Coactivation pattern analysis reveals altered whole-brain functional transient dynamics in autism spectrum disorder.

Recent studies on autism spectrum disorder (ASD) have identified recurring states dominated by similar coactivation pattern (CAP) and revealed associations between dysfunction in seed-based large-scale brain networks and clinical symptoms. However, the presence of abnormalities in moment-to-moment whole-brain dynamics in ASD remains uncertain. In this study, we employed seed-free CAP analysis to identify transient brain activity configurations and investigate dynamic abnormalities in ASD. We utilized a substantial multisite resting-state fMRI dataset consisting of 354 individuals with ASD and 446 healthy controls (HCs, from HC groups and 2). CAP were generated from a subgroup of all HC subjects (HC group 1) through temporal K-means clustering, identifying four CAPs. These four CAPs exhibited either the activation or inhibition of the default mode network (DMN) and were grouped into two pairs with opposing spatial CAPs. CAPs for HC group 2 and ASD were identified by their spatial similarity to those for HC group 1. Compared with individuals in HC group 2, those with ASD spent more time in CAPs involving the ventral attention network but less time in CAPs related to executive control and the dorsal attention network. Support vector machine analysis demonstrated that the aberrant dynamic characteristics of CAPs achieved an accuracy of 74.87% in multisite classification. In addition, we used whole-brain dynamics to predict symptom severity in ASD. Our findings revealed whole-brain dynamic functional abnormalities in ASD from a single transient perspective, emphasizing the importance of the DMN in abnormal dynamic functional activity in ASD and suggesting that temporally dynamic techniques offer novel insights into time-varying neural processes.

TUSPM-NET: A multi-task model for thyroid ultrasound standard plane recognition and detection of key anatomical structures of the thyroid.

The thyroid gland is a vital gland located in the anterior part of the neck. Ultrasound imaging of the thyroid gland is a non-invasive and widely used technique for diagnosing nodular growth, inflammation, and enlargement of the thyroid gland. In ultrasonography, the acquisition of ultrasound standard planes is crucial for disease diagnosis. However, the acquisition of standard planes in ultrasound examinations can be subjective, laborious and heavily reliant on the sonographer's clinical experience. To overcome these challenges, we design a multi-task model TUSP Multi-task Network (TUSPM-NET) that can recognize Thyroid Ultrasound Standard Plane (TUSP) and detect key anatomical structures in TUSPs in real-time. To improve TUSPM-NET's accuracy and learn prior knowledge in medical images, we proposed the plane target classes loss function and the plane targets position filter. Additionally, we collected 9778 TUSP images of 8 standard planes to train and validate the model. Experiments have shown that TUSPM-NET can accurately detect anatomical structures in TUSPs and recognize TUSP images. Compared to current models with better performance, TUSPM-NET's object detection map@0.5:0.95 improves by 9.3%; the precision and recall of plane recognition improve by 3.49% and 4.39%, respectively. Furthermore, TUSPM-NET recognizes and detects a TUSP image in just 19.9 ms, which means that the method is well suited to the needs of real-time clinical scanning.

Risk prediction models for intracranial hemorrhage in acute ischemic stroke patients receiving intravenous alteplase treatment: a systematic review.

Objectives: To identify and compare published models that use related factors to predict the risk of intracranial hemorrhage (ICH) in acute ischemic stroke patients receiving intravenous alteplase treatment. Methods: Risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment were collected from PubMed, Embase, Web of Science, and the Cochrane Library up to April 7, 2023. A meta-analysis was performed using Stata 13.0, and the included models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Results: A total of 656 references were screened, resulting in 13 studies being included. Among these, one was a prospective cohort study. Ten studies used internal validation; five studies used external validation, with two of them using both. The area under the receiver operating characteristic (ROC) curve for subjects reported in the models ranged from 0.68 to 0.985. Common predictors in the prediction models include National Institutes of Health Stroke Scale (NIHSS) (OR = 1.17, 95% CI 1.09-1.25, p < 0.0001), glucose (OR = 1.54, 95% CI 1.09-2.17, p < 0.05), and advanced age (OR = 1.50, 95% CI 1.15-1.94, p < 0.05), and the meta-analysis shows that these are independent risk factors. After PROBAST evaluation, all studies were assessed as having a high risk of bias but a low risk of applicability concerns. Conclusion: This study systematically reviews available evidence on risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment. Few models have been externally validated, while the majority demonstrate significant discriminative power.

[Graduate training mode of acupuncture-moxibustion and tuina based on "three crosses and two integrations": a preliminary study].

In view of the core tasks and weak links in the training of medical graduate in the new era, based on the characteristics and development needs of the discipline, a new "three crosses and two integrations" graduate training mode of acupuncture-moxibustion and tuina is proposed, with "equal emphasis on inheritance and innovation, theory and practice" as the core, with "curriculum cross" as the basis, with "academic cross" as the connotation, and with "discipline cross" as the pathway. This new training mode focuses on the comprehensive cultivation of graduates' comprehensive abilities, aiming to achieve the training goal of "strong inheritance ability, excellent innovation ability, good practical ability and broad international perspective".

[Heavy Metal Emissions from Coal-fired Power Plants and Heavy Metal Pollution Characteristics and Health Risks in Surrounding Soils].

The aim of this study was to reveal the influence of heavy metal emissions from the flue gas of coal-fired power plants on the surrounding soil environment. Seven heavy metals, including As, Cd, Cr, Cu, Pb, Hg, and Ni, were detected in the flue gas of six coal-fired power plants in Shijiazhuang, and the heavy metals in the soil surrounding the power plants were analyzed. The source analysis and health risk assessment of the heavy metals were carried out. The results showed that after a series of flue gas pollutant control measures, the emission concentrations of different heavy metals in the flue gas of the coal-fired power plants ranged from 0.11 to 6.32 mg·(MW·h)-1, and Cu, Cr, and Ni were the main pollutants. The total amount of the seven heavy metal elements discharged into the atmosphere by each power plant was 33.56-275.71 kg·a-1. The average contents of Cr, Cu, Pb, Hg, and Ni in the surface soil surrounding the coal-fired power plant were higher than the background values of Hebei soil, and the contents were 1.16-2.32 times higher than the background values. The heavy metal content in the soil around the power plants was proportional to the heavy metal emissions in the flue gas. The heavy metal content in the soil under different wind directions first increased and then decreased gradually with the increase in distance from the power plants. Source analysis showed that coal combustion emissions contributed the most to heavy metals in soil around the power plants (41.4%), followed by industrial emissions (23.6%) and transportation emissions (19.6%). Altogether, human activities played a leading role in soil heavy metal enrichment, accounting for 84.6%. The health risk assessment showed that the overall health risk of metal elements in the soil surrounding the power plant was within acceptable limits.

Neural synchronization predicts marital satisfaction.

Marital attachment plays an important role in maintaining intimate personal relationships and sustaining psychological well-being. Mate-selection theories suggest that people are more likely to marry someone with a similar personality and social status, yet evidence for the association between personality-based couple similarity measures and marital satisfaction has been inconsistent. A more direct and useful approach for understanding fundamental processes underlying marital satisfaction is to probe similarity of dynamic brain responses to maritally and socially relevant communicative cues, which may better reflect how married couples process information in real time and make sense of their mates and themselves. Here, we investigate shared neural representations based on intersubject synchronization (ISS) of brain responses during free viewing of marital life-related, and nonmarital, object-related movies. Compared to randomly selected pairs of couples, married couples showed significantly higher levels of ISS during viewing of marital movies and ISS between married couples predicted higher levels of marital satisfaction. ISS in the default mode network emerged as a strong predictor of marital satisfaction and canonical correlation analysis revealed a specific relation between ISS in this network and shared communication and egalitarian components of martial satisfaction. Our findings demonstrate that brain similarities that reflect real-time mental responses to subjective perceptions, thoughts, and feelings about interpersonal and social interactions are strong predictors of marital satisfaction, reflecting shared values and beliefs. Our study advances foundational knowledge of the neurobiological basis of human pair bonding.

Cofluctuation analysis reveals aberrant default mode network patterns in adolescents and youths with autism spectrum disorder.

Resting-state functional connectivity (rsFC) approaches provide informative estimates of the functional architecture of the brain, and recently-proposed cofluctuation analysis temporally unwraps FC at every moment in time, providing refined information for quantifying brain dynamics. As a brain network disorder, autism spectrum disorder (ASD) was characterized by substantial alteration in FC, but the contribution of moment-to-moment-activity cofluctuations to the overall dysfunctional connectivity pattern in ASD remains poorly understood. Here, we used the cofluctuation approach to explore the underlying dynamic properties of FC in ASD, using a large multisite resting-state functional magnetic resonance imaging (rs-fMRI) dataset (ASD = 354, typically developing controls [TD] = 446). Our results verified that the networks estimated using high-amplitude frames were highly correlated with the traditional rsFC. Moreover, these frames showed higher average amplitudes in participants with ASD than those in the TD group. Principal component analysis was performed on the activity patterns in these frames and aggregated over all subjects. The first principal component (PC1) corresponds to the default mode network (DMN), and the PC1 coefficients were greater in participants with ASD than those in the TD group. Additionally, increased ASD symptom severity was associated with the increased coefficients, which may result in excessive internally oriented cognition and social cognition deficits in individuals with ASD. Our finding highlights the utility of cofluctuation approaches in prevalent neurodevelopmental disorders and verifies that the aberrant contribution of DMN to rsFC may underline the symptomatology in adolescents and youths with ASD.

circRNA_0000285 knockdown suppresses viability and promotes apoptosis of cervical cancer cells by sponging microRNA-654-3p.

Cervical cancer (CC) is one of the most common gynecological tumors worldwide. Several studies have reported that circular RNAs (circRNAs) play important roles in various types of diseases, including cancer. Thus, the present study aimed to investigate the role of circRNA_0000285 in CC development. Dual-luciferase reporter and RNA pull-down assays were performed to verify the binding region between circRNA_0000285 and miR-654-3p. The expression levels of circRNA_0000285 and miR-654-3p were analyzed in CC and the corresponding normal tissues, as well as in SiHa, HeLa, and NC104 cells using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). In addition, the effect of circRNA_0000285 inhibition on cell viability, apoptosis, and the expression of apoptosis-related markers was assessed using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide), flow cytometry, and Western blotting assays, respectively. The results verified that miR-654-3p directly targeted circRNA_0000285 expression. circRNA_0000285 was overexpressed and miR-654-3p expression was downregulated in CC tissues and cells compared to that in control. Moreover, circRNA_0000285 knockdown suppressed the viability and promoted the apoptosis of CC cells, which was accompanied by the downregulated and upregulated expressions B-cell lymphoma-2 (Bcl-2) and Bcl-2 associated X (Bax), respectively. The ratio of Bax/Bcl-2 levels also increased following circRNA_0000285 knockdown. However, these findings were abrogated after miR-654-3p inhibitor treatment. Hence, circRNA_0000285 knockdown suppressed cell viability and promoted apoptosis by targeting miR-654-3p in CC.

Dysregulation of KIF14 regulates the cell cycle and predicts poor prognosis in cervical cancer: a study based on integrated approaches.

Cervical cancer (CC) is the most common malignant tumor in females. Although persistent high-risk human papillomavirus (HPV) infection is a leading factor that causes CC, few women with HPV infection develop CC. Therefore, many mechanisms remain to be explored, such as aberrant expression of oncogenes and tumor suppressor genes. To identify promising prognostic factors and interpret the relevant mechanisms of CC, the RNA sequencing profile of CC was downloaded from the Cancer Genome Atlas and the Gene Expression Omnibus databases. The GSE63514 dataset was analyzed, and differentially expressed genes (DEGs) were obtained by weighted coexpression network analysis and the edgeR package in R. Fifty-three shared genes were mainly enriched in nuclear chromosome segregation and DNA replication signaling pathways. Through a protein-protein interaction network and prognosis analysis, the kinesin family member 14 (KIF14) hub gene was extracted from the set of 53 shared genes, which was overexpressed and associated with poor overall survival (OS) and disease-free survival (DFS) of CC patients. Mechanistically, gene set enrichment analysis showed that KIF14 was mainly enriched in the glycolysis/gluconeogenesis signaling pathway and DNA replication signaling pathway, especially in the cell cycle signaling pathway. RT-PCR and the Human Protein Atlas database confirmed that these genes were significantly increased in CC samples. Therefore, our findings indicated the biological function of KIF14 in cervical cancer and provided new ideas for CC diagnosis and therapies.

Dysregulation of KIF14 regulates the cell cycle and predicts poor prognosis in cervical cancer: a study based on integrated approaches

Cervical cancer (CC) is the most common malignant tumor in females. Although persistent high-risk human papillomavirus (HPV) infection is a leading factor that causes CC, few women with HPV infection develop CC. Therefore, many mechanisms remain to be explored, such as aberrant expression of oncogenes and tumor suppressor genes. To identify promising prognostic factors and interpret the relevant mechanisms of CC, the RNA sequencing profile of CC was downloaded from the Cancer Genome Atlas and the Gene Expression Omnibus databases. The GSE63514 dataset was analyzed, and differentially expressed genes (DEGs) were obtained by weighted coexpression network analysis and the edgeR package in R. Fifty-three shared genes were mainly enriched in nuclear chromosome segregation and DNA replication signaling pathways. Through a protein-protein interaction network and prognosis analysis, the kinesin family member 14 (KIF14) hub gene was extracted from the set of 53 shared genes, which was overexpressed and associated with poor overall survival (OS) and disease-free survival (DFS) of CC patients. Mechanistically, gene set enrichment analysis showed that KIF14 was mainly enriched in the glycolysis/gluconeogenesis signaling pathway and DNA replication signaling pathway, especially in the cell cycle signaling pathway. RT-PCR and the Human Protein Atlas database confirmed that these genes were significantly increased in CC samples. Therefore, our findings indicated the biological function of KIF14 in cervical cancer and provided new ideas for CC diagnosis and therapies.

Orientin Improves Cognition by Enhancing Autophagosome Clearance in an Alzheimer's Mouse Model.

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by the presence of ß-amyloid (Aß) plaques and defective autophagy in the brain, which is believed to cause neuronal dysfunction. By using APP/PS1 transgenic AD mice, we investigated the influence of orientin (Ori) on cognitive function and its underlying mechanisms in AD models. Our data indicated that Ori improved spatial learning and memory in APP/PS1 mice, possibly through decreasing brain Aß deposition and attenuating autophagy impairment. Ori decreased the LC3-II/I ratio, p62 and cathepsin D (Ctsd) protein levels and the number of autolysosomes, whereas the protein levels of Ulk1 and Beclin-1 were no different between the control and treatment groups, indicating increased autolysosome clearance and thus a decreased Aß burden in the brain. Our results showed that Ori could enhance autolysosome clearance, decrease brain Aß deposition and improve learning and memory in AD mice.

Berberine ameliorates diabetic neuropathic pain in a rat model: involvement of oxidative stress, inflammation, and µ-opioid receptors.

Berberine, a chemical found in plants, is used as a supplement for diabetes. This study aimed to investigate the effects and the underlying molecular regulations of berberine in diabetic neuropathic pain in a rat model of diabetes. Rats were injected with streptozotocin (STZ) to induce diabetes and then were treated with berberine. Blood glucose levels and body weight were measured. Thermal and mechanical nociception were assessed by paw pressure test and hot tail immersion test. Oxidative stress was assessed by lipid peroxidation, production of reactive oxygen species (ROS) and catalase activity. Neuroinflammation was assessed by tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) protein levels. Finally, µ-opioid receptor (MOR) protein and mRNA levels were measured. We found that berberine treatment partially suppressed blood glucose levels and restored body weight in diabetic rats. Berberine also suppressed STZ-induced oversensitivity of mechanical and thermal nociception. Additionally, berberine partially suppressed oxidative stress and inflammation of diabetic rats. Finally, berberine significantly enhanced protein and mRNA expression levels of µ-opioid receptor (MOR). Our findings suggest that berberine is a potential therapeutic alleviating diabetes and diabetic neuropathic pain, probably through suppression of oxidative stress and neuroinflammation that may be mediated by MOR.

Sample injection and electrophoretic separation on a simple laminated paper based analytical device.

We described a strategy to perform multistep operations on a simple laminated paper-based separation device by using electrokinetic flow to manipulate the fluids. A laminated crossed-channel paper-based separation device was fabricated by cutting a filter paper sheet followed by lamination. Multiple function units including sample loading, sample injection, and electrophoretic separation were integrated on a single paper based analytical device for the first time, by applying potential at different reservoirs for sample, sample waste, buffer, and buffer waste. As a proof-of-concept demonstration, mixed sample solution containing carmine and sunset yellow were loaded in the sampling channel, and then injected into separation channel followed by electrophoretic separation, by adjusting the potentials applied at the four terminals of sampling and separation channel. The effects of buffer pH, buffer concentration, channel width, and separation time on resolution of electrophoretic separation were studied. This strategy may be used to perform multistep operations such as reagent dilution, sample injection, mixing, reaction, and separation on a single microfluidic paper based analytical device, which is very attractive for building micro total analysis systems on microfluidic paper based analytical devices.