Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast.

PURPOSE: Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automated valve-tracking 2D method for measuring flow through the dynamic tricuspid valve. METHODS: Nine healthy subjects and 2 patients were imaged. The approach uses a previously trained deep learning network, TVnet, to automatically track the tricuspid valve plane from long-axis cine images. Subsequently, the tracking information is used to acquire 2D phase contrast (PC) with a dynamic (moving) acquisition plane that tracks the valve. Direct diastolic net flows evaluated from the dynamic PC sequence were compared with flows from 2D-PC scans acquired in a static slice localized at the end-systolic valve position, and also ventricular stroke volumes (SVs) using both planimetry and 2D PC of the great vessels. RESULTS: The mean tricuspid valve systolic excursion was 17.8 ± 2.5 mm. The 2D valve-tracking PC net diastolic flow showed excellent correlation with SV by right-ventricle planimetry (bias ± 1.96 SD = -0.2 ± 10.4 mL, intraclass correlation coefficient [ICC] = 0.92) and aortic PC (-1.0 ± 13.8 mL, ICC = 0.87). In comparison, static tricuspid valve 2D PC also showed a strong correlation but had greater bias (p = 0.01) versus the right-ventricle SV (10.6 ± 16.1 mL, ICC = 0.61). In most (8 of 9) healthy subjects, trace regurgitation was measured at begin-systole. In one patient, valve-tracking PC displayed a high-velocity jet (380 cm/s) with maximal velocity agreeing with echocardiography. CONCLUSION: Automated valve-tracking 2D PC is a feasible route toward evaluation of tricuspid regurgitant velocities, potentially solving a major clinical challenge.

Capsaicin combined with stem cells improved mitochondrial dysfunction in PIG3V cells, an immortalized human vitiligo melanocyte cell line, by inhibiting the HSP70/TLR4/mTOR/FAK signaling axis.

BACKGROUND: Vitiligo is a common autoimmune skin disease. Capsaicin has been found to exert a positive effect on vitiligo treatment, and mesenchymal stem cells (MSCs) are also confirmed to be an ideal cell type. This study aimed to explore the influence of capsaicin combined with stem cells on the treatment of vitiligo and to confirm the molecular mechanism of capsaicin combined with stem cells in treating vitiligo. METHODS AND RESULTS: PIG3V cell proliferation and apoptosis were detected using CCK-8 and TUNEL assays, MitoSOX Red fluorescence staining was used to measure the mitochondrial ROS level, and JC-1 staining was used to detect the mitochondrial membrane potential. The expression of related genes and proteins was detected using RT‒qPCR and Western blotting. Coimmunoprecipitation was used to analyze the protein interactions between HSP70 and TLR4 or between TLR4 and mTOR. The results showed higher expression of HSP70 in PIG3V cells than in PIG1 cells. The overexpression of HSP70 reduced the proliferation of PIG3V cells, promoted apoptosis, and aggravated mitochondrial dysfunction and autophagy abnormalities. The expression of HSP70 could be inhibited by capsaicin combined with MSCs, which increased the levels of Tyr, Tyrp1 and DCT, promoted the proliferation of PIG3V cells, inhibited apoptosis, activated autophagy, and improved mitochondrial dysfunction. In addition, capsaicin combined with MSCs regulated the expression of TLR4 through HSP70 and subsequently affected the mTOR/FAK signaling pathway CONCLUSIONS: Capsaicin combined with MSCs inhibits TLR4 through HSP70, and the mTOR/FAK signaling pathway is inhibited to alleviate mitochondrial dysfunction and autophagy abnormalities in PIG3V cells.

Biological scaffold as potential platforms for stem cells: Current development and applications in wound healing.

Wound repair is a complex challenge for both clinical practitioners and researchers. Conventional approaches for wound repair have several limitations. Stem cell-based therapy has emerged as a novel strategy to address this issue, exhibiting significant potential for enhancing wound healing rates, improving wound quality, and promoting skin regeneration. However, the use of stem cells in skin regeneration presents several challenges. Recently, stem cells and biomaterials have been identified as crucial components of the wound-healing process. Combination therapy involving the development of biocompatible scaffolds, accompanying cells, multiple biological factors, and structures resembling the natural extracellular matrix (ECM) has gained considerable attention. Biological scaffolds encompass a range of biomaterials that serve as platforms for seeding stem cells, providing them with an environment conducive to growth, similar to that of the ECM. These scaffolds facilitate the delivery and application of stem cells for tissue regeneration and wound healing. This article provides a comprehensive review of the current developments and applications of biological scaffolds for stem cells in wound healing, emphasizing their capacity to facilitate stem cell adhesion, proliferation, differentiation, and paracrine functions. Additionally, we identify the pivotal characteristics of the scaffolds that contribute to enhanced cellular activity.

Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability.

The functional connectivity (FC) graph of the brain has been widely recognized as a ``fingerprint'' that can be used to identify individuals from a group of subjects. Research has indicated that individual identification accuracy can be improved by eliminating the impact of shared information among individuals. However, current research extracts not only shared information of inter-subject but also individual-specific information from FC graphs, resulting in incomplete separation of shared information and fingerprint information among individuals, leading to lower individual identification accuracy across all functional magnetic resonance imaging (fMRI) states session pairs and poor cognitive behavior prediction performance. In this paper, we propose a method to enhance inter-subject variability combining conditional variational autoencoder (CVAE) network and sparse dictionary learning (SDL) module. By embedding fMRI state information in the encoding and decoding processes, the CVAE network can better capture and represent the common features among individuals and enhance inter-subject variability by residual. Our experimental results on Human Connectome Project (HCP) data show that the refined connectomes obtained by using CVAE with SDL can accurately distinguish an individual from the remaining participants. The success accuracies reached 99.7 % and 99.6 % in the session pair rest1-rest2 and reverse rest2-rest1, respectively. In the identification experiment involving task-task combinations carried out on the same day, the identification accuracies ranged from 94.2 % to 98.8 %. Furthermore, we showed the Frontoparietal and Default networks make the most significant contributions to individual identification and the edges that significantly contribute to individual identification are found within and between the Frontoparietal and Default networks. Additionally, high-level cognitive behaviors can also be better predicted with the obtained refined connectomes, suggesting that higher fingerprinting can be useful for resulting in higher behavioral associations. In summary, our proposed framework provides a promising approach to use functional connectivity networks for studying cognition and behavior, promoting a deeper understanding of brain functions.

Red cell distribution width to total serum calcium ratio and in-hospital mortality risk in patients with acute ischemic stroke: A MIMIC-IV retrospective analysis.

We investigated the relationship among red cell distribution width (RDW), to total serum calcium (TSC) ratio (RCR), and in-hospital mortality in patients with acute ischemic stroke (AIS). This study was a retrospective analysis. The data of 2700 AIS patients was retrospectively analyzed from the Medical Information Mart for Intensive Care database (version IV). The main outcome of interest was in-hospital mortality. A Cox proportional hazards regression model was used to determine whether RCR was independently associated with in-hospital mortality. The Kaplan-Meier method was used to plot the survival curves for RCR. Subgroup analyses were performed to measure the mortality across various subgroups. The area under curve (AUC) of receiver operating characteristic curve (ROC) was calculated to ascertain the quality of RCR as a predictor of in-hospital mortality in patients with AIS. In the multivariate analysis, statistically significant differences were identified in age, ethnicity, length of ICU stay, mechanical ventilation, sequential organ failure assessment (SOFA) score, RDW, hemoglobin, RCR, whether taking anticoagulants, hyperlipidemia, and atrial fibrillation (P < .05). A threshold inflection point value of 1.83 was obtained through a two-piecewise regression model. There was a non-linear relationship between RCR and hospital mortality in patients with AIS. The hazard ratio (HR) and the 95% confidence intervals (CI) on the right and left of the inflection point were 0.93 (0.57-1.51; P = .7660) and 2.96 (1.37-6.42; P = .0060), respectively. The Kaplan-Meier curve indicated that survival rates were higher when RCR was ≤ 1.83 and lower when RDW was > 1.83 after adjustment for age, gender, BMI, ethnicity. The area under curve (AUC) of RCR was 0.715. A higher RCR was associated with an increased risk of in-hospital mortality in patients with AIS.

Modular multimodal hospital-home chain physical activity rehabilitation programme (3M2H-PARP) in liver cancer: a protocol for a randomised controlled trial.

INTRODUCTION: Patients with liver cancer are susceptible to experiencing a decline in muscle mass and function, which can lead to physical frailty and have a negative impact on prognosis. However, there is currently a lack of physical activity interventions specifically tailored for these patients. Therefore, we have developed a modular multimodal hospital-home chain physical activity rehabilitation programme (3M2H-PARP) designed specifically for patients with liver cancer undergoing transarterial chemoembolisation (TACE). We aim to validate the effectiveness and feasibility of this programme through a randomised controlled trial (RCT). METHODS AND ANALYSIS: 3M2H-PARP RCT will compare a 12-week, modular, multimodal physical activity rehabilitation programme that includes supervised exercise in a hospital setting and self-management exercise at home. The programmes consist of aerobic, resistance, flexibility and balance exercise modules, and standard survivorship care in a cohort of liver cancer survivors who have undergone TACE. The control group will receive standard care. A total of 152 participants will be randomly assigned to either the 3M2H-PARP group or the control group. Assessments will be conducted at three time points: baseline, after completing the intervention and a 24-week follow-up visit. The following variables will be evaluated: liver frailty index, Functional Assessment of Cancer Therapy-Hepatobiliary subscale, Cancer Fatigue Scale, Pittsburgh Sleep Quality Index, Hospital Anxiety and Depression Scale and physical activity level. After the completion of the training programme, semi-structured interviews will be conducted with participants from the 3M2H-PARP group to investigate the programme's impact on their overall well-being. SPSS V.26.0 software will be used for statistical analyses. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Jiangnan University School of Medicine Research Ethics Committee. The findings will be disseminated through publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ChiCTR2300076800.

Multi-Stimulus Least-Squares Transformation With Online Adaptation Scheme to Reduce Calibration Effort for SSVEP-Based BCIs.

Steady-state visual evoked potential (SSVEP), one of the most popular electroencephalography (EEG)-based brain-computer interface (BCI) paradigms, can achieve high performance using calibration-based recognition algorithms. As calibration-based recognition algorithms are time-consuming to collect calibration data, the least-squares transformation (LST) has been used to reduce the calibration effort for SSVEP-based BCI. However, the transformation matrices constructed by current LST methods are not precise enough, resulting in large differences between the transformed data and the real data of the target subject. This ultimately leads to the constructed spatial filters and reference templates not being effective enough. To address these issues, this paper proposes multi-stimulus LST with online adaptation scheme (ms-LST-OA). METHODS: The proposed ms-LST-OA consists of two parts. Firstly, to improve the precision of the transformation matrices, we propose the multi-stimulus LST (ms-LST) using cross-stimulus learning scheme as the cross-subject data transformation method. The ms-LST uses the data from neighboring stimuli to construct a higher precision transformation matrix for each stimulus to reduce the differences between transformed data and real data. Secondly, to further optimize the constructed spatial filters and reference templates, we use an online adaptation scheme to learn more features of the EEG signals of the target subject through an iterative process trial-by-trial. RESULTS: ms-LST-OA performance was measured for three datasets (Benchmark Dataset, BETA Dataset, and UCSD Dataset). Using few calibration data, the ITR of ms-LST-OA achieved 210.01±10.10 bits/min, 172.31±7.26 bits/min, and 139.04±14.90 bits/min for all three datasets, respectively. CONCLUSION: Using ms-LST-OA can reduce calibration effort for SSVEP-based BCIs.

The relationship between red cell distribution width, serum calcium ratio, and in-hospital mortality among patients with acute respiratory failure: A retrospective cohort study of the MIMIC-IV database.

To investigate the impact of RDW/CA (the ratio of red cell distribution width to calcium) on in-hospital mortality in patients with acute respiratory failure (ARF). This retrospective cohort study analyzed the data of 6981 ARF patients from the Medical Information Mart for Intensive Care (MIMIC-IV) database 2.0. Critically ill participants between 2008 and 2019 at the Beth Israel Deaconess Medical Center in Boston. The primary outcome of interest was in-hospital mortality. A Cox proportional hazards regression model was used to determine whether the RDW/CA ratio independently correlated with in-hospital mortality. The Kaplan-Meier method was used to plot the survival curves of the RDW/CA. Subgroup analyses were performed to measure the mortality across various subgroups. After adjusting for potential covariates, we found that a higher RDW/CA was associated with an increased risk of in-hospital mortality (HR = 1.17, 95% CI: 1.01-1.35, P = .0365) in ARF patients. A nonlinear relationship was observed between RDW/CA and in-hospital mortality, with an inflection point of 1.97. When RDW/CA ≥ 1.97 was positively correlated with in-hospital mortality in patients with ARF (HR = 1.554, 95% CI: 1.183-2.042, P = .0015). The Kaplan-Meier curve indicated the higher survival rates for RDW/CA < 1.97 and the lower for RDW/CA ≥ 1.97 after adjustment for age, gender, body mass index, and ethnicity. RDW/CA is an independent predictor of in-hospital mortality in patients with ARF. Furthermore, a nonlinear relationship was observed between RDW/CA and in-hospital mortality in patients with ARF.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we proposed an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules, and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

Isoliquiritigenin limits inflammasome activation of macrophage via docking into Syk to alleviate murine non-alcoholic fatty liver disease.

Isoliquiritigenin (ISL) is a chalcone-type flavonoid derived from the root of licorice with antioxidant, anti-inflammatory, anti-tumour and neuroprotective properties. ISL has been proven to downregulate the productions of IL-1ß, TNF-α and IL-6 by macrophages. However, detailed molecular mechanisms of this modulation remain elusive. Here, ISL suppressed Syk phosphorylation and CD80, CD86, IL-1ß, TNF-α and IL-6 expressions in lipopolysaccharide-stimulated macrophages ex vivo. ApoC3-transgenic (ApoC3TG) mice had more activated macrophages. ISL was also able to downregulate the inflammatory activities of macrophages from ApoC3TG mice. Administration of ISL inhibited Syk activation and inflammatory activities of macrophages in ApoC3TG mice in vivo. The treatment of ISL further alleviated MCD-induced non-alcoholic fatty liver disease (NAFLD) in wild-type and ApoC3TG mice, accompanied by less recruitment and activation of liver macrophages. Due to the inhibition of Syk phosphorylation, ISL-treated macrophages displayed less production of cytoplasmic ROS, NLRP3, cleaved-GSDMD and cleaved-IL-1ß, suggesting less inflammasome activation. Finally, the molecular docking study demonstrated that ISL bound to Syk directly with the Kd of 1.273 × 10-8 M. When the Syk expression was knocked down by its shRNA, the inhibitory effects of ISL on activated macrophages disappeared, indicating that Syk was at least one of key docking-molecules of ISL. Collectively, ISL could alleviate MCD-induced NAFLD in mice involved with the inhibition of macrophage inflammatory activity by the blockade of Syk-induced inflammasome activation.

Functional overlap between the mammalian Sar1a and Sar1b paralogs in vivo.

Proteins carrying a signal peptide and/or a transmembrane domain enter the intracellular secretory pathway at the endoplasmic reticulum (ER) and are transported to the Golgi apparatus via COPII vesicles or tubules. SAR1 initiates COPII coat assembly by recruiting other coat proteins to the ER membrane. Mammalian genomes encode two SAR1 paralogs, SAR1A and SAR1B. While these paralogs exhibit ~90% amino acid sequence identity, it is unknown whether they perform distinct or overlapping functions in vivo. We now report that genetic inactivation of Sar1a in mice results in lethality during midembryogenesis. We also confirm previous reports that complete deficiency of murine Sar1b results in perinatal lethality. In contrast, we demonstrate that deletion of Sar1b restricted to hepatocytes is compatible with survival, though resulting in hypocholesterolemia that can be rescued by adenovirus-mediated overexpression of either SAR1A or SAR1B. To further examine the in vivo function of these two paralogs, we genetically engineered mice with the Sar1a coding sequence replacing that of Sar1b at the endogenous Sar1b locus. Mice homozygous for this allele survive to adulthood and are phenotypically normal, demonstrating complete or near-complete overlap in function between the two SAR1 protein paralogs in mice. These data also suggest upregulation of SAR1A gene expression as a potential approach for the treatment of SAR1B deficiency (chylomicron retention disease) in humans.

Repressing miR-23a promotes the transdifferentiation of pancreatic α cells to ß cells via negatively regulating the expression of SDF-1α.

Pancreatic ß-cell failure is a pathological feature in type 1 diabetes. One promising approach involves inducing transdifferentiation of related pancreatic cell types, specifically α cells that produce glucagon. The chemokine stromal cell-derived factor-1 alpha (SDF-1α) is implicated in pancreatic α-to-ß like cell transition. Here, the serum level of SDF-1α was lower in T1D with C-peptide loss, the miR-23a was negatively correlated with SDF-1α. We discovered that exosomal miR-23a, secreted from ß cells, functionally downregulates the expression of SDF-1α, leading to increased Pax4 expression and decreased Arx expression in vivo. Adenovirus-vectored miR-23a sponge and mimic were constructed to further explored the miR-23a on pancreatic α-to-ß like cell transition in vitro, which yielded results consistent with our cell-based assays. Suppression of miR-23a upregulated insulin level and downregulated glucagon level in STZ-induced diabetes mice models, effectively promoting α-to-ß like cell transition. Our findings highlight miR-23a as a new therapeutic target for regenerating pancreatic ß cells from α cells.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Heterometallic MIL-125(Ti-Al) frameworks for electrochemical determination of ascorbic acid, dopamine and uric acid.

The detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) is not only of great significance in the areas of biomedicine and neurochemistry but also helpful in disease diagnosis and pathology research. Due to their diverse structures, designability, and large specific surface areas, metal-organic frameworks (MOFs) have recently caught considerable attention in the electrochemical field. Herein, a family of heterometallic MOFs with amino modification, MIL-125(Ti-Al)-xNH2 (x = 0%, 25%, 50%, 75%, and 100%), were synthesized and employed as electrochemical sensors for the detection of AA, DA, and UA. Among them, MIL-125(Ti-Al)-75%NH2 exhibited the most promising electrochemical behavior with 40% doping of carbon black in 0.1 M PBS (pH = 7.10), which displayed individual detection performance with wide linear detection ranges (1.0-6.5 mM for AA, 5-100 µM for DA and 5-120 µM for UA) and low limits of detection (0.215 mM for AA, 0.086 µM for DA, and 0.876 µM for UA, S/N = 3). Furthermore, the as-prepared MIL-125(Ti-Al)-75%NH2/GCE provided a promising platform for future application in real sample analysis, owing to its excellent anti-interference performance and good stability.

Visualization Analysis of Artificial Intelligence Literature in Forensic Research.

OBJECTIVES: To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database, to explore research hotspots and developmental trends. METHODS: A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the literature measuring tool CiteSpace. The authors, institution, country (region), title, journal, keywords, cited references and other information of relevant literatures were analyzed. RESULTS: A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries (regions) were identified, with the number of articles published showing an increasing trend year by year. Among them, the United States had the highest number of publications and China ranked the second. Academy of Forensic Science had the highest number of publications among the institutions. Forensic Science International, Journal of Forensic Sciences, International Journal of Legal Medicine ranked high in publication and citation frequency. Through the analysis of keywords, it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technology for sex and age estimation, cause of death analysis, postmortem interval estimation, individual identification and so on. CONCLUSIONS: It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research. Exploring the combination of advanced artificial intelligence technologies with forensic research will be a hotspot and direction for future research.

Sex differences in mortality and liver-related events in non-alcoholic fatty liver disease: A systematic review and meta-analysis.

BACKGROUND & AIMS: Many systematic reviews explore the association of non-alcoholic fatty liver disease (NAFLD) with mortality, but none of them explores sex-based differences in detail. We aimed to assess whether NAFLD is associated with cause-specific mortality, all-cause mortality, and cancer incidence in both men and women. METHODS: The PubMed, Embase, and Medline databases were searched from inception through April 2023 for eligible studies. We separately pooled relative risks (RRs) for men and women using a random effects model. Subsequently, the RRs and 95% CIs (confidence intervals) in each study were used to calculate the women-to-men ratio of RRs (RRR). Furthermore, subgroup analyses were performed to explore the robustness of outcomes. The random-effects model was employed to conduct sensitivity analyses to determine the impact of specific studies on the overall findings. RESULTS: The meta-analysis included nine cohort studies comprising 557 614 patients with NAFLD were chosen. Women were 44% more likely than men to get cancer among those with NAFLD (RRR: 1.44; 95% CI: 1.02-2.04; p = .039). However, no sex-related differences were observed between NAFLD and all-cause mortality (RRR: 1.06; 95% CI: 0.56-2.01; p = .861), liver-related mortality (RRR: 1.06; 95% CI: 0.02-69.82; p = .977), cardiovascular mortality (RRR: 1; 95% CI: 0.65-1.53; p = .987) and liver cancer (RRR: 0.76; 95% CI: 0.43-1.36; p = .36). CONCLUSIONS: There may be sex variations between NAFLD and the risk of cancer, with the connection being stronger in females than in males.

Exploring the effect of disc displacement on the risk and severity of condylar erosion in adult temporomandibular disorder patients: A CBCT and MRI study.

OBJECTIVE: The objective of the study was to investigate the relationship between types of disc displacement (DD) diagnosed by magnetic resonance imaging (MRI), and the risk (presence or absence) and severity of condylar erosion (CE) graded using cone-beam computed tomography (CBCT) in adult Temporomandibular disorders (TMD) patients. METHODS: A total of 353 TMD patients (283 females, 70 males) underwent MRI scans to categorise DD as normal (NA), anterior displacement with reduction (ADDR), or anterior displacement without reduction (ADDNR). CE severity was graded on a scale of 0-3 (absence, mild, moderate or severe) using CBCT. To establish the plausibility and cut-off points for CE diagnosis, the severity of CE was then further divided into three classifications: Grade 0 versus 1 + 2 + 3; Grades 0 + 1 versus 2 + 3; Grades 0 + 1 + 2 versus 3. Logistic regression analysis was performed, adjusting for age, gender and joint correlation. RESULTS: ADDNR significantly increased the risk of CE compared with NA (OR = 10.04, 95% CI: [6.41, 15.73]) and showed a significant increase in CE severity across all classifications (ORs = 10.04-18.95). The effects of ADDNR were significant in both genders (p < .001) and had a greater impact in females. ADDR was predominantly associated with mild CE. CONCLUSIONS: ADDNR significantly increased the risk and severity of CE independent of gender when compared to NA, whereas ADDR was mainly associated with mild CE. Slight cortical discontinuity may represent a subclinical diagnosis requiring further investigation.

Functional overlap between the mammalian Sar1a and Sar1b paralogs in vivo.

Proteins carrying a signal peptide and/or a transmembrane domain enter the intracellular secretory pathway at the endoplasmic reticulum (ER) and are transported to the Golgi apparatus via COPII vesicles or tubules. SAR1 initiates COPII coat assembly by recruiting other coat proteins to the ER membrane. Mammalian genomes encode two SAR1 paralogs, SAR1A and SAR1B. While these paralogs exhibit ~90% amino acid sequence identity, it is unknown whether they perform distinct or overlapping functions in vivo. We now report that genetic inactivation of Sar1a in mice results in lethality during mid-embryogenesis. We also confirm previous reports that complete deficiency of murine Sar1b results in perinatal lethality. In contrast, we demonstrate that deletion of Sar1b restricted to hepatocytes is compatible with survival, though resulting in hypocholesterolemia that can be rescued by adenovirus-mediated overexpression of either SAR1A or SAR1B. To further examine the in vivo function of these 2 paralogs, we genetically engineered mice with the Sar1a coding sequence replacing that of Sar1b at the endogenous Sar1b locus. Mice homozygous for this allele survive to adulthood and are phenotypically normal, demonstrating complete or near-complete overlap in function between the two SAR1 protein paralogs in mice. These data also suggest upregulation of SAR1A gene expression as a potential approach for the treatment of SAR1B deficiency (chylomicron retention disease) in humans.

Repetitive peripheral magnetic stimulation combined with transcranial magnetic stimulation in rehabilitation of upper extremity hemiparesis following stroke: a pilot study.

OBJECTIVE: To investigate the effect of combined repetitive peripheral magnetic stimulation and transcranial magnetic stimulation on upper extremity function in subacute stroke patients. DESIGN: Pilot study. SUBJECTS: Subacute stroke patients. METHODS: Included patients were randomized into 3 groups: a central-associated peripheral stimulation (CPS) group, a central-stimulation-only (CS) group, and a control (C) group. The CPS group underwent a new paired associative stimulation (combined repetitive peripheral magnetic stimulation and transcranial magnetic stimulation), the CS group underwent repetitive transcranial magnetic stimulation, and the C group underwent sham stimulation. All 3 groups received physiotherapy after the stimulation or sham stimulation. The treatment comprised 20 once-daily sessions. Primary outcome was the Fugl-Meyer Assessment Upper Extremity (FMA-UE) score, and secondary outcomes were the Barthel Index and Comprehensive Functional Assessment scores, and neurophysiological assessments were mainly short-interval intracortical inhibition. A 3-group (CPS, CS, C) × 2-time (before, after intervention) repeated measures analysis of variance was conducted to determine whether changes in scores were significantly different between the 3 groups. RESULTS: A total of 45 patients were included in the analysis. Between-group comparisons on the FMA-UE demonstrated a significant improvement (group × time interaction, F2,42 = 4.86; p = 0.013; C vs CS, p = 0.020; C vs CPS, p = 0.016; CS vs CPS, p = 0.955). Correlation analysis did not find any substantial positive correlation between changes in FMA-UE and short-interval intracortical inhibition variables (C, r = -0.196, p = 0.483; CS, r = -0.169, p = 0.546; CPS, r = -0.424, p = 0.115). CONCLUSION: This study suggests that the real-stimulus (CS and CPS) groups had better outcomes than the control (C) group. In addition, the CPS group showed a better trend in clinical and neurophysiological assessments compared with the CS group.

Leptin receptor deficiency impedes metabolic surgery related-weight loss through inhibition of energy expenditure in db/db mice.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is an effective metabolic surgery against diabetes and obesity. Clinical evidence indicates that patients with severe obesity have a poor curative effect in losing weight if they suffer from leptin or its receptor deficiency, but the underlying mechanism remains elusive. Here, we investigated the effect of leptin receptor deficiency on metabolic dysfunction in db/db mice treated by RYGB surgery. METHODS: The db/db mice and their heterozygote control db/m mice were subjected to RYGB or sham surgery. Body weight, blood glucose, food intake and glucose tolerance were evaluated. Micro-PET/CT and histological analysis were performed to examine the glucose uptake of tissues and the fat changes in mice. The key factors in glucose and fatty acid metabolism were detected by western blot analysis. RESULTS: Compared with the sham group, the db/db mice in the RYGB group showed more significant weight regain after surgical recovery and improvement in hyperinsulinemia and glucose tolerance. However, the total body fat and multiple organ lipid deposition of RYGB-treated db/db mice was increased. The underlying mechanism studies suggested that the activation of AMPK regulated GLUT4 to increase glucose uptake, but AMPK could not promote fatty acid oxidation through the JAK2/STAT3 pathway under leptin receptor deficiency in db/db mice. CONCLUSION: We conclude that leptin receptor deficiency impedes the AMPK activation-mediated fat catabolism but does not affect AMPK-related glucose utilization after metabolic surgery in db/db mice. This result helps select surgical indications for patients with obesity and diabetes.