Comparative transcriptomic analysis reveals the molecular changes of acute pancreatitis in experimental models.

BACKGROUND: Acute pancreatitis (AP) encompasses a spectrum of pancreatic inflammatory conditions, ranging from mild inflammation to severe pancreatic necrosis and multisystem organ failure. Given the challenges associated with obtaining human pancreatic samples, research on AP predominantly relies on animal models. In this study, we aimed to elucidate the fundamental molecular mechanisms underlying AP using various AP models. AIM: To investigate the shared molecular changes underlying the development of AP across varying severity levels. METHODS: AP was induced in animal models through treatment with caerulein alone or in combination with lipopolysaccharide (LPS). Additionally, using Ptf1α to drive the specific expression of the hM3 promoter in pancreatic acinar cells transgenic C57BL/6J- hM3/Ptf1α(cre) mice were administered Clozapine N-oxide to induce AP. Subsequently, we conducted RNA sequencing of pancreatic tissues and validated the expression of significantly different genes using the Gene Expression Omnibus (GEO) database. RESULTS: Caerulein-induced AP showed severe inflammation and edema, which were exacerbated when combined with LPS and accompanied by partial pancreatic tissue necrosis. Compared with the control group, RNA sequencing analysis revealed 880 significantly differentially expressed genes in the caerulein model and 885 in the caerulein combined with the LPS model. Kyoto Encyclopedia of Genes and Genomes enrichment analysis and Gene Set Enrichment Analysis indicated substantial enrichment of the TLR and NOD-like receptor signaling pathway, TLR signaling pathway, and NF-κB signaling pathway, alongside elevated levels of apoptosis-related pathways, such as apoptosis, P53 pathway, and phagosome pathway. The significantly elevated genes in the TLR and NOD-like receptor signaling pathways, as well as in the apoptosis pathway, were validated through quantitative real-time PCR experiments in animal models. Validation from the GEO database revealed that only MYD88 concurred in both mouse pancreatic tissue and human AP peripheral blood, while TLR1, TLR7, RIPK3, and OAS2 genes exhibited marked elevation in human AP. The genes TUBA1A and GADD45A played significant roles in apoptosis within human AP. The transgenic mouse model hM3/Ptf1α(cre) successfully validated significant differential genes in the TLR and NOD-like receptor signaling pathways as well as the apoptosis pathway, indicating that these pathways represent shared pathological processes in AP across different models. CONCLUSION: The TLR and NOD receptor signaling pathways play crucial roles in the inflammatory progression of AP, notably the MYD88 gene. Apoptosis holds a central position in the necrotic processes of AP, with TUBA1A and GADD45A genes exhibiting prominence in human AP.

Modulating Cholesterol Metabolism via ACAT1 Knockdown Enhances Anti-B-Cell Lymphoma Activities of CD19-Specific Chimeric Antigen Receptor T Cells by Improving the Cell Activation and Proliferation.

CD19-specific CAR-T immunotherapy has been extensively studied for the treatment of B-cell lymphoma. Recently, cholesterol metabolism has emerged as a modulator of T lymphocyte function and can be exploited in immunotherapy to increase the efficacy of CAR-based systems. Acetyl-CoA acetyltransferase 1 (ACAT1) is the major cholesterol esterification enzyme. ACAT1 inhibitors previously shown to modulate cardiovascular diseases are now being implicated in immunotherapy. In the present study, we achieved knockdown of ACAT1 in T cells via RNA interference technology by inserting ACAT1-shRNA into anti-CD19-CAR-T cells. Knockdown of ACAT1 led to an increased cytotoxic capacity of the anti-CD19-CAR-T cells. In addition, more CD69, IFN-γ, and GzmB were expressed in the anti-CD19-CAR-T cells. Cell proliferation was also enhanced in both antigen-independent and antigen-dependent manners. Degranulation was also improved as evidenced by an increased level of CD107a. Moreover, the knockdown of ACAT1 led to better anti-tumor efficacy of anti-CD19 CAR-T cells in the B-cell lymphoma mice model. Our study demonstrates novel CAR-T cells containing ACAT1 shRNA with improved efficacy compared to conventional anti-CD19-CAR-T cells in vitro and in vivo.

A distinct tumor microenvironment makes anaplastic thyroid cancer more lethal but immunotherapy sensitive than papillary thyroid cancer.

Both anaplastic thyroid cancer (ATC) and papillary thyroid cancer (PTC) originate from thyroid follicular epithelial cells, but ATC has a significantly worse prognosis and shows resistance to conventional therapies. However, clinical trials found that immunotherapy works better in ATC than late-stage PTC. Here, we used single-cell RNA sequencing (scRNA-Seq) to generate a single-cell atlas of thyroid cancer. Differences in ATC and PTC tumor microenvironment components (including malignant cells, stromal cells, and immune cells) leading to the polarized prognoses were identified. Intriguingly, we found that CXCL13+ T lymphocytes were enriched in ATC samples and might promote the development of early tertiary lymphoid structure (TLS). Last, murine experiments and scRNA-Seq analysis of a treated patient's tumor demonstrated that famitinib plus anti-PD-1 antibody could advance TLS in thyroid cancer. We displayed the cellular landscape of ATC and PTC, finding that CXCL13+ T cells and early TLS might make ATC more sensitive to immunotherapy.

Metal-Organic Framework Based Mucoadhesive Nanodrugs for Multifunction Helicobacter Pylori Targeted Eradication, Inflammation Regulation and Gut Flora Protection.

The prevalence of drug-resistant bacteria presents a significant challenge to the antibiotic treatment of Helicobacter pylori (H. pylori), while traditional antimicrobial agents often suffer from shortcomings such as poor gastric retention, inadequate alleviation of inflammation, and significant adverse effects on the gut microbiota. Here, a selenized chitosan (CS-Se) modified bismuth-based metal-organic framework (Bi-MOF@CS-Se) nanodrug is reported that can target mucin through the charge interaction of the outer CS-Se layer to achieve mucosal adhesion and gastric retention. Additionally, the Bi-MOF@CS-Se can respond to gastric acid and pepsin degradation, and the exposed Bi-MOF exhibits excellent antibacterial properties against standard H. pylori as well as clinical antibiotic-resistant strains. Remarkably, the Bi-MOF@CS-Se effectively alleviates inflammation and excessive oxidative stress by regulating the expression of inflammatory factors and the production of reactive oxygen species (ROS), thereby exerting therapeutic effects against H. pylori infection. Importantly, this Bi-MOF@CS-Se nanodrug does not affect the homeostasis of gut microbiota, providing a promising strategy for efficient and safe treatment of H. pylori infection.

Tonghua Liyan granules in the treatment of Laryngopharyngeal reflux disease with stagnation of phlegm and qi syndrome: a randomized, double-blind, placebo-controlled study.

Background: Laryngopharyngeal reflux disease (LPRD) is an extraesophageal syndromic manifestation of gastroesophageal reflux disease (GERD). Despite the increasing incidence of and concern about LPRD, treatment with proton pump inhibitors (PPIs) is unsatisfactory. Here, LPRD was treated with Tonghua Liyan (THLY) granules in combination with PPIs to evaluate treatment efficacy and possible adverse reactions. Methods: Seventy-six LPRD patients with stagnation of phlegm and qi syndrome (SPQS) were randomly divided into an experimental group and a control group. The experimental group received THLY granules combined with rabeprazole capsules. The control group received THLY granule placebo combined with rabeprazole capsules. A parallel, randomized, double-blind, placebo-controlled clinical trial was conducted with these two groups. The treatment cycle was 8 weeks. The reflux symptom index (RSI), clinical symptom score, salivary pepsin content, reflux finding score (RFS) and gastroesophageal reflux disease questionnaire (GerdQ) were used to evaluate clinical efficacy. The final efficacy rate was evaluated according to the RSI and clinical symptom score. Results: Compared with those at baseline, all the indicators in the experimental group and control group significantly improved (p < 0.01). In terms of the RSI, clinical symptom score, and RFS, the experimental group had a higher degree of improvement (p < 0.05), and the overall efficacy rate was higher (p < 0.05). In terms of the salivary pepsin concentration and GerdQ, there was no significant difference between the test group and the control group (p > 0.05). Both groups of safety indicators showed no abnormalities and did not cause any allergic reactions in the body. Conclusion: Compared with PPIs alone, THLY granules combined with PPIs are more effective in the treatment of LPRD patients with SPQS in terms of symptoms and signs. This combination treatment, because of its higher clinical efficacy and lack of obvious adverse reactions, is worthy of clinical promotion and further in-depth study. Clinical Trial Registration: www.chictr.org.cn, identifier ChiCTR2100046614.

Diagnosis of pulmonary tuberculosis with 3D neural network based on multi-scale attention mechanism.

This paper presents a novel multi-scale attention residual network (MAResNet) for diagnosing patients with pulmonary tuberculosis (PTB) by computed tomography (CT) images. First, a three-dimensional (3D) network structure is applied in MAResNet based on the continuity and correlation of nodal features on different slices of CT images. Secondly, MAResNet incorporates the residual module and Convolutional Block Attention Module (CBAM) to reuse the shallow features of CT images and focus on key features to enhance the feature distinguishability of images. In addition, multi-scale inputs can increase the global receptive field of the network, extract the location information of PTB, and capture the local details of nodules. The expression ability of both high-level and low-level semantic information in the network can also be enhanced. The proposed MAResNet shows excellent results, with overall 94% accuracy in PTB classification. MAResNet based on 3D CT images can assist doctors make more accurate diagnosis of PTB and alleviate the burden of manual screening. In the experiment, a called Grad-CAM was employed to enhance the class activation mapping (CAM) technique for analyzing the model's output, which can identify lesions in important parts of the lungs and make transparent decisions.

Bibliometric analysis of pancreatic diseases and gut microbiota research from 2002 to 2022.

Background: An increasing number of studies have indicated that pancreatic diseases are associated with the structure of the gut microbiota. We aimed to assess the research hotspots and trends in this field through a quantitative method. Materials and methods: Articles related to pancreatic diseases and the gut microbiota published from 2002 to 2022 were retrieved from the Web of Science database. We visualized the countries/regions, institutions, authors, journals, and keywords using VOSviewer and CiteSpace software. The interplay between pancreatic diseases and the gut microbiota was also analysed. Results: A total of 129 publications were finally identified. The number of papers increased gradually, and China held the dominant position with respect to publication output. Shanghai Jiao Tong University was the most influential institution. Zeng Yue ranked highest in the number of papers, and Scientific Reports was the most productive journal. The keywords "gut", "bacterial translocation", and "acute pancreatitis" appeared early for the first time, and "gut microbiota", "community", and "diversity" have been increasingly focused on. The predominant pancreatic disease correlated with the gut microbiota was pancreatic inflammatory disease (50.39%). Pancreatic diseases are associated with alterations in the gut microbiota, characterized by a decrease in beneficial bacteria and an increase in harmful bacteria. Conclusion: This is the first comprehensive bibliometric analysis of all pancreatic diseases and the gut microbiota. The research on the relationship between them is still in the preliminary stage, and the trend is toward a gradual deepening of the research and precise treatment development. The interaction between the gut microbiota and pancreatic diseases will be of increasing concern in the future.

The Prognostic and Immune Significance of CILP2 in Pan-Cancer and Its Relationship with the Progression of Pancreatic Cancer.

Cartilage intermediate layer protein 2 (CILP2) facilitates interactions between matrix components in cartilage and has emerged as a potential prognostic biomarker for cancer. This study aimed to investigate the function and mechanisms of CILP2 in pan-cancer. We evaluated the pan-cancer expression, methylation, and mutation data of CILP2 for its clinical prognostic value. Additionally, we explored the immunological characteristics of CILP2 in pan-cancer and then focused specifically on pancreatic ductal adenocarcinoma (PAAD). The subtype analysis of PAAD identified subtype-specific expression and immunological characteristics. Finally, in vitro and in vivo experiments assessed the impact of CILP2 on pancreatic cancer progression. CILP2 exhibited high expression in most malignancies, with significant heterogeneity in epigenetic modifications across multiple cancer types. The abnormal methylation and copy number variations in CILP2 were correlated with poor prognoses. Upregulated CILP2 was associated with TGFB/TGFBR1 and more malignant subtypes. CILP2 exhibited a negative correlation with immune checkpoints in PAAD, suggesting potential for immunotherapy. CILP2 activated the AKT pathway, and it increased proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) in pancreatic cancer. We demonstrated that CILP2 significantly contributes to pancreatic cancer progression. It serves as a prognostic biomarker and a potential target for immunotherapy.

Integrated single-cell and spatial transcriptomics reveals heterogeneity of fibroblast and pivotal genes in psoriasis.

Psoriasis, which is one of the most common skin diseases, involves an array of complex immune constituents including T cells, dendritic cells and monocytes. Particularly, the cytokine IL17A, primarily generated by TH17 cells, assumes a crucial function in the etiology of psoriasis. In this study, a comprehensive investigation utilizing bulk RNA analysis, single-cell RNA sequencing, and spatial transcriptomics was employed to elucidate the underlying mechanisms of psoriasis. Our study revealed that there is an overlap between the genes that are differentially expressed in psoriasis patients receiving three anti-IL17A monoclonal antibody drugs and the genes that are differentially expressed in lesion versus non-lesion samples in these patients. Further analysis using single-cell and spatial data from psoriasis samples confirmed the expression of hub genes that had low expressions in psoriasis tissue but were up-regulated after anti-IL17A treatments. These genes were found to be associated with the treatment effects of brodalumab and methotrexate, but not adalimumab, etanercept, and ustekinumab. Additionally, these genes were predominantly expressed in fibroblasts. In our study, fibroblasts were categorized into five clusters. Notably, hub genes exhibited predominant expression in cluster 3 fibroblasts, which were primarily engaged in the regulation of the extracellular matrix and were predominantly located in the reticular dermis. Subsequent analysis unveiled that cluster 3 fibroblasts also established communication with epithelial cells and monocytes via the ANGPTL-SDC4 ligand-receptor configuration, and their regulation was governed by the transcription factor TWIST1. Conversely, cluster 4 fibroblasts, responsible for vascular endothelial regulation, were predominantly distributed in the papillary dermis. Cluster 4 predominantly engaged in interactions with endothelial cells via MDK signals and was governed by the distinctive transcription factor, ERG. By means of an integrated analysis encompassing bulk transcriptomics, single-cell RNA sequencing, and spatial transcriptomics, we have discerned genes and clusters of fibroblasts that potentially contribute to the pathogenesis of psoriasis.

Co-expression of IL-4/IL-15-based inverted cytokine receptor in CAR-T cells overcomes IL-4 signaling in immunosuppressive pancreatic tumor microenvironment.

The efficacy of CAR-T cell therapy has been hindered by several factors that are intrinsic to the tumor microenvironment. Many strategies are being employed to overcome these barriers and improve immunotherapies efficacy. Interleukin (IL)- 4 is a cytokine released by tumor cells inside the tumor microenvironment and it can oppose T cell effector functions via engagement with the IL-4 receptor on the surface of T cells. To overcome IL-4-mediated immunosuppressive signals, we designed a novel inverted cytokine receptor (ICR). Our novel CAR construct (4/15NKG2D-CAR), consisted of an NKG2D-based chimeric antigen receptor, co-expressing IL-4R as an extracellular domain and IL-15R as a transmembrane and intracellular domain. In this way, IL-4R inhibitory signals were converted into IL-15R activation signals downstream. This strategy increased the efficacy of NKG2D-CAR-T cells in the pancreatic tumor microenvironment in vitro and in vivo. 4/15NKG2D-CAR-T cells exhibited increased activation, degranulation, cytokine release, and cytotoxic ability of NKG2D-CAR-T cells against IL-4+ pancreatic cell lines. Furthermore, 4/15NKG2D-CAR-T cells exhibited more expansion, less exhaustion, and an increased percentage of less differentiated T cell phenotypes in vitro when compared with NKG2D-CAR-T cells. That is why IL-4R/IL-15R-modified CAR-T cells eradicated more tumors in vivo and outperformed NKG2D-CAR-T cells. Thus, we report here a novel NKG2D-CAR-T cells that could overcome IL-4-mediated immunosuppression in solid tumors.

Research trends on the relationship between Helicobacter pylori and microbiota: A bibliometric analysis.

BACKGROUND: Increasing evidence has indicated that Helicobacter pylori infection is associated with the complex microbiota in the digestive tract of the human body. We aimed to assess the research trends and hotspots in the field of H. pylori and microbiota using a quantitative method. MATERIALS AND METHODS: The clinical studies on H. pylori and microbiota published from 2001 to 2022 were extracted from the Web of Science database. We visualized and analyzed countries/regions, institutions, authors, journals, and keywords through VOSviewer and CiteSpace software. The test techniques, specimen type, as well as microbiota variation after H. pylori infection and eradication were also evaluated. RESULTS: A total of 98 publications were finally identified, and the number of annual papers increased gradually. China showed its dominant position in the publication outputs, and Nanchang University was the most productive institution. Cong He, Xu Shu, and Yin Zhu published the highest number of papers, whereas Helicobacter was the most productive journal. "Helicobacter pylori" ranked highest in the keyword occurrences. 16S rRNA gene sequencing was the most frequently used method for microbiota analysis. Fecal samples had the highest frequency of use, followed by gastric mucosa and saliva. H. pylori infection was associated with the alterations of microbiota through the digestive tract, characterized by the enrichment of Helicobacter in the stomach. Triple and quadruple therapy were the most utilized eradication regimens, and probiotics supplementation therapy has been proven to reduce side effects and restore microbial diversity. CONCLUSIONS: This bibliometric analysis provides an overview of advancements in the field of H. pylori and microbiota. While numerous studies have been conducted on the correlation between H. pylori and the alterations of microbiota, future research is warranted to investigate the mechanisms underlying the interplay between H. pylori and other microbes in the development of related diseases.

Unleashing the Potential of EIL Transcription Factors in Enhancing Sweet Orange Resistance to Bacterial Pathologies: Genome-Wide Identification and Expression Profiling.

The ETHYLENE INSENSITIVE3-LIKE (EIL) family is one of the most important transcription factor (TF) families in plants and is involved in diverse plant physiological and biochemical processes. In this study, ten EIL transcription factors (CsEILs) in sweet orange were systematically characterized via whole-genome analysis. The CsEIL genes were unevenly distributed across the four sweet orange chromosomes. Putative cis-acting regulatory elements (CREs) associated with CsEIL were found to be involved in plant development, as well as responses to biotic and abiotic stress. Notably, quantitative reverse transcription polymerase chain reaction (qRT-PCR) revealed that CsEIL genes were widely expressed in different organs of sweet orange and responded to both high and low temperature, NaCl treatment, and to ethylene-dependent induction of transcription, while eight additionally responded to Xanthomonas citri pv. Citri (Xcc) infection, which causes citrus canker. Among these, CsEIL2, CsEIL5 and CsEIL10 showed pronounced upregulation. Moreover, nine genes exhibited differential expression in response to Candidatus Liberibacter asiaticus (CLas) infection, which causes Citrus Huanglongbing (HLB). The genome-wide characterization and expression profile analysis of CsEIL genes provide insights into the potential functions of the CsEIL family in disease resistance.

Nonpharmacological Interventions for Management of the Pain-Fatigue-Sleep Disturbance Symptom Cluster in Breast Cancer Patients: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

Background: The pain-fatigue-sleep disturbance symptom cluster is commonly experienced by breast cancer patients, and a variety of nonpharmacological interventions are used to treat this symptom cluster. Objective: To compare the efficacy of nonpharmacological interventions in improving the symptoms of the pain-fatigue-sleep disturbance symptom cluster in breast cancer patients. Methods: A comprehensive literature search was conducted in the PubMed, EMBASE, Cochrane Library, CINAHL, CNKI, and Wanfang databases to identify randomized controlled studies from database inception to May 2022. Two reviewers independently performed data retrieval and risk of bias assessments. The consistency model was used to conduct network meta-analyses (NMA) based on the frequentist framework to assess the interventions, which were ranked by the surface under the cumulative ranking curve (SUCRA). Finally, the CINeMA application was used to evaluate the results of the NMA and the evidence of quality. The results Twenty-three eligible studies assessing 14 interventions were included. According to SUCRA values, among the management effects of the three symptoms, the effect of progressive muscle relaxation (PMR) ranked first, followed by mindfulness-based stress reduction (MBSR). The overall evidence quality of our study ranges from very low to moderate. Conclusion: PMR and MBSR were effective interventions for the pain-fatigue-sleep disturbance symptom cluster in breast cancer patients. Clinical recommendations prioritize PMR for symptom management, followed by MBSR. However, this should be interpreted cautiously, as the confidence in the evidence was not high.

Interpretable machine-learning model for Predicting the Convalescent COVID-19 patients with pulmonary diffusing capacity impairment.

INTRODUCTION: The COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors' prognosis of pulmonary function, but the current studies focusing on prediction of the pulmonary diffusing capacity of these people are limited. The aim of this study was to develop and validate a machine learning (ML) model for predicting PDCI in the COVID-19 patients using routinely available clinical data, thus assisting the clinical diagnosis. METHODS: Collected from a follow-up study from August to September 2021 of 221 hospitalized survivors of COVID-19 18 months after discharge from Wuhan, including the demographic characteristics and clinical examination, the data in this study were randomly separated into a training (80%) data set and a validation (20%) data set. Six popular machine learning models were developed to predict the pulmonary diffusing capacity of patients infected with COVID-19 in the recovery stage. The performance indicators of the model included area under the curve (AUC), Accuracy, Recall, Precision, Positive Predictive Value(PPV), Negative Predictive Value (NPV) and F1. The model with the optimum performance was defined as the optimal model, which was further employed in the interpretability analysis. The MAHAKIL method was utilized to balance the data and optimize the balance of sample distribution, while the RFECV method for feature selection was utilized to select combined features more favorable to machine learning. RESULTS: A total of 221 COVID-19 survivors were recruited in this study after discharge from hospitals in Wuhan. Of these participants, 117 (52.94%) were female, with a median age of 58.2 years (standard deviation (SD) = 12). After feature selection, 31 of the 37 clinical factors were finally selected for use in constructing the model. Among the six tested ML models, the best performance was accomplished in the XGBoost model, with an AUC of 0.755 and an accuracy of 78.01% after experimental verification. The SHAPELY Additive explanations (SHAP) summary analysis exhibited that hemoglobin (Hb), maximal voluntary ventilation (MVV), severity of illness, platelet (PLT), Uric Acid (UA) and blood urea nitrogen (BUN) were the top six most important factors affecting the XGBoost model decision-making. CONCLUSION: The XGBoost model reported here showed a good prognostic prediction ability for PDCI of COVID-19 survivors during the recovery period. Among the interpretation methods based on the importance of SHAP values, Hb and MVV contributed the most to the prediction of PDCI outcomes of COVID-19 survivors in the recovery period.

TERT accelerates BRAF mutant-induced thyroid cancer dedifferentiation and progression by regulating ribosome biogenesis.

TERT reactivation occurs frequently in human malignancies, especially advanced cancers. However, in vivo functions of TERT reactivation in cancer progression and the underlying mechanism are not fully understood. In this study, we expressed TERT and/or active BRAF (BRAF V600E) specifically in mouse thyroid epithelium. While BRAF V600E alone induced papillary thyroid cancer (PTC), coexpression of BRAF V600E and TERT resulted in poorly differentiated thyroid carcinoma (PDTC). Spatial transcriptome analysis revealed that tumors from mice coexpressing BRAF V600E and TERT were highly heterogeneous, and cell dedifferentiation was positively correlated with ribosomal biogenesis. Mechanistically, TERT boosted ribosomal RNA (rRNA) expression and protein synthesis by interacting with multiple proteins involved in ribosomal biogenesis. Furthermore, we found that CX-5461, an rRNA transcription inhibitor, effectively blocked proliferation and induced redifferentiation of thyroid cancer. Thus, TERT promotes thyroid cancer progression by inducing cancer cell dedifferentiation, and ribosome inhibition represents a potential strategy to treat TERT-reactivated cancers.

Ultrasonography-assisted assessment of the influence of the volar prominence of the plate on the median nerve in distal radius fractures.

OBJECTIVE: The study aimed to explore the effect of differing volar locking plate (VLP) prominence on the median nerve (MN) in distal radius fracture (DRF) with ultrasound assistance to guide clinical treatment. METHODS: Forty-four patients who received VLP for DRF at our department were admitted and followed-up between January 2019 and May 2021. Different plate positions were graded using Soong classification; 13 were Grade 0, 18 were Grade 1, and 13 were Grade 2. The MN parameters at different wrist positions in patients with different Soong grades were measured with ultrasound assistance, including the median nerve cross-sectional area (MNCSA), diameter in the radial-ulnar direction (D1), and diameter in the dorsal-palmar direction (D2). The sensation in the affected finger and grip strength were collected at follow-up, scored using the Disabilities of the Arm, Shoulder, and Hand (DASH) scale to determine function, and statistically analysed. RESULTS: The MNCSA differed significantly across Soong grades. The MNCSA at the flexed, neutral, and extended wrist positions was smallest at Grade 0 and largest at Grade 2 (P < 0.05), and that at the neutral position was not significantly different between Grades 1 and 2 (P > 0.05). There was no significant interaction between the wrist positions and Soong grade (P > 0.05). The differences in D1 and D2 among different Soong grades were not statistically significant (P > 0.05). There were no statistical differences in grip strength, DASH, and sensation among different Soong grades (P > 0.05). CONCLUSIONS: Differing plate protrusions in DRF treatment did not cause clinical symptoms during follow-up; however, excessive plate protrusion (Soong Grade 2) increased the cross-sectional area of the MN. We recommend placing the plate as proximal as possible during VLP treatment of DRFs to avoid excessive bulges affecting the MN.

A nomogram based on radiomics intermuscular adipose analysis to indicate arteriosclerosis in patients with newly diagnosed type 2 diabetes.

Objective: Early identifying arteriosclerosis in newly diagnosed type 2 diabetes (T2D) patients could contribute to choosing proper subjects for early prevention. Here, we aimed to investigate whether radiomic intermuscular adipose tissue (IMAT) analysis could be used as a novel marker to indicate arteriosclerosis in newly diagnosed T2D patients. Methods: A total of 549 patients with newly diagnosed T2D were included in this study. The clinical information of the patients was recorded and the carotid plaque burden was used to indicate arteriosclerosis. Three models were constructed to evaluate the risk of arteriosclerosis: a clinical model, a radiomics model (a model based on IMAT analysis proceeded on chest CT images), and a clinical-radiomics combined model (a model that integrated clinical-radiological features). The performance of the three models were compared using the area under the curve (AUC) and DeLong test. Nomograms were constructed to indicate arteriosclerosis presence and severity. Calibration curves and decision curves were plotted to evaluate the clinical benefit of using the optimal model. Results: The AUC for indicating arteriosclerosis of the clinical-radiomics combined model was higher than that of the clinical model [0.934 (0.909, 0.959) vs. 0.687 (0.634, 0.730), P < 0.001 in the training set, 0.933 (0.898, 0.969) vs. 0.721 (0.642, 0.799), P < 0.001 in the validation set]. Similar indicative efficacies were found between the clinical-radiomics combined model and radiomics model (P = 0.5694). The AUC for indicating the severity of arteriosclerosis of the combined clinical-radiomics model was higher than that of both the clinical model and radiomics model [0.824 (0.765, 0.882) vs. 0.755 (0.683, 0.826) and 0.734 (0.663, 0.805), P < 0.001 in the training set, 0.717 (0.604, 0.830) vs. 0.620 (0.490, 0.750) and 0.698 (0.582, 0.814), P < 0.001 in the validation set, respectively]. The decision curve showed that the clinical-radiomics combined model and radiomics model indicated a better performance than the clinical model in indicating arteriosclerosis. However, in indicating severe arteriosclerosis, the clinical-radiomics combined model had higher efficacy than the other two models. Conclusion: Radiomics IMAT analysis could be a novel marker for indicating arteriosclerosis in patients with newly diagnosed T2D. The constructed nomograms provide a quantitative and intuitive way to assess the risk of arteriosclerosis, which may help clinicians comprehensively analyse radiomics characteristics and clinical risk factors more confidently.

Stem cells therapy for diabetes: from past to future.

Diabetes mellitus is a chronic disease of carbohydrate metabolism characterized by uncontrolled hyperglycemia due to the body's impaired ability to produce or respond to insulin. Oral or injectable exogenous insulin and its analogs cannot mimic endogenous insulin secreted by healthy individuals, and pancreatic and islet transplants face a severe shortage of sources and transplant complications, all of which limit the widespread use of traditional strategies in diabetes treatment. We are now in the era of stem cells and their potential in ameliorating human disease. At the same time, the rapid development of gene editing and cell-encapsulation technologies has added to the wings of stem cell therapy. However, there are still many unanswered questions before stem cell therapy can be applied clinically to patients with diabetes. In this review, we discuss the progress of strategies to obtain insulin-producing cells from different types of stem cells, the application of gene editing in stem cell therapy for diabetes, as well as summarize the current advanced cell encapsulation technologies in diabetes therapy and look forward to the future development of stem cell therapy in diabetes.

Charge-to-spin conversion in fully epitaxial Ru/Cu hybrid nanolayers with interface control.

The demonstration of the charge-to-spin conversion, especially with enhanced spin Hall conductivity, is crucial for the development of energy-efficient spintronic devices such as spin-orbit torque (SOT) based magnetoresistive random access memories. In this work, fully epitaxial Ru/Cu heterostructures were fabricated with interface engineering and nanolayer insertions consisting of Cu (1 nm)/Ru (1 nm) structures with different numbers of periods. The atomically controlled interface was confirmed by the high-resolution high-angle annular dark-field scanning transmission electron microscopy, and the epitaxial relationship persists even in the hybrid nanolayer insertion structures. The spin current generation was detected by the measurement of unidirectional spin Hall magnetoresistance, and the effective damping-like spin Hall efficiency (ξDL) was further quantitatively evaluated by the spin-torque ferromagnetic resonance with thickness dependence of the ferromagnetic layer. It is found that the sharp interface Ru/Cu film has a sizeableξDLof -2.2% and the insertion of Cu/Ru nanolayers at the interface can increase theξDLvalue to -3.7%. The former could be attributed to the interface spin-orbit filtering effect and the latter may be further understood by the intrinsic contribution from the local electronic structure tuning due to the lattice distortion near the interface. A large effective spin Hall conductivity is achieved to be (3∼5) × 105ℏ2eΩ-1m-1in the epitaxial Ru/Cu hybrid nanolayers, which is in the same range as that of platinum. This work indicates that the interfacial control with hybrid nanolayer structures can extend the SOT-based materials to highly conductive metals, even with weak spin-orbit interactions, toward high stability, low cost, and low energy consumption for spintronic applications.