Prognostic value of tertiary lymphoid structures in hepatocellular carcinoma: a meta-analysis and systematic review.

Background: Multiple investigations and scholarly articles have presented compelling evidence indicating that tertiary lymphoid structures (TLS) play a pivotal role in inhibiting and controlling the advancement of tumors. While there is an abundance of information highlighting the importance of TLS in different cancer types, their prognostic significance specifically in hepatocellular carcinoma (HCC) cancers remains unclear. Thus, this meta-analysis aimed to explore the prognostic relevance of TLS in HCC. Methods: We conducted a thorough search across four databases, namely Web of Science, PubMed, Embase, and the Cochrane Library, to identify pertinent studies. The search utilized the keywords "tertiary lymphoid structures" and "hepatocellular carcinoma." The primary outcomes of interest encompassed overall survival (OS), recurrence-free survival (RFS), early recurrence, and late recurrence. The statistical effect size for these measures was expressed in terms of hazard ratios (HR). Results: Six studies were incorporated into the analysis. Among them, four studies, encompassing 6 datasets and involving 1490 patients, and three studies, comprising 5 datasets and involving 656 patients, respectively, investigated the correlation between intratumoral and peritumoral TLSs and the prognosis in HCC patients. The meta-analysis revealed that the presence of intratumoral TLSs is linked to longer RFS and reduced early recurrence (HR, 0.60; 95% CI, 0.50-0.67; p <0.001 and HR, 0.49; 95% CI, 0.36-0.65; p <0.001, respectively). However, no significant association was observed with OS and late recurrence. Sensitivity analysis demonstrated the robustness of these findings, and heterogeneities were minimal. Additionally, the meta-analysis did not detect a relationship between peritumoral TLSs and OS or RFS in HCC patients. Conclusion: The presence of intratumoral TLSs is correlated with better RFS and reduced early recurrence in HCC patients. Further investigation is warranted to elucidate the roles of peritumoral TLSs in the prognosis of HCC patients. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42023466793.

How does the SARS-CoV-2 reinfection rate change over time? The global evidence from systematic review and meta-analysis.

BACKGROUND: There is a significant increase in the number of SARS-CoV-2 reinfection reports in various countries. However, the trend of reinfection rate over time is not clear. METHODS: We searched PubMed, Web of Science, Medline, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, and Wanfang for cohort studies, case-control studies, and cross-sectional studies up to March 16, 2023, to conduct a meta-analysis of global SARS-CoV-2 reinfection rate. Subgroup analyses were performed for age, country, study type, and study population, and time-varying reinfection rates of SARS-CoV-2 were estimated using meta-regression. The risk of bias was assessed using the Newcastle-Ottawa Scale and the Joanna Briggs Institute critical appraisal tool. RESULT: A total of 55 studies involving 111,846 cases of SARS-CoV-2 reinfection were included. The pooled SARS-CoV-2 reinfection rate was 0.94% (95% CI: 0.65 -1.35%). In the subgroup analyses, there were statistically significant differences in the pooled reinfection rates by reinfection variant, and study type (P < 0.05). Based on meta-regression, the reinfection rate fluctuated with time. CONCLUSION: Meta-regression analysis found that the overall reinfection rate increased and then decreased over time, followed by a period of plateauing and then a trend of increasing and then decreasing, but the peak of the second wave of reinfection rate was lower than the first wave. SARS-CoV-2 is at risk of reinfection and the Omicron variant has a higher reinfection rate than other currently known variants. The results of this study could help guide public health measures and vaccination strategies in response to the Coronavirus Disease 2019 (COVID-19) pandemic.

Intestinal metabolite UroB alleviates cerebral ischemia/reperfusion injury by promoting competition between TRIM65 and TXNIP for binding to NLRP3 inflammasome in response to neuroinflammation.

Our previous research suggests that targeting NLRP3 inflammasomes holds promise for mitigating cerebral ischemia/reperfusion injury. The gut metabolite Urolithin B (UroB) has been shown to inhibit the neuroinflammation. However, the specific role of UroB in cerebral ischemia/reperfusion injury and its potential impact on NLRP3 inflammasome remain unclear. In this study, acute stroke was simulated using the MCAO model in male Sprague-Dawley rats. UroB was intraperitoneally administered after 1 h of reperfusion. The effects of UroB on brain tissue were evaluated, including infarct volume, brain edema, and neurobehavioral changes. Western blotting and immunofluorescence were performed to investigate the effect of UroB on inflammation-related proteins. Furthermore, TRIM65 knockdown and TXNIP overexpression experiments elucidated the role of UroB in NLRP3 inflammasome activation. The ( demonstrate the neuroprotective effect of UroB in acute stroke, reducing brain tissue damage and improving motor function. Mechanistically, UroB modulated neuroinflammation by influencing TXNIP and TRIM65 protein expression, as well as competitive binding to the NLRP3 inflammasome, attenuating cerebral ischemia/reperfusion injury. In conclusion, the potential of UroB as a protective agent against cerebral ischemia/reperfusion injury in acute stroke stands out as it regulates TRIM65 and TXNIP competitive binding to the NLRP3 inflammasome. These findings suggest that UroB is a promising drug candidate for the treatment of acute stroke.

Mechanisms of biochar assisted di-2-ethylhexyl phthalate (DEHP) biodegradation in tomato rhizosphere by metabolic and metagenomic analysis.

The intensive accumulation of di-2-ethylhexyl phthalate (DEHP) in agricultural soils has resulted in severe environmental pollution that endangers ecosystem and human health. Biochar is an eco-friendly material that can help in accelerating organic pollutant degradation; nevertheless, its roles in enhancing DEHP removal in rhizosphere remain unclear. This work investigated the impacts of biochar dosage (0%-2.0%) on DEHP degradation performance in tomato rhizosphere by comprehensively exploring the change in DEHP metabolites, bacterial communities and DEHP-degrading genes. Our results showed a significant increase of rhizosphere pH, organic matter and humus by biochar amendment, which achieved a satisfactorily higher DEHP removal efficiency, maximally 77.53% in treatments with 1.0% of biochar. Biochar addition also remarkably changed rhizosphere bacterial communities by enriching some potential DEHP degraders of Nocardioides, Sphingomonas, Bradyrhizobium and Rhodanobacter. The abundance of genes encoding key enzymes (hydrolase, esterase and cytochrome P450) and DEHP-degrading genes (pht3, pht4, pht5, benC-xylZ and benD-xylL) were increased after biochar amendment, leading to the change in DEHP degradation metabolism, primarily from benzoic acid pathway to protocatechuic acid pathway. Our findings evidenced that biochar amendment could accelerate DEHP degradation by altering rhizosphere soil physicochemical variables, bacterial community composition and metabolic genes, providing clues for the mechanisms of biochar-assisted DEHP degradation in organic contaminated farmland soils.

MTFR2-dependent mitochondrial fission promotes HCC progression.

BACKGROUND: The role of mitochondrial dynamics, encompassing fission, fusion, and mitophagy, in cancer progression has been extensively studied. However, the specific impact of mitochondrial dynamics on hepatocellular carcinoma (HCC) is still under investigation. METHODS: In this study, mitochondrial dynamic genes were obtained from the MitoCarta 3.0 database, and gene expression data were collected from The Cancer Genome Atlas (TCGA) database. Based on the expression of these dynamic genes and differentially expressed genes (DEGs), patients were stratified into two clusters. Subsequently, a prognostic model was constructed using univariate COX regression and the least absolute shrinkage and selection operator (LASSO) regression, and the prognostic signature was evaluated. We analyzed the interaction between these model genes and dynamic genes to identify hub genes and reveal mitochondrial status. Furthermore, we assessed immune infiltration, tumor mutational burden (TMB), tumor stemness indices (TSI), and the response to immune checkpoint block (ICB) therapy using the TIDE algorithm and risk scores. Additionally, transmission electron microscopy (TEM), hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC), western blotting (WB), and immunofluorescence (IF) were conducted to afford detailed visualization of the morphology of the mitochondria and the expression patterns of fission-associated proteins. RESULTS: Patients in Cluster 2 exhibited heightened mitochondrial fission and had a worse prognosis. The up-regulated dynamic genes in Cluster 2 were identified as fission genes. GO/KEGG analyses reconfirmed the connection of Cluster 2 to augmented mitochondrial fission activities. Subsequently, a ten-gene prognostic signature based on the differentially expressed genes between the two clusters was generated, with all ten genes being up-regulated in the high-risk group. Moreover, the potential links between these ten signature genes and mitochondrial dynamics were explored, suggesting their involvement in mediating mitochondrial fission through interaction with MTFR2. Further investigation revealed that the high-risk group had an unfavorable prognosis, with a higher mutation frequency of TP53, increased immune checkpoint expression, a higher TIS score, and a lower TIDE score. The mitochondrial imbalance characterized by increased fission and upregulated MTFR2 and DNM1L expression was substantiated in both HCC specimens and cell lines. CONCLUSIONS: In conclusion, we developed a novel MTFR2-related prognostic signature comprising ten mitochondrial dynamics genes. These genes play crucial roles in mitochondrial fission and have the potential to serve as important predictors and therapeutic targets for HCC.

Ultra-High-Density Ferroelectric Array Formed by Sliding Ferroelectric Moiré Superlattices.

2D van der Waals (vdW) materials offer infinite possibilities for constructing unique ferroelectrics through simple layer stacking and rotation. In this work, we stack nonferroelectric GeS2 and ferroelectric CuInP2S6 to form heterostructures by combining sliding ferroelectric polarization with displacement ferroelectric polarization to achieve multiple polarization states. First-principles calculations reveal that the polarization reversal of the CuInP2S6 component in the GeS2/CuInP2S6/GeS2 heterostructure can simultaneously drive the switching of sliding ferroelectric polarization, displaying a robust coupling of the two polarizations and leading to the overall polarization switching. Based on this, ferroelectric arrays with a density of 6.55 × 1012 cm-2 (equivalent to a storage density of 0.7 TB cm-2) were constructed in a moiré superlattice, and the polarization strength of array elements was 11.77 pC/m, higher than that of all reported 2D vdW out-of-plane ferroelectrics. High density, large polarization, and electrically switchable array elements in ferroelectric arrays provide unprecedented opportunities to design 2D high-density nonvolatile ferroelectric memories.

Evaluation of models for multi-step forecasting of hand, foot and mouth disease using multi-input multi-output: A case study of Chengdu, China.

BACKGROUND: Hand, foot and mouth disease (HFMD) is a public health concern that threatens the health of children. Accurately forecasting of HFMD cases multiple days ahead and early detection of peaks in the number of cases followed by timely response are essential for HFMD prevention and control. However, many studies mainly predict future one-day incidence, which reduces the flexibility of prevention and control. METHODS: We collected the daily number of HFMD cases among children aged 0-14 years in Chengdu from 2011 to 2017, as well as meteorological and air pollutant data for the same period. The LSTM, Seq2Seq, Seq2Seq-Luong and Seq2Seq-Shih models were used to perform multi-step prediction of HFMD through multi-input multi-output. We evaluated the models in terms of overall prediction performance, the time delay and intensity of detection peaks. RESULTS: From 2011 to 2017, HFMD in Chengdu showed seasonal trends that were consistent with temperature, air pressure, rainfall, relative humidity, and PM10. The Seq2Seq-Shih model achieved the best performance, with RMSE, sMAPE and PCC values of 13.943~22.192, 17.880~27.937, and 0.887~0.705 for the 2-day to 15-day predictions, respectively. Meanwhile, the Seq2Seq-Shih model is able to detect peaks in the next 15 days with a smaller time delay. CONCLUSIONS: The deep learning Seq2Seq-Shih model achieves the best performance in overall and peak prediction, and is applicable to HFMD multi-step prediction based on environmental factors.

City-level meteorological conditions modify the relationships between exposure to multiple air pollutants and the risk of pediatric hand, foot, and mouth disease in the Sichuan Basin, China.

Background: Several studies have examined the effects of city-level meteorological conditions on the associations between meteorological factors and hand, foot, and mouth disease (HFMD) risk. However, evidence that city-level meteorological conditions modify air pollutant-HFMD associations is lacking. Methods: For each of the 17 cities in the Sichuan Basin, we obtained estimates of the relationship between exposures to multiple air pollutants and childhood HFMD risk by using a unified distributed lag nonlinear model (DLNM). Multivariate meta-regression models were used to identify the effects of city-level meteorological conditions as effect modifiers. Finally, we conducted subgroup analyses of age and sex to explore whether the modification effects varied in different subgroups. Results: The associations between PM2.5/CO/O3 and HFMD risk showed moderate or substantial heterogeneity among cities (I2 statistics: 48.5%, 53.1%, and 61.1%). Temperature conditions significantly modified the PM2.5-HFMD association, while relative humidity and rainfall modified the O3-HFMD association. Low temperatures enhanced the protective effect of PM2.5 exposure against HFMD risk [PM2.5 <32.7 µg/m3 or PM2.5 >100 µg/m3, at the 99th percentile: relative risk (RR) = 0.14, 95% CI: 0.03-0.60]. Low relative humidity increased the adverse effect of O3 exposure on HFMD risk (O3 >128.7 µg/m3, at the 99th percentile: RR = 2.58, 95% CI: 1.48-4.50). However, high rainfall decreased the risk of HFMD due to O3 exposure (O3: 14.1-41.4 µg/m3). In addition, the modification effects of temperature and relative humidity differed in the female and 3-5 years-old subgroups. Conclusion: Our findings revealed moderate or substantial heterogeneity in multiple air pollutant-HFMD relationships. Temperature, relative humidity, and rainfall modified the relationships between PM2.5 or O3 exposure and HFMD risk.

Ketogenic diet ameliorates attention deficit hyperactivity disorder in rats via regulating gut microbiota.

Attention deficit hyperactivity disorder (ADHD) is a common mental behavioral disorder in children. Alterations in gut microbiota composition are associated with neurological disorders. We aimed to investigate whether a ketogenic diet (KD) can be an alternative therapy for ADHD by altering the gut microbiota. Male spontaneously hypertensive rats (SHR) and Wistar Kyoto (WKY) rats were randomly allocated to the normal diet (ND), methylphenidate (MPH), and KD groups. SHR in groups KD and MPH exhibited a significant increase in behavioral characteristics of ADHD, such as distance moved and immobility time. KD and MPH treatment led to a significant elevation in concentrations of 5-HT, AC, cAMP, and NE of brain tissue and the expression of DRD1, DAT, PKA, DARPP32, and cAMP at the protein level in WKY rats and SHR. KD and MPH significantly increased the richness and diversity of gut microbiota in SHR. The abundance of Ruminococcus_gauvreauii_group, Bacteroides, Bifidobacterium, and Blautia significantly increased, whereas that of Lactobacillus, Romboutsia, Facklamia, and Turicibacter significantly declined in the KD group compared with the ND group. The gut microbiota in the KD group of SHR mainly participated in amino acid metabolism- and sugar metabolism-related pathways. KD might alleviate behavioral disorders in ADHD by regulating gut microbiota. This study provides novel insights for the use of KD in treating ADHD.

New mechanisms of biochar-assisted vermicomposting by recognizing different active di-(2-ethylhexyl) phthalate (DEHP) degraders across pedosphere, charosphere and intestinal sphere.

Biochar-assisted vermicomposting can significantly accelerate soil DEHP degradation, but little information is known about the underlying mechanisms as different microspheres exist in soil ecosystem. In this study, we identified the active DEHP degraders in biochar-assisted vermicomposting by DNA stable isotope probing (DNA-SIP) and surprisingly found their different compositions in pedosphere, charosphere and intestinal sphere. Thirteen bacterial lineages (Laceyella, Microvirga, Sphingomonas, Ensifer, Skermanella, Lysobacter, Archangium, Intrasporangiaceae, Pseudarthrobacter, Blastococcus, Streptomyces, Nocardioides and Gemmatimonadetes) were responsible for in situ DEHP degradation in pedosphere, whereas their abundance significantly changed in biochar or earthworm treatments. Instead, some other active DEHP degraders were identified in charosphere (Serratia marcescens and Micromonospora) and intestinal sphere (Clostridiaceae, Oceanobacillus, Acidobacteria, Serratia marcescens and Acinetobacter) with high abundance. In biochar-assisted vermicomposting, the majority of active DEHP degraders were found in charosphere, followed by intestinal sphere and pedosphere. Our findings for the first time unraveled the spatial distribution of active DEHP degraders in different microspheres in soil matrices, explained by DEHP dynamic adsorption on biochar and desorption in earthworm gut. Our work highlighted that charosphere and intestinal sphere exhibited more contribution to the accelerated DEHP biodegradation than pedosphere, providing novel insight into the mechanisms of biochar and earthworm in improving contaminant degradation.

Epidemiological analysis and risk prediction of scrub typhus from 2006 to 2021 in Sichuan, China.

Background: In the past decade, the number of reported cases of scrub typhus (ST) has increased dramatically in Sichuan Province. We aimed to overview the epidemiological characteristics of ST, identify the variables contributing to the spatial distribution, and estimate the risk areas of ST occurrence. Methods: Daily ST cases reported at the county level from 2006 to 2021 and datasets on environmental and socioeconomic variables were obtained. Joinpoint regression model was utilized to examine the incidence trends and to calculate the annual percentage change. Global spatial autocorrelation analysis was employed to explore the spatial temporal patterns. Then BRT model was employed to identify variables that make sense and predict the risk areas of ST occurrence. Result: It has been reported that there were 6,338 ST cases in Sichuan Province from 2006 to 2021, and the incidence rates continued to rise. Most cases were distributed between June and October each year, peaking in August. During the study period, the cases showed spatial clustering at the county level, mainly in the Panxi area, and then slowly spread to the northwest and northeast. Shrubs, precipitation, farmland and maximum temperature were the primary variables that affected the spatial distribution of this disease. It was estimated that the areas including Liangshan, Panzhihua, Bazhong, and Guangyuan were most at risk of transmission. and there were approximately 32.315 million people living in the areas with potential risk of infection throughout Sichuan. Conclusion: Many counties in Sichuan Province were estimated to be susceptible to ST. Our found in this data-driven study could be used to guide the implementation of targeted prevention and control measures in high-risk areas.

Necroptosis-Related Prognostic Model for Pancreatic Carcinoma Reveals Its Invasion and Metastasis Potential through Hybrid EMT and Immune Escape.

Necroptosis, pro-inflammatory programmed necrosis, has been reported to exert momentous roles in pancreatic cancer (PC). Herein, the objective of this study is to construct a necroptosis-related prognostic model for detecting pancreatic cancer. In this study, the intersection between necroptosis-related genes and differentially expressed genes (DEGs) of pancreatic ductal adenocarcinoma (PDAC) was obtained based on GeneCards database, GEO database (GSE28735 and GSE15471), and verified using The Cancer Genome Atlas (TCGA). Next, a prognostic model with Cox and LASSO regression analysis, and divided the patients into high-risk and low-risk groups. Subsequently, the Kaplan-Meier (KM) survival curve and the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of overall survival (OS) of PC patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the potential biofunction and possible mechanical pathways. The EMTome database and an immune analysis were applied to further explore underlying mechanism. Finally, clinical samples of PDAC patients were utilized to verify the expression of model genes via immunohistochemistry (IHC), and the normal human pancreatic ductal cell line, hTERT-HPNE as well as human pancreatic ductal carcinoma cell lines, PANC-1 and PL45, were used to identify the levels of model genes by Western blot (WB) and immunofluorescence (IF) in vitro. The results showed that 13 necroptosis-related DEGs (NRDEGs) were screened based on GEO database, and finally four of five prognostic genes, including KRT7, KRT19, IGF2BP3, CXCL5, were further identified by TCGA to successfully construct a prognostic model. Univariate and multivariate Cox analysis ultimately confirmed that this prognostic model has independent prognostic significance, KM curve suggested that the OS of low-risk group was longer than high-risk group, and the area under receiver (AUC) of ROC for 1, 3, 5 years was 0.733, 0.749 and 0.667, respectively. A GO analysis illustrated that model genes may participate in cell-cell junction, cadherin binding, cell adhesion molecule binding, and neutrophil migration and chemotaxis, while KEGG showed involvement in PI3K-Akt signaling pathway, ECMreceptor interaction, IL-17 signaling pathway, TNF signaling pathway, etc. Moreover, our results showed KRT7 and KRT19 were closely related to EMT markers, and EMTome database manifested that KRT7 and KRT19 are highly expressed in both primary and metastatic pancreatic cancer, declaring that model genes promoted invasion and metastasis potential through EMT. In addition, four model genes were positively correlated with Th2, which has been reported to take part in promoting immune escape, while model genes except CXCL5 were negatively correlated with TFH cells, indicating that model genes may participate in immunity. Additionally, IHC results showed that model genes were higher expressed in PC tissues than that in adjacent tumor tissues, and WB and IF also suggested that model genes were more highly expressed in PANC-1 and PL45 than in hTERT-HPNE. Tracing of a necroptosis-related prognostic model for pancreatic carcinoma reveals its invasion and metastasis potential through EMT and immunity. The construction of this model and the possible mechanism of necroptosis in PDAC was preliminarily explored to provide reliable new biomarkers for the early diagnosis, treatment, and prognosis for pancreatic cancer patients.

Di-2-ethylhexyl phthalate (DEHP) degradation and microbial community change in mangrove rhizosphere gradients.

Di-2-ethylhexyl phthalate (DEHP) is a widespread persistent organic pollutant in the environment. As an ultimate barrier preventing pollutant entry into the ocean, mangrove plays an important role in coastal ecosystem. However, little information is known about DEHP degradation in mangrove rhizosphere. In this study, a rhizobox was used to separate four consecutive rhizosphere compartments with distance of 0-2, 2-4, 4-6, and > 6 mm to the rhizoplane of Kandelia obovata and investigate DEHP gradient degradation behavior in rhizosphere. Sediments closer to the rhizoplane exhibited higher DEHP degradation efficiencies (74.4 % in 0-2 mm layer). More precisely, mangrove rhizosphere promoted the benzoic acid pathway and non-selectively accelerated the production of mono(2-ethylhexyl) phthalate, phthalic acid and benzoic acid. Higher sediment organic matter content, lower pH and less humus in rhizosphere benefited DEHP hydrolysis. In addition, rhizosphere significantly increased microbial biomass and activities comparing to bulk sediments. Some bacterial lineages with potential DEHP degradation capability exhibited a distance-dependent pattern that decreased with the distance to the rhizoplane, including Bacillales, Acidothermaceae, Gammaproteobacteria, and Sphingobacteriales. Our findings suggested that mangrove rhizosphere could accelerate DEHP degradation by altering sediment physicochemical properties and microbial composition, showing positive effects on coastal ecosystem services for eliminating phthalate acid ester contamination.

Cell Cycle-Related Gene SPC24: A Novel Potential Diagnostic and Prognostic Biomarker for Laryngeal Squamous Cell Cancer.

Laryngeal squamous cell cancer (LSCC) is a common malignant tumor with a high degree of malignancy, and its etiology remains unclear. Therefore, screening potential biomarkers is necessary to facilitate the treatment and diagnosis of LSCC. Robust rank aggregation (RRA) analysis was used to integrate two gene expression datasets of LSCC patients from the Gene Expression Omnibus (GEO) database and identify differentially expressed genes (DEGs) between LSCC and nonneoplastic tissues. A gene coexpression network was constructed using weighted gene correlation network analysis (WGCNA) to explore potential associations between the module genes and clinical features of LSCC. Combining differential gene expression analysis and survival analysis, we screened potential hub genes, including CDK1, SPC24, HOXB7, and SELENBP1. Subsequently, western blotting and immunohistochemistry were used to test the protein levels in clinical specimens to verify our findings. Finally, four candidate diagnostic and prognostic biomarkers (CDK1, SPC24, HOXB7, and SELENBP1) were identified. We propose, for the first time, that SPC24 is a gene that may associate with LSCC malignancy and is a novel therapeutic target. These findings may provide important mechanistic insight of LSCC.

Optimizing laboratory-based surveillance networks for monitoring multi-genotype or multi-serotype infections.

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

Inhibition of miR-423-5p Exerts Neuroprotective Effects in an Experimental Rat Model of Cerebral Ischemia/Reperfusion Injury.

MicroRNAs (miRNAs) are widely acknowledged to play a unique role in cerebrovascular disease. This research investigates the function of microRNAs in ischemic stroke via a middle cerebral artery occlusion (MCAO) model. Four differentially expressed microRNAs in rat brains were identified by bioinformatics analysis, and qRT-PCR showed that miR-423-5p exhibited the highest expression in cerebral ischemia/reperfusion injury in rats, with peak levels observed at 24 hours. After microRNA inhibitors and mimics were administrated in the rat model of MCAO, the neurological scores and brain water content were detected, and triphenyltetrazolium chloride (TTC), Hematoxylin and Eosin (H&E), and Nissl staining were conducted to explore the influence of miR-423-5p on ischemic stroke. Subsequently, western blot, ELISA, MPO, TUNEL and commercial assay kits were applied to assess the influence of miR-423-5p on NLRP3 inflammasome, apoptosis, and oxidative stress levels in ischemic penumbra tissue. The results showed that miR-423-5p knockdown could effectively improve neurological indicators, such as cerebral infarct volume, brain water content, neurological scores, and nerve tissue damage, and inhibit the NLRP3 inflammasome, apoptosis, and oxidative stress. In contrast, the miR-423-5p mimic yielded opposite results. In conclusion, inhibition of miR-423-5p expression could effectively attenuate ischemic stroke and might be considered a promising target for stroke.

Editorial for the Special Issue "Nanoscale Ferroic Materials-Ferroelectric, Piezoelectric, Magnetic, and Multiferroic Materials".

Ferroic materials, including ferroelectric, piezoelectric, magnetic, and multiferroic materials, are receiving great scientific attentions due to their rich physical properties [...].

Healthy cities initiative in China: Progress, challenges, and the way forward.

China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Along with related urban health governmental initiatives, the program has helped put health on the agenda of local governments while raising public awareness. Healthy City actions taken at the municipal scale also prepared cities to deal with the COVID-19 pandemic. However, after intermittent trials spanning the past two decades, the Healthy Cities initiative in China has reached a crucial juncture. It risks becoming inconsequential given its overlap with other health promotion efforts, changing public health priorities in response to the pandemic, and the partial adoption of the Healthy Cities approach advanced by the World Health Organization (WHO). We recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health. Achieving this alignment will require leveraging the full spectrum of best practices in Healthy Cities actions and expanding assessment efforts. Funding: Tsinghua-Toyota Joint Research Fund "Healthy city systems for smart cities" program.