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Abstract Background SARC-F questionnaire is a simple and convenient tool for sarcopenia screening, and SARC-CalF is a modified version of it. The developments of their Chinese versions are warranted for the clinical use for Chinese population. This study aimed to culturally adapt the SARC-F questionnaire into Chinese using standardized methods, validate the reliability and diagnostic accuracy of the Chinese version SARC-F and SARC-CalF against five sarcopenia diagnosis criteria, and determine optimal cut-off values for clinical practice in Chinese population. Methods The translation and cross-cultural adaptation of SARC-F into Chinese were conducted following the methodological report from European Union Geriatric Medicine Society Sarcopenia Special Interest Group. The Chinese version of SARC-F was validated through a diagnostic test, using diagnostic criteria of sarcopenia recommended by the revised 2019 European Working Group on Sarcopenia in Older People (EWGSOP2) consensus, Asian Working Group for Sarcopenia (AWGS2019) consensus, the International Working Group on Sarcopenia (IWGS), the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium and the Sarcopenia Definition and Outcomes Consortium (SDOC). Additional analysis was done against the criteria of severe sarcopenia according to the revised EWGSOP2 and AWGS2019. Results The Chinese version of SARC-F was well translated and demonstrated good reliability and acceptability. The diagnostic test included 1859 community-dwelling older individuals from two medical centers. Against five different definitions of sarcopenia, the Chinese version of SARC-F showed reasonable diagnostic accuracy for sarcopenia screening (AUC 0.614–0.821), and was demonstrated low sensitivity (13.7–37.9%) but high specificity (94.8–97.7%) with a cut-off value of ≥ 4. SARC-CalF significantly enhanced the diagnostic accuracy of SARC-F when using definitions of EWGSOP2, AWGS2019 and IWGS (all P ≤ 0.001). A score of ≥ 2 for SARC-F and ≥ 7 for SARC-CalF were established as optimal cut-off points for identifying older individuals as at risk of sarcopenia in Chinese population. Conclusions The Chinese version SARC-F is of reasonable reliability and validity for sarcopenia screening. Despite its low sensitivity, it proves to be a useful tool to identify severe cases in community taking advantage of its simplicity. SARC-CalF appears to be a more suitable screening tool for clinical use in detecting sarcopenia.

Summary: Background: High ulnar nerve injuries result in intrinsic muscle weakness and are inconvenient for patients. Moreover, conventional surgical techniques often fail to achieve satisfactory motor recovery. A potential reconstructive solution in the form of the supercharge end-to-side (SETS) anterior interosseous nerve (AIN) transfer method has emerged. Therefore, this study aims to compare surgical outcomes of patients with transected and in-continuity high ulnar nerve lesions following SETS AIN transfer. Methods: Between June 2015 and May 2023, patients with high ulnar palsy in the form of transection injuries or lesion-in-continuity were recruited. The assessment encompassed several objective results, including grip strength, key pinch strength, compound muscle action potential, sensory nerve action potential, and two-point discrimination tests. The muscle power of finger abduction and adduction was also recorded. Additionally, subjective questionnaires were utilized to collect data on patient-reported outcomes. Overall, the patients were followed up for up to 2 years. Results: Patients with transected high ulnar nerve lesions exhibited worse baseline performance than those with lesion-in-continuity, including motor and sensory functions. However, they experienced greater motor improvement but less sensory recovery, resulting in comparable final motor outcomes in both groups. In contrast, the transection group showed worse sensory outcomes. Conclusions: Our findings suggest that SETS AIN transfer benefits patients with high ulnar nerve palsy, regardless of the lesion type. Nonetheless, improvements may be more pronounced in patients with transected lesions.

Abstract Background Application of autologous adipose-derived stem cells (ASC) for diabetic chronic wounds has become an emerging treatment option. However, ASCs from diabetic individuals showed impaired cell function and suboptimal wound healing effects. We proposed that adopting a low-glucose level in the culture medium for diabetic ASCs may restore their pro-healing capabilities. Methods ASCs from diabetic humans and mice were retrieved and cultured in high-glucose (HG, 4.5 g/L) or low-glucose (LG, 1.0 g/L) conditions. Cell characteristics and functions were investigated in vitro. Moreover, we applied diabetic murine ASCs cultured in HG or LG condition to a wound healing model in diabetic mice to compare their healing capabilities in vivo. Results Human ASCs exhibited decreased cell proliferation and migration with enhanced senescence when cultured in HG condition in vitro. Similar findings were noted in ASCs derived from diabetic mice. The inferior cellular functions could be partially recovered when they were cultured in LG condition. In the animal study, wounds healed faster when treated with HG- or LG-cultured diabetic ASCs relative to the control group. Moreover, higher collagen density, more angiogenesis and cellular retention of applied ASCs were found in wound tissues treated with diabetic ASCs cultured in LG condition. Conclusions In line with the literature, our study showed that a diabetic milieu exerts an adverse effect on ASCs. Adopting LG culture condition is a simple and effective approach to enhance the wound healing capabilities of diabetic ASCs, which is valuable for the clinical application of autologous ASCs from diabetic patients.

Acute cellular rejection (ACR) is a significant immune issue among recipients following liver transplantation. Although diffusion-weighted magnetic resonance imaging (DWI) is widely used for diagnosing liver disease, it has not yet been utilized for monitoring ACR in patients after liver transplantation. Therefore, the aim of this study was to evaluate the efficacy of DWI in monitoring treatment response among recipients with ACR. This study enrolled 25 recipients with highly suspected ACR rejection, and all subjects underwent both biochemistry and DWI scans before and after treatment. A pathological biopsy was performed 4 to 24 h after the first MRI examination to confirm ACR and degree of rejection. All patients were followed up and underwent a repeated MRI scan when their liver function returned to the normal range. After data acquisition, the DWI data were post-processed to obtain the apparent diffusion coefficient (ADC) map on a voxel-by-voxel basis. Five regions of interest were identified on the liver parenchyma to measure the mean ADC values from each patient. Finally, the mean ADC values and biochemical markers were statistically compared between ACR and non-ACR groups. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the ADC and biochemical data in detecting ACR, and correlation analysis was used to understand the relationship between the ADC values, biochemical markers, and the degree of rejection. The histopathologic results revealed that 20 recipients had ACR, including 10 mild, 9 moderate, and 1 severe rejection. The results demonstrated that the ACR patients had significantly lower hepatic ADC values than those in patients without ACR. After treatment, the hepatic ADC values in ACR patients significantly increased to levels similar to those in non-ACR patients with treatment. The ROC analysis showed that the sensitivity and specificity for detecting ACR were 80% and 95%, respectively. Furthermore, the correlation analysis revealed that the mean ADC value and alanine aminotransferase level had strong and moderate negative correlation with the degree of rejection, respectively (r = −0.72 and −0.47). The ADC values were useful for detecting hepatic ACR and monitoring treatment response after immunosuppressive therapy.

Abstract It is well‐known that muscle regeneration declines with aging, and aged muscles undergo degenerative atrophy or sarcopenia. While exercise and acute injury are both known to induce muscle regeneration, the molecular signals that help trigger muscle regeneration have remained unclear. Here, mass spectrometry imaging (MSI) is used to show that injured muscles induce a specific subset of prostanoids during regeneration, including PGG1, PGD2, and the prostacyclin PGI2. The spike in prostacyclin promotes skeletal muscle regeneration via myoblasts, and declines with aging. Mechanistically, the prostacyclin spike promotes a spike in PPARγ/PGC1a signaling, which induces a spike in fatty acid oxidation (FAO) to control myogenesis. LC–MS/MS and MSI further confirm that an early FAO spike is associated with normal regeneration, but muscle FAO became dysregulated during aging. Functional experiments demonstrate that the prostacyclin‐PPARγ/PGC1a‐FAO spike is necessary and sufficient to promote both young and aged muscle regeneration, and that prostacyclin can synergize with PPARγ/PGC1a‐FAO signaling to restore aged muscles’ regeneration and physical function. Given that the post‐injury prostacyclin‐PPARγ‐FAO spike can be modulated pharmacologically and via post‐exercise nutrition, this work has implications for how prostacyclin‐PPARγ‐FAO might be fine‐tuned to promote regeneration and treat muscle diseases of aging.

Abstract Age‐associated obesity and muscle atrophy (sarcopenia) are intimately connected and are reciprocally regulated by adipose tissue and skeletal muscle dysfunction. During ageing, adipose inflammation leads to the redistribution of fat to the intra‐abdominal area (visceral fat) and fatty infiltrations in skeletal muscles, resulting in decreased overall strength and functionality. Lipids and their derivatives accumulate both within and between muscle cells, inducing mitochondrial dysfunction, disturbing β‐oxidation of fatty acids, and enhancing reactive oxygen species (ROS) production, leading to lipotoxicity and insulin resistance, as well as enhanced secretion of some pro‐inflammatory cytokines. In turn, these muscle‐secreted cytokines may exacerbate adipose tissue atrophy, support chronic low‐grade inflammation, and establish a vicious cycle of local hyperlipidaemia, insulin resistance, and inflammation that spreads systemically, thus promoting the development of sarcopenic obesity (SO). We call this the metabaging cycle. Patients with SO show an increased risk of systemic insulin resistance, systemic inflammation, associated chronic diseases, and the subsequent progression to full‐blown sarcopenia and even cachexia. Meanwhile in many cardiometabolic diseases, the ostensibly protective effect of obesity in extremely elderly subjects, also known as the ‘obesity paradox’, could possibly be explained by our theory that many elderly subjects with normal body mass index might actually harbour SO to various degrees, before it progresses to full‐blown severe sarcopenia. Our review outlines current knowledge concerning the possible chain of causation between sarcopenia and obesity, proposes a solution to the obesity paradox, and the role of fat mass in ageing.

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection of furcation involvements (FI) on periapical radiographs (PAs) is crucial for the success of periodontal therapy. This research proposes a deep learning-based approach to furcation defect detection using convolutional neural networks (CNN) with an accuracy rate of 95%. This research has undergone a rigorous review by the Institutional Review Board (IRB) and has received accreditation under number 202002030B0C505. A dataset of 300 periapical radiographs of teeth with and without FI were collected and preprocessed to enhance the quality of the images. The efficient and innovative image masking technique used in this research better enhances the contrast between FI symptoms and other areas. Moreover, this technology highlights the region of interest (ROI) for the subsequent CNN models training with a combination of transfer learning and fine-tuning techniques. The proposed segmentation algorithm demonstrates exceptional performance with an overall accuracy up to 94.97%, surpassing other conventional methods. Moreover, in comparison with existing CNN technology for identifying dental problems, this research proposes an improved adaptive threshold preprocessing technique that produces clearer distinctions between teeth and interdental molars. The proposed model achieves impressive results in detecting FI with identification rates ranging from 92.96% to a remarkable 94.97%. These findings suggest that our deep learning approach holds significant potential for improving the accuracy and efficiency of dental diagnosis. Such AI-assisted dental diagnosis has the potential to improve periodontal diagnosis, treatment planning, and patient outcomes. This research demonstrates the feasibility and effectiveness of using deep learning algorithms for furcation defect detection on periapical radiographs and highlights the potential for AI-assisted dental diagnosis. With the improvement of dental abnormality detection, earlier intervention could be enabled and could ultimately lead to improved patient outcomes.

The double-stranded DNA receptor AIM2 is able to sense the environmental pollutant perfluorooctane sulfonate, a prototypical perfluoro-alkyl substrate. Activation of the AIM2 pathway leads to inflammation and tissue damage via IL-1β secretion and pyroptosis of affected innate immune cells.

Chemoresistance is one of the main challenges for cancer therapy success. Here, the authors show that dual-specificity phosphatase 16 (DUSP16) expression is associated with chemoresistance in several types of cancer through impairing mitochondria-associated apoptosis.

PurposesThis study investigated the nutritional problems and risks of Chinese non-hospitalized cancer survivors through an online survey.MethodsThe survey included nutritional and clinical questions distributed to non-hospitalized cancer survivors. All data were screened and analyzed with strict quality control. Nutrition Risk Screening-2002 (NRS-2002) was adopted and the related factors were analyzed.ResultsSix thousand six hundred eighty-five questionnaires were included. The prevalence of nutritional risk was 33.9%, which varied according to age, sex, cancer type, TNM staging, oncologic treatment, time interval since last treatment, etc. In the regression analysis, nutritional risk was associated with age, TNM staging, and nutrition support. Patients with leukemia and digestive cancer had the highest NRS-2002 score (3.33 ± 1.45 and 3.25 ± 1.61); the prevalence of nutritional risk (NRS-2002 ≥ 3) was 66.7 and 55.1%, respectively. Patients with a higher TNM stage had higher NRS-2002 scores in non-digestive cancer, which was not seen in digestive cancer. Among digestive, bone, nervous, and respiratory cancer patients, the NRS-2002 score mainly consisted of “impaired nutritional status,” which coincided with the “disease severity score” in leukemia patients. Nutrition intervention was achieved in 79.7 and 15.2% of patients with nutritional risk and no risk. Of the patients, 60.3% exhibited confusion about nutritional problems, but only 25.1% had professional counseling.ConclusionsRegular nutritional risk screening, assessment, and monitoring are needed to cover non-hospitalized cancer survivors to provide nutrition intervention for better clinical outcome and quality of life. By online survey, the nutritional risk of non-hospitalized cancer survivors was found high in China, but the nutrition support or professional consultation were not desirable. The composition of nutritional risk should also be aware of.

Abstract Background Ageing, chronic diseases, prolonged inactivity, and inadequate nutrition pose a severe threat to skeletal muscle health and function. To date, experimental evidence suggests that ageing‐related subclinical inflammation could be an important causative factor in sarcopenia. Although inflammatory signalling has been implicated in the pathogenesis of experimental animal models of sarcopenia, few studies have surveyed the clinical association between circulating factors and muscle mass in patients before and after lifestyle interventions. In this study, we evaluated whether proinflammatory cytokines are associated with the onset of sarcopenia, which circulating factors are associated with the severity of sarcopenia, and how these factors change after lifestyle interventions in sarcopenic elderly persons. Methods A total of 56 elderly subjects (age ≥ 60 years) with sarcopenia and 56 elderly non‐sarcopenic subjects, who met entry criteria and had given informed consent, were selected from the Peking Union Medical College Hospital multicentre prospective longitudinal sarcopenia study for testing relevant circulating factors. Thirty‐two elderly subjects from the sarcopenic cohort completed a 12 week intensive lifestyle intervention programme with whey supplements (30 g/day) and a personalized resistance training regimen. The levels of proinflammatory cytokines and metabolic hormones, pre‐intensive and post‐intensive lifestyle interventions, were measured. Results The sarcopenic group was significantly older (72.05 ± 6.54 years; P 11.15 pg/mL) and TWEAK (>1276.48 pg/mL) were associated with a 7.6‐fold and 14.3‐fold increased risk of sarcopenia, respectively. After adjustment for confounding variables, high levels of TWEAK were still associated with a 13.4‐fold increased risk of sarcopenia. Intensive lifestyle interventions led to significant improvements in sarcopenic patients' muscle mass and serum profiles of TWEAK, TNF‐α, IL‐18, insulin, and adiponectin (all P

It has been reported that supplementing certain amino acids has therapeutic effects on ulcerative colitis (UC). We intend to explore whether citrulline (Cit) supplementation has protective effects on UC. Fifteen male Wistar rats were divided into normal control group (NC group), UC group and UC+Cit group, with five rats in each group. The UC model was established by TNBS/ethanol method. Rats in UC+Cit group were intragastrically administered with Cit for 7 consecutive days after modeling. All rats were sacrificed after 7 days. Blood samples were collected to detect the number of monocytes. Colon tissues were taken for HE staining. Immunohistochemistry staining for CD68 and p-STAT3 were performed to detect the infiltration of monocytes and the phosphorylation of STAT3 in colon tissues. The concentrations of MCP-1, IL-6 and IL-17A and the protein expression of p-STAT3 in colon tissues were measured by ELISA and western blot methods, respectively. The body weight of UC group rats decreased significantly after 7 days (p0.05). The number of peripheral blood monocytes in UC+Cit group was significantly lower than that in UC group (p

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, using the difference in pixel values to cut the image into several equal sections and then connecting each cavity feature point to extend a curve that completes the description of the separated jaw. The curve is shifted up and down to look for the gap between the teeth, to identify and address missing teeth and overlapping. Under FDI World Dental Federation notation, the left and right sides receive eight-code sequences to mark each tooth, which provides improved convenience in clinical use. According to the literature, X-ray film cannot be marked correctly when a tooth is missing. This paper utilizes artificial center positioning and sets the teeth gap feature points to have the same count. Then, the gap feature points are connected as a curve with the curve of the jaw to illustrate the dental segmentation. In addition, we incorporate different image-processing methods to sequentially strengthen the X-ray film. The proposed procedure had an 89.95% accuracy rate for tooth positioning. As for the tooth cutting, where the edge of the cutting box is used to determine the position of each tooth number, the accuracy of the tooth positioning method in this proposed study is 92.78%.

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early, the treatment will be relatively easy, which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However, the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology, this research solves the problem that the original cutting technology cannot extract certain single teeth, and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN), which can identify caries and restorations from the bitewing images. Moreover, it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image, which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization, (2) a dental image cropping procedure to obtain individually separated tooth samples, and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks, namely, AlexNet, GoogleNet, Vgg19, and ResNet50, experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%, respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film.

The catechol quinone (CQ) motif is present in many biologically relevant molecules throughout endogenous metabolic products, foods, drugs, and environmental pollutants. The CQ derivatives may undergo Michael addition, and has been shown to yield covalent bonds with nucleophilic sites of cysteine, lysine, or histidine residue of proteins. The CQ-adducted proteins may exhibit cytotoxicity or biological functions different from their un-adducted forms. Identification, characterization, and quantification of relevant protein targets are essential but challenging goals. Mass spectrometry (MS) is well-suited for the analysis of proteins and protein modifications. Technical development of bottom-up proteomics has greatly advanced the field of biomolecular MS, including protein adductomics. This mini-review focuses on the use of biomolecular MS in (1) structural and functional characterization of CQ adduction on standards of proteins, (2) identification of endogenous adduction targets, and (3) quantification of adducted blood proteins as exposure index. The reactivity and outcome of CQ adduction are discussed with emphases on endogenous species, such as dopamine and catechol estrogens. Limitations and advancements in sample preparation, MS instrumentation, and software to facilitate protein adductomics are also discussed.

Long non-coding RNA (lncRNA) plays important biological regulatory functions at different levels. lncRNA NONRATT021477.2 (lncRNA77.2) was identified as a key gene under cold stress conditions in rats. From the literature, lncRNA77.2 may have important roles during antioxidant, but this conjecture requires investigation. To address this knowledge gap, we investigated the effects of lncRNA77.2 interference on H2O2- induced oxidative stress in rat liver cells (Buffalo rat liver, BRL).In the current study, H2O2 treatment simulated BRL cell oxidative stress. H2O2 treatment led to a significant increase in oxidative stress levels in BRL cells, whereas the gene expression levels of antioxidase and lncRNA 77.2 and cell viability were significantly reduced. Additionally, the expression of Nrf2 and Keap1 proteins decreased significantly compared to the control group. BRL cells were transfected with antisense oligonucleotides (ASO) or a negative control ASO (ASO-NC) and then treated with H2O2. The results showed lncRNA77.2 interference increased oxidative stress levels, reduced gene expression of antioxidant enzymes, Nrf2 and Keap1 expression levels. The results indicated that lncRNA77.2 interference aggravated H2O2-induced oxidative stress in BRL cells, which suggested that lncRNA77.2 is an antioxidant factor that plays an important role in the regulation of oxidative stress in BRL cells.

Purpose: The combination of pharmacological and non-pharmacological interventions is strongly recommended by current guidelines for knee osteoarthritis. However, few systematic reviews have validated their combined efficacy. In this study, we investigated the effects of the combination of pharmacological agents and exercise on knee osteoarthritis. Methods: Randomized controlled trials that investigated the efficacy of pharmacological agents combined with exercise for knee osteoarthritis were searched in PubMed, Embase, and Cochrane Library up to February 2024. The network meta-analysis was performed within the frequentist framework. Standardized mean difference (SMD) with 95% CI was estimated for pain and function. Grading of recommendations, assessment, development, and evaluations were used to evaluate the certainty of evidence. Results: In total, 71 studies were included. The combination therapy outperformed pharmacological or exercise therapy alone. Among the various pharmacological agents combined with exercise, mesenchymal stem cell injection was ranked the best for short-term pain reduction (SMD: −1.53, 95% CI: −1.92 to −1.13, high certainty), followed by botulinum toxin A, dextrose, and platelet-rich plasma. For long-term pain relief, dextrose prolotherapy was the optimal (SMD: −1.76, 95% CI: −2.65 to −0.88, moderate certainty), followed by mesenchymal stem cells, platelet rich in growth factor, and platelet-rich plasma. Conclusion: Exercise programs should be incorporated into clinical practice and trial design. For patients undergoing exercise therapies, mesenchymal stem cell, dextrose, platelet-rich plasma, platelet rich in growth factor, and botulinum toxin A may be the optimal agents.

This article explores the integration of the Triple Bottom Line concept in Smart Product Service Systems (S-PSS) within the banking industry. It emphasizes the importance of balancing economic, social, and environmental factors for sustainable development. By implementing personalized solutions and environmentally friendly practices, banks can strengthen customer relationships, drive loyalty, and reduce their ecological footprint. The study also highlights the benefits of effective information interaction and the potential for new financial services that prioritize economic value, societal well-being, and environmental conservation. Overall, the document provides a comprehensive framework for sustainable business practices in the banking sector.

We performed a systematic review and meta-analysis on sodium benzoate’s effects on cognitive function and other psychiatric symptoms in individuals with neuropsychiatric disorders. We searched PubMed, Embase, Cochrane Library, and PsychInfo databases until September 2023. A random-effects meta-analysis was performed within a frequentist framework. To investigate the potential sources of heterogeneity, we performed subgroup analyses based on sex, dose, diagnosis, and risk of bias of the included studies. Trial sequential analyses were performed to investigate the statistical power of the synthesized studies. The certainty in evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach. A total of 10 studies were included in the analysis. Sodium benzoate demonstrated a small-to-moderate positive effect on global cognitive function compared with placebo (standardized mean difference 0.40, 95% confidence interval 0.20 to 0.60, high certainty). Subgroup analyses suggested more pronounced effects in women; individuals receiving doses >500 mg/day; and individuals with early-phase Alzheimer’s disease, chronic schizophrenia, or major depressive disorder. Sodium benzoate also demonstrated potential efficacy in enhancing the speed of processing, working memory, verbal learning and memory, visual learning and memory, and reasoning and problem solving. Furthermore, sodium benzoate was effective for positive psychotic symptoms but not for negative psychotic and depressive symptoms with moderate certainty. The current evidence strongly supports the positive effects of sodium benzoate on cognitive function in neuropsychiatric disorders. Further research is required to confirm its efficacy across different subtypes or stages of neurocognitive disorders and within specific cognitive domains.Systematic Review RegistrationPROSPERO, identifier CRD42023457462

ObjectiveTo investigate the diagnostic efficacy of the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model based on ultrasonographic radiomics for the differentiation of small clear cell Renal Cell Carcinoma (ccRCC) and Renal Angiomyolipoma (RAML).MethodsThe clinical, ultrasound, and contrast-enhanced CT(CECT) imaging data of 302 small renal tumors (maximum diameter ≤ 4cm) patients in Tianjin Medical University Cancer Institute and Hospital from June 2018 to June 2022 were retrospectively analyzed, with 182 patients of ccRCC and 120 patients of RAML. The ultrasound images of the largest diameter of renal tumors were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from ROI segmented images. The patients were randomly divided into training and internal validation cohorts in the ratio of 7:3. The Random Forest algorithm of the Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model. The efficacy of the prediction models was verified in an independent external validation cohort consisting of 69 patients, from 230 small renal tumor patients in two different institutions. The Delong test compared the predictive ability of three models and CECT. Calibration Curve and clinical Decision Curve Analysis were applied to evaluate the model and determine the net benefit to patients.Results491 ultrasonographic radiomics features were extracted from 302 small renal tumor patients, and 9 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. In the internal validation cohort, the area under the curve (AUC), sensitivity, specificity, and accuracy of the clinical ultrasound imaging model, ultrasonographic radiomics model, comprehensive model, and CECT were 0.75, 76.7%, 60.0%, 70.0%; 0.80, 85.6%, 61.7%, 76.0%; 0.88, 90.6%, 76.7%, 85.0% and 0.90, 92.6%, 88.9%, 91.1%, respectively. In the external validation cohort, AUC, sensitivity, specificity, and accuracy of the three models and CECT were 0.73, 67.5%, 69.1%, 68.3%; 0.89, 86.7%, 80.0%, 83.5%; 0.90, 85.0%, 85.5%, 85.2% and 0.91, 94.6%, 88.3%, 91.3%, respectively. The DeLong test showed no significant difference between the clinical ultrasound imaging model and the ultrasonographic radiomics model (Z=-1.287, P=0.198). The comprehensive model showed superior diagnostic performance than the ultrasonographic radiomics model (Z=4. 394, P

Abstract Background Stress hyperglycemia ratio (SHR) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are independently associated with increased mortality risk in diabetic patients with coronary artery disease (CAD). However, the role of these biomarkers in patients with diabetes and multivessel disease (MVD) remains unknown. The present study aimed to assess the relative and combined abilities of these biomarkers to predict all-cause mortality in patients with diabetes and MVD. Methods This study included 1148 diabetic patients with MVD who underwent coronary angiography at Tianjin Chest Hospital between January 2016 and December 2016. The patients were divided into four groups according to their SHR (SHR-L and SHR-H) and NT-proBNP (NT-proBNP-L and NT-proBNP-H) levels. The primary outcome was all-cause mortality. Multivariate Cox regression analyses were performed to evaluate the association of SHR and NT-proBNP levels with all-cause mortality. Results During a mean 4.2 year follow-up, 138 patients died. Multivariate analysis showed that SHR and NT-proBNP were strong independent predictors of all-cause mortality in diabetic patients with MVD (SHR: HR hazard ratio [2.171; 95%CI 1.566–3.008; P