Genetic and clinical profile of 15 Chinese families with GDAP1-related Charcot-Marie-Tooth disease and identification of H256R as a frequent mutation.

BACKGROUND AND AIMS: Mutations in ganglioside-induced differentiation-associated protein 1 (GDAP1) cause axonal or demyelinating Charcot-Marie-Tooth disease (CMT) with autosomal dominant or recessive inheritance. In this study, we aim to report the genotypic and phenotypic features of GDAP1-related CMT in a Chinese cohort. METHODS: Clinical, neurophysiological, genetic data, and available muscle/brain imaging information of 28 CMT patients with GDAP1 variants were retrospectively collected. RESULTS: We identified 16 GDAP1 pathogenic variants, among which two novel variants c.980dup(p.L328FfsX25) and c.480+4T>G were first reported. Most patients (16/28) presented with AR or AD CMT2K phenotype. Clinical characteristics in our cohort demonstrated that the AR patients presented earlier onset, more severe phenotype compared with the AD patients. Considerable intra-familial phenotypic variability was observed among three AD families. Muscle atrophy and fatty infiltration in the lower extremity were detected by Muscle magnetic resonance imaging (MRI) scans in four patients. MRI showed two AR patients showed more severe muscle involvement of the posterior compartment than those of the anterolateral compartment in the calf. One patient carrying Q38*/H256R variants accompanied with mild periventricular leukoaraiosis. CONCLUSIONS: In this study, we conducted an analysis of clinical features of the GDAP1-related CMT patients, expanded the mutation spectrum in GDAP1 by reporting two novel variants, and presented the prevalent occurrence of the H256R mutation in China. The screening of GDAP1 should be particularly emphasized in Chinese patients with CMT2, given the incomplete penetrance and pathogenic inheritance patterns involving dominant and recessive modes.

CCDC25 suppresses clear cell renal cell carcinoma progression by LATS1/YAP-mediated regulation of the hippo pathway.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent renal cancers, and the molecular mechanisms underlying its progression are still not fully understood. The expression of CCDC25, a notably underexpressed gene in many tumors, has been understudied in ccRCC. This research aims to explore the role of CCDC25 in ccRCC's clinical outcomes and uncover the molecular pathways influenced by it. METHODS: A multi-tiered approach was adopted involving bioinformatic analysis, tissue sample evaluation, in vitro and in vivo experiments. CCDC25 expression levels in tumor vs. normal tissues were quantified using Western blot and immunofluorescence studies. Cell proliferation and migration were analyzed using CCK8, EDU, Transwell assays, and wound healing assays. RNA sequencing was performed to elucidate the molecular pathways affected, followed by detailed protein-protein interaction studies and mouse xenograft models. RESULTS: CCDC25 was predominantly underexpressed in ccRCC tumors and associated with advanced clinical stages and poor prognosis. Overexpression of CCDC25 in renal cancer cell lines resulted in reduced proliferation and migration. RNA sequencing revealed significant alterations in the Hippo pathway. Overexpression of CCDC25 inhibited the expression of downstream Hippo pathway proteins ITGA3 and CCND1 and promoted YAP phosphorylation. Mechanistic studies showed that CCDC25 interacts with YAP and influences YAP phosphorylation through LATS1. In vivo, CCDC25 overexpression inhibited tumor growth and promoted apoptosis. CONCLUSION: CCDC25 acts as a potential tumor suppressor in ccRCC by inhibiting cell proliferation and migration, potentially through regulating the Hippo signaling pathway. These findings highlight the potential of CCDC25 as a therapeutic target in ccRCC treatment.

Radiogenomic analysis based on lipid metabolism-related subset for non-invasive prediction for prognosis of renal clear cell carcinoma.

PURPOSE: Multiple lipid metabolism pathways alterations are associated with clear cell renal cell carcinoma (ccRCC) development and aggressiveness. In this study, we aim to develop a novel radiogenomics signature based on lipid metabolism-related genes (LMRGs) that may accurately predict ccRCC patients' survival. MATERIALS AND METHODS: First, 327 ccRCC were used to screen survival-related LMRGs and construct a gene signature based on The Cancer Genome Atlas (TCGA) database. Then, 182 ccRCC were analyzed to establish radiogenomics signature linking LMRGs signature to radiomic features in The Cancer Imaging Archive (TCIA) database included enhanced CT images and transcriptome sequencing data. Lastly, we validated the prognostic power of the identified radiogenomics signature using these patients of TCIA and the Third Xiangya Hospital. RESULTS: We identified the LMRGs signature, consisting of 13 genes, which could efficiently discriminate between low-risk and high-risk patients and serve as an independent and reliable predictor of overall survival (OS). Radiogenomics signature, comprised of 9 radiomic features, was created and could accurately predict the expression level of LMRGs signature (low- or high-risk) for patients. The predictive performance of this radiogenomics signature was demonstrated through AUC values of 0.75 and 0.74 for the training and validation sets (at a ratio of 7:3), respectively. Radiogenomics signature was proven to be an independent risk factor for OS by multivariable analysis (HR = 4.98, 95 % CI:1.72-14.43, P = 0.003). CONCLUSIONS: The LMRGs radiogenomics signature could serve as a novel prognostic predictor.

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks.

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a simulated-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms. The PnP OA-LFE module's versatility was further demonstrated by its successful application to xQSM, a distinct DL-QSM network for dipole inversion. In conclusion, this work introduces a new DL paradigm, allowing researchers to develop innovative QSM methods without requiring a complete overhaul of their existing architectures.

Development and validation of a clinical factors and body fat distribution-based nomogram to predict refractoriness of transarterial chemoembolization in hepatocellular carcinoma.

Background: Transarterial chemoembolization (TACE) is an important treatment modality for hepatocellular carcinoma (HCC). However, some patients may develop TACE refractoriness during treatment. We aimed to construct a prediction model incorporating computed tomography (CT) body composition and clinical factors to preoperatively predict the risk of developing TACE refractoriness in patients with HCC, enabling the rapid identification of patients at high risk of TACE refractoriness. Methods: This study included 128 HCC patients treated with TACE who were randomly assigned to the training (n=89) and validation groups (n=39) in a 7:3 ratio. Multiple body-composition parameters were outlined from CT images of the third lumbar vertebra level of each patient. Standardized values of body-composition parameters were calculated, such as visceral-to-subcutaneous adipose tissue area ratio (VSR). Multifactor logistic regression analysis was performed to identify independent predictors of TACE-refractoriness in patients and to develop predictive models. High- and low-risk subgroup analyses were performed for the predictive model. Results: Alpha-fetoprotein (AFP) level (P=0.041), tumor size (P=0.001), and VSR (P=0.043) were independent risk factors for TACE refractoriness. The combined clinical-body composition model had an area under the curve (AUC) value of 0.875 in the training cohort and an AUC value of 0.837 in the validation cohort. Calibration curves and decision curves revealed the specific optimal performance and clinical utility of the combined model. Subgroup analysis showed differences in predicted TACE refractoriness between the high- and low-risk groups (P<0.001). Conclusions: The combined clinical-body fat distribution model has the good performance in predicting a patient's risk of TACE refractoriness preoperatively and can help clinicians make the best clinical decisions in advance for the treatment of high-risk patients.

Development and validation of MRI-based scoring models for predicting placental invasiveness in high-risk women for placenta accreta spectrum.

OBJECTIVES: To develop and validate MRI-based scoring models for predicting placenta accreta spectrum (PAS) invasiveness. MATERIALS AND METHODS: This retrospective study comprised a derivation cohort and a validation cohort. The derivation cohort came from a systematic review of published studies evaluating the diagnostic performance of MRI signs for PAS and/or placenta percreta in high-risk women. The significant signs were identified and used to develop prediction models for PAS and placenta percreta. Between 2016 and 2021, consecutive high-risk pregnant women for PAS who underwent placental MRI constituted the validation cohort. Two radiologists independently evaluated the MRI signs. The reference standard was intraoperative and pathologic findings. The predictive ability of MRI-based models was evaluated using the area under the curve (AUC). RESULTS: The derivation cohort included 26 studies involving 2568 women and the validation cohort consisted of 294 women with PAS diagnosed in 258 women (88%). Quantitative meta-analysis revealed that T2-dark bands, placental/uterine bulge, loss of T2 hypointense interface, bladder wall interruption, placental heterogeneity, and abnormal intraplacental vascularity were associated with both PAS and placenta percreta, and myometrial thinning and focal exophytic mass were exclusively associated with PAS. The PAS model was validated with an AUC of 0.90 (95% CI: 0.86, 0.93) for predicting PAS and 0.85 (95% CI: 0.79, 0.90) for adverse peripartum outcome; the placenta percreta model showed an AUC of 0.92 (95% CI: 0.86, 0.98) for predicting placenta percreta. CONCLUSION: MRI-based scoring models established based on quantitative meta-analysis can accurately predict PAS, placenta percreta, and adverse peripartum outcome. CLINICAL RELEVANCE STATEMENT: These proposed MRI-based scoring models could help accurately predict PAS invasiveness and provide evidence-based risk stratification in the management of high-risk pregnant women for PAS. KEY POINTS: • Accurately identifying placenta accreta spectrum (PAS) and assessing its invasiveness depending solely on individual MRI signs remained challenging. • MRI-based scoring models, established through quantitative meta-analysis of multiple MRI signs, offered the potential to predict PAS invasiveness in high-risk pregnant women. • These MRI-based models allowed for evidence-based risk stratification in the management of pregnancies suspected of having PAS.

CT enterography-based radiomics combined with body composition to predict infliximab treatment failure in Crohn's disease.

PURPOSE: Accurately predicting the treatment response in patients with Crohn's disease (CD) receiving infliximab therapy is crucial for clinical decision-making. We aimed to construct a prediction model incorporating radiomics and body composition features derived from computed tomography (CT) enterography for identifying individuals at high risk for infliximab treatment failure. METHODS: This retrospective study included 137 patients with CD between 2015 and 2021, who were divided into a training cohort and a validation cohort with a ratio of 7:3. Patients underwent CT enterography examinations within 1 month before infliximab initiation. Radiomic features of the intestinal segments involved were extracted, and body composition features were measured at the level of the L3 lumbar vertebra. A model that combined radiomics with body composition was constructed. The primary outcome was the occurrence of infliximab treatment failure within 1 year. The model performance was evaluated using discrimination, calibration, and decision curves. RESULTS: Fifty-two patients (38.0%) showed infliximab treatment failure. Eight significant radiomic features were used to develop the radiomics model. The model incorporating radiomics model score, skeletal muscle index (SMI), and creeping fat showed good discrimination for predicting infliximab treatment failure, with an area under the curve (AUC) of 0.88 (95% CI 0.81, 0.95) in the training cohort and 0.83 (95% CI 0.66, 1.00) in the validation cohort. The favorable clinical application was observed using decision curve analysis. CONCLUSIONS: We constructed a comprehensive model incorporating radiomics and muscle volume, which could potentially be used to facilitate the individualized prediction of infliximab treatment response in patients with CD.

Establishment and application of the BRP prognosis model for idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently lacking. This study aimed to construct an easy-to-use and robust prediction model for transplant-free survival (TFS) of IPF based on clinical and radiological information. METHODS: A multicenter prognostic study was conducted involving 166 IPF patients who were followed up for 3 years. The end point of follow-up was death or lung transplantation. Clinical information, lung function tests, and chest computed tomography (CT) scans were collected. Body composition quantification on CT was performed using 3D Slicer software. Risk factors in blood routine examination-radiology-pulmonary function (BRP) were identified by Cox regression and utilized to construct the "BRP Prognosis Model". The performance of the BRP model and the gender-age-physiology variables (GAP) model was compared using time-ROC curves, calibration curves, and decision curve analysis (DCA). Furthermore, histopathology fibrosis scores in clinical specimens were compared between the different risk stratifications identified by the BRP model. The correlations among body composition, lung function, serum inflammatory factors, and profibrotic factors were analyzed. RESULTS: Neutrophil percentage > 68.3%, pericardial adipose tissue (PAT) > 94.91 cm3, pectoralis muscle radiodensity (PMD) ≤ 36.24 HU, diffusing capacity of the lung for carbon monoxide/alveolar ventilation (DLCO/VA) ≤ 56.03%, and maximum vital capacity (VCmax) < 90.5% were identified as independent risk factors for poor TFS among patients with IPF. We constructed a BRP model, which showed superior accuracy, discrimination, and clinical practicability to the GAP model. Median TFS differed significantly among patients at different risk levels identified by the BRP model (low risk: TFS > 3 years; intermediate risk: TFS = 2-3 years; high risk: TFS ≈ 1 year). Patients with a high-risk stratification according to the BRP model had a higher fibrosis score on histopathology. Additionally, serum proinflammatory markers were positively correlated with visceral fat volume and infiltration. CONCLUSIONS: In this study, the BRP prognostic model of IPF was successfully constructed and validated. Compared with the commonly used GAP model, the BRP model had better performance and generalization with easily obtainable indicators. The BRP model is suitable for clinical promotion.

Comprehensive Scrna-Seq Analysis and Identification of CD8_+T Cell related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma.

BACKGROUND: Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis. METHODS: Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy. RESULTS: We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility. CONCLUSION: To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

From the West to the East: an evidence-based educational reform for modern medical students in traditional Chinese medicine learning.

Introduction: Generally, Traditional Chinese Medicine (TCM) courses are now given to modern medicine students without proper course scheduling, resulting in poor teaching results. Methods: To analyze the main factors affecting TCM learning, we surveyed the medical students and TCM teachers from Xiangya School of Medicine of Central South University via online questionnaires. The questionnaire comprised two parts, the students' part included the basic information, the subjective cognition in TCM, the attitude toward TCM course arrangements, and the attitude toward curriculum content and the design of TCM. The teachers' part included the basic information, the attitudes and opinions on TCM course arrangements, and suggestions and views on TCM teaching reform. The related data were collected from 187 medical students divided into two groups, namely, clinical medical students and non-clinical medical students. Results: We found a more positive attitude toward TCM [including "Scientific nature of TCM" (P = 0.03) and "Necessity for modern medicine students to learn TCM" (P = 0.037)] in clinical medical students compared with non-clinical medical students, clinical and non-clinical medical students tended to find TCM courses difficult, and the students prefer clinical training to be better than theoretical teaching, while the teachers believe that lecture-based education should have a more significant proportion. Discussion: Hence, to optimize the current TCM teaching, we conducted education reform, including differentiated teaching, hybrid teaching, and selective teaching.

PCMT1 is a potential target related to tumor progression and immune infiltration in liver cancer.

BACKGROUND: Liver cancer is a prevalent and deadly form of cancer with high incidence and mortality rates. The PCMT1 protein has been linked to cell anti-apoptosis and tumor metastasis, but its significance in liver hepatocellular carcinoma (LIHC) remains largely unexplored. METHODS: We conducted a pan-cancer analysis to examine the expression differences of PCMT1. Kaplan-Meier curves were employed to assess the prognostic impact of PCMT1 on LIHC patients, and we investigated the association between PCMT1 and clinical features, which we validated using a GEO therapeutic dataset. Gene enrichment analysis helped identify signaling pathways associated with PCMT1 expression. Moreover, we evaluated the relationship between PCMT1 and immune cell infiltration, as well as the differences in gene mutations between high-expression and low-expression groups. In vitro and in vivo experiments were performed to assess the effect of PCMT1 on tumor cell lines and mouse tumor models, and potential pathways were explored through gene sequencing. RESULT: PCMT1 is highly expressed in most tumors and exhibits a significant association with prognosis in LIHC patients. Pathway enrichment analysis revealed that PCMT1 is involved in cell cycle regulation, immunity, and other processes. Further immune analysis demonstrated that high expression of PCMT1 could reduce tumor-killing immune cell infiltration. In vitro experiments indicated that PCMT1 knockdown could inhibit cancer cell proliferation and migration while promoting apoptosis. In vivo experiments showed that PCMT1 knockdown significantly reduced tumor growth rate, enhanced CD8+T cell infiltration, and increased caspase-3 expression in the tumor area. Gene sequencing suggested that PCMT1 may function through the PI3K-AKT pathway. CONCLUSION: Our findings suggest that PCMT1 acts as a promoter of liver cancer progression and may serve as a novel prognostic indicator and therapeutic target for patients with LIHC.

Expanding the genetic and clinical spectrum of SORD-related peripheral neuropathy by reporting a novel variant c.210T>G and evidence of subclinical muscle involvement.

BACKGROUND AND AIMS: Biallelic variants in the sorbitol dehydrogenase (SORD) gene have been identified as the genetic cause of autosomal recessive (AR) peripheral neuropathy (PN) manifesting as Charcot-Marie-Tooth disease type 2 (CMT2) or distal hereditary motor neuropathy (dHMN). We aim to observe the genetic and clinical spectrum of a cohort of patients with SORD-related PN (SORD-PN). METHODS: A total of 107 patients with AR or sporadic CMT2/dHMN underwent molecular diagnosis by whole-exome sequencing and subsequent Sanger sequencing validation. Available phenotypic data for SORD-PN were collected and analyzed. RESULTS: Eleven (10.28%) of 107 patients were identified as SORD-PN, including four with CMT2 and seven with dHMN. The SORD variant c.210 T > G;p.His70Gln in F-d3 was firstly reported and subsequent analysis showed that it resulted in loss of SORD enzyme function. Evidence of subclinical muscle involvement was frequently detected in patients with SORD-PN, including mildly to moderately elevated serum creatine kinase (CK) levels in 10 patients, myogenic electrophysiological changes in one patient, and muscle edema in five patients undergoing lower extremity MRI. Fasting serum sorbitol level was 88-fold higher in SORD-PN patients (9.69 ± 1.07 mg/L) than in healthy heterozygous subjects (0.11 ± 0.01 mg/L) and 138-fold higher than in healthy controls (0.07 ± 0.02 mg/L). INTERPRETATION: The novel SORD variant c.210 T > G;p.His70Gln and evidence of subclinical muscle involvement were identified, which expanded the genetic and clinical spectrum of SORD-PN. Subclinical muscle involvement might be a common but easily overlooked clinical feature. The serum CK and fasting serum sorbitol levels were expected to be sensitive biomarkers confirmed by follow-up cohort study.

Ketoglutaric acid can reprogram the immunophenotype of triple-negative breast cancer after radiotherapy and improve the therapeutic effect of anti-PD-L1.

BACKGROUND: Great progress has been made in applying immunotherapy to the clinical treatment of tumors. However, many patients with triple-negative breast cancer (TNBC) cannot benefit from immunotherapy due to the immune desert type of TNBC, which is unresponsive to immunotherapy. DMKG, a cell-permeable derivative of α-KG, has shown potential to address this issue. METHOD: We investigated the effects of combining DMKG with radioimmunotherapy on TNBC. We assessed the ability of DMKG to promote tumor cell apoptosis and immunogenic death induced by radiotherapy (RT), as well as its impact on autophagy reduction, antigen and inflammatory factor release, DC cell activation, and infiltration of immune cells in the tumor area. RESULT: Our findings indicated that DMKG significantly promoted tumor cell apoptosis and immunogenic death induced by RT. DMKG also significantly reduced autophagy in tumor cells, resulting in increased release of antigens and inflammatory factors, thereby activating DC cells. Furthermore, DMKG promoted infiltration of CD8 + T cells in the tumor area and reduced the composition of T-regulatory cells after RT, reshaping the tumor immune microenvironment. Both DMKG and RT increased the expression of PD-L1 at immune checkpoints. When combined with anti-PD-L1 drugs (α-PD-L1), they significantly inhibited tumor growth without causing obvious side effects during treatment. CONCLUSION: Our study underscores the potential of pairing DMKG with radioimmunotherapy as an effective strategy for treating TNBC by promoting apoptosis, immunogenic death, and remodeling the tumor immune microenvironment. This combination therapy could offer a promising therapeutic avenue for TNBC patients unresponsive to conventional immunotherapy.

PTEN-related risk classification models for predicting prognosis and immunotherapy response of hepatocellular carcinoma.

INTRODUCTION: PTEN often mutates in tumors, and its manipulation is suggested to be used in the development of preclinical tools in cancer research. This study aims to explore the biological impact of gene expression related to PTEN mutations and to develop a prognostic classification model based on the heterogeneity of PTEN expression, and to explore its sensitivity as an indicator of prognosis and molecular and biologic features in hepatocellular carcinoma (HCC). MATERIAL AND METHODS: RNA-seq data and mutation data of the LIHC cohort sample downloaded from The Cancer Genome Atlas (TCGA). The HCC samples were grouped according to the mean expression of PTEN, and the tumor microenvironment (TME) was evaluated by ESTIMATE and ssGSEA. The prognostic classification model related to PTEN were constructed by COX and LASSO regression analysis of differentially expressed genes (DEGs) between PTEN-high and -low expressed group. RESULTS: The expression of PTEN was affected by copy number variation (CNV) and negatively correlated with immune score, IFNγ score and immune cell infiltration. 1281 DEGs were detected between PTEN-high and PTEN-low expressed group, 8 of the DEGs were finally filtered for developing a prognosis classification model. This model showed better prognostic value than other clinicopathological parameters, and the prediction accuracy of prognosis and ICB treatment for immunotherapy cohorts was better than that of TIDE model. CONCLUSIONS: This study demonstrated the effect of CNV on PTEN expression and the negative immune correlation of PTEN, and constructed a classification model related to the expression of PTEN, which was of guiding significance for evaluating prognostic results of HCC patients and ICB treatment response of cancer immunotherapy cohorts.

Effect of laparoscopic sleeve gastrectomy on mobilization of site-specific body adipose depots: a prospective cohort study.

BACKGROUND: Effect of bariatric surgery on mobilization of site-specific body adipose depots is not well investigated. Herein, the authors conducted a prospective cohort study to assess whether bariatric surgery can differentially affect specific fat storage pools and to further investigate correlations between site-specific fat mobilization and clinical outcomes. MATERIALS AND METHODS: In this single-centre prospective cohort study, 49 participants underwent laparoscopic sleeve gastrectomy (LSG) from 24 May 2022 to 20 October 2022 and underwent MRI to estimate subcutaneous fat area, visceral fat area (VFA), hepatic and pancreatic proton density fat fraction (PDFF) at baseline and 3 months after surgery. The protocol for this study was registered on clinicaltrials.gov. RESULTS: Among 49 patients who met all inclusion criteria, the median [interquartile range (IQR)] age was 31.0 (23.0-37.0) years, the median (IQR) BMI was 38.1 (33.7-42.2) kg/m 2 and 36.7% were male. Median (IQR) percentage hepatic PDFF loss was the greatest after bariatric surgery at 68.8% (47.3-79.7%), followed by percentage pancreatic PDFF loss at 51.2% (37.0-62.1%), percentage VFA loss at 36.0% (30.0-42.4%), and percentage subcutaneous fat area loss at 22.7% (17.2-32.4%) ( P <0.001). By calculating Pearson correlation coefficient and partial correlation coefficient, the positive correlations were confirmed between change in VFA and change in glycated haemoglobin ( r =0.394, P =0.028; partial r =0.428, P =0.042) and between change in hepatic PDFF and change in homoeostatic model assessment of insulin resistance ( r =0.385, P =0.025; partial r =0.403, P =0.046). CONCLUSIONS: LSG preferentially mobilized hepatic fat, followed by pancreatic fat and visceral adipose tissue, while subcutaneous adipose tissue was mobilized to the least extent. Reduction in visceral adipose tissue and hepatic fat is independently associated with the improvement of glucose metabolism after LSG.

Controversial role of ILC3s in intestinal diseases: A novelty perspective on immunotherapy.

ILC3s have been identified as crucial immune regulators that play a role in maintaining host homeostasis and modulating the antitumor response. Emerging evidence supports the idea that LTi cells play an important role in initiating lymphoid tissue development, while other ILC3s can promote host defense and orchestrate adaptive immunity, mainly through the secretion of specific cytokines and crosstalk with other immune cells or tissues. Additionally, dysregulation of ILC3-mediated overexpression of cytokines, changes in subset abundance, and conversion toward other ILC subsets are closely linked with the occurrence of tumors and inflammatory diseases. Regulation of ILC3 cytokines, ILC conversion and LTi-induced TLSs may be a novel strategy for treating tumors and intestinal or extraintestinal inflammatory diseases. Herein, we discuss the development of ILCs, the biology of ILC3s, ILC plasticity, the correlation of ILC3s and adaptive immunity, crosstalk with the intestinal microenvironment, controversial roles of ILC3s in intestinal diseases and potential applications for treatment.

SS-TBN: A Semi-Supervised Tri-Branch Network for COVID-19 Screening and Lesion Segmentation.

Insufficient annotated data and minor lung lesions pose big challenges for computed tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To address this issue, we propose a Semi-Supervised Tri-Branch Network (SS-TBN). First, we develop a joint TBN model for dual-task application scenarios of image segmentation and classification such as CT-based COVID-19 diagnosis, in which pixel-level lesion segmentation and slice-level infection classification branches are simultaneously trained via lesion attention, and individual-level diagnosis branch aggregates slice-level outputs for COVID-19 screening. Second, we propose a novel hybrid semi-supervised learning method to make full use of unlabeled data, combining a new double-threshold pseudo labeling method specifically designed to the joint model and a new inter-slice consistency regularization method specifically tailored to CT images. Besides two publicly available external datasets, we collect internal and our own external datasets including 210,395 images (1,420 cases versus 498 controls) from ten hospitals. Experimental results show that the proposed method achieves state-of-the-art performance in COVID-19 classification with limited annotated data even if lesions are subtle, and that segmentation results promote interpretability for diagnosis, suggesting the potential of the SS-TBN in early screening in insufficient labeled data situations at the early stage of a pandemic outbreak like COVID-19.

Salmonella-mediated blood‒brain barrier penetration, tumor homing and tumor microenvironment regulation for enhanced chemo/bacterial glioma therapy.

Chemotherapy is an important adjuvant treatment of glioma, while the efficacy is far from satisfactory, due not only to the biological barriers of blood‒brain barrier (BBB) and blood‒tumor barrier (BTB) but also to the intrinsic resistance of glioma cells via multiple survival mechanisms such as up-regulation of P-glycoprotein (P-gp). To address these limitations, we report a bacteria-based drug delivery strategy for BBB/BTB transportation, glioma targeting, and chemo-sensitization. Bacteria selectively colonized into hypoxic tumor region and modulated tumor microenvironment, including macrophages repolarization and neutrophils infiltration. Specifically, tumor migration of neutrophils was employed as hitchhiking delivery of doxorubicin (DOX)-loaded bacterial outer membrane vesicles (OMVs/DOX). By virtue of the surface pathogen-associated molecular patterns derived from native bacteria, OMVs/DOX could be selectively recognized by neutrophils, thus facilitating glioma targeted delivery of drug with significantly enhanced tumor accumulation by 18-fold as compared to the classical passive targeting effect. Moreover, the P-gp expression on tumor cells was silenced by bacteria type III secretion effector to sensitize the efficacy of DOX, resulting in complete tumor eradication with 100% survival of all treated mice. In addition, the colonized bacteria were finally cleared by anti-bacterial activity of DOX to minimize the potential infection risk, and cardiotoxicity of DOX was also avoided, achieving excellent compatibility. This work provides an efficient trans-BBB/BTB drug delivery strategy via cell hitchhiking for enhanced glioma therapy.

Curcumol Reduces Aerobic Glycolysis and Overcomes Chemoresistance by Inducing Cdh1-Mediated Skp2 Ubiquitination.

Colorectal cancer (CRC) is the third most common cancer worldwide. The main obstacle in treating advanced CRC is tumor recurrence and metastasis due to chemoresistance. S-phase kinase associated protein 2 (Skp2), an E3 ligase, is highly associated with tumor resistance and a poor prognosis. The results of immunoblotting, immunohistochemical staining, ubiquitination analysis, and co-immunoprecipitation (co-IP) assay revealed that the plant curcuma, curcumol, is a novel Skp2 inhibitor for CRC treatment. Curcumol inhibits aerobic glycolysis in CRC by inducing Skp2 degradation. Co-immunoprecipitation results showed that curcumol enhanced the interaction between cadherin-1 (Cdh1) and Skp2 and led to the ubiquitination and degradation of Skp2. Curcumol exhibited significant antitumor effects against CRC, such as increased intrinsic apoptosis and decreased tumorigenic properties, both in vivo and in vitro. Furthermore, curcumol overcame 5-fluorouracil (5-Fu) resistance in CRC and induced apoptosis in 5-Fu-resistant CRC cells. The present data revealed a novel antitumor mechanism of glycolytic regulation by curcumol, suggesting that curcumol may be a potential chemical candidate for treating 5-Fu-resistant CRC.