[Randomized,double-blind,parallel controlled,multicenter clinical trial of effectiveness and safety of Shexiang Zhuifeng Zhitong Ointment in alleviating pain in knee osteoarthritis(syndrome of cold-dampness obstruction)].

The Shexiang Zhuifeng Zhitong Ointment with the effects of dispelling wind, removing dampness, dissipating cold, and relieving pain is used for treating arthralgia, muscular pain, and sprain pain caused by cold-dampness obstruction. To evaluate the efficacy and safety of Shexiang Zhuifeng Zhitong Ointment in relieving the pain due to knee osteoarthritis(syndrome of cold-dampness obstruction), a randomized, double-blind, parallel controlled, multicenter clinical trial was conducted. The stratified randomization method was used to randomize the 240 subjects into a treatment group and a control group in a ratio of 1∶1. In each group, 60 patients received external application for 12 h and the other 60 patients received external application for 6 h. The treatment group received external application of Shexiang Zhuifeng Zhitong Ointment, while the control group received external application of Shexiang Zhuifeng Ointment. The treatment lasted for 21 days in both groups. Follow-up was conducted on days 7, 14, and 21 of treatment. The results based on the full analysis set were as follows.(1)In visual analog scale(VAS) score, the mean difference in the VAS score between baseline and 12 h post-treatment was 3.02 in the treatment group and 2.31 in the control group, with a significant difference(P<0.05). The mean difference in the VAS score between baseline and 6 h post-treatment was 3.19 in the treatment group and 2.48 in the control group, with a significant difference(P<0.05).(2)Response rate in terms of VAS score, after treatment for 12 h, the response rate was 93.22% in the treatment group and 73.33% in the control group, with a significant difference(P<0.05). After treatment for 6 h, theresponse rate in the treatment group was 88.33%, which was higher than that(63.33%) in the control group(P<0.05).The results showed that Shexiang Zhuifeng Zhitong Ointment applied for 12 and 6 h effectively relieved the knee joint pain of patients with knee osteoarthritis due to cold-dampness obstruction, as demonstrated by the reduced VAS score, Western Ontario and McMaster Universities Arthritis Index(WOMAC), stiffness, and joint function score. Moreover, Shexiang Zhuifeng Zhitong Ointment outperformed the positive control Shexiang Zhuifeng Ointment in terms of reducing the VAS score, demonstrating a definitetherapeutic effect on the pain due to knee osteoarthritis(syndrome of cold-dampness obstruction).In addition, Shexiang Zhuifeng Zhitong Ointment did not cause other adverse reactions except for mild allergic reactions, which were common in the external application of traditional Chinese medicine plasters on the skin, inseveral patients.Neither other adverse reactions nor abnormalities of liver and kidney functions and electrocardiogram were observed. This ointment had high safety and could be popularized in clinical application.

Mild and catalytic electrocyclizations of heptatrienyl anions.

We report the synthesis of functionalized cycloheptanes by thermal electrocyclization of heptatrienyl anions under mild conditions. In addition, we disclose the first examples of this electrocyclization manifold conducted under catalytic conditions. Previously, electrocyclization of heptatrienyl systems required formation of anions with a strong base, resulting in limited functional group compatibility. We demonstrate that polarization of heptatrienyl anions using strategically positioned electron-withdrawing groups lowers the energy landscape of the reaction by stabilizing both the acyclic heptatrienyl anion and cycloheptadienyl product. Divergent reactivity is observed between aliphatic and aromatic substrates, with the latter requiring only catalytic amounts of base for complete conversion. This can be rationalized by the relative stability of the acyclic and cyclic anions and their ability to participate in a chain reaction process.

Effects of apparent temperature on daily outpatient and inpatient visits for cause-specific respiratory diseases in Ganzhou, China: a time series study.

BACKGROUND: Non-optimum temperatures are associated with increased risk of respiratory diseases, but the effects of apparent temperature (AT) on respiratory diseases remain to be investigated. METHODS: Using daily data from 2016 to 2020 in Ganzhou, a large city in southern China, we analyzed the impact of AT on outpatient and inpatient visits for respiratory diseases. We considered total respiratory diseases and five subtypes (influenza and pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma and chronic obstructive pulmonary disease [COPD]). Our analysis employed a distributed lag nonlinear model (DLNM) combined with a generalized additive model (GAM). RESULTS: We recorded 94,952 outpatients and 72,410 inpatients for respiratory diseases. We found AT significantly non-linearly associated with daily outpatient and inpatient visits for total respiratory diseases, influenza and pneumonia, and URTI, primarily during comfortable AT levels, while it was exclusively related with daily inpatient visits for LRTI and COPD. Moderate heat (32.1 °C, the 75.0th centile) was observed with a significant effect on both daily outpatient and inpatient visits for total respiratory diseases at a relative risk of 1.561 (1.161, 2.098) and 1.276 (1.027, 1.585), respectively (both P < 0.05), while the results of inpatients became insignificant with the adjustment for CO and O3. The attributable fractions in outpatients and inpatients were as follows: total respiratory diseases (24.43% and 18.69%), influenza and pneumonia (31.54% and 17.33%), URTI (23.03% and 32.91%), LRTI (37.49% and 30.00%), asthma (9.83% and 3.39%), and COPD (30.67% and 10.65%). Stratified analyses showed that children ≤5 years old were more susceptible to moderate heat than older participants. CONCLUSIONS: In conclusion, our results indicated moderate heat increase the risk of daily outpatient and inpatient visits for respiratory diseases, especially among children under the age of 5.

Predicting lncRNA-protein interactions through deep learning framework employing multiple features and random forest algorithm.

RNA-protein interaction (RPI) is crucial to the life processes of diverse organisms. Various researchers have identified RPI through long-term and high-cost biological experiments. Although numerous machine learning and deep learning-based methods for predicting RPI currently exist, their robustness and generalizability have significant room for improvement. This study proposes LPI-MFF, an RPI prediction model based on multi-source information fusion, to address these issues. The LPI-MFF employed protein-protein interactions features, sequence features, secondary structure features, and physical and chemical properties as the information sources with the corresponding coding scheme, followed by the random forest algorithm for feature screening. Finally, all information was combined and a classification method based on convolutional neural networks is used. The experimental results of fivefold cross-validation demonstrated that the accuracy of LPI-MFF on RPI1807 and NPInter was 97.60% and 97.67%, respectively. In addition, the accuracy rate on the independent test set RPI1168 was 84.9%, and the accuracy rate on the Mus musculus dataset was 90.91%. Accordingly, LPI-MFF demonstrated greater robustness and generalization than other prevalent RPI prediction methods.

Analysis of drug-induced posterior reversible encephalopathy syndrome using the food and drug administration adverse drug events reporting system database.

OBJECTIVE: In this retrospective pharmacovigilance study, we gathered data on drug-induced posterior reversible encephalopathy syndrome (PRES). Our goal was to identify the primary suspect drugs in PRES by analyzing the Food and Drug Administration Adverse Events Reporting System (FAERS) database. METHODS: We identified and analyzed reports of PRES listed in the FAERS database between 2004 and 2021. Using the reporting odds ratio and 95% confidence interval, we evaluated the safety signals for each of the drugs associated with PRES. RESULTS: We reviewed 11,077 reports of adverse events corresponding to PRES. The primary suspect drug categories were antineoplastics, immunosuppressants, and glucocorticoids. PRES was 24.77% more likely to occur in females than in males. Drug-induced PRES usually occurs in individuals with cancer, those who have undergone an organ/stem cell transplant, and those with autoimmune conditions. CONCLUSION: Our results show that the drugs most commonly suspected to cause PRES were antineoplastics, immunosuppressants, and glucocorticoids. Future studies are needed to illuminate the pathophysiological alterations that underlie PRES. In the meantime, prescribers and patients should be made aware of the potential risks of PRES associated with pharmaceutical therapy, and the summaries of product characteristics for individual drugs should be updated to include this information.

Clinical data mining: challenges, opportunities, and recommendations for translational applications.

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

Personalized differential expression analysis in triple-negative breast cancer.

Identification of individual-level differentially expressed genes (DEGs) is a pre-step for the analysis of disease-specific biological mechanisms and precision medicine. Previous algorithms cannot balance accuracy and sufficient statistical power. Herein, RankCompV2, designed for identifying population-level DEGs based on relative expression orderings, was adjusted to identify individual-level DEGs. Furthermore, an optimized version of individual-level RankCompV2, named as RankCompV2.1, was designed based on the assumption that the rank positions of genes and relative rank differences of gene pairs would influence the identification of individual-level DEGs. In comparison to other individualized analysis algorithms, RankCompV2.1 performed better on statistical power, computational efficiency, and acquired coequal accuracy in both simulation and real paired cancer-normal data from ten cancer types. Besides, single sample GSEA and Gene Set Variation Analysis analysis showed that pathways enriched with up-regulated and down-regulated genes presented higher and lower enrichment scores, respectively. Furthermore, we identified 16 genes that were universally deregulated in 966 triple-negative breast cancer (TNBC) samples and interacted with Food and Drug Administration (FDA)-approved drugs or antineoplastic agents, indicating notable therapeutic targets for TNBC. In addition, we also identified genes with highly variable deregulation status and used these genes to cluster TNBC samples into three subgroups with different prognoses. The subgroup with the poorest outcome was characterized by down-regulated immune-regulated pathways, signal transduction pathways, and apoptosis-related pathways. Protein-protein interaction network analysis revealed that OAS family genes may be promising drug targets to activate tumor immunity in this subgroup. In conclusion, RankCompV2.1 is capable of identifying individual-level DEGs with high accuracy and statistical power, analyzing mechanisms of carcinogenesis and exploring therapeutic strategy.

Association between increased C-reactive protein and cardiovascular disease among patients with rectal cancer.

Purpose: This study aimed to investigate the association between increased C-reactive protein (CRP) and cardiovascular disease (CVD) in individuals with rectal cancer, as well as to understand the effect of chemotherapy for cancer on increasing CRP and its underlying mechanisms. Patients and methods: From January 1, 2010 to December 31, 2020, individuals with rectal cancer were evaluated at the First Affiliated Hospital of Gannan Medical University. Then, in patients with rectal cancer, the relationship between increased CRP and CVD attributes was summarized, and the impact of chemotherapy on CRP levels was qualitatively assessed. For further investigation into potential regulatory mechanisms of CRP, differentially expressed genes (DEGs), GO and KEGG enrichment analyses were conducted. Results: A total of 827 individuals were included in the study, including 175 with CVD (21.16%) and 652 without CVD. A significant association between increased CRP and CVD events was observed in rectal cancer patients (p < 0.01), and it significantly improved the classification performance of the CVD predictive model in the AUC (0.724 vs 0.707) and NRI (0.069, 95% CI 0.05-0.14). Furthermore, a comparison of CRP levels before and after chemotherapy revealed a significant increase among rectal cancers post-treatment (p < 0.001). Analysis of differentially expressed genes and co-expression indicated that 96 DEGs were involved in the pathophysiology of increased CRP after chemotherapy, and three hub genes were implicated in atherosclerotic susceptibility. Conclusion: In conclusion, our findings indicated that increased CRP levels following chemotherapy profoundly impacted CVD events in individuals with rectal cancer, and may be beneficial in promoting CVD prediction in clinical practice.

Effects of elevated carbon dioxide (CO2)and ozone (O3)concentrations on ectoenzyme activities in rice rhizospheric soil.

Rising atmospheric carbon dioxide (CO2) and ozone (O3) concentrations are the main global change drivers. Soil ectoenzymes play an important role in maintaining soil ecosystem services. Exploring the responses of soil ectoenzymes to elevated CO2 and O3 concentrations is important for combating global climate change. In this study, we simulated elevated CO2 concentrations (+200 µmol·mol-1, eCO2), elevated O3 concentrations (0.04 µmol·mol-1, eO3), and their combination (eCO2+eO3) in open-top chambers (OTCs), and investigated the responses of rhizospheric soil ectoenzyme activities. The results showed that eCO2 significantly increased the ß-D-Glucosidase (ßG) activity by 73.0%, and decreased that of polyphenol oxidase (PHO), peroxidase (PEO), and acid phosphatase (AP) by 48.9%, 46.6% and 72.9% respectively, but did not affect that of cellulose hydrolase (CBH) and ß-N-Acetylglucosaminidase (NAG). eO3 significantly reduced the activities of CBH and AP by 34.2% and 30.4%, respectively. The activities of PHO and AP were reduced by 87.3% and 32.3% under the eCO2+eO3 compared with the control, respectively. Results of the principal coordinate analysis, permutation multivariate analysis of variance and redundancy analysis showed that both elevated CO2 and O3 significantly affected soil ectoenzyme activities, with stronger effects of elevated CO2 than elevated O3. Root nitrogen content, root carbon to nitrogen ratio, soil microbial biomass carbon and nitrate nitrogen were the main drivers of soil ectoenzyme activities under elevated CO2 and O3. Elevated O3 could partially neutralize the effects of elevated CO2 on soil ectoenzyme activities. In conclusion, elevated CO2 and O3 restrained the activities of most soil ectoenzyme, suggesting that climate change would threat soil ecosystem services and functions in the agroecosystem.

Molecular and Morphological Identification of Monilia yunnanensis Causing Brown Rot on Chinese Quince and Peach in Yunnan, China.

More than 30% of fruits of Chinese Quince (Chaenomeles speciosa) and peach (Prunus persica) showed circular, water-soaked and brown spots in July 2022 in Kunming, Yunnan, China. The center of these spots was covered by a large number of earthy brown and oblate sporogeneous mycelium containing conidiophore and conidia, which were one-celled, limoniform, hyaline (13.73 to 22.77 x 8.17 to 12.84 µm, n=50). By September 2022, almost 100% of fruits showed symptoms. Later, most of them fell or a few stiff, black and mummified fruits were left on the trees. Fungal isolates were isolated by single-spore technique on Potato Dextrose agar (PDA) from the diseased fruits, and incubated at room temperature (20-28 °C) in darkness for 14 days. The colony was gray, smooth at margins, 7.6-8.0 cm in diameter. To fullfill Koch's postulates, mycelial plugs of one representative isolate YHD611 from Chinese Quince and another YHD610 from peach were used to inoculate three wounded and three non-wounded surface-disinfected fruits of both hosts at room temperature (19-27 °C), respectively. Three wounded and three non-wounded fruits inoculated with sterile PDA plugs served as the control. The wounded peaches appeared water-soaked and had brown lesions after three days of inoculation, then completely decayed after nine days, while non-wounded fruits showed symptoms after five days. The wounded fruits of Chinese Quince developed similar symptoms after eight days of inoculation, and completely decayed after 13 days, while non-wounded fruits showed obvious symptoms after 15 days. In a subsequent study, isolate YHD611 was inoculated to peach while isolate YHD610 was inoculated to Chinese Quince to understand host specificity of the isolates. The results showed that when peaches were infected with YHD611, symptoms were observed on wounded fruits after three days while on non-wounded fruits after five days. When Chinese Quince was infected with YHD610, symptoms were observed on wounded fruits after 14 days while on non-wounded fruits after 21 days. Fungal isolates from symptomatic fruits were identical to the original isolates. There were no symptoms on the control fruits of both hosts. Molecular identification was confirmed based on the sequences of internal transcribed spacer (ITS, primers ITS1 and ITS4) and ß-tubulin (TUB2, primers Bt2a and Bt2b) genes (Niu et al. 2016). BLASTn analysis of the ITS (OQ15519and OQ155196) and TUB2 (OQ185202 and OQ185201) of YHD611 and YHD610 revealed a 100% sequence identity, respectively, to Monilia yunnanensis AH7-2 (KT735924.1 for ITS, KT736008.1 for TUB2). In the phylogenetic analyses based on ITS and TUB2 sequence data, the isolates YHD611 and YHD610 belonged to the M. yunnanensis clade. Based on morphological and molecular identification, both isolates were identified as M. yunnanensis, which was reported as the pathogen causing brown rot of plum, peach, apple and pear in Yunnan, China (Hu et al. 2011; Yin et al. 2015). To our knowledge, this is the first report of M. yunnanensis causing brown rot on the fruits of Chinese Quince in Yunnan, China. This study also reports that M. yunnanensis from Chinese Quince can infect peach, and the pathogen from peach can infect Chinese Quince. These findings suggest that M. yunnanensis can transfer from one host to another and causing serious economic losses in multiple fruit crops in Yunnan, China. References: Hu, M. J., et al. 2011. PLoS One. 6:e24990. Niu, C. W., et al. 2016. Mycosystema, 35(10):1. Yin, L. F., et al. 2015. Plant Dis. 99:1775.

Floral trait variation across individual plants within a population enhances defense capability to nectar robbing.

Floral trait variation may help pollinators and nectar robbers identify their target plants and, thus, lead to differential selection pressure for defense capability against floral antagonists. However, the effect of floral trait variation among individuals within a population on multi-dimensional plant-animal interactions has been little explored. We investigated floral trait variation, pollination, and nectar robbing among individual plants in a population of the bumble bee-pollinated plant, Caryopteris divaricata, from which flowers are also robbed by bumble bees with varying intensity across individuals. We measured the variation in corolla tube length, nectar volume and sugar concentration among individual plants, and evaluated whether the variation were recognized by pollinators and robbers. We investigated the influence of nectar robbing on legitimate visitation and seed production per fruit. We found that the primary nectar robber (Bombus nobilis) preferred to forage on plants with long-tubed flowers, which produced less nectar and had lower sugar concentration compared to those with shorter corolla tubes. Individuals with shorter corolla tubes had comparatively lower nectar robbing intensity but higher visitation by legitimate visitors (mainly B. picipes) and higher seed production. Nectar robbing significantly reduced seed production because it decreased pollinator visits. However, neither pollination nor seed production differed between plants with long and short corolla tubes when nectar robbers were excluded. This finding suggests that floral trait variation might not be driven by pollinators. Such variation among individual plants thus allows legitimate visitors and nectar robbers to segregate niches and enhances population defense against nectar robbing in unpredictable conditions.

Progress in the diagnosis of lymph node metastasis in rectal cancer: a review.

Historically, the chief focus of lymph node metastasis research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen a rapid accumulation of massive omics and imaging data catalyzed by the rapid development of advanced technologies. This rapid increase in data has driven improvements in the accuracy of diagnosis of lymph node metastasis, and its analysis further demands new methods and the opportunity to provide novel insights for basic research. In fact, the combination of omics data, imaging data, clinical medicine, and diagnostic methods has led to notable advances in our basic understanding and transformation of lymph node metastases in rectal cancer. Higher levels of integration will require a concerted effort among data scientists and clinicians. Herein, we review the current state and future challenges to advance the diagnosis of lymph node metastases in rectal cancer.

Biosensor-Enabled Discovery of CaERG6 Inhibitors and Their Antifungal Mode of Action against Candida albicans.

Fungal infections caused by opportunistic pathogens, such as Candida albicans, are generally underappreciated by the public in spite of their high mortality rates. Antifungal arsenals are extremely limited. Herein, based on biosynthetic pathway comparison and functional characterization, CaERG6, a crucial sterol 24-C-methyltransferase involved in the biosynthesis of ubiquitous ergosterol in C. albicans, was set up as an antifungal target. CaERG6 inhibitors were identified from the in-house small-molecule library by a biosensor-based high-throughput screening. The CaERG6 inhibitor NP256 (palustrisoic acid E) is a potential antifungal natural product that acts by inhibiting ergosterol biosynthesis, downregulating the gene expression level in hyphal formation, blocking biofilm formation, and disrupting morphological transition in C. albicans. NP256 enhances C. albicans susceptibility to some known antifungals significantly. The present study demonstrated the CaERG6 inhibitor NP256 as a potential class of antifungal compound for monotherapy or combinatory therapy.

eccDB: a comprehensive repository for eccDNA-mediated chromatin contacts in multi-species.

SUMMARY: We developed the eccDB database to integrate available resources for extrachromosomal circular DNA (eccDNA) data. eccDB is a comprehensive repository for storing, browsing, searching, and analyzing eccDNAs from multispecies. The database provides regulatory and epigenetic information on eccDNAs, with a focus on analyzing intrachromosomal and interchromosomal interactions to predict their transcriptional regulatory functions. Moreover, eccDB identifies eccDNAs from unknown DNA sequences and analyzes the functional and evolutionary relationships of eccDNAs among different species. Overall, eccDB offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher the molecular regulatory mechanisms of eccDNAs. AVAILABILITY AND IMPLEMENTATION: eccDB is freely available at http://www.xiejjlab.bio/eccDB.

Data mining for signal detection of adverse events for taxanes based on the food and drug administration adverse drug events reporting system database.

BACKGROUND: This study aimed to mine and compare the positive signals of adverse drug events (ADE) in paclitaxel, docetaxel, and nab-paclitaxel to evaluate the accuracy of current drug package information inserts and enable clinicians to select the appropriate treatment. RESEARCH DESIGN AND METHODS: ADE data reported from January 2006 to December 2020 were extracted from the Food and Drug Adverse Drug Events Reporting System (FAERS) database, and the reporting odds ratio (ROR) was used to detect the risk signals of the 3 taxanes. The definition relied on system organ class (SOCs) and preferred terms (PTs) by the Medical Dictionary for Regulatory Activities (MedDRA). RESULTS: A total of 39,163 case reports on paclitaxel, docetaxel and nab-paclitaxel involving 25 different system organ classes (SOCs) were retrieved from the database. The ADE paclitaxel and nab-paclitaxel reports mainly focused on 'general disorders and administration site conditions' and the docetaxel ADE reports focused on 'skin and subcutaneous tissue diseases.' Among the three taxanes, nab-paclitaxel had the highest positive signal for serious adverse events. CONCLUSIONS: Overall, the most common ADE signals and ADE mapping systems obtained in this study were consistent with the package inserts. However, some inconsistencies were noted. Further research is recommended to confirm some of the strong risk signals for ADEs for taxanes before updating the drug package information inserts.

Construct of qualitative diagnostic biomarkers specific for glioma by pairing serum microRNAs.

BACKGROUND: Serum microRNAs (miRNAs) are promising non-invasive biomarkers for diagnosing glioma. However, most reported predictive models are constructed without a large enough sample size, and quantitative expression levels of their constituent serum miRNAs are susceptible to batch effects, decreasing their clinical applicability. METHODS: We propose a general method for detecting qualitative serum predictive biomarkers using a large cohort of miRNA-profiled serum samples (n = 15,460) based on the within-sample relative expression orderings of miRNAs. RESULTS: Two panels of miRNA pairs (miRPairs) were developed. The first was composed of five serum miRPairs (5-miRPairs), reaching 100% diagnostic accuracy in three validation sets for distinguishing glioma and non-cancer controls (n = 436: glioma = 236, non-cancers = 200). An additional validation set without glioma samples (non-cancers = 2611) showed a predictive accuracy of 95.9%. The second panel included 32 serum miRPairs (32-miRPairs), reaching 100% diagnostic performance in training set on specifically discriminating glioma from other cancer types (sensitivity = 100%, specificity = 100%, accuracy = 100%), which was reproducible in five validation datasets (n = 3387: glioma = 236, non-glioma cancers = 3151, sensitivity> 97.9%, specificity> 99.5%, accuracy> 95.7%). In other brain diseases, the 5-miRPairs classified all non-neoplastic samples as non-cancer, including stroke (n = 165), Alzheimer's disease (n = 973), and healthy samples (n = 1820), and all neoplastic samples as cancer, including meningioma (n = 16), and primary central nervous system lymphoma samples (n = 39). The 32-miRPairs predicted 82.2 and 92.3% of the two kinds of neoplastic samples as positive, respectively. Based on the Human miRNA tissue atlas database, the glioma-specific 32-miRPairs were significantly enriched in the spinal cord (p = 0.013) and brain (p = 0.015). CONCLUSIONS: The identified 5-miRPairs and 32-miRPairs provide potential population screening and cancer-specific biomarkers for glioma clinical practice.

Association of ambient carbon monoxide exposure with hospitalization risk for respiratory diseases: A time series study in Ganzhou, China.

Background: Ambient carbon monoxide (CO) exposure is associated with increased mortality and hospitalization risk for total respiratory diseases. However, evidence on the risk of hospitalization for specific respiratory diseases from ambient CO exposure is limited. Methods: Data on daily hospitalizations for respiratory diseases, air pollutants, and meteorological factors from January 2016 to December 2020 were collected in Ganzhou, China. A generalized additive model with the quasi-Poisson link and lag structures was used to estimate the associations between ambient CO concentration and hospitalizations of total respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), and influenza-pneumonia. Possible confounding co-pollutants and effect modification by gender, age, and season were considered. Results: A total of 72,430 hospitalized cases of respiratory diseases were recorded. Significant positive exposure-response relationships were observed between ambient CO exposure and hospitalization risk from respiratory diseases. For each 1 mg/m3 increase in CO concentration (lag0-2), hospitalizations for total respiratory diseases, asthma, COPD, LRTI, and influenza-pneumonia increased by 13.56 (95% CI: 6.76%, 20.79%), 17.74 (95% CI: 1.34%, 36.8%), 12.45 (95% CI: 2.91%, 22.87%), 41.25 (95% CI: 18.19%, 68.81%), and 13.5% (95% CI: 3.41%, 24.56%), respectively. In addition, the associations of ambient CO with hospitalizations for total respiratory diseases and influenza-pneumonia were stronger during the warm season, while women were more susceptible to ambient CO exposure-associated hospitalizations for asthma and LRTI (all P < 0.05). Conclusion: In brief, significant positive exposure-response relationships were found between ambient CO exposure and hospitalization risk for total respiratory diseases, asthma, COPD, LRTI, and influenza-pneumonia. Effect modification by season and gender was found in ambient CO exposure-associated respiratory hospitalizations.

Associations between short-term PM2.5 exposure and daily hospital admissions for circulatory system diseases in Ganzhou, China: A time series study.

Objective: Previous epidemiological studies have shown that both long-term and short-term exposure to fine particulate matters (PM2.5) were associated with the morbidity and mortality of circulatory system diseases (CSD). However, the impact of PM2.5 on CSD remains inconclusive. This study aimed to investigate the associations between PM2.5 and circulatory system diseases in Ganzhou. Methods: We conducted this time series study to explore the association between ambient PM2.5 exposure and daily hospital admissions for CSD from 2016 to 2020 in Ganzhou by using generalized additive models (GAMs). Stratified analyses were also performed by gender, age, and season. Results: Based on 201,799 hospitalized cases, significant and positive associations were found between short-term PM2.5 exposure and hospital admissions for CSD, including total CSD, hypertension, coronary heart disease (CHD), cerebrovascular disease (CEVD), heart failure (HF), and arrhythmia. Each 10 µg/m3 increase in PM2.5 concentrations was associated with a 2.588% (95% confidence interval [CI], 1.161%-4.035%), 2.773% (95% CI, 1.246%-4.324%), 2.865% (95% CI, 0.786%-4.893%), 1.691% (95% CI, 0.239%-3.165%), 4.173% (95% CI, 1.988%-6.404%) and 1.496% (95% CI, 0.030%-2.983%) increment in hospitalizations for total CSD, hypertension, CHD, CEVD, HF, and arrhythmia, respectively. As PM2.5 concentrations rise, the hospitalizations for arrhythmia showed a slow upward trend, while other CSD increased sharply at high PM2.5 levels. In subgroup analyses, the impacts of PM2.5 on hospitalizations for CSD were not materially changed, although the females had higher risks of hypertension, HF, and arrhythmia. The relationships between PM2.5 exposure and hospitalizations for CSD were more significant among individuals aged ≤65 years, except for arrhythmia. PM2.5 had stronger effects on total CSD, hypertension, CEVD, HF, and arrhythmia during cold seasons. Conclusion: PM2.5 exposure was positively associated with daily hospital admissions for CSD, which might provide informative insight on adverse effects of PM2.5.