Spexin ameliorated obesity-related metabolic disorders through promoting white adipose browning mediated by JAK2-STAT3 pathway.

BACKGROUND: Spexin, a 14 amino acid peptide, has been reported to regulate obesity and its associated complications. However, little is known about the underlying molecular mechanism. Therefore, this study aimed to investigate the effects of spexin on obesity and explore the detailed molecular mechanisms in vivo and in vitro. METHODS: Male C57BL/6J mice were fed a high-fat diet (HFD) for 12 weeks to induce obesity, and mice fed a standard fat diet were used as controls. Then, these mice were treated with SPX or Vehicle by intraperitoneal injection for an additional 12 weeks, respectively. The metabolic profile, fat-browning specific markers and mitochondrial contents were detected. In vitro, 3T3-L1 cells were used to investigate the molecular mechanisms. RESULTS: After 12 weeks of treatment, SPX significantly decreased body weight, serum lipid levels, and improved insulin sensitivity in HFD-induced obese mice. Moreover, SPX was found to promote oxygen consumption in HFD mice, and it increased mitochondrial content as well as the expression of brown-specific markers in white adipose tissue (WAT) of HFD mice. These results were consistent with the increase in mitochondrial content and the expression of brown-specific markers in 3T3-L1 mature adipocytes. Of note, the spexin-mediated beneficial pro-browning actions were abolished by the JAK2/STAT3 pathway antagonists in mature 3T3-L1 cells. CONCLUSIONS: These data indicate that spexin ameliorates obesity-induced metabolic disorders by improving WAT browning via activation of the JAK2/STAT3 signaling pathway. Therefore, SPX may serve as a new therapeutic candidate for treating obesity.

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review.

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Altered functional-structural coupling may predict Parkinson's patient's depression.

We aimed to elucidate the neurobiological basis of depression in Parkinson's disease and identify potential imaging markers for depression in patients with Parkinson's disease. We recruited 43 normal controls (NC), 46 depressed Parkinson's disease patients (DPD) and 56 non-depressed Parkinson's disease (NDPD). All participants underwent routine T2-weighted, T2Flair, and resting-state scans on the same 3.0 T magnetic resonance imaging (MRI) scanner at our hospital. Pre-processing includes calculating surface-based Regional Homogeneity (2DReHo) and cortical thickness. Then we defined the correlation coefficient between 2DReHo and cortical thickness as the functional-structural coupling index. Between-group comparisons were conducted on the Fisher's Z-transformed correlation coefficients. To identify specific regions of decoupling, the 2DReHo for each participant were divided by cortical thickness at each vertex, followed by threshold-free cluster enhancement (TFCE) multiple comparison correction. Binary logistic regression analysis was performed with DPD as the dependent variable, and significantly altered indicators as the independent variables. Receiver operating characteristic curves were constructed to compare the diagnostic performance of individual predictors and combinations using R and MedCalc software. DPD patients exhibited a significantly lower whole-brain functional-structural coupling index than NDPD patients and NC. Abnormal functional-structural coupling was primarily observed in the left inferior parietal lobule and right primary and early visual cortices in DPD patients. Receiver operating characteristic analysis revealed that the combination of cortical functional-structural coupling, surface-based ReHo, and thickness had the best diagnostic performance, achieving a sensitivity of 65% and specificity of 77.7%. This is the first study to explore the relationship between functional and structural changes in DPD patients and evaluate the diagnostic performance of these altered correlations to predict depression in Parkinson's disease patients. We posit that these changes in functional-structural relationships may serve as imaging biomarkers for depression in Parkinson's disease patients, potentially aiding in the classification and diagnosis of Parkinson's disease. Additionally, our findings provide functional and structural imaging evidence for exploring the neurobiological basis of depression in Parkinson's disease.

Wearable 12-Lead ECG Acquisition Using a Novel Deep Learning Approach from Frank or EASI Leads with Clinical Validation.

The 12-lead electrocardiogram (ECG) is crucial in assessing patient decisions. However, portable ECG devices capable of acquiring a complete 12-lead ECG are scarce. For the first time, a deep learning-based method is proposed to reconstruct the 12-lead ECG from Frank leads (VX, VY, and VZ) or EASI leads (VES, VAS, and VAI). The innovative ECG reconstruction network called M2Eformer is composed of a 2D-ECGblock and a ProbDecoder module. The 2D-ECGblock module adaptively segments EASI leads into multi-periods based on frequency energy, transforming the 1D time series into a 2D tensor representing within-cycle and between-cycle variations. The ProbDecoder module aims to extract Probsparse self-attention and achieve one-step output for the target leads. Experimental results from comparing recorded and reconstructed 12-lead ECG using Frank leads indicate that M2Eformer outperforms traditional ECG reconstruction methods on a public database. In this study, a self-constructed database (10 healthy individuals + 15 patients) was utilized for the clinical diagnostic validation of ECG reconstructed from EASI leads. Subsequently, both the ECG reconstructed using EASI and the recorded 12-lead ECG were subjected to a double-blind diagnostic experiment conducted by three cardiologists. The overall diagnostic consensus among three cardiology experts, reaching a rate of 96%, indicates the significant utility of EASI-reconstructed 12-lead ECG in facilitating the diagnosis of cardiac conditions.

Machine learning for the early prediction of acute respiratory distress syndrome (ARDS) in patients with sepsis in the ICU based on clinical data.

Background: Acute respiratory distress syndrome (ARDS) is a fatal outcome of severe sepsis. Machine learning models are helpful for accurately predicting ARDS in patients with sepsis at an early stage. Objective: We aim to develop a machine-learning model for predicting ARDS in patients with sepsis in the intensive care unit (ICU). Methods: The initial clinical data of patients with sepsis admitted to the hospital (including population characteristics, clinical diagnosis, complications, and laboratory tests) were used to predict ARDS, and screen out the crucial variables. After comparing eight different algorithms, namely, XG boost, logistic regression, light GBM, random forest, GaussianNB, complement NB, support vector machine (SVM), and K nearest neighbors (KNN), rebuilding a prediction model with the best one. When remodeling with the best algorithm, 10% was randomly selected to test, and the remaining was trained for cross-validation. Using the area under the curve (AUC), sensitivity, accuracy, specificity, positive and negative predictive value, F1 score, kappa value, and clinical decision curve to evaluate the model's performance. Eventually, the application in the model illustrated by the SHAP package. Results: Ten critical features were screened utilizing the lasso method, namely, PaO2/PAO2, A-aDO2, PO2(T), CRP, gender, PO2, RDW, MCH, SG, and chlorine. The prior ranking of variables demonstrated that PaO2/PAO2 was the most significant variable. Among the eight algorithms, the performance of the Gaussian NB algorithm was significantly better than that of the others. After remodeling with the best algorithm, the AUC in the training and validation sets were 0.777 and 0.770, respectively, and the algorithm performed well in the test set (AUC = 0.781, accuracy = 78.6%, sensitivity = 82.4%, F1 score = 0.824). A comparison of the overlap factors with those of previous models revealed that the model we developed performs better. Conclusion: Sepsis-associated ARDS can be accurately predicted early via a machine learning model based on existing clinical data. These findings are helpful for accurate identification and improvement of the prognosis in patients with sepsis-associated ARDS.

impHFrEF trial: study protocol for an open-label, multicentre study of improvement the outcome of patients with heart failure in China using a mobile hEalth-supported platForm.

BACKGROUND: Patients with chronic heart failure (CHF) often have a long duration of illness, difficulty in attending follow-up visits, and poor adherence to treatment. As a result, they frequently cannot receive guideline-directed medical therapy (GDMT) at the desired or maximum tolerable drug dosage. This leads to high hospitalisation and mortality rates for HF patients. Therefore, effective management and monitoring of patients with HF to ensure they receive GDMT is crucial for improving the prognosis. DESIGN AND METHODS: This is a multicentre, open-label, randomised, parallel-group study involving patients with CHF across five centres. The study aims to assess the impact of an optimised GDMT model for HF patients, established on a mobile health (mHealth) platform, compared with a control group. Patients must have a left ventricular ejection fraction of less than 50% and be receiving medication titration therapy that has not yet reached the target dose, with a modest increase in N-terminal pro-B-type natriuretic peptide level. The primary composite outcome is worsening HF events (hospitalisation or emergency treatment with intravenous fluids) or cardiovascular death. ETHICS AND DISSEMINATION: On 22 December 2021, this study received ethical approval from the Ethics Review Board of the First Affiliated Hospital of Nanjing Medical University, with the ethics number 2021-SR-530. All study participants will be informed of the research purpose and their participation will be voluntary. Informed consent will be obtained by providing and signing an informed consent form. We will ensure compliance with relevant laws and regulations regarding privacy and data protection. The results of this study will be published in a peer-reviewed academic journal. We will ensure that the dissemination of study results is accurate, clear and timely. TRIAL REGISTRATION NUMBER: ChiCTR2200056527.

Alterations in cortical volume and complexity in Parkinson's disease with depression.

AIMS: The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients. METHODS: A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel-based morphometry (VBM) and surface-based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one-way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale-17 (HAMD-17) scores. RESULTS: PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal-occipital-temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD-17 scores in the PDD group tended to be significant (r = -0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth. CONCLUSION: Our research shows extensive cortical structural changes in the insular cortex, parietal-occipital-temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease.

Role of micronucleus-activated cGAS-STING signaling in antitumor immunity. / å¾®æ ¸æ¿€æ´»cGAS-STINGä¿¡å·é€šè·¯çš„æœºåˆ¶åŠå ¶è‚¿ç˜¤å ç–«åŠŸèƒ½.

Cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) signaling is a significant component of the innate immune system and functions as a vital sentinel mechanism to monitor cellular and tissue aberrations in microbial invasion and organ injury. cGAS, a cytosolic DNA sensor, is specialized in recognizing abnormally localized cytoplasmic double-stranded DNA (dsDNA) and catalyzes the formation of a second messenger cyclic-GMP-AMP (cGAMP), which initiates a cascade of type Ⅰ interferon and inflammatory responses mediated by STING. Micronucleus, a byproduct of chromosomal missegregation during anaphase, is also a significant contributor to cytoplasmic dsDNA. These unstable subcellular structures are susceptible to irreversible nuclear envelope rupture, exposing genomic dsDNA to the cytoplasm, which potently recruits cGAS and activates STING-mediated innate immune signaling and its downstream activities, including type Ⅰ interferon and classical nuclear factor-κB (NF-κB) signaling pathways lead to senescence, apoptosis, autophagy activating anti-cancer immunity or directly killing tumor cells. However, sustained STING activation-induced endoplasmic reticulum stress, activated chronic type Ⅰ interferon and nonclassical NF-κB signaling pathways remodel immunosuppressive tumor microenvironment, leading to immune evasion and facilitating tumor metastasis. Therefore, activated cGAS-STING signaling plays a dual role of suppressing or facilitating tumor growth in tumorigenesis and therapy. This review elaborates on research advances in mechanisms of micronucleus inducing activation of cGAS-STING signaling and its implications in tumorigenesis and therapeutic strategies of malignant tumors.

Deletion of cis-regulatory Element in FOXL2 Promoter in a Chinese Family of Type II Blepharophimosis-ptosis-epicanthus Inversus Syndrome with Polydactyly.

Blepharophimosis-ptosis-epicanthus inversus syndrome (BPES) is a relatively uncommon autosomal-dominant genetic disorder, primarily attributed to mutations in the forkhead box L2 (FOXL2) gene. Albeit the involvement of protein-coding regions of FOXL2 has been observed in the majority of BPES cases, whether deficiencies in regulatory elements lead to the pathogenesis remains poorly understood. Herein, an autosomal-dominant BPES type II family was included. Peripheral venous blood has been collected, and genomic DNA has been extracted from leukocytes. A whole exome sequencing analysis has been performed and analyzed (Deposited in NODE database: OER422653). The promoter region of FOXL2 was amplified using polymerase chain reaction (PCR). The luciferase reporter assay was performed to identify the activity of this region. In this study, we present a Chinese family diagnosed with type II BPES, characterized by the presence of small palpebral fissures, ptosis, telecanthus, and epicanthus inversus. Notably, all male individuals within the family display polydactyly. A 225-bp deletion in the 556-bp 5'-upstream to transcription start site of FOXL2 , decorated by multiple histone modifications, was identified in affected members of the family. This deletion significantly decreased FOXL2 promoter activity, as measured by the luciferase assay. Conclusively, a novel 255-bp-deletion of the FOXL2 promoter was identified in Chinese families with BPES. Our results expand the spectrum of known FOXL2 mutations and provide additional insight into the genotype-phenotype relationships of the BPES pathogenesis. In addition, this study indicates the important role of genetic screening of cis-regulatory elements in testing heritable diseases.

Neuromuscular Electrical Stimulation for Post-Stroke Dysphagia Treatment: A Systemic Evaluation and Meta-Analysis of Randomized Controlled Trials.

Neuromuscular electrical stimulation (NMES) is a novel treatment method that stimulates patients' swallowing functions. This systemic review was designed to evaluate the impact of NMES on dysphagia in stroke patients. Databases including PubMed, Embase, Web of Science, and Cochrane Library were searched from the date of establishment to January 28th, 2022. Two investigators identified all included studies and compared the swallowing function after NMES treatment with traditional therapy (TT). The Cochrane risk bias assessment tool was utilized to analyze the quality of included studies. Research outcomes included Swallowing Quality of Life (SWAL-QoL), Penetration-Aspiration Scale (PAS), Functional Oral Intake Scale (FOIS), Dysphagia Outcomes and Severity Scale (DOSS), the Repeat Salivary Swallowing Test (RSST), and Water Swallowing Test (WST). We extracted the mean and standard deviation of specific outcomes at the baseline level and after the treatment in both NMES and TT groups for subsequent meta-analysis. 9 randomized controlled trials (RCTs) and quasi-RCTs were included, and remarkable differences were found between patients treated with or without NMES in respect of FOIS scores (SMD = 0.48; 95% CI 0.26-0.70, P < 0.0001), PAS scores (SMD = - 0.56; 95% CI 1.01-0.10, P = 0.02), and SWAL-QoL scores (SMD = 0.57; 95% CI 0.00-1.14, P = 0.05). No significant difference was manifested in WST, RSST, and DOSS (SMD: - 0.02; 95% CI  0.38-0.35, P = 0.93). Evidence suggests that NMES is more effective for post-stroke dysphagia patients than treatment without NMES.

Slow-Reflow and Prognosis in Patients with High Parathyroid Hormone Levels Undergoing Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction.

We aimed to evaluate the correlation among serum parathyroid hormone (PTH) and slow-reflow during primary percutaneous coronary intervention (PCI) and prognosis in patients with ST-segment elevation myocardial infarction (STEMI). A total of 262 patients were enrolled and divided into a slow-reflow group (n = 61) and a control group (n = 201). PTH was an independent risk factor for slow-reflow (P < 0.05), and the regression model had good discrimination and calibration. ROC curve analysis showed that PTH (≥ 63.65 pg/ml) had a predictive value for slow-reflow (P < 0.001). During the 1-year follow-up, the patients were divided into a PTH-h group (≥ 63.65 pg/ml, n = 100) and a PTH-l group (< 63.65 pg/ml, n = 162). Readmission for HF was independently associated with PTH levels (P < 0.05). KM survival analysis suggested that PTH-h had a predictive value for MACEs, especially for readmission for HF (P < 0.05). PTH levels were associated with slow-reflow during PCI and MACEs during follow-up in patients with STEMI.

Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

Background: Although the study of the neuroanatomical correlates of depression in Parkinson's Disease (PD) is gaining increasing interest, up to now the cortical gyrification pattern of PD-related depression has not been reported. This study was conducted to investigate the local gyrification index (LGI) in PD patients with depression, and its associations with the severity of depression. Methods: LGI values, as measured using FreeSurfer software, were compared between 59 depressed PD (dPD), 27 non-depressed PD (ndPD) patients and 43 healthy controls. The values were also compared between ndPD and mild-depressed PD (mi-dPD), moderate-depressed PD (mo-dPD) and severe-depressed PD (se-dPD) patients as sub-group analyses. Furthermore, we evaluated the correlation between LGI values and depressive symptom scores within dPD group. Results: Compared to ndPD, the dPD patients exhibited decreased LGI in the left parietal, the right superior-frontal, posterior cingulate and paracentral regions, and the LGI values within these areas negatively correlated with the severity of depression. Specially, reduced gyrification was observed in mo-dPD and involving a larger region in se-dPD, but not in mi-dPD group. Conclusion: The present study demonstrated that cortical gyrification is decreased within specific brain regions among PD patients with versus without depression, and those changes were associated with the severity of depression. Our findings suggested that cortical gyrification might be a potential neuroimaging marker for the severity of depression in patients with PD.

Distinct changes in global brain synchronization in different motor subtypes of Parkinson's disease.

This study investigated alterations in degree centrality (DC) in different motor subtypes of Parkinson's disease (PD) and analyzed its clinical significance during disease occurrence. A total of 146 subjects were recruited in the study, including 90 patients with PD [51 and 39 with tremor dominant (TD) and akinetic-rigid dominant (ARD) disease, respectively] and 56 healthy controls (HCs). The resting-state functional magnetic resonance imaging data of all the subjects were obtained by 3.0 T magnetic resonance scans. The DC values, an indicator of whole brain synchronization, were calculated and compared among the TD, ARD, and HC groups. Disparities in DC values among the three groups were evaluated by analysis of variance and post hoc two-sample t-tests. Correlation between brain regions with DC differences and clinical variables were performed using partial correlation analysis after controlling for age, gender, and disease duration. Compared to the HCs, both TD and ARD groups demonstrated increased DC values bilaterally in the cerebellum; DC values were decreased in the left putamen and paracentral lobule in the TD group and in the left anterior cingulate gyrus and right supplementary motor area in the ARD group. Compared to the ARD group, the TD group showed decreased DC values in bilateral cerebellar hemispheres and increased DC values in the left anterior cingulate gyrus and right supplementary motor area. The DC of the whole brain showed inconsistencies and shared neural bases among patients with the two subtypes of PD. The differences between brain regions with abnormal DC values may be closely related to different clinical presentations of the two motor subtypes. Our findings provide new insights into the clinical heterogeneity of PD with respect to different motor subtypes.

Severe thrombocytopenia induced by tirofiban after percutaneous coronary intervention: a case report.

BACKGROUND: Tirofiban is a nonpeptide glycoprotein IIb/IIIa receptor antagonist used widely in patients subjected to percutaneous coronary intervention. While the usage of tirofiban sets an important clinical benefit, severe thrombocytopenia can occur with use of this agent. CASE PRESENTATION: A 76-year-old Chinese man was admitted with 1-month history of sudden onset of chest tightness. He was diagnosed as having subacute inferior myocardial infarction, and percutaneous coronary intervention was performed. After the procedure, patient received tirofiban at 0.15 µg/kg/minute for 4 h. A blood sample was obtained for a complete blood count; severe thrombocytopenia was reported according to routine orders at our hospital. All antiplatelet drugs including tirofiban, aspirin, and clopidogrel were immediately discontinued. The patient received platelet transfusions and was treated with immunoglobulin G. Two days later, the patient's platelet count had increased to 75 × 109/L. There was a significant improvement after day 5, and the platelet count was 112 × 109/L. Seven days after the acute thrombocytopenia, he was discharged with normal platelet count. CONCLUSIONS: Clinicians should be particularly aware of tirofiban-induced thrombocytopenia in routine practice.

Neural functional network of early Parkinson's disease based on independent component analysis.

This work explored neural network changes in early Parkinson's disease: Resting-state functional magnetic resonance imaging was used to investigate functional alterations in different stages of Parkinson's disease (PD). Ninety-five PD patients (50 early/mild and 45 early/moderate) and 37 healthy controls (HCs) were included. Independent component analysis revealed significant differences in intra-network connectivity, specifically in the default mode network (DMN) and right frontoparietal network (RFPN), in both PD groups compared to HCs. Inter-network connectivity analysis showed reduced connectivity between the executive control network (ECN) and DMN, as well as ECN-left frontoparietal network (LFPN), in early/mild PD. Early/moderate PD exhibited decreased connectivity in ECN-LFPN, ECN-RFPN, ECN-DMN, and DMN-auditory network, along with increased connectivity in LFPN-cerebellar network. Correlations were found between ECN-DMN and ECN-LFPN connections with UPDRS-III scores in early/mild PD. These findings suggest that PD progression involves dysfunction in multiple intra- and inter-networks, particularly implicating the ECN, and a wider range of abnormal functional networks may mark the progression of the disease.

Association Between Intermediate End Points, Progression-free Survival, and Overall Survival in First-line Advanced or Recurrent Endometrial Cancer.

PURPOSE: Advanced/recurrent endometrial cancer is associated with poor long-term outcomes. Clinical studies of novel regimens are ongoing, but given that data on overall survival (OS) take a long time to mature, surrogate end points are often used to support clinical-research interpretation. The aim of this study was to explore the correlation between progression-free survival (PFS)/time to progression (TTP) and OS across multiple time points in the first-line treatment of advanced/recurrent endometrial cancer. METHODS: This study comprised meta-analyses of Phase 2/3 randomized, controlled trials of first-line treatments in patients with advanced primary or first-recurrent endometrial cancer identified via systematic literature review. The strength of the surrogacy relationship was assessed by correlation analyses (estimated with Spearman and Pearson correlation coefficients) and weighted linear regression. FINDINGS: Data from 15 studies were included. PFS and TTP (TTP was reported in one study only) were highly correlated with future OS at multiple time points (Spearman values, 0.83-0.90; Pearson values, 0.86-0.93), suggesting that a change in PFS/TTP would likely be correlated with a change in OS in the same direction. On weighted linear regression, a 10% increase in PFS/TTP probability was significantly associated with a 9.3% to 13.3% increase in the probability of future OS. The strong positive association between PFS/TTP and OS was supported by findings from sensitivity analyses based on identified sources of interstudy heterogeneity. IMPLICATIONS: PFS/TTP is a good potential candidate for predicting long-term OS outcomes in trials of first-line treatment in patients with advanced/recurrent endometrial cancer. The findings from this report may help to inform health-authority and clinical decision makers that PFS/TTP improvements are likely to translate into subsequent OS improvements once data mature.

Outcomes for Dostarlimab and Real-World Treatments in Post-platinum Patients With Advanced/Recurrent Endometrial Cancer: The GARNET Trial Versus a US Electronic Health Record-Based External Control Arm.

Background: Patients with advanced or recurrent endometrial cancer (EC) have limited treatment options following platinum-based chemotherapy and poor prognosis. The single-arm, Phase I GARNET trial (NCT02715284) previously reported dostarlimab efficacy in mismatch repair-deficient/microsatellite instability-high advanced or recurrent EC. Objectives: The objective of this study was to compare overall survival (OS) and describe time to treatment discontinuation (TTD) for dostarlimab (GARNET Cohort A1 safety population) with an equivalent real-world external control arm receiving non-anti-programmed death (PD)-1/PD-ligand (L)1/2 treatments (constructed using data from a nationwide electronic health record-derived de-identified database and applied GARNET eligibility criteria). Methods: Propensity scores constructed from prognostic factors, identified by literature review and clinical experts, were used for inverse probability of treatment weighting (IPTW). Kaplan-Meier curves were constructed and OS/TTD was estimated (Cox regression model was used to estimate the OS-adjusted hazard ratio). Results: Dostarlimab was associated with a 52% lower risk of death vs real-world treatments (hazard ratio, 0.48; 95% confidence interval [CI], 0.35-0.66). IPTW-adjusted median OS for dostarlimab (N=143) was not estimable (95% CI, 19.4-not estimable) versus 13.1 months (95% CI, 8.3-15.9) for real-world treatments (N = 185). Median TTD was 11.7 months (95% CI, 6.0-38.7) for dostarlimab and 5.3 months (95% CI, 4.1-6.0) for the real-world cohort. Discussion: Consistent with previous analyses, patients treated with dostarlimab had significantly longer OS than patients in the US real-world cohort after adjusting for the lack of randomization using stabilized IPTW. Additionally, patients had a long TTD when treated with dostarlimab, suggesting a favorable tolerability profile. Conclusion: Patients with advanced or recurrent EC receiving dostarlimab in GARNET had significantly lower risk of death than those receiving real-world non-anti-PD-(L)1/2 treatments.

Identication and validation of cell senescence biomarkers in idiopathic pulmonary hypertension via integrated transcriptome analyses and machine learning.

BACKGROUND: Idiopathic pulmonary hypertension (IPAH) is a rare and severe disease that affects the pulmonary vasculature. As the diagnosis of IPAH requires invasive right heart catheterization surgery, early detection of this condition is notoriously challenging. Therefore, it is of utmost importance to investigate biomarkers present in peripheral blood that could aid physicians in the early identification and management of IPAH. METHOD: We speculate that cellular senescence may be involved in the occurrence and development of IPAH through various pathways. In this study, we utilized integrated transcriptome analyses and machine learning-based approach to develop a diagnostic model for IPAH cell senescence. To select genetic features, we employed two machine learning algorithms: the Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF). Additionally, we validated our findings through both external data sets and qRT-PCR experiments. RESULTS: The resulting diagnostic nomogram was able to identify five important biomarkers that can aid in the diagnosis of IPAH, including TNFRSF1B, CCL16, GCLM, IL15, and SOD1. These genes are primarily associated with the immune system, as well as with cell senescence and apoptosis. CONCLUSION: Our study demonstrates the utility of machine learning algorithms in making accurate diagnoses of IPAH, providing clinicians with a more directed approach to the diagnosis and treatment of this disease.

Surface-Based Functional Alterations in Early-Onset and Late-Onset Parkinson's Disease: A Multi-Modal MRI Study.

This study used a surface-based method to investigate brain functional alteration patterns in early-onset Parkinson's disease (EOPD) and late-onset Parkinson's disease (LOPD) to provide more reliable imaging indicators for the assessment of the two subtypes. A total of 58 patients with Parkinson's disease were divided into two groups according to age at onset: EOPD (≤50 years; 16 males and 15 females) and LOPD (>50 years; 17 males and 10 females) groups. Two control groups were recruited from the community: young adults (YC; ≤50 years; 8 males and 19 females) and older adults (OC; >50 years; 12 males and 10 females). No significant differences were observed between the EOPD and YC groups or the LOPD and OC groups in terms of age, sex, education, and MMSE scores (p > 0.05). No statistically significant differences were observed between the EOPD and LOPD groups in terms of education, H-Y scale, UPDRS score, or HAMD score (p > 0.05). Data preprocessing and surface-based regional homogeneity (2D-ReHo) calculations were subsequently performed using the MATLAB-based DPABIsurf software. The EOPD group showed decreased 2D-ReHo values in the left premotor area and right dorsal stream visual cortex, along with increased 2D-ReHo values in the left dorsolateral prefrontal cortex. In patients with LOPD, 2D-ReHo values were decreased in bilateral somatosensory and motor areas and the right paracentral lobular and mid-cingulate. The imaging characterization of surface-based regional changes may serve useful as monitoring indicators and will help to better understand the mechanisms underlying divergent clinical presentations.

Irisin inhibits neutrophil extracellular traps formation and protects against acute pancreatitis in mice.

INTRODUCTION: Irisin is a newly discovered myokine which links exercise to inflammation and inflammation-related diseases through macrophage regulation. However, the effect of irisin on the activity of inflammation related immune cells (such as neutrophils) has not been clearly described. OBJECTIVES: The objective of our study was to explore the effect of irisin on the neutrophil extracellular traps (NETs) formation. METHODS: Phorbol-12-myristate-13-acetate (PMA) was used to construct a classic neutrophil inflammation model that was used to observe the formation of NETs in vitro. We studied the effect of irisin on NETs formation and its regulation mechanism. Subsequently, acute pancreatitis (AP) was used to verify the protective effect of irisin in vivo, which was an acute aseptic inflammatory response disease model closely related to NETs. RESULTS: Our study found that addition of irisin significantly reduced the formation of NETs via regulation of the P38/MAPK pathway through integrin αVß5, which might be the one of key pathways in NETs formation, and which could theoretically offset the immunoregulatory effect of irisin. Systemic treatment with irisin reduced the severity of tissue damage common in the disease and inhibited the formation of NETs in pancreatic necrotic tissue of two classical AP mouse models. CONCLUSION: The findings confirmed for the first time that irisin could inhibit NETs formation and protect mice from pancreatic injury, which further elucidated the protective effect of exercise on acute inflammatory injury.