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Abstract Background Recently studies had showed that the amygdala may take part in the cognitive impairment in schizophrenia (SC). However, the mechanism is still unclear, so we explored the relationship between the amygdala resting state magnetic resonance imaging (rsMRI) signal and cognitive function, to provide a reference for the follow-up study. Methods We collected 59 drug-naïve SCs and 46 healthy controls (HCs) from the Third People’s Hospital of Foshan. The rsMRI technique and automatic segmentation tool were used to extract the volume and functional indicators of the SC’s amygdala. The Positive and Negative Syndrome Scale (PANSS) was used to assess the severity of the disease, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used to assess cognitive function. Pearson correlation analysis was used to compare the relationship between the structural and functional indicators of the amygdala and PANSS and RBANS. Results (1) There was no significant difference between SC and HC in age, gender and years of education. Compared with HC, the PANSS score of SC increased and the RBANS score decreased significantly. Meanwhile, the left amygdala volume decreased (t=-3.675, p

Abstract Background Acute kidney injury (AKI) is a common and severe complication of cardiac surgery with cardiopulmonary bypass (CPB). This study aimed to establish a model to predict the probability of postoperative AKI in patients undergoing cardiac surgery with CPB. Methods We conducted a retrospective, multicenter study to analyze 1082 patients undergoing cardiac surgery under CPB. The least absolute shrinkage and selection operator regression model was used to optimize feature selection for the AKI model. Multivariable logistic regression analysis was applied to build a prediction model incorporating the feature selected in the previously mentioned model. Finally, we used multiple methods to evaluate the accuracy and clinical applicability of the model. Results Age, gender, hypertension, CPB duration, intraoperative 5% bicarbonate solution and red blood cell transfusion, urine volume were identified as important factors. Then, these risk factors were created into nomogram to predict the incidence of AKI after cardiac surgery under CPB. Conclusion We developed a nomogram to predict the incidence of AKI after cardiac surgery. This model can be used as a reference tool for evaluating early medical intervention to prevent postoperative AKI.

ObjectivePrevious studies have established significant differences in the neuroimaging characteristics between healthy controls (HCs) and patients with schizophrenia (SCZ). However, the relationship between homotopic connectivity and clinical features in patients with SCZ is not yet fully understood. Furthermore, there are currently no established neuroimaging biomarkers available for the diagnosis of SCZ or for predicting early treatment response. The aim of this study is to investigate the association between regional homogeneity and specific clinical features in SCZ patients.MethodsWe conducted a longitudinal investigation involving 56 patients with SCZ and 51 HCs. The SCZ patients underwent a 3-month antipsychotic treatment. Resting-state functional magnetic resonance imaging (fMRI), regional homogeneity (ReHo), support vector machine (SVM), and support vector regression (SVR) were used for data acquisition and analysis.ResultsIn comparison to HCs, individuals with SCZ demonstrated reduced ReHo values in the right postcentral/precentral gyrus, left postcentral/inferior parietal gyrus, left middle/inferior occipital gyrus, and right middle temporal/inferior occipital gyrus, and increased ReHo values in the right putamen. It is noteworthy that there was decreased ReHo values in the right inferior parietal gyrus after treatment compared to baseline data.ConclusionThe observed decrease in ReHo values in the sensorimotor network and increase in ReHo values in the right putamen may represent distinctive neurobiological characteristics of patients with SCZ, as well as a potential neuroimaging biomarker for distinguishing between patients with SCZ and HCs. Furthermore, ReHo values in the sensorimotor network and right putamen may serve as predictive indicators for early treatment response in patients with SCZ.

Depression is a common mental disorder that seriously affects patients’ social function and daily life. Its accurate diagnosis remains a big challenge in depression treatment. In this study, we used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) and measured the whole brain EEG signals and forehead hemodynamic signals from 25 depression patients and 30 healthy subjects during the resting state. On one hand, we explored the EEG brain functional network properties, and found that the clustering coefficient and local efficiency of the delta and theta bands in patients were significantly higher than those in normal subjects. On the other hand, we extracted brain network properties, asymmetry, and brain oxygen entropy as alternative features, used a data-driven automated method to select features, and established a support vector machine model for automatic depression classification. The results showed the classification accuracy was 81.8% when using EEG features alone and increased to 92.7% when using hybrid EEG and fNIRS features. The brain network local efficiency in the delta band, hemispheric asymmetry in the theta band and brain oxygen sample entropy features differed significantly between the two groups (p

ObjectivePrior researches have identified distinct differences in neuroimaging characteristics between healthy controls (HCs) and patients with major depressive disorder (MDD). However, the correlations between homotopic connectivity and clinical characteristics in patients with MDD have yet to be fully understood. The present study aimed to investigate common and unique patterns of homotopic connectivity and their relationships with clinical characteristics in patients with MDD.MethodsWe recruited 42 patients diagnosed with MDD and 42 HCs. We collected a range of clinical variables, as well as exploratory eye movement (EEM), event-related potentials (ERPs) and resting-state functional magnetic resonance imaging (rs-fMRI) data. The data were analyzed using correlation analysis, support vector machine (SVM), and voxel-mirrored homotopic connectivity (VMHC).ResultsCompared with HCs, patients with MDD showed decreased VMHC in the insula, and increased VMHC in the cerebellum 8/vermis 8/vermis 9 and superior/middle occipital gyrus. SVM analysis using VMHC values in the cerebellum 8/vermis 8/vermis 9 and insula, or VMHC values in the superior/middle occipital gyrus and insula as inputs can distinguish HCs and patients with MDD with high accuracy, sensitivity, and specificity.ConclusionThe study demonstrated that decreased VMHC in the insula and increased VMHC values in the sensory-motor networks may be a distinctive neurobiological feature for patients with MDD, which could potentially serve as imaging markers to discriminate HCs and patients with MDD.

BackgroundSepsis is organ dysfunction due to the host’s deleterious response to infection, and the kidneys are one of the organs damaged in common sepsis. Sepsis-associated acute kidney injury (SA-AKI) increases the mortality in patients with sepsis. Although a substantial volume of research has improved the prevention and treatment of the disease, SA-SKI is still a significant clinical concern.PurposeAimed to use weighted gene co-expression network analysis (WGCNA) and immunoinfiltration analysis to study SA-AKI-related diagnostic markers and potential therapeutic targets.MethodsImmunoinfiltration analysis was performed on SA-AKI expression datasets from the Gene Expression Synthesis (GEO) database. A weighted gene co-expression network analysis (WGCNA) analysis was performed on immune invasion scores as trait data, and modules associated with immune cells of interest were identified as hub modules. Screening hub geneset in the hub module using protein-protein interaction (PPI) network analysis. The hub gene was identified as a target by intersecting with significantly different genes screened by differential expression analysis and validated using two external datasets. Finally, the correlation between the target gene, SA-AKI, and immune cells was verified experimentally.ResultsGreen modules associated with monocytes were identified using WGCNA and immune infiltration analysis. Differential expression analysis and PPI network analysis identified two hub genes (AFM and GSTA1). Further validation using additional AKI datasets GSE30718 and GSE44925 showed that AFM was significantly downregulated in AKI samples and correlated with the development of AKI. The correlation analysis of hub genes and immune cells showed that AFM was significantly associated with monocyte infiltration and hence, selected as a critical gene. In addition, Gene single-enrichment analysis (GSEA) and PPI analyses results showed that AFM was significantly related to the occurrence and development of SA-AKI.ConclusionsAFM is inversely correlated with the recruitment of monocytes and the release of various inflammatory factors in the kidneys of AKI. AFM can be a potential biomarker and therapeutic target for monocyte infiltration in sepsis-related AKI.

Chronic kidney disease (CKD) is defined by persistent urine aberrations, structural abnormalities, or impaired excretory renal function. Diabetes is the leading cause of CKD. Their common pathological manifestation is renal fibrosis. Approximately half of all patients with type 2 diabetes and one-third with type 1 diabetes will develop CKD. However, renal fibrosis mechanisms are still poorly understood, especially post-transcriptional and epigenetic regulation. And an unmet need remains for innovative treatment strategies for preventing, arresting, treating, and reversing diabetic kidney disease (DKD). People believe that protein methylation, including histone and non-histone, is an essential type of post-translational modification (PTM). However, prevalent reviews mainly focus on the causes such as DNA methylation. This review will take insights into the protein part. Furthermore, by emphasizing the close relationship between protein methylation and DKD, we will summarize the clinical research status and foresee the application prospect of protein methyltransferase (PMT) inhibitors in DKD treatment. In a nutshell, our review will contribute to a more profound understanding of DKD’s molecular mechanism and inspire people to dig into this field.

Sepsis is a systemic inflammatory response caused by a severe infection that leads to multiple organ damage, including acute kidney injury (AKI). In intensive care units (ICU), the morbidity and mortality associated with sepsis-associated AKI (SA-AKI) are gradually increasing due to lack of effective and early detection, as well as proper treatment. Non-coding RNAs (ncRNAs) exert a regulatory function in gene transcription, RNA processing, post-transcriptional translation, and epigenetic regulation of gene expression. Evidence indicated that miRNAs are involved in inflammation and programmed cell death during the development of sepsis-associated AKI (SA-AKI). Moreover, lncRNAs and circRNAs appear to be an essential regulatory mechanism in SA-AKI. In this review, we summarized the molecular mechanism of ncRNAs in SA-AKI and discussed their potential in clinical diagnosis and treatment.

Facing irreversible and catastrophic changes on the earth, China has committed to peak the net carbon emission by 2030 and to achieve carbon neutrality by 2060. The pledge requires significant mitigation immediately and sustainably. Considering this background, some perspectives are given in this article based on the comprehensive use of natural resources. First, utilizing the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model and statistical data, net carbon emissions of provinces in China are anticipated, which lays a foundation for the further “three-step” carbon neutralization route. Second, a strategy of water–temperature–radiation–land coupling use is proposed, considering 1) the carbon emission cut, which relies on comparing the energy intensity and energy structure in China with those in developed countries; 2) the carbon sink increase, which depends on the evaluation of constraints of hydrometeorological factors on ecological productivity. Finally, the necessity and possibility of carbon trading and redistribution of the natural resources are discussed to ensure that China's national net carbon emission would be reduced to zero by 2060.

Abstract Neuropathic pain (NP) is ranked as one of the major forms of chronic pain and emerges as a direct consequence of a lesion or disease affecting the somatosensory nervous system. Despite great advances into the mechanisms of NP, clinical practice is still not satisfactory. Fortunately, progress in elucidating unique features and multiple molecular mechanisms of long non-coding RNAs (lncRNAs) in NP has emerged in the past 10 years, suggesting that novel therapeutic strategies for pain treatment may be proposed. In this review, we will concentrate on recent studies associated with lncRNAs in NP. First, we will describe the alterations of lncRNA expression after spinal cord injury (SCI) and peripheral nerve injury (PNI), and then we illustrate the role of some specific lncRNAs in detail, which may offer new insights into our understanding of the etiology and pathophysiology of NP. Finally, we put special emphasis on the altered expression of lncRNAs in the diverse biological process of NP. Recent advances we summarized above in the development of NP may facilitate translation of these findings from bench to bedside in the future.

Aims: Osteoporosis is underdiagnosed because of the lack of a convenient diagnostic method. Circulating microRNAs (miRNAs) emerge as novel biomarkers for disease diagnosis. Here, we conducted a case-control study that included a total of 448 serum samples collected from 182 healthy participants, 132 osteopenia participants, and 134 osteoporosis patients. Methods: Circulating miRNAs dysregulated during osteoporosis were screened and analyzed in three randomly determined sub-cohorts: the discovery cohort identified 22 candidate miRNAs; the training cohort tested the candidate miRNAs and constructed Index 1, comprising five miRNAs by logistic regression, and Index 2, comprising four miRNAs, was developed by linear combination. Results: Both indices were tested in the validation cohort and showed statistically significant results in distinguishing osteoporosis patients from healthy and osteopenic patients. Moreover, Index 1 also showed improved performance over traditional bone turnover biomarkers type I pro-collagen (tPINP) and type I collagen (β-CTx). Conclusion: In conclusion, circulating miRNAs are potential biomarkers for osteoporosis. The diagnostic panel of circulating miRNAs could be a complementary method for dual-energy X-ray absorptiometry (DXA) in mass screening and routine examination to enhance the osteoporosis detection rate.

Angular displacement sensor with shared magnetic field has strong environmental adaptability and high measurement accuracy. However, its 3-D structure is multi-pole double-layer structure, using time stepping finite element method (TSFEM) to optimize the structure is time-consuming and uneconomical. Therefore, a magnetic equivalent loop method (MELM) is proposed to simplify the optimal design of sensors. By reasonably setting the node position, the mechanical structure parameters, winding coefficients and input voltage of the sensor are integrated into a mathematical model to calculate of the induced voltage. The calculation results are compared with the simulation results, and a sensor prototype is made to test the optimized effect of the MELM.

Traditional dc magnetron sputtering has a low ionization rate when preparing metallic thin films. With the development of thin film science and the market demand for thin film material applications, it is necessary to improve the density of magnetron-sputtered films. High-power pulsed magnetron sputtering (HiPIMS) technology is a physical vapor deposition technology with a high ionization rate and high energy. Therefore, in this work, HiPIMS was applied to prepare metallic tungsten films and compare the surface morphology and microstructure of metallic tungsten films deposited using HiPIMS and dc magnetron sputtering (dcMS) technology under different pulse lengths, as well as related thermal resistance performance, followed by annealing treatment for comparative analysis. We used AFM, SEM, XRD, and plasma characterization testing to comprehensively analyze the changes in the TCR value, stability, repeatability and other related performance of the metallic tungsten thin-film sensor deposited by the HiPIMS technology. It was determined that the thin film prepared by the HiPIMS method is denser, with fewer defects, and the film sensor was stable. The 400 °C annealed sample prepared using HiPIMS with a 100 μs pulse length reaches the largest recorded TCR values of 1.05 × 10−3 K−1. In addition, it shows better stability in repeated tests. [ABSTRACT FROM AUTHOR]