Meso-scale reorganization of local-global brain networks under mild sedation of propofol anesthesia.

The fragmentation of the functional brain network has been identified through the functional connectivity (FC) analysis in studies investigating anesthesia-induced loss of consciousness (LOC). However, it remains unclear whether mild sedation of anesthesia can cause similar effects. This paper aims to explore the changes in local-global brain network topology during mild anesthesia, to better understand the macroscopic neural mechanism underlying anesthesia sedation. We analyzed high-density EEG from 20 participants undergoing mild and moderate sedation of propofol anesthesia. By employing a local-global brain parcellation in EEG source analysis, we established binary functional brain networks for each participant. Furthermore, we investigated the global-scale properties of brain networks by estimating global efficiency and modularity, and examined the changes in meso-scale properties of brain networks by quantifying the distribution of high-degree and high-betweenness hubs and their corresponding rich-club coefficients. It is evident from the results that the mild sedation of anesthesia does not cause a significant change in the global-scale properties of brain networks. However, network components centered on SomMot L show a significant decrease, while those centered on Default L, Vis L and Limbic L exhibit a significant increase during the transition from wakefulness to mild sedation (p<0.05). Compared to the baseline state, mild sedation almost doubled the number of high-degree hubs in Vis L, DorsAttn L, Limbic L, Cont L, and reduced by half the number of high-degree hubs in SomMot R, DorsAttn R, SalVentAttn R. Further, mild sedation almost doubled the number of high-betweenness hubs in Vis L, Vis R, Limbic R, Cont R, and reduced by half the number of high-betweenness hubs in SomMot L, SalVentAttn L, Default L, and SomMot R. Our results indicate that mild anesthesia cannot affect the global integration and segregation of brain networks, but influence meso-scale function for integrating different resting-state systems involved in various segregation processes. Our findings suggest that the meso-scale brain network reorganization, situated between global integration and local segregation, could reflect the autonomic compensation of the brain for drug effects. As a direct response and adjustment of the brain network system to drug administration, this spontaneous reorganization of the brain network aims at maintaining consciousness in the case of sedation.

Macro-analysis of climatic factors for COVID-19 pandemic based on Köppen-Geiger climate classification.

This study integrated dynamic models and statistical methods to design a novel macroanalysis approach to judge the climate impacts. First, the incidence difference across Köppen-Geiger climate regions was used to determine the four risk areas. Then, the effective influence of climate factors was proved according to the non-climate factors' non-difference among the risk areas, multi-source non-major component data assisting the proof. It is found that cold steppe arid climates and wet temperate climates are more likely to transmit SARS-CoV-2 among human beings. Although the results verified that the global optimum temperature was around 10 °C, and the average humidity was 71%, there was evident heterogeneity among different climate risk areas. The first-grade and fourth-grade risk regions in the Northern Hemisphere and fourth-grade risk regions in the Southern Hemisphere are more sensitive to temperature. However, the third-grade risk region in the Southern Hemisphere is more sensitive to relative humidity. The Southern Hemisphere's third-grade and fourth-grade risk regions are more sensitive to precipitation.

Exploring meteorological impacts based on Köppen-Geiger climate classification after reviewing China's response to COVID-19.

More than 30 months into the novel coronavirus 2019 (COVID-19) pandemic, efforts to bring this prevalence under control have achieved tentative achievements in China. However, the continuing increase in confirmed cases worldwide and the novel variants imply a severe risk of imported viruses. High-intensity non-pharmaceutical interventions (NPIs) are the mainly used measures of China's early response to COVID-19, which enabled effective control in the first wave of the epidemic. However, their efficiency is relatively low across China at the current stage. Therefore, this study focuses on whether measurable meteorological variables be found through global data to learn more about COVID-19 and explore flexible controls. This study first examines the control measures, such as NPIs and vaccination, on COVID-19 transmission across 189 countries, especially in China. Subsequently, we estimate the association between meteorological factors and time-varying reproduction numbers based on the global data by meta-population epidemic model, eliminating the aforementioned anthropogenic factors. According to this study, we find that the basic reproduction number of COVID-19 transmission varied wildly among Köppen-Geiger climate classifications, which is of great significance for the flexible adjustment of China's control protocols. We obtain that in southeast China, Köppen-Geiger climate sub-classifications, Cwb, Cfa, and Cfb, are more likely to spread COVID-19. In August, the RSIM of Cwb climate subclassification is about three times that of Dwc in April, which implies that the intensity of control efforts in different sub-regions may differ three times under the same imported risk. However, BSk and BWk, the most widely distributed in northwest China, have smaller basic reproduction numbers than Cfa, distributed in southeast coastal areas. It indicates that northwest China's control intensity could be appropriately weaker than southeast China under the same prevention objectives.

Remote Sensing Image Classification Using the Spectral-Spatial Distance Based on Information Content.

Among many types of efforts to improve the accuracy of remote sensing image classification, using spatial information is an effective strategy. The classification method integrates spatial information into spectral information, which is called the spectral-spatial classification approach, has better performance than traditional classification methods. Construct spectral-spatial distance used for classification is a common method to combine the spatial and spectral information. In order to improve the performance of spectral-spatial classification based on spectral-spatial distance, we introduce the information content (IC) in which two pixels are shared to measure spatial relation between them and propose a novel spectral-spatial distance measure method. The IC of two pixels shared was computed from the hierarchical tree constructed by the statistical region merging (SRM) segmentation. The distance we proposed was applied in two distance-based contextual classifiers, the k-nearest neighbors-statistical region merging (k-NN-SRM) and optimum-path forest-statistical region merging (OPF-SRM), to obtain two new contextual classifiers, the k-NN-SRM-IC and OPF-SRM-IC. The classifiers with the novel distance were implemented in four land cover images. The classification results of the classifier based on our spectral-spatial distance outperformed all the other competitive contextual classifiers, which demonstrated the validity of the proposed distance measure method.

Emergence of HIV-1 drug resistance mutations among children and adolescents undergoing prolonged antiretroviral therapy in Guangxi.

OBJECTIVE: Antiretroviral therapy (ART) has been implemented in Guangxi for a long time, and there are no reports of HIV drug resistance mutation (DRM) among children and adolescents experiencing virologic failure after ART. This study aimed to analyse HIV DRM prevalence, patterns, and influencing factors among children and adolescents experiencing virologic failure after ART in Guangxi. METHODS: We collected samples from a total of 491 HIV-infected individuals under 18 years old experiencing virologic failure after ART from 14 cities in Guangxi. Sequencing and DRM analysis were performed based on pol region. Multivariate logistic regression was employed to analysis the influencing factors of DRM. RESULTS: Among these patients, 396 cases were successfully sequenced. Of all, 52.53% exhibited HIV DRM, including NNRTI (48.48%), NRTI (34.85%) and PI (1.01%). NRTI and NNRTI dual-class resistance was prevalent (30.3%). M184V/I and K103N mutations were the common mutations in NRTI and NNRTI, respectively. Male sex (aOR = 2.1, 95% CI: 1.26-3.50), CRF01_AE subtype (OR = 2.50, 95% CI: 1.02-5.88), the primary regimen 3TC+AZT+NVP (OR = 10.00, 95% CI: 5.00-25.00), low pretreatment CD4+ T lymphocytes (<200 cells/mm³) (OR = 1.85, 95% CI: 1.00-3.45), and high viral load (>1000 copies/mL) (OR = 4.90, 95% CI: 1.03-23.39) showed higher risk of DRM. CONCLUSION: HIV DRM is pervasive among children and adolescents experiencing virologic failure in Guangxi. Timely HIV DRM monitoring is crucial to mitigate major mutation accumulation and inform effective treatment strategies.

TSG6 Plays a Role in Improving Orbital Inflammatory Infiltration and Extracellular Matrix Accumulation in TAO Model Mice.

Introduction: TSG-6 plays a wide anti-inflammatory and therapeutic role in a variety of autoimmune diseases as the key mediator of mesenchymal stem cells (MSCs). Purpose: We aimed to test whether TSG-6 could exert similar effects as MSCS in TAO via establishing TAO animal model immunized by hTSHR-A subunit plasmid. Material and Methods: We tested the expression level of TSG-6 on intraconal orbital fat from controls and patients with TAO. We established a stable thyroid-associated ophthalmopathy animal model by immunizing 6-week-old female Balb/c mice with recombination hTSHR-A subunit plasmid. After four immunizations, TSG-6 or dexamethasone was injected through the tail vein. The effects of the drugs on body weight, thyroid function, orbital inflammation, fibrosis and lipogenesis were observed. Results: The expression of TSG-6 in the orbital tissues of TAO patient is lower than that of normal people. In our animal model, mice showed weight loss, higher TT4 and TSHR antibody levels, and ocular symptoms such as inflammation and proptosis. TSG-6 can reduce ocular fibrosis and lipogenesis by inhibiting the infiltration of CD3+ T lymphocytes and macrophages in the mouse model of thyroid associated ophthalmopathy. Compared with dexamethasone, TSG-6 showed comparable anti-inflammatory effect, moreover, it has given a better performance in inhibiting adipogenesis. Conclusion: It was demonstrated that TSG-6 has a considerable positive impact on improving eye symptoms of TAO mice, which could be a novel candidate for the early treatment of TAO.

MEGA: Machine Learning-Enhanced Graph Analytics for Infodemic Risk Management.

The COVID-19 pandemic brought not only global devastation but also an unprecedented infodemic of false or misleading information that spread rapidly through online social networks. Network analysis plays a crucial role in the science of fact-checking by modeling and learning the risk of infodemics through statistical processes and computation on mega-sized graphs. This article proposes MEGA, Machine Learning-Enhanced Graph Analytics, a framework that combines feature engineering and graph neural networks to enhance the efficiency of learning performance involving massive graphs. Infodemic risk analysis is a unique application of the MEGA framework, which involves detecting spambots by counting triangle motifs and identifying influential spreaders by computing the distance centrality. The MEGA framework is evaluated using the COVID-19 pandemic Twitter dataset, demonstrating superior computational efficiency and classification accuracy.

Behavioral and emotional difficulties and HIV treatment outcomes among HIV-infected children in rural southwestern China.

BACKGROUND: Previous studies have not clearly demonstrated the impact of behavioral and emotional problems (BEDs) on treatment outcomes among HIV-infected children on antiretroviral therapy (ART). This study aimed to describe the prevalence of BEDs among this population and identify the factors associated with HIV treatment outcomes. METHODS: This cross-sectional study was conducted in Guangxi, China, between July and August 2021. HIV-infected children answered questionnaires about BEDs, physical health, social support, and whether they have missed doses in the past month. BEDs were assessed using the Chinese version of the self-reported Strengths and Difficulties Questionnaire (SDQ-C). The self-reported survey data were linked to participants' HIV care information that was obtained from the national surveillance database. Univariate and multivariate logistic regression models were used to identify factors that were associated with missed doses in the past month and virological failure. RESULTS: The study sample was 325 HIV-infected children. HIV-infected children had a higher proportion of abnormal scores on SDQ-C total difficulties compared to their peers in the general population (16.9 vs 10.0%; P = 0.002). An abnormal SDQ-C total difficulties score (AOR = 2.06, 95%CI: 1.10-3.88) and infrequency of receiving assistance and support from parents over the past 3 months (AOR = 1.85, 95%CI: 1.12-3.06) were significantly associated with missed doses in the past month. Between the ages of 14-17 years (AOR = 2.66, 95% CI: 1.37-5.16), female (AOR = 2.21, 95% CI: 1.20-4.08), and suboptimal adherence (AOR = 2.45, 95% CI: 1.32-4.57) were significantly associated with virological failure. CONCLUSIONS: Children's mental health plays a role in HIV treatment outcomes. Psychological interventions should be promoted in pediatric HIV care clinics to improve children's mental health status and HIV treatment outcomes.

Vanishing and spreading conditions for a free-boundary epidemic model with subclinical infections and vaccination.

This paper presents a free-boundary epidemic model with subclinical infections and vaccination.We prove the existence and uniqueness of solutions to the model.Moreover, sufficient conditions for the disease vanishing and spreading are given.The disease will vanish if the basic reproduction number $ R_0 < 1 $, that the corresponding ODE model defines without spatial expansion. However, the disease will spread to the whole area if $ R^F_0(t_0) > 1 $ for some $ t_0 > 0 $ when it is introduced spatial heterogeneity. $ R^F_0(0) < R_0 $ implies that the spillovers from hotspots to areas with no confirmed cases will reduce the outbreak threshold and increase the difficulty of prevention and control in the whole region. Under the condition $ R^F_0(0) < 1 < R_0 $, if the free boundary condition of infectives $ h(t) < \infty $, $ t \to \infty $, then the disease is vanishing, which indicates that $ R^F_0(0) < 1 $ can also control the disease if the scope of hotspots expansion is limited. Furthermore, the numerical simulations illustrate that the routine vaccination would decrease the basic reproduction number and then change the disease from spreading to vanishing.

Constructing and validating of m6a-related genes prognostic signature for stomach adenocarcinoma and immune infiltration: Potential biomarkers for predicting the overall survival.

Background: Stomach adenocarcinoma (STAD) arises from the mutations of stomach cells and has poor overall survival. Chemotherapy is commonly indicated for patients with stomach cancer following surgical resection. The most prevalent alteration that affects cancer growth is N6-methyladenosine methylation (m6A), although the possible function of m6A in STAD prognosis is not recognized. Method: The research measured predictive FRGs in BLCA samples from the TCGA and GEO datasets. Data on the stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and corresponding clinical characteristics were obtained from TCGA and GEO. STAD from TCGA and GEO at 24 m6A was investigated. Lasso regression was used to construct the prediction model to assess the m6A prognostic signals in STAD. In addition, the correlation between m6a and immune infiltration in STAD patients was discussed using GSVA and ssGSEA analysis. Based on these genes, GO and KEGG analyses were performed to identify key biological functions and key pathways. Result: A significant relationship was discovered between numerous m6A clusters and the tumor immune microenvironment, as well as three m6A alteration patterns with different clinical outcomes. Furthermore, GSVA and ssGSEA showed that m6A clusters were significantly associated with immune infiltration in the STAD. The low-m6Ascore group had a lower immunotherapeutic response than the high-m6Ascore group. ICIs therapy was more effective in the group with a higher m6Ascore. Three writers (VIRMA, ZC3H13, and METTL3) showed significantly lower expression, whereas five authors (METTL14, METTL16, WTAP, RBM15, and RBM15B) showed considerably higher expression. Three readers (YTHDC2, YTHDF2, and LRPPRC) had higher levels of expression, whereas eleven readers (YTHDC1, YTHDF1, YTHDF3, HNRNPC, FMR1, HNRNPA2B1, IGFBP1, IGFBP2, IGFBP3, and RBMX) had lower levels. As can be observed, the various types of m6 encoders have varied ramifications for STAD control. Conclusion: STAD occurrence and progression are linked to m6A-genes. Corresponding prognostic models help forecast the prognosis of STAD patients. m6A-genes and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in STAD, which requires further trials. In addition, the m6a-related gene signature offers a viable alternative to predict bladder cancer, and these m6A-genes show a prospective research area for STAD targeted treatment in the future.

A Scenario-Based Evaluation of COVID-19-Related Essential Clinical Resource Demands in China.

The coronavirus disease 2019 (COVID-19) pandemic is a global crisis, and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses. This study aimed to assess COVID-19-related essential clinical resource demands in China, based on different scenarios involving COVID-19 spreads and interventions. We used a susceptible-exposed-infectious-hospitalized/isolated-removed (SEIHR) transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed. We found that, under strict non-pharmaceutical interventions (NPIs) or mass vaccination of the population, China would be able to contain community transmission and local outbreaks rapidly. However, under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated, the use of a peacetime-wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system. The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment. An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources; however, attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases. This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic. It also provides guidance for essential healthcare investment and resource allocation.

Antibacterial Activity of Manganese Dioxide Nanosheets by ROS-Mediated Pathways and Destroying Membrane Integrity.

Manganese dioxide (MnO2) nanosheets have shown exciting potential in nanomedicine because of their ultrathin thickness, large surface area, high near-infrared (NIR) absorbance and good biocompatibility. However, the effect of MnO2 nanosheets on bacteria is still unclear. In this study, MnO2 nanosheets were shown for the first time to possess highly efficient antibacterial activity by using Salmonella as a model pathogen. The growth curve and surface plate assay uncovered that 125 µg/mL MnO2 nanosheets could kill 99.2% of Salmonella, which was further verified by fluorescence-based live/dead staining measurement. Mechanism analysis indicated that MnO2 nanosheet treatment could dramatically induce reactive oxygen species production, increase ATPase activity and cause the leakage of electrolytes and protein contents, leading to bacterial death. These results uncover the previously undefined role of MnO2 nanosheets and provide novel strategies for developing antimicrobial agents.

High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology.

Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherapeutics for neurological and psychiatric disorders. Here, we describe an in vivo drug screening strategy that combines high-throughput technology to generate large-scale brain activity maps (BAMs) with machine learning for predictive analysis. This platform enables evaluation of compounds' mechanisms of action and potential therapeutic uses based on information-rich BAMs derived from drug-treated zebrafish larvae. From a screen of clinically used drugs, we found intrinsically coherent drug clusters that are associated with known therapeutic categories. Using BAM-based clusters as a functional classifier, we identify anti-seizure-like drug leads from non-clinical compounds and validate their therapeutic effects in the pentylenetetrazole zebrafish seizure model. Collectively, this study provides a framework to advance the field of systems neuropharmacology.

Autonomous system for cross-organ investigation of ethanol-induced acute response in behaving larval zebrafish.

Ethanol is widely consumed and has been associated with various diseases in different organs. It is therefore important to study ethanol-induced responses in living organisms with the capability to address specific organs in an integrative manner. Here, we developed an autonomous system based on a series of microfluidic chips for cross-organ investigation of ethanol-induced acute response in behaving larval zebrafish. This system enabled high-throughput, gel-free, and anesthetic-free manipulation of larvae, and thus allowed real-time observation of behavioral responses, and associated physiological changes at cellular resolution within specific organs in response to acute ethanol stimuli, which would otherwise be impossible by using traditional methods for larva immobilization and orientation. Specifically, three types of chips ("motion," "lateral," and "dorsal"), based on a simple hydrodynamic design, were used to perform analysis in animal behavior, cardiac, and brain physiology, respectively. We found that ethanol affected larval zebrafish in a dose-dependent manner. The motor function of different body parts was significantly modulated by ethanol treatment, especially at a high dose of 3%. These behavioral changes were temporally associated with a slow-down of heart-beating and a stereotyped activation of certain brain regions. As we demonstrated in this proof-of-concept study, this versatile Fish-on-Chip platform could potentially be adopted for systematic cross-organ investigations involving chemical or genetic manipulations in zebrafish model.

[The survey of prosthetic treatment in the elderly].

OBJECTIVE: To acquire teeth and prosthetic conditions of the elderly. METHODS: 1166 patients of over 60 years old had been given prosthetic treatment, and the teeth conditions were analyzed. RESULTS: The average number of missing teeth was 10.25. The maxillary missing teeth were more than mandibular ones. The rate of missing teeth were as follows: maxillary teeth > mandibular teeth; molars > bicuspids > incisors > cuspid. 1120 cases were treated with removable dentures. 59% of the removable partial dentures had free-end saddles. 46 cases were treated with fixed bridges. CONCLUSION: The characteristics of prosthetic patients in the elderly were as follows: a large number of missing teeth and free-end missing teeth, attrition of resident teeth, food impaction, existing-residual root and loosen teeth. Removable denture was the main method of the prosthetic therapy for the elderly patients. Fixed bridge was used when the patient condition was good. The cuspid, treated residual root and the third molar should be used for the retention and support of the prosthesis.