vascular remodeling in extraembryonic tissues. Ddx24 knockdown suppressed VSMC proliferation via cell cycle arrest, likely due to increased DNA damage. DDX24 protein bound to and stabilized the mRNA of FANCA (FA complementation group A) that responded to DNA damage. Consistent with the function of DDX24, depletion of FANCA also impacted cell cycle and DNA repair of VSMCs. Overexpression of FANCA was able to rescue the alterations caused by DDX24 deficiency. CONCLUSIONS: Our study unveiled a critical role of DDX24 in VSMC-mediated vascular development, highlighting a potential therapeutic target for VSMC-related pathological conditions.

Predicting lung cancer survival prognosis based on the conditional survival bayesian network.

Lung cancer is a leading cause of cancer deaths and imposes an enormous economic burden on patients. It is important to develop an accurate risk assessment model to determine the appropriate treatment for patients after an initial lung cancer diagnosis. The Cox proportional hazards model is mainly employed in survival analysis. However, real-world medical data are usually incomplete, posing a great challenge to the application of this model. Commonly used imputation methods cannot achieve sufficient accuracy when data are missing, so we investigated novel methods for the development of clinical prediction models. In this article, we present a novel model for survival prediction in missing scenarios. We collected data from 5,240 patients diagnosed with lung cancer at the Weihai Municipal Hospital, China. Then, we applied a joint model that combined a BN and a Cox model to predict mortality risk in individual patients with lung cancer. The established prognostic model achieved good predictive performance in discrimination and calibration. We showed that combining the BN with the Cox proportional hazards model is highly beneficial and provides a more efficient tool for risk prediction.

High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies.

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 µg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Successful ECMO treatment in patients with cerebral hemorrhage and PROC gene mutation associated with VTE: a case report.

In this report, we report a case of a middle-aged male, admitted to the ICU with cerebral hemorrhage resulting from a severe high-altitude fall. The patient encountered significant challenges in oxygenation index correction, attributed to extensive embolism in both the primary and branch pulmonary arteries. Consequently, the patient underwent an immediate initiation of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) therapy, persisting for 20 days. During this treatment period, a mutation in the protein C (PROC) gene was identified. The medical team meticulously navigated the delicate balance between anticoagulation and bleeding risks. Eventually, the patient was successfully weaned off VA-ECMO and subsequently discharged. This report aims to delve into the etiology and therapeutic approaches of this uncommon case, with the intention of offering insightful reference for managing similar clinical scenarios in the future.

Clinical practice guidelines for the nutrition of colorectal cancer patients: a systematic review.

PURPOSE: The aim of this study is to rigorously assess the methodological quality of published clinical practice guidelines (CPGs) related to nutrition among colorectal cancer patients, to compile consensus recommendations, and to evaluate the quality of the included CPGs. METHODS: The systematic search covered eight electronic databases, two relevant professional association websites, and six guideline websites from their inception up to January 22, 2023. The methodological quality of the eligible guidelines was evaluated using the Appraisal of Guidelines Research and Evaluation II (AGREE II) instrument, and then, consensus recommendations were synthesized. The scores for each domain were expressed as the mean ± standard deviation (SD). Using the mean score as the benchmark for comparison, they were subsequently ranked from highest to lowest. The included guidelines were then categorized as having "high," "moderate," or "low" quality based on their scores. RESULTS: The literature search yielded ten guidelines. The findings indicated that the "Clarity of presentation" domain had the highest mean score (65.2 ± 7.7). This demonstrates how the guidelines effectively articulate recommendations. Additionally, the "Scope and purpose" domain achieved a mean score of 60.7 ± 10.9, followed by "Rigor of development" (51.7 ± 15.7), "Editorial independence" (51.1 ± 21), "Stakeholder involvement" (48 ± 16.8), and "Applicability" domains (47.5 ± 17.3). Two CPGs received an overall rating of "high quality" and were recommended; four CPGs received an overall rating of "moderate" and were recommended with modifications; and four CPGs received an overall rating of "low quality" and were not recommended. Furthermore, this study compiled twenty consensus recommendations related to nine distinct clinical issues. CONCLUSION: This study identified disparities in the methodological quality of the included CPGs, particularly in the "Applicability" domain, thus emphasizing the need for advancement in clinical feasibility and implementation. Notably, there is few guidelines specifically targeting colorectal cancer nutrition. These synthesized findings provided an intuitive, convenient, and comprehensive reference for evaluating nutrition among colorectal cancer patients. When applying these results, users should make careful decisions based on their specific situations.

The association between PM2.5 components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models.

BACKGROUND: PM2.5 is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develop an analytical methodology combining traditional and novel machine learning models to evaluate PM2.5's combined effects on blood pressure (BP) and identify the most toxic components. METHODS: We measured late-pregnancy BP of 1138 women from the Heshan cohort while simultaneously analyzing 31 PM2.5 components. We utilized multiple linear regression modeling to establish the relationship between PM2.5 components and late-pregnancy BP and applied Random Forest (RF) and generalized Weighted Quantile Sum (gWQS) regression to identify the most toxic components contributing to elevated BP and to quantitatively evaluate the cumulative effect of the PM2.5 component mixtures. RESULTS: The results revealed that 16 PM2.5 components, such as EC, OC, Ti, Fe, Mn, Cu, Cd, Mg, K, Pb, Se, Na+, K+, Cl-, NO3-, and F-, contributed to elevated systolic blood pressure (SBP), while 26 components, including two carbon components (EC, OC), fourteen metallics (Ti, Fe, Mn, Cr, Mo, Co, Cu, Zn, Cd, Na, Mg, Al, K, Pb), one metalloid (Se), and nine water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO42-, F-), contributed to elevated diastolic blood pressure (DBP). Mn and Cr were the most toxic components for elevated SBP and DBP, respectively, as analyzed by RF and gWQS models and verified against each other. Exposure to PM2.5 component mixtures increased SBP by 1.04 mmHg (95% CI: 0.33-1.76) and DBP by 1.13 mmHg (95% CI: 0.47-1.78). CONCLUSIONS: Our study highlights the effectiveness of combining traditional and novel models as an analytical strategy to quantify the health effects of PM2.5 constituent mixtures.

A chemically inducible IL-2 receptor signaling complex allows for effective in vitro and in vivo selection of engineered CD4+ T cells.

Engineered T cells represent an emerging therapeutic modality. However, complex engineering strategies can present a challenge for enriching and expanding therapeutic cells at clinical scale. In addition, lack of in vivo cytokine support can lead to poor engraftment of transferred T cells, including regulatory T cells (Treg). Here, we establish a cell-intrinsic selection system that leverages the dependency of primary T cells on IL-2 signaling. FRB-IL2RB and FKBP-IL2RG fusion proteins were identified permitting selective expansion of primary CD4+ T cells in rapamycin supplemented medium. This chemically inducible signaling complex (CISC) was subsequently incorporated into HDR donor templates designed to drive expression of the Treg master regulator FOXP3. Following editing of CD4+ T cells, CISC+ engineered Treg (CISC EngTreg) were selectively expanded using rapamycin and maintained Treg activity. Following transfer into immunodeficient mice treated with rapamycin, CISC EngTreg exhibited sustained engraftment in the absence of IL-2. Furthermore, in vivo CISC engagement increased the therapeutic activity of CISC EngTreg. Finally, an editing strategy targeting the TRAC locus permitted generation and selective enrichment of CISC+ functional CD19-CAR-T cells. Together, CISC provides a robust platform to achieve both in vitro enrichment and in vivo engraftment and activation, features likely beneficial across multiple gene-edited T cell applications.

The Response of Growth and Transcriptome Profiles of Tea Grey Blight Disease Pathogen Pestalotiopsis theae to the Variation of Exogenous L-Theanine.

Tea grey blight disease is one of the most destructive diseases that infects tea and is caused by the pathogen Pestalotiopsis theae (Sawada) Steyaert. L-theanine is a unique non-protein amino acid of the tea plant. Different concentrations of L-theanine exhibit significant inhibitory effects on the growth and sporulation ability of the pathogen causing tea grey blight disease. To understand the effect mechanism of L-theanine on P. theae, transcriptome profiling was performed on the pathogenic mycelium treated with three different concentrations of L-theanine: no L-theanine treatment (TH0), 20 mg/mL theanine treatment (TH2), and 40 mg/mL theanine treatment (TH4). The colony growths were significantly lower in the treatment with L-theanine than those without L-theanine. The strain cultured with a high concentration of L-theanine produced no spores or only a few spores. In total, 2344, 3263, and 1158 differentially expressed genes (DEGs) were detected by RNA-sequencing in the three comparisons, Th2 vs. Th0, Th4 vs. Th0, and Th4 vs. Th2, respectively. All DEGs were categorized into 24 distinct clusters. According to GO analysis, low concentrations of L-theanine primarily affected molecular functions, while high concentrations of L-theanine predominantly affected biological processes including external encapsulating structure organization, cell wall organization or biogenesis, and cellular amino acid metabolic process. Based on KEGG, the DEGs of Th2 vs. Th0 were primarily involved in pentose and glucuronate interconversions, histidine metabolism, and tryptophan metabolism. The DEGs of Th4 vs. Th0 were mainly involved in starch and sucrose metabolism, amino sugar, and nucleotide sugar metabolism. This study indicated that L-theanine has a significant impact on the growth and sporulation of the pathogen of tea grey blight disease and mainly affects amino acid metabolism, carbohydrate metabolism, and cellular structure-related biosynthesis processes of pathogenic fungi. This work provides insights into the direct control effect of L-theanine on pathogenic growth and also reveals the molecular mechanisms of inhibition of L-theanine to P. theae.

Gut mycobiome as a potential non-invasive tool in early detection of lung adenocarcinoma: a cross-sectional study.

BACKGROUND: The gut mycobiome of patients with lung adenocarcinoma (LUAD) remains unexplored. This study aimed to characterize the gut mycobiome in patients with LUAD and evaluate the potential of gut fungi as non-invasive biomarkers for early diagnosis. METHODS: In total, 299 fecal samples from Beijing, Suzhou, and Hainan were collected prospectively. Using internal transcribed spacer 2 sequencing, we profiled the gut mycobiome. Five supervised machine learning algorithms were trained on fungal signatures to build an optimized prediction model for LUAD in a discovery cohort comprising 105 patients with LUAD and 61 healthy controls (HCs) from Beijing. Validation cohorts from Beijing, Suzhou, and Hainan comprising 44, 17, and 15 patients with LUAD and 26, 19, and 12 HCs, respectively, were used to evaluate efficacy. RESULTS: Fungal biodiversity and richness increased in patients with LUAD. At the phylum level, the abundance of Ascomycota decreased, while that of Basidiomycota increased in patients with LUAD. Candida and Saccharomyces were the dominant genera, with a reduction in Candida and an increase in Saccharomyces, Aspergillus, and Apiotrichum in patients with LUAD. Nineteen operational taxonomic unit markers were selected, and excellent performance in predicting LUAD was achieved (area under the curve (AUC) = 0.9350) using a random forest model with outcomes superior to those of four other algorithms. The AUCs of the Beijing, Suzhou, and Hainan validation cohorts were 0.9538, 0.9628, and 0.8833, respectively. CONCLUSIONS: For the first time, the gut fungal profiles of patients with LUAD were shown to represent potential non-invasive biomarkers for early-stage diagnosis.

Prediction model for hyperprogressive disease in patients with advanced solid tumors received immune-checkpoint inhibitors: a pan-cancer study.

BACKGROUND: Hyper progressive disease (HPD) describes the phenomenon that patients can't benefit from immunotherapy but cause rapid tumor progression. HPD is a particular phenomenon in immunotherapy but lacks prediction methods. Our study aims to screen the factors that may forecast HPD and provide a predictive model for risky stratifying. METHODS: We retrospectively reviewed advanced-stage tumor patients who received immune checkpoint inhibitors (ICI) in the General PLA Hospital. Subsequently, we calculated the tumor growth kinetics ratio (TGKr) and identified typical HPD patients. Differences analysis of clinical characteristics was performed, and a predictive binary classification model was constructed. RESULTS: 867 patients with complete image information were screened from more than 3000 patients who received ICI between January 2015 and January 2020. Among them, 36 patients were identified as HPD for TGKr > 2. After the propensity score matched, confounding factors were limited. Survival analysis revealed that the clinical outcome of HPD patients was significantly worse than non-HPD patients. Besides, we found that Body Mass Index (BMI), anemia, lymph node metastasis in non-draining areas, pancreatic metastasis, and whether combined with anti-angiogenesis or chemotherapy therapy were closely connected with the HPD incidence. Based on these risk factors, we constructed a visualised predicted nomogram model, and the Area Under Curve (AUC) is 0.850 in the train dataset, whereas 0.812 in the test dataset. CONCLUSION: We carried out a retrospective study for HPD based on real-world patients and constructed a clinically feasible and practical model for predicting HPD incidence, which could help oncologists to stratify risky patients and select treatment strategies.

Gut mycobiome and metabolic diseases: The known, the unknown, and the future.

Metabolic diseases, such as type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD) and obesity, have become a major public health problem worldwide. In recent years, most research on the role of gut microbes in metabolic diseases has focused on bacteria, whereas fungal microbes have been neglected. This review aims to provide a comprehensive overview of gut fungal alterations in T2DM, obesity, and NAFLD, and to discuss the mechanisms associated with disease development. In addition, several novel strategies targeting gut mycobiome and/or their metabolites to improve T2DM, obesity and NAFLD, including fungal probiotics, antifungal drugs, dietary intervention, and fecal microbiota transplantation, are critically discussed. The accumulated evidence suggests that gut mycobiome plays an important role in the occurrence and development of metabolic diseases. The possible mechanisms by which the gut mycobiome affects metabolic diseases include fungal-induced immune responses, fungal-bacterial interactions, and fungal-derived metabolites. Candida albicans, Aspergillus and Meyerozyma may be potential pathogens of metabolic diseases because they can activate the immune system and/or produce harmful metabolites. Moreover, Saccharomyces boulardii, S. cerevisiae, Alternaria, and Cochliobolus fungi may have the potential to improve metabolic diseases. The information may provide an important reference for the development of new therapeutics for metabolic diseases based on gut mycobiome.

Speckle-tracking echocardiography provides sensitive measurements of subtle early alterations associated with cardiac dysfunction in T2DM rats.

BACKGROUND: Diabetic cardiomyopathy results in cardiac structural and functional abnormalities. Previous studies have demonstrated that inhibiting the RhoA/ROCK signalling pathway increases the injury resistance of cardiomyocytes. The early detection of cardiac structural and functional alterations may facilitate an improved understanding of the pathophysiologic progress and guide therapy. This study aimed to identify the optimal diagnostic measures for the subtle early alterations of cardiac dysfunction in type 2 diabetes mellitus (T2DM) rats. METHODS: Twenty-four rat models were divided into four groups and received treatments for 4 weeks: the CON group (control rats), the DM group (T2DM rats), the DMF group (T2DM rats receiving fasudil) and the CONF group (control rats receiving fasudil) group. Left ventricular (LV) structure was quantified by histological staining and transmission electron microscopy. LV function and myocardial deformation were assessed by high-frequency echocardiography. RESULTS: Treatment with fasudil, a ROCK inhibitor, significantly protected against diabetes-induced myocardial hypertrophy, fibrosis and mitochondrial dysfunction. Impaired LV performance was found in T2DM rats, as evidenced by significant reductions in the ejection fraction (EF), fractional shortening (FS) and the mitral valve (MV) E/A ratio (which decreased 26%, 34% and 20%, respectively). Fasudil failed to improve the conventional ultrasonic parameters in T2DM rats, but the myocardial deformation measured by speckle-tracking echocardiography (STE) were significantly improved (global circumferential strain, GCS: P = 0.003; GCS rate, GCSR: P = 0.021). When receiver operating characteristic (ROC) curves were used in combination with linear regression analysis, STE parameters were found to be characterized by both optimal prediction of cardiac damage [AUC (95% CI): fractional area change, FAC: 0.927 (0.744, 0.993); GCS: 0.819 (0.610, 0.945); GCSR: 0.899 (0.707, 0.984)] and stronger correlations with cardiac fibrosis (FAC: r = -0.825; GCS: r = 0.772; GCSR: r = 0.829) than conventional parameters. CONCLUSION: The results suggest that STE parameters are more sensitive and specific than conventional parameters in predicting the subtle cardiac functional changes that occur in the early stage, providing new insight into the management of diabetic cardiomyopathy.

Pralsetinib-associated pneumonia in RET fusion-positive non-small cell lung cancer.

OBJECTIVE: Oncogenic alternation in RET is one of the important targets of non-small cell lung cancer (NSCLC). Pralsetinib has shown great efficacy in RET fusion-positive NSCLC, but a series of adverse reactions will inevitably occur in the meantime. We aimed to explore the clinical characteristics of patients with pneumonia and recognition it in early stage, so patients could longer benefit from pralsetinib. METHODS: This is a multicenter, retrospective study. RET fusion-positive advanced NSCLC patients who developed pneumonia during pralsetinib treatment from January 2020 to December 2022 were included. Clinical data, time to onset of pneumonia, methods of pneumonia diagnosis, treatment with pneumonia, prognosis of pneumonia, and the effect of pneumonia on the efficacy of pralsetinib. RESULTS: A total of 8 patients with pneumonia were included in the study, most of which were non-smoking female patients and the main fusion gene was KIF5B (87.5%), which was consistent with the general characteristics of RET fusion population. The median occurrence time of pralsetinib-associated pneumonia was 2.15 (range 1.1-6.63) months. All patients were infected by opportunistic pathogens, and the most common pathogen was human herpesviruses and pneumospora yerbii. Fever was always the first symptom, and timely anti-infective treatment including antibiotics, antiviral drugs, and antifungal drugs was effective. Until February 28, 2023, the median follow-up time was 18.7 months, the mean PFS of patients was 17.4 months, and the median PFS was not reached. Fortunately, patients who restarted pralsetinib after infection control continued to benefit. CONCLUSIONS: Opportunistic infection may be a unique adverse effect of pralsetinib. During the treatment of pralsetinib, we should be vigilant about the occurrence of pneumonia and achieve early recognition and timely treatment.

Association between depression and dysmenorrhea among adolescent girls: multiple mediating effects of binge eating and sleep quality.

BACKGROUND: Dysmenorrhea has a significant negative impact on teenagers' quality of life, and its prevalence is increasing annually. Although studies have explored the factors affecting dysmenorrhea, it remains unclear how these factors interact with one another. This study aimed to explore the mediating role of binge eating and sleep quality between depression and dysmenorrhea. METHODS: This cross-sectional study recruited adolescent girls from the Health Status Survey of adolescents in Jinan, Shandong Province, and used multistage stratified cluster random sampling. Data was collected using an electronic questionnaire between March 9, 2022, and June 20, 2022. The Numerical Rating Scale and Cox Menstrual Symptom Scale were used to assess dysmenorrhea and the Patient Health Questionnaire-9 to assess depression. The mediation model was tested by Mplus 8.0, and the mediating effect was analyzed using the Product of Coefficients approach and the Bootstrap method. RESULTS: Among the total of 7818 adolescent girls included in this study, the prevalence of dysmenorrhea is 60.5%. A significant positive association was found between dysmenorrhea and depression. Binge eating and sleep quality seemingly mediate this association. The mediating effect of sleep quality (21.31%) was greater than that of binge eating (6.18%). CONCLUSIONS: The findings of this study point in the right direction for preventing and treating dysmenorrhea in adolescents. For adolescent dysmenorrhea, mental health should be considered and proactive steps taken for educating adolescents on healthy lifestyles to reduce negative consequences of dysmenorrhea. Longitudinal studies on the causal link and influence mechanisms between depression and dysmenorrhea should be conducted in the future.

Factors for incidence risk and prognosis of synchronous brain metastases in pulmonary large cell carcinoma patients: a population-based study.

BACKGROUND: Patients with pulmonary large cell carcinoma (LCC) have a high incidence of synchronous brain metastases (SBM) and a poor prognosis. Our study was to evaluate the predictive and prognostic value of the clinical characteristics of pulmonary LCC patients with SBM at initial diagnosis by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: LCC patients, diagnosed from 2010 to 2019, were identified from the latest SEER database which was released in April 2022. Logistic regression and Cox regression were used to identify the predictive and prognostic factors for LCC patients with SBM. Propensity score matching (PSM) and Kaplan-Meier analyses were applied to assess different therapy modalities. RESULTS: A total of 1375 LCC patients were enrolled in this study and 216 (15.7%) of them had SBM at the initial diagnosis. The median overall survival (OS) of LCC patients with SBM was 4 months. Multivariate Cox regression identified age 60-79 (OR 0.57; 95% CI 0.41-0.78; p < 0.001), age ≥ 80 (OR 0.23; 95% CI 0.12-0.45; p < 0.001) and bone metastases (OR 1.75; 95% CI 1.22-2.51; p < 0.001) as significant independent predictors for developing SBM. Multivariable Cox regression revealed that age 60-79, T stage, bone metastases and chemotherapy were independent prognostic factor for OS. The surgery combined with chemotherapy and radiotherapy group, in which all patients were N0 stage and had no other site-specific metastases, exhibited the best median OS of 15 months. CONCLUSIONS: LCC patients with age < 60 or bone metastases were more likely to have SBM at initial diagnosis. Age, T stage, bone metastases and chemotherapy were independent prognostic factors for OS of LCC patients with SBM. Highly selected patients might achieve the best survival benefit from surgery combined with chemotherapy and radiotherapy.

The Role of Macrophage Autophagy in Asthma: A Novel Therapeutic Strategy.

Asthma is a chronic respiratory disease frequently associated with airway inflammation and remodeling. The development of asthma involves various inflammatory phenotypes that impact therapeutic effects, and macrophages are master innate immune cells in the airway that exert diverse functions including phagocytosis, antigen presentation, and pathogen clearance, playing an important role in the pathogeneses of asthma. Recent studies have indicated that autophagy of macrophages affects polarization of phenotype and regulation of inflammation, which implies that regulating autophagy of macrophages may be a potential strategy for the treatment of asthma. Thus, this review summarizes the signaling pathways and effects of macrophage autophagy in asthma, which will provide a tactic for the development of novel targets for the treatment of this disease.