Multimodal neuroimaging network associated with executive function in adolescent major depressive disorder patients via cognition-guided magnetic resonance imaging fusion.

Adolescents are high-risk population for major depressive disorder. Executive dysfunction emerges as a common feature of depression and exerts a significant influence on the social functionality of adolescents. This study aimed to identify the multimodal co-varying brain network related to executive function in adolescent with major depressive disorder. A total of 24 adolescent major depressive disorder patients and 43 healthy controls were included and completed the Intra-Extra Dimensional Set Shift Task. Multimodal neuroimaging data, including the amplitude of low-frequency fluctuations from resting-state functional magnetic resonance imaging and gray matter volume from structural magnetic resonance imaging, were combined with executive function using a supervised fusion method named multimodal canonical correlation analysis with reference plus joint independent component analysis. The major depressive disorder showed more total errors than the healthy controls in the Intra-Extra Dimensional Set Shift task. Their performance on the Intra-Extra Dimensional Set Shift Task was negatively related to the 14-item Hamilton Rating Scale for Anxiety score. We discovered an executive function-related multimodal fronto-occipito-temporal network with lower amplitude of low-frequency fluctuation and gray matter volume loadings in major depressive disorder. The gray matter component of the identified network was negatively related to errors made in Intra-Extra Dimensional Set Shift while positively related to stages completed. These findings may help to deepen our understanding of the pathophysiological mechanisms of cognitive dysfunction in adolescent depression.

Single-cell RNA sequencing and immune repertoire analysis revealed dynamic immune characteristics associated with peripheral blood during sepsis.

Sepsis is a potentially fatal condition arising from an abnormal immune response to an infection, which can result in organ failure and even death. To explore the mechanism underlying the dysregulated immune response during sepsis and identify potential therapeutic targets, single-cell RNA sequencing (scRNA-seq) and immune repertoire analysis were conducted to depict the cellular landscape of peripheral blood cells in septic mice. We observed significant alterations in the number and proportion of peripheral blood cell populations driven by sepsis. By combining single-cell gene expression profiles and B cell receptor (BCR) repertoire analysis, we discerned that infection inflicted serious damage on the antigen presentation ability of B cells and the diversity of BCR in a short time. In addition, we found that the cecal ligation and puncture procedure in mice inhibited the communication signals of CD4+ and CD8+ T cells and decreased the interactions between B cells and other cells. Our study provides detailed insights into the dynamic changes in the biological characteristics of peripheral blood cells driven by sepsis and provides important advances in our understanding of immune disorders during sepsis.

Differential effects of sleep deprivation on behavior and microglia in a brain-region-specific manner in young and aged male mice.

Microglia, resident immune cells in the central nervous system, constantly monitor the state of the surrounding brain activity. The animal model induced by sleep deprivation (SD) is widely used to study the pathophysiological mechanisms of insomnia and bipolar disorder. However, it remains unclear whether SD affects behaviors in young and aged male mice and microglia in various brain regions. In this study, we confirmed brain region-specific changes in microglial density and morphology in the accumbens nucleus (Acb), amygdala (AMY), cerebellum (Cb), corpus callosum (cc), caudate putamen, hippocampus (HIP), hypothalamus (HYP), medial prefrontal cortex (mPFC), and thalamus (TH) of young mice. In addition, the density of microglia in old mice was higher than that in young mice. Compared with young mice, old mice showed a markedly increased microglial size, decreased total length of microglial processes, and decreased maximum length. Importantly, we found that 48-h SD decreased microglial density and morphology in old mice, whereas SD increased microglial density and morphology in most observed brain regions in young mice. SD-induced hyperactivity was observed only in young mice but not in old mice. Moreover, microglial density (HIP, AMY, mPFC, CPu) was significantly positively correlated with behaviors in SD- and vehicle-treated young mice. Contrarily, negative correlations were shown between the microglial density (cc, Cb, TH, HYP, Acb, AMY) and behaviors in vehicle-treated young and old mice. These results suggest that SD dysregulates the homeostatic state of microglia in a region- and age-dependent manner. Microglia may be involved in regulating age-related behavioral responses to SD.

The Reduced Gray Matter Volume and Functional Connectivity of the Cerebellum in Type 2 Diabetes Mellitus with High Insulin Resistance.

INTRODUCTION: Insulin resistance is widely thought to be a critical feature in type 2 diabetes mellitus (T2DM), and there is significant evidence indicating a higher abundance of insulin receptors in the human cerebellum than cerebrum. However, the specific structural or functional changes in the cerebellum related to T2DM remain unclear, and the association between cerebellar alterations, insulin resistance, cognition, and emotion is yet to be determined. METHODS: We investigated neuropsychological performance, and structural and functional changes in specific cerebellar subregions in 43 T2DM patients with high insulin resistance (T2DM-highIR), 72 T2DM patients with low insulin resistance (T2DM-lowIR), and 50 controls. Furthermore, the correlation and stepwise multiple linear regression analysis were performed. RESULTS: Compared to the controls, T2DM exhibited lower cognitive scores and higher depressive/anxious scores. Furthermore, T2DM-highIR patients showed reduced gray matter volume (GMV) in the right cerebellar lobules VIIb, Crus I/II, and T2DM showed reduced GMV in left lobules I-IV compared to controls. Additionally, functional connectivity decrease was observed between the right lobules I-V and orbital part of the superior frontal gyrus in T2DM-highIR compared to both T2DM-lowIR and controls. Notably, there were negative correlations between the GMV of the lobules VIIb, Crus I/II, and updated homeostatic model assessment of insulin resistance, and positive correlation with executive/visuospatial performance in T2DM patients. CONCLUSIONS: These results suggest that the cerebellar lobules VIIb, Crus I/II, represent vulnerable brain regions in the context of insulin resistance. Overall, this study offers new insights into the neuropathophysiological mechanisms of brain impairment in patients with T2DM.

Nanomaterial-related hemoglobin-based oxygen carriers, with emphasis on liposome and nano-capsules, for biomedical applications: current status and future perspectives.

Oxygen is necessary for life and plays a key pivotal in maintaining normal physiological functions and treat of diseases. Hemoglobin-based oxygen carriers (HBOCs) have been studied and developed as a replacement for red blood cells (RBCs) in oxygen transport due to their similar oxygen-carrying capacities. However, applications of HBOCs are hindered by vasoactivity, oxidative toxicity, and a relatively short circulatory half-life. With advancements in nanotechnology, Hb encapsulation, absorption, bioconjugation, entrapment, and attachment to nanomaterials have been used to prepare nanomaterial-related HBOCs to address these challenges and pend their application in several biomedical and therapeutic contexts. This review focuses on the progress of this class of nanomaterial-related HBOCs in the fields of hemorrhagic shock, ischemic stroke, cancer, and wound healing, and speculates on future research directions. The advancements in nanomaterial-related HBOCs are expected to lead significant breakthroughs in blood substitutes, enabling their widespread use in the treatment of clinical diseases.

NLRP4E regulates actin cap formation through SRC and CDC42 during oocyte meiosis.

BACKGROUND: Members of the nucleotide-binding oligomerization domain, leucine rich repeat and pyrin domain containing (NLRP) family regulate various physiological and pathological processes. However, none have been shown to regulate actin cap formation or spindle translocation during the asymmetric division of oocyte meiosis I. NLRP4E has been reported as a candidate protein in female fertility, but its function is unknown. METHODS: Immunofluorescence, reverse transcription polymerase chain reaction (RT-PCR), and western blotting were employed to examine the localization and expression levels of NLRP4E and related proteins in mouse oocytes. small interfering RNA (siRNA) and antibody transfection were used to knock down NLRP4E and other proteins. Immunoprecipitation (IP)-mass spectrometry was used to identify the potential proteins interacting with NLRP4E. Coimmunoprecipitation (Co-IP) was used to verify the protein interactions. Wild type (WT) or mutant NLRP4E messenger RNA (mRNA) was injected into oocytes for rescue experiments. In vitro phosphorylation was employed to examine the activation of steroid receptor coactivator (SRC) by NLRP4E. RESULTS: NLRP4E was more predominant within oocytes compared with other NLRP4 members. NLRP4E knockdown significantly inhibited actin cap formation and spindle translocation toward the cap region, resulting in the failure of polar body extrusion at the end of meiosis I. Mechanistically, GRIN1, and GANO1 activated NLRP4E by phosphorylation at Ser429 and Thr430; p-NLRP4E is translocated and is accumulated in the actin cap region during spindle translocation. Next, we found that p-NLRP4E directly phosphorylated SRC at Tyr418, while p-SRC negatively regulated p-CDC42-S71, an inactive form of CDC42 that promotes actin cap formation and spindle translocation in the GTP-bound form. CONCLUSIONS: NLRP4E activated by GRIN1 and GANO1 regulates actin cap formation and spindle translocation toward the cap region through upregulation of p-SRC-Tyr418 and downregulation of p-CDC42-S71 during meiosis I.

Development of a machine learning model and nomogram to predict seizures in children with COVID-19: a two-center study.

OBJECTIVE: This study aimed to use machine learning to evaluate the risk factors of seizures and develop a model and nomogram to predict seizures in children with coronavirus disease 2019 (COVID-19). MATERIAL AND METHODS: A total of 519 children with COVID-19 were assessed to develop predictive models using machine learning algorithms, including extreme gradient boosting (XGBoost), random forest (RF) and logistic regression (LR). The performance of the models was assessed using area under the receiver operating characteristic curve (AUC) values. Importance matrix plot and SHapley Additive exPlanations (SHAP) values were calculated to evaluate feature importance and to show the visualization results. The nomogram and clinical impact curve were used to validate the final model. RESULTS: Two hundred and seventeen children with COVID-19 had seizures. According to the AUC, the RF model performed the best. Based on the SHAP values, the top three most important variables in the RF model were neutrophil percentage, cough and fever duration. The nomogram and clinical impact curve also verified that the RF model possessed significant predictive value. CONCLUSIONS: Our research indicates that the RF model demonstrates excellent performance in predicting seizures, and our novel nomogram can facilitate clinical decision-making and potentially offer benefit for clinicians to prevent and treat seizures in children with COVID-19.

Two-Layer Edge Intelligence for Task Offloading and Computing Capacity Allocation with UAV Assistance in Vehicular Networks.

With the exponential growth of wireless devices and the demand for real-time processing, traditional server architectures face challenges in meeting the ever-increasing computational requirements. This paper proposes a collaborative edge computing framework to offload and process tasks efficiently in such environments. By equipping a moving unmanned aerial vehicle (UAV) as the mobile edge computing (MEC) server, the proposed architecture aims to release the burden on roadside units (RSUs) servers. Specifically, we propose a two-layer edge intelligence scheme to allocate network computing resources. The first layer intelligently offloads and allocates tasks generated by wireless devices in the vehicular system, and the second layer utilizes the partially observable stochastic game (POSG), solved by duelling deep Q-learning, to allocate the computing resources of each processing node (PN) to different tasks. Meanwhile, we propose a weighted position optimization algorithm for the UAV movement in the system to facilitate task offloading and task processing. Simulation results demonstrate the improved performance by applying the proposed scheme.

Development of an MRI-Based Radiomics-Clinical Model to Diagnose Liver Fibrosis Secondary to Pancreaticobiliary Maljunction in Children.

BACKGROUND: Preoperative diagnosis of liver fibrosis in children with pancreaticobiliary maljunction (PBM) is needed to guide clinical decision-making and improve patient prognosis. PURPOSE: To develop and validate an MR-based radiomics-clinical nomogram for identifying liver fibrosis in children with PBM. STUDY TYPE: Retrospective. POPULATION: A total of 136 patients with PBM from two centers (center A: 111 patients; center B: 25 patients). Cases from center A were randomly divided into training (74 patients) and internal validation (37 patients) sets. Cases from center B were assigned to the external validation set. Liver fibrosis was determined by histopathological examination. FIELD STRENGTH/SEQUENCE: A 3.0 T (two vendors)/T1-weighted imaging and T2-weighted imaging. ASSESSMENT: Clinical factors associated with liver fibrosis were evaluated. A total of 3562 radiomics features were extracted from segmented liver parenchyma. Maximum relevance minimum redundancy and least absolute shrinkage and selection operator were recruited to screen radiomics features. Based on the selected variables, multivariate logistic regression was used to construct the clinical model, radiomics model, and combined model. The combined model was visualized as a nomogram to show the impact of the radiomics signature and key clinical factors on the individual risk of developing liver fibrosis. STATISTICAL TESTS: Mann-Whitney U and chi-squared tests were used to compare clinical factors. P < 0.05 was considered statistically significant in the final models. RESULTS: Two clinical factors and four radiomics features were selected as they were associated with liver fibrosis in the training (AUC, 0.723, 0.927), internal validation (AUC, 0.718, 0.885), and external validation (AUC, 0.737, 0.865) sets. The radiomics-clinical nomogram yielded the best performance in the training (AUC, 0.977), internal validation (AUC, 0.921), and external validation (AUC, 0.878) sets, with good calibration (P > 0.05). DATA CONCLUSION: Our radiomic-based nomogram is a noninvasive, accurate, and preoperative diagnostic tool that is able to detect liver fibrosis in PBM children. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Alterations of Spontaneous Cortical and Subcortical Activity in Type 2 Diabetes Mellitus with and without Depression.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) patients with depression have a higher risk of complications and mortality than T2DM without depression. However, the exact neuropathophysiological mechanism remains unclear. Consequently, the current study aimed to investigate the alteration of cortical and subcortical spontaneous neural activity in T2DM patients with and without depression. METHODS: The demographic data, clinical variables, neuropsychological tests, and functional and anatomical magnetic resonance imaging of depressed T2DM (n = 47) of non-depressed T2DM (n = 59) and healthy controls (n = 41) were collected and evaluated. The correlation analysis, stepwise multiple linear regression, and receiver operating characteristic curve were performed for further analysis. RESULTS: Abnormal neural activities in the bilateral posterior cingulate cortex (PCC) and hippocampus were observed in depressed and non-depressed T2DM and the right putamen of the depressed T2DM. Interestingly, the subcortical degree centrality (DC) of the right hippocampus and putamen were higher in depressed than non-depressed T2DM. Furthermore, the cortical amplitude of low-frequency fluctuation (ALFF) in PCC, subcortical DC in the putamen of depressed T2DM, and hippocampus of non-depressed T2DM was correlated with cognitive scores. In contrast, the cortical fractional ALFF in PCC of non-depressed T2DM was correlated with depression scores. CONCLUSIONS: The abnormalities of spontaneous cortical activity in PCC and subcortical activity in the hippocampus might represent the neurobiological feature of cerebral dysfunction in T2DM. Notably, the altered subcortical activity in the right putamen might mainly associate with negative emotion in T2DM, which could be a promising biomarker for recognizing early cerebral dysfunction in depressed T2DM. This study provided a novel insight into the neuropathophysiological mechanism of brain dysfunction in T2DM with and without depression.

Expression and function of myelin expression factor 2 in hepatocellular carcinoma.

INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the most common malignant tumours in the world and has a high mortality rate. However, the pathogenesis of HCC remains unclear. This study aimed to investigate the potential biomarkers of HCC. METHODS: ONCOMINE, HCCDB and THE HUMAN PROTEIN ATLAS were used to identify myelin expression factor 2 (MYEF2) as a potential biomarker for HCC. The Cancer Genome Atlas database was used to further validate and analyse the value of MYEF2. Kaplan-Meier Plotter was used for the prognostic analysis. The COX regression model and Kaplan-Meier method were used to investigate the clinical value of MYEF2 in the prognosis of HCC by reviewing the survival status of patients. Fluorescent quantitative polymerase chain reaction (qPCR) and immunohistochemistry were used to detect the expressions of the MYEF2 mRNA and protein in HCC tissues and cell lines. qPCR and Western blotting were used to validate the efficiency of MYEF2 knockout and overexpression in HCC cells. The invasion and migration abilities regulated by MYEF2 were detected by performing transwell and wound healing assays. RESULTS: MYEF2 is significantly upregulated in HCC and is mainly located in the nucleus of HCC cells. MYEF2 expression is significantly associated with the tumour stage, histological grade and TNM stage. High MYEF2 expression is an independent prognostic factor for patients with HCC. Functionally, elevated MYEF2 facilitated cell migration and invasion in vitro. In contrast, decreased MYEF2 inhibited cell migration and invasion. CONCLUSIONS: MYEF2 may be a novel biomarker with potential diagnosis and prognosis values and as a potential therapeutic target for HCC.

Identification and validation of radiomic features from computed tomography for preoperative classification of neuroblastic tumors in children.

BACKGROUND: To identify radiomic features that can predict the pathological type of neuroblastic tumor in children. METHODS: Data on neuroblastic tumors in 104 children were retrospectively analyzed. There were 14 cases of ganglioneuroma, 24 cases of ganglioneuroblastoma, and 65 cases of neuroblastoma. Stratified sampling was used to randomly allocate the cases into the training and validation sets in a ratio of 3:1. The maximum relevance-minimum redundancy algorithm was used to identify the top 10 of two clinical features and 851 radiomic features in portal venous-phase contrast-enhanced computed tomography images. Least absolute shrinkage and selection operator regression was used to classify tumors in two binary steps: first as ganglioneuroma compared to the other two types, then as ganglioneuroblastoma compared to neuroblastoma. RESULTS: Based on 10 clinical-radiomic features, the classifier identified ganglioneuroma compared to the other two tumor types in the validation dataset with sensitivity of 100.0%, specificity of 81.8%, and an area under the receiver operating characteristic curve (AUC) of 0.875. The classifier identified ganglioneuroblastoma versus neuroblastoma with a sensitivity of 83.3%, a specificity of 87.5%, and an AUC of 0.854. The overall accuracy of the classifier across all three types of tumors was 80.8%. CONCLUSION: Radiomic features can help predict the pathological type of neuroblastic tumors in children.

Clinical Effect of Rehabilitation New Fluid Combined with Sanjie Analgesic Capsules in the Treatment of Granulomatous Mastitis and Thyroiditis and Impact on Immune Indexes of Patients.

Objective: To analyze the clinical effect of rehabilitation new fluid combined with Sanjie analgesic capsules in the treatment of granulomatous lobular mastitis (GLM) and thyroiditis and the impact on immune indexes of patients. Methods: For a retrospective study, we selected 150 patients with GLM and 150 patients with thyroiditis admitted to The Fourth Hospital of Shijiazhuang from January 2021 to January 2022. We divided them into three groups based on the treatment methods. Control group 1 (CG1) included patients treated with rehabilitation new fluid alone, while control group 2 (CG2) included patients treated with the Sanjie analgesic capsules alone. The third group, the observation group (OG), included patients treated with rehabilitation new fluid (extract of drying body from Periplaneta americana) at an oral dose of 10 ml combined with Sanjie analgesic capsules. There were 50 patients in each group. The clinical efficacy, symptom improvement, the level changes of free triiodothyronine (FT3), free tetraiodothyronine (FT4), and thyroid stimulating hormone (TSH), and the changes of immune indexes such as CD4+ (cluster of differentiation 4+), CD25+ (cluster of differentiation 25+), CD68+ (cluster of differentiation 68+) and CD138+ (cluster of differentiation 138+) were analyzed. Results: After treatment, the total treatment effectiveness of GLM in the OG was 94%, which was significantly higher than 80% in the CG1 and 78% in the CG2 (P = .037, .021), while the total treatment effectiveness of thyroiditis in the OG was 92%, which was significantly higher than 76% in the CG1 and 74% in the CG2 (P = .029, 0.017). The scores of breast pain, breast overflow, tumor size, local skin changes, and axillary fossa lymphadenectasis of the affected side in the OG of GLM were better than those in CG1 (Pbreast pain < .001, 95%CI: 0.573-1.747; Pbreast overflow = .022, 95%CI: 0.074-0.905; Ptumor size = .008, 95%CI: 0.231-1.489; Plocal skin changes = .001, 95%CI: 0.382-1.498; Paxillary fossa lymphadenectasis of the affected side = .011, 95%CI: 0.096-0.704) and CG2 (Pbreast pain = .001, 95%CI: 0.449-1.711; Pbreast overflow = .049, 95%CI: 0.002-0.798; Ptumor size =0.019, 95%CI: 0.132-1.428; Plocal skin changes < .001, 95%CI: 0.563-1.517; Paxillary fossa lymphadenectasis of the affected side = .001, 95%CI: 0.202-0.678). The levels of FT3 and FT4 in the OG of thyroiditis were higher than CG1 (PFT3 < .001, 95%CI: 0.951-1.590; PFT4 < .001, 95%CI: 1.421-2.618) and CG2 (PFT3 < .001, 95%CI: 0.943-1.643; PFT4 < .001, 95%CI: 1.521-2.758), and the TSH level was lower compared with CG1 (PTSH < .001, 95%CI: 2.409-3.070) and CG2 (PTSH < .001, 95%CI: 2.540-3.230). The immune indexes of GLM were improved, and the levels of CD4+, CD25+, CD68+, and CD138+ in the OG were better than those in the CG1 (PCD4+ < .001, 95%CI: 2.967-4.912; PCD25+ < .001, 95%CI: 3.707-5.212; PCD68+ < .001, 95%CI: 1.445-2.200; PCD138+ < .001, 95%CI: 3.922-5.510) and CG2 (PCD4+ < .001, 95%CI: 3.093-4.995; PCD25+ < .001, 95%CI: 3.527-4.904; PCD68+ < .001, 95%CI: 1.334-2.216; PCD138+ < .001, 95%CI: 3.878-5.352). The immune indexes of thyroiditis were improved, and the levels of CD4+, CD25+, CD68+, and CD138+ in the OG were better than those in the CG1 (PCD4+ < .001, 95%CI: 4.235-6.117; PCD25+ < .001, 95%CI: 3.300-4.810; PCD68+ < .001, 95%CI: 1.173-1.939; PCD138+ < .001, 95%CI: 3.704-4.881) and CG2 (PCD4+ < .001, 95%CI: 3.136-5.422; PCD25+ < .001, 95%CI: 3.182-4.615; PCD68+ < .001, 95%CI: 1.216-2.113; PCD138+ < .001, 95%CI: 4.145-5.527). Conclusion: The clinical effect of rehabilitation new fluid combined with Sanjie analgesic capsule in the treatment of GLM and thyroiditis is remarkable, which enables enhancement of the treatment efficiency, and improves patients' clinical symptoms, functional indexes, and the levels of immune indexes, as a direction for the follow-up treatment in the clinic.

Using machine learning models to predict acute pancreatitis in children with pancreaticobiliary maljunction.

PURPOSE: To develop a model to identify risk factors and predictors of acute pancreatitis in children with pancreaticobiliary maljunction (PBM). METHODS: We screened consecutive PBM patients treated at two centers between January, 2015 and July, 2021. For machine learning, the cohort was divided randomly at a 6:4 ratio to a training dataset and a validation dataset. Three parallel models were developed using logistic regression (LR), a support vector machine (SVM), and extreme gradient boosting (XGBoost), respectively. Model performance was judged primarily based on the area under the receiver operating curves (AUC). RESULTS: A total of 99 patients were included in the analysis, 17 of whom suffered acute pancreatitis and 82 did not. The XGBoost (AUC = 0.814) and SVM (AUC = 0.813) models produced similar performance in the validation dataset; both outperformed the LR model (AUC = 0.805). Based on the SHapley Additive exPlanation values, the most important variable in both the XGBoost and SVM models were age, protein plugs, and white blood cell count. CONCLUSIONS: Machine learning models, especially XGBoost and SVM, could be used to predict acute pancreatitis in children with PBM. The most important contributing factor to the models were age, protein plugs, and white blood cell count.

Resveratrol, a New Allosteric Effector of Hemoglobin, Enhances Oxygen Supply Efficiency and Improves Adaption to Acute Severe Hypoxia.

Acute altitude hypoxia represents the cause of multiple adverse consequences. Current treatments are limited by side effects. Recent studies have shown the protective effects of resveratrol (RSV), but the mechanism remains unknown. To address this, the effects of RSV on the structure and function of hemoglobin of adult (HbA) were preliminarily analyzed using surface plasmon resonance (SPR) and oxygen dissociation assays (ODA). Molecular docking was conducted to specifically analyze the binding regions between RSV and HbA. The thermal stability was characterized to further validate the authenticity and effect of binding. Changes in the oxygen supply efficiency of HbA and rat RBCs incubated with RSV were detected ex vivo. The effect of RSV on the anti-hypoxic capacity under acute hypoxic conditions in vivo was evaluated. We found that RSV binds to the heme region of HbA following a concentration gradient and affects the structural stability and rate of oxygen release of HbA. RSV enhances the oxygen supply efficiency of HbA and rat RBCs ex vivo. RSV prolongs the tolerance times of mice suffering from acute asphyxia. By enhancing the oxygen supply efficiency, it alleviates the detrimental effects of acute severe hypoxia. In conclusion, RSV binds to HbA and regulates its conformation, which enhances oxygen supply efficiency and improves adaption to acute severe hypoxia.

SARS-CoV-2 Infection Causes Hyperglycemia in Cats.

Isolated reports of new-onset diabetes in patients with coronavirus disease 2019 (COVID-19) have led researchers to hypothesize that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human exocrine and endocrine pancreatic cells ex vivo and in vivo. However, existing research lacks experimental evidence indicating that SARS-CoV-2 can infect pancreatic tissue. Here, we found that cats infected with a high dose of SARS-CoV-2 exhibited hyperglycemia. We also detected SARS-CoV-2 RNA in pancreatic tissues of these cats, and immunohistochemical staining revealed the presence of SARS-CoV-2 nucleocapsid protein (NP) in islet cells. SARS-CoV-2 NP and spike proteins were primarily detected in glucagon-positive cells, and most glucagon-positive cells expressed ACE2. Additionally, immune protection experiments conducted on cats showed that blood glucose levels of immunized cats did not increase postchallenge. Our data indicate cat pancreas as a SARS-CoV-2 target and suggest that the infection of glucagon-positive cells could contribute to the metabolic dysregulation observed in SARS-CoV-2-infected cats.

[Application Value of Random Urine Potassium-to-Creatinine Ratio in Diagnosing Renal Potassium Loss].

Objective: To analyze the value of applying random urine potassium-to-creatinine ratio (rUK/Ucr) in diagnosing renal potassium loss. Methods: patients diagnosed with hypokalemia, including 373 cases of renal potassium loss, 83 cases of non-renal potassium loss , and 358 cases of normal serum potassium, between 2017 and 2021 were enrolled. The clinical data of the patients were collected and the correlation between rUK/Ucr and 24-hour urine potassium (24 hUK) in the three groups was analyzed. The receiver operating characteristic (ROC) curve was used to analyze the value of applying rUK/Ucr in diagnosing renal potassium loss. Results: Serum potassium decreased in the normal serum potassium group, the renal potassium loss group, and the non-renal renal potassium loss group ( P<0.01). The 24 hUK and the rUK/Ucr of the renal potassium loss group were higher than those of the non-renal potassium loss group and normal serum potassium group ( P<0.01). rUK/Ucr showed low to moderate correlation with 24 hUK. The AUC of 24 hUK and rUK/Ucr for determining renal potassium loss were 0.73 and 0.71, respectively. When the optimal cutoff point of rUK/Ucr for determining renal potassium loss was 3.4, the sensitivity was 67.6% and the specificity was 67.5%. Conclusion: rUK/Ucr shows a moderate correlation with 24 hUK and its accuracy in determining renal potassium loss is comparable to that of 24 hUK. When 24-hour urine samples cannot be obtained, it is recommended that rUK/Ucr be used instead of 24 hUK to determine whether renal potassium loss exists, with the optimal cutoff point for diagnosis being 3.4.

Ternary 14-electron XB2Be2 (X = Si, Ge, Sn, Pb) clusters: a planar tetracoordinate silicon (ptSi) system and its ptGe/Sn/Pb congeners.

A class of ternary 14-electron clusters, XB2Be2 (X = Si, Ge, Sn, Pb), have been computationally predicted with a planar tetracoordinate silicon (ptSi) unit, as well as its heavier ptGe/Sn/Pb congeners. These pentaatomic ptSi/Ge/Sn/Pb species are established as global-minimum structures via computer global searches, followed by electronic structure calculations at the PBE0-D3, B3LYP-D3, and single-point CCSD(T) levels. Molecular dynamics simulations indicate that they are also kinetically stable against isomerization or decomposition. Chemical bonding analyses show that the clusters have double 2π/2σ aromaticity. The latter concept underlies the stability of ptSi/Ge/Sn/Pb clusters, overriding the 14-electron count or its variants, such as the 18-electron rule. No sp3 hybridization occurs in these species, which naturally explains why they are ptSi/Ge/Sn/Pb (rather than traditional tetrahedral) systems.

Inhibition of Phosphoinositide 3-Kinase Gamma Protects Endothelial Cells via the Akt Signaling Pathway in Sepsis-Induced Acute Kidney Injury.

INTRODUCTION: Sepsis is a primary cause of death in critically ill patients and is characterized by multiple organ dysfunction, including sepsis-induced acute kidney injury (AKI), which contributes to high mortality in sepsis. However, its pathophysiological mechanisms remain unclear. The kidney has one of the richest and most diversified endothelial cell populations in the body. This study was designed to investigate the effects of endothelial dysfunction in sepsis-induced AKI and explore possible intervention measures to offer new insight into the pathogenesis and treatment of sepsis-induced AKI. METHODS: The circulating levels of endothelial adhesion molecules were detected in patients with sepsis and healthy controls to observe the role of endothelial damage in sepsis and sepsis-induced AKI. A murine sepsis model induced by cecal ligation and perforation was pretreated with a phosphoinositide 3-kinase gamma (PI3Kγ) inhibitor (CZC24832), and survival, kidney damage, and renal endothelial injury were assessed by pathological examination, immunohistochemistry, quantitative polymerase chain reaction, and Western blotting. Lipopolysaccharides and CZC24832 were administered to human umbilical vein endothelial cells in vitro, and endothelial cell function and the expression of adhesion molecules were evaluated. RESULTS: Endothelial damage was more serious in sepsis-induced AKI than that in non-AKI, and the inhibition of PI3Kγ alleviates renal endothelial injury in a murine sepsis model, protecting endothelial cell function and repairing endothelial cell injury through the Akt signaling pathway. CONCLUSIONS: In this study, endothelial cell dysfunction plays an important role in sepsis-induced AKI, and the inhibition of PI3Kγ alleviates endothelial cell injury in sepsis-induced AKI through the PI3Kγ/Akt pathway, providing novel targets for treating sepsis and related kidney injury.

Data-driven study on resting-state functional magnetic resonance imaging during early abstinence of alcohol dependence in male patients and its predictive value for relapse.

BACKGROUND: Alcohol dependence is a mental disorder with a high relapse rate. However, specific neuroimaging biomarkers have not been determined for alcohol dependence and its relapse. We conducted data-driven research to investigate resting-state functional magnetic resonance imaging (rs-fMRI) during early abstinence from alcohol dependence and its potential ability to predict relapse. METHODS: Participants included 68 alcohol-dependent patients and 68 healthy controls (HCs). The regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were compared between the alcohol dependence group and the HCs and between the relapse group and the nonrelapse group. The brain regions that presented significantly different ReHo and/or fALFF between the alcohol-dependent patients and HCs and/or between the relapsed and nonrelapsed patients were selected as the seeds to calculate the functional connectivities (FCs). RESULTS: During a 6-month follow-up period, 52.24% of alcohol-dependent patients relapsed. A regression model for differentiating alcohol-dependent patients and HCs showed that reductions in ReHo in the left postcentral region, fALFF in the right fusiform region, and FC in the right fusiform region to the right middle cingulum were independently associated with alcohol dependence, with an area under the receiver operating characteristic curve (AUC) of 0.841. The baseline FC of the left precentral to the left cerebellum of the relapse group was significantly lower than that of the nonrelapse group. The AUC of this FC to predict relapse was 0.774. CONCLUSIONS: Our findings contribute to advancing research on the neurobiological etiology and predictive biomarkers for relapse associated with alcohol dependence.