Comparative genomic analysis and multilocus sequence typing of Staphylococcus aureus reveals candidate genes for low-temperature tolerance

Staphylococcus aureus is one of the most frequently detected foodborne pathogens in cold chain foods. Worryingly, small colony variants (SCVs) can survive in cold environments for a long time and can revert to rapidly growing cells in suitable environments, causing serious food safety issues. This study investigated the underlying mechanism of SCV formation at low temperature (4 °C) via comparative genomics. Multilocus sequence typing (MLST) of 105 strains of S. aureus was divided into 9 sequence types. The ST352 strains exhibited the greatest tolerance to low temperature, with a mean reduction in survival rate of 10.34 % (p < 0.05). Comparative genomics revealed a total of 1941 core genes in the three S. aureus strains, and BB-1 had 468 specific genes, which were enriched mainly in translation, DNA recombination, DNA repair, metabolic pathways, two-component systems, and quorum sensing. Molecular docking analysis revealed that the binding of the RsbW protein to the SigB protein of BB-1 decreased due to base mutations in rsbW, while the binding to the RsbV protein was enhanced. In addition, the results of real-time quantitative PCR showed that the RsbV-RsbW/SigB system of BB-1 may play a role in the low-temperature survival of S. aureus and the formation of SCVs. These results suggest that genes specific to BB-1 may contribute to the mechanism of adaptation to low temperature and the formation of SCVs. This study helps elucidate the causes of SCV formation by S. aureus at low temperature at the molecular level and provides a basis for exploring the safety control of cold chain food environments.

Effect of carbon and nitrogen mineralization of chitosan and its composites with hematite/gibbsite on soil acidification of an Ultisol induced by urea

Chitosan is a biodegradable polymer with a vast range of applications. Along with its metal composites, chitosan has been applied in the remediation of polluted soils as well as a biofertilizer. However, little attention has been given to the degradation of chitosan composites in soil and how they affect soil respiration rate and other physicochemical parameters. In this study, the degradation of chitosan and its composites with gibbsite and hematite in an acidic Ultisol and the effect on urea (200 mg N kg-1) transformation were investigated in a 70-d incubation experiment. The results showed that the change trends of soil pH, N forms, and CO2 emissions were similar for chitosan and its composites when applied at rates <5 g C kg-1. At a rate of 5 g C kg-1, the C and N mineralization trends suggested that the chitosan-gibbsite composite was more stable in soil and this stability was owed to the formation of a new chemical bond (CH-N-Al-Gibb) as observed in the Fourier-transform infrared spectrum at 1644 cm-1. The mineralization of the added materials significantly increased soil pH and decreased soil exchangeable acidity (P < 0.01). This played an important role in decreasing the amount of H+ produced during urea transformation in the soil. The soil's initial pH was an important factor influencing C and N mineralization trends. For instance, increasing the initial soil pH significantly increased the nitrification rate and chitosan decomposition trend (P < 0.01) and thus, the contribution of chitosan and its composites to increase soil pH and inhibit soil acidification during urea transformation was significantly decreased (P < 0.01). These findings suggest that to achieve long-term effects of chitosan in soils, applying it as a chitosan-gibbsite complex is a better option.

Patterns of Spatial Variation in Rumen Microbiology, Histomorphology, and Fermentation Parameters in Tarim wapiti (Cervus elaphus yarkandensis)

The rumen is divided into multiple rumen sacs based on anatomical structure, and each has its unique physiological environment. Tarim wapiti preserved roughage tolerance after domestication, and adaptation to the desertified environment led to the development of a unique rumen shape and intraruminal environment. In this work, six Tarim wapiti were chosen and tested for fermentation parameters, microbes, and histomorphology in four rumen areas (Dorsal sac, DS; Ventral sac, VS; Caudodorsal blind sac, CDBS; Caudoventral blind sac, CVBS). Tarim wapiti's rumen blind sac had better developed rumen histomorphology, the ventral sac was richer in VFAs, and the dominant bacteria varied most notably in the phylum Firmicutes, which was enriched in the caudoventral blind sac. The ventral sac biomarkers focused on carbohydrate fermentation-associated bacteria, the dorsal sac focused on N recycling, and the caudoventral blind sac identified the only phylum-level bacterium, Firmicutes; we were surprised to find a probiotic bacterium, Bacillus clausii, identified as a biomarker in the ventral sac. This research provides a better understanding of rumen fermentation parameters, microorganisms, and histomorphology in the Tarim wapiti rumen within a unique ecological habitat, laying the groundwork for future regulation targeting the rumen microbiota and subsequent animal production improvement.

Age-Dependent Developmental Changes of Selenium Content and Selenoprotein Expression and Content in Longissimus Dorsi Muscle and Liver of Duroc Pigs

The trace element selenium (Se) plays a key role in development and various physiological processes, mainly through its transformation into selenoproteins. To investigate the developmental patterns of Se content and expression of selenoproteins, the liver and longissimus dorsi (LD) muscle of Duroc pigs were collected at 1, 21, 80, and 185 days of age (7 pigs each age) for the determination of Se content, mRNA expression of selenoproteins, and concentrations of glutathione peroxidase (GPX), thioredoxin reductase (TrxR or TXNRD), and selenoprotein P (SELP). The results showed that age significantly affected the expression of GPX1, GPX2, GPX3, TXNRD1, TXNRD2, TXNRD3, iodothyronine deiodinases 2 (DIO2), DIO3, SELF, SELH, SELM, SELP, SELS, SELW, and selenophosphate synthetase2 (SPS2) in the liver, as well as GPX3, GPX4, TXNRD1, TXNRD2, DIO2, DIO3, SELF, SELN, SELP, SELR, SELS, and SELW in the LD muscle of Duroc pigs. The concentrations of GPX, TrxR, and SELP showed an increasing trend with age, and they were positively correlated with Se content at 1, 21, and 185 days of age and negatively correlated at 80 days of age, both in the liver and LD muscle. The Se content decreased at the age of 80 days, especially in the LD muscle. In summary, our study revealed developmental changes in Se content and expression of selenoproteins in the liver and LD muscle of Duroc pigs at different growth stages, which provided a theoretical basis for further study of Se nutrition and functions of selenoproteins.

Barriers to blockchain adoption in the seaport industry: A fuzzy DEMATEL analysis

Blockchain technology, marked as a disruptive force across various sectors, including seaport logistics, faces challenges and obstacles that impede its effective adoption. We aim to empirically identify the significant barriers impeding blockchain adoption in the seaport industry and elucidate the interconnected relationships between these impediments. Utilizing the Fuzzy Decision-Making Trial and Evaluation Laboratory Analysis (Fuzzy DEMATEL) technique, we quantify the cause-and-effect relationships between various barriers to blockchain adoption. Structured interviews involving 18 experts were conducted, collecting both qualitative interview data and quantitative data. The nature of ports and the maritime industry did not seem to be accurately reflected in the literature about blockchain adoption, presenting several new findings in this study. Four primary obstacles were identified: 1) Lack of management support and commitment. 2) Issues in supply chain collaboration, communication and coordination. 3) Resistance from and lack of involvement of external stakeholders. 4) The high cost. Furthermore, cost was reaffirmed as a significant factor influencing blockchain adoption. We enhance existing literature by revealing the interdependencies among identified barriers and offers insights for policymakers and industry practitioners. We aim to foster successful blockchain integration in the seaport industry, improving its sustainability performance. During this research, it has been acknowledged by the business sector that the effective employment of business process re-engineering (BPR) and the strategic implementation of blockchain technology are crucial strategies to surmount the obstacles that have impeded the extensive integration of blockchain within port operations.

Socioeconomic, meteorological factors and spatiotemporal distribution of human brucellosis in China between 2004 and 2019-A study based on spatial panel model

BACKGROUND

Human brucellosis continues to be a great threat to human health in China. The present study aimed to investigate the spatiotemporal distribution of human brucellosis in China from 2004 to 2019, to analyze the socioeconomic factors, meteorological factors and seasonal effect affecting human brucellosis incidence in different geographical regions with the help of spatial panel model, and to provide a scientific basis for local health authorities to improve the prevention of human brucellosis.

METHODS

The monthly reported number and incidence of human brucellosis in China from January 2004 to December 2019 were obtained from the Data Center for China Public Health Science. Monthly average air temperature and monthly average relative humidity of 31 provincial-level administrative units (22 provinces, 5 autonomous regions and 4 municipalities directly under the central government) in China from October 2003 to December 2019 were obtained from the National Meteorological Science Data Centre. The inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield and gross pastoral product of 31 provincial-level administrative units in China from 2004 to 2019 were obtained from the National Bureau of Statistics of China. The temporal and geographical distribution of human brucellosis was displayed with Microsoft Excel and ArcMap software. The spatial autocorrelation and hotspot analysis was used to describe the association among different areas. Spatial panel model was constructed to explore the combined effects on the incidence of human brucellosis in China.

RESULTS

A total of 569,016 cases of human brucellosis were reported in the 31 provincial-level administrative units in China from January 2004 to December 2019. Human brucellosis cases were concentrated between March and July, with a peak in May, showing a clear seasonal increase. The incidence of human brucellosis in China from 2004 to 2019 showed significant spatial correlations, and hotspot analysis indicated that the high incidence of human brucellosis was mainly in the northern China, particularly in Inner Mongolia, Shanxi, and Heilongjiang. The results from spatial panel model suggested that the inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature (the same month, 2-month lagged and 3-month lagged), average relative humidity (the same month) and season variability were significantly associated with human brucellosis incidence in China.

CONCLUSIONS

The epidemic area of human brucellosis in China has been expanding and the spatial clustering has been observed. Inner Mongolia and adjacent provinces or autonomous regions are the high-risk areas of human brucellosis. The inventory of cattle and sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature, average relative humidity and season variability played a significant role in the progression of human brucellosis. The present study strengthens the understanding of the relationship between socioeconomic, meteorological factors and the spatial heterogeneity of human brucellosis in China, through which 'One Health'-based strategies and countermeasures can be provided for the government to tackle the brucellosis menace.

Cyclovirobuxine D pretreatment ameliorates septic heart injury through mitigation of ferroptosis

Myocardial dysfunction is a frequent complication in patients with severe sepsis. However, effective drugs for the prevention of myocardial dysfunction and the molecular mechanisms of the disease remain elusive. The present study demonstrated that Cyclovirobuxine D (CVB-D) could improve cardiac dysfunction in a cecal ligation and puncture (CLP) model in rodents and in a lipopolysaccharide (LPS) model in vitro. Echocardiography and histopathological examination were used to detect changes in cardiac structure and function. Kits were used to detect indicators of cardiac injury, transmission electron microscopy to detect structural changes in mitochondria and reverse transcription-quantitative PCR to detect prostaglandin-endoperoxide synthase 2 and hamp expression levels. L-Glutathione and malondialdehyde levels and superoxide dismutase activity were measured using kits. Cell viability was measured with the Cell Counting Kit-8. Iron metabolism-related proteins, inflammatory factor levels and related pathway proteins were detected using western blot analysis. Changes in L-type calcium currents were detected by membrane clamp, and contractility of cardiomyocytes was measured by Ion Optix. CVB-D attenuated CLP-induced cardiac malfunction in septic rats, with changes observed in myocardial pathological structure, creatine kinase isoenzyme (CK-MB), lactate dehydrogenase (LDH) and cardiac troponin I (cTnI). CVB-D attenuated sepsis-induced lipid peroxidation and iron overload. In addition, CVB-D decreased the expression of CK-MB, LDH and cTnI, suppressed oxidative stress index levels and reduced the production of reactive oxygen species. CVB-D decreased LPS-induced cytoplasmic iron overload by increasing upregulation of iron uptake molecules. Conversely, CVB-D significantly increased the upregulation of ferroportin 1. CVB-D pretreatment significantly reduced the levels of hamp mRNA compared with the LPS-treated group. CVB-D pretreatment significantly reduced inflammatory factor levels and the ratio of phosphorylated vs. total signal transducer and activator of transcription 3. The expression of SLC7A11 and GPX4 was upregulated in septic cells pretreated with CVB-D, however treatment with ML385 largely decreased this upregulation. Of note, CVB-D inhibited the inward flow of calcium ions through the LTCC. In conclusion, these findings suggest that CVB-D alleviated sepsis-induced cardiac iron toxicity by alleviating iron metabolism.

Mapping Research Trends of Medications for Multidrug-Resistant Pulmonary Tuberculosis Based on the Co-Occurrence of Specific Semantic Types in the MeSH Tree: A Bibliometric and Visualization-Based Analysis of PubMed Literature (1966-2020)

Background

Before the COVID-19 pandemic, tuberculosis is the leading cause of death from a single infectious agent worldwide for the past 30 years. Progress in the control of tuberculosis has been undermined by the emergence of multidrug-resistant tuberculosis. The aim of the study is to reveal the trends of research on medications for multidrug-resistant pulmonary tuberculosis (MDR-PTB) through a novel method of bibliometrics that co-occurs specific semantic Medical Subject Headings (MeSH).

Methods

PubMed was used to identify the original publications related to medications for MDR-PTB. An R package for text mining of PubMed, pubMR, was adopted to extract data and construct the co-occurrence matrix-specific semantic types. Biclustering analysis of high-frequency MeSH term co-occurrence matrix was performed by gCLUTO. Scientific knowledge maps were constructed by VOSviewer to create overlay visualization and density visualization. Burst detection was performed by CiteSpace to identify the future research hotspots.

Results

Two hundred and eight substances (chemical, drug, protein) and 147 diseases related to MDR-PTB were extracted to form a specific semantic co-occurrence matrix. MeSH terms with frequency greater than or equal to six were selected to construct high-frequency co-occurrence matrix (42 × 20) of specific semantic types contains 42 substances and 20 diseases. Biclustering analysis divided the medications for MDR-PTB into five clusters and reflected the characteristics of drug composition. The overlay map indicated the average age gradients of 42 high-frequency drugs. Fifteen top keywords and 37 top terms with the strongest citation bursts were detected.

Conclusion

This study evaluated the literatures related to MDR-PTB drug therapy, providing a co-occurrence matrix model based on the specific semantic types and a new attempt for text knowledge mining. Compared with the macro knowledge structure or hot spot analysis, this method may have a wider scope of application and a more in-depth degree of analysis.

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Serine Administration Improves Selenium Status, Oxidative Stress, and Mitochondrial Function in Longissimus Dorsi Muscle of Piglets with Intrauterine Growth Retardation

Intrauterine growth retardation (IUGR) causes oxidative stress in the skeletal muscle. Serine and selenoproteins are involved in anti-oxidative processes; however, whether IUGR affects selenium status and whether serine has beneficial effects remain elusive. Here, we investigated the effects of serine administration on selenium nutritional status and oxidative stress in the longissimus dorsi muscle of piglets with IUGR. Six newborn Min piglets having normal birth weight were administered saline, and 12 IUGR piglets were either administered saline or 0.8% serine. The results showed a lower selenium content in skeletal muscle in IUGR piglets, which was restored after serine administration. IUGR piglets showed a disturbed expression of genes encoding selenoproteins, with decreased expression of GPX2, GPX4, TXNRD1, and TXNRD3 and increased expression of DIO1, DIO2, SELF, SELM, SELP, and SELW. Notably, serine administration restored the expression levels of these genes. In accordance with the changes in gene expression, the activity of GPX, TXNRD, and DIO and the content of GSH and SELP were also altered, whereas serine administration restored their contents and activities. Moreover, we observed severe oxidative stress in the skeletal muscle of IUGR piglets, as indicated by decreased GSH content and increased MDA and PC content, whereas serine administration alleviated these changes. In conclusion, our results indicate that IUGR piglets showed a disturbed expression of genes encoding selenoproteins, accompanied by severe oxidative stress. Serine administration can improve selenium status, oxidative stress, and mitochondrial function in the longissimus dorsi muscle of piglets with IUGR. These results suggest that serine could potentially be used in the treatment of IUGR in piglets.

Porphyromonas gingivalis regulates atherosclerosis through an immune pathway

Atherosclerosis (AS) is a chronic inflammatory disease, involving a pathological process of endothelial dysfunction, lipid deposition, plaque rupture, and arterial occlusion, and is one of the leading causes of death in the world population. The progression of AS is closely associated with several inflammatory diseases, among which periodontitis has been shown to increase the risk of AS. Porphyromonas gingivalis (P. gingivalis), presenting in large numbers in subgingival plaque biofilms, is the “dominant flora” in periodontitis, and its multiple virulence factors are important in stimulating host immunity. Therefore, it is significant to elucidate the potential mechanism and association between P. gingivalis and AS to prevent and treat AS. By summarizing the existing studies, we found that P. gingivalis promotes the progression of AS through multiple immune pathways. P. gingivalis can escape host immune clearance and, in various forms, circulate with blood and lymph and colonize arterial vessel walls, directly inducing local inflammation in blood vessels. It also induces the production of systemic inflammatory mediators and autoimmune antibodies, disrupts the serum lipid profile, and thus promotes the progression of AS. In this paper, we summarize the recent evidence (including clinical studies and animal studies) on the correlation between P. gingivalis and AS, and describe the specific immune mechanisms by which P. gingivalis promotes AS progression from three aspects (immune escape, blood circulation, and lymphatic circulation), providing new insights into the prevention and treatment of AS by suppressing periodontal pathogenic bacteria.

Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model

Hand, foot, and mouth disease (HFMD) is an important public health problem and has received concern worldwide. Moreover, the coronavirus disease 2019 (COVID-19) epidemic also increases the difficulty of understanding and predicting the prevalence of HFMD. The purpose is to prove the usability and applicability of the automatic machine learning (Auto-ML) algorithm in predicting the epidemic trend of HFMD and to explore the influence of COVID-19 on the spread of HFMD. The AutoML algorithm and the autoregressive integrated moving average (ARIMA) model were applied to construct and validate models, based on the monthly incidence numbers of HFMD and meteorological factors from May 2008 to December 2019 in Henan province, China. A total of four models were established, among which the Auto-ML model with meteorological factors had minimum RMSE and MAE in both the model constructing phase and forecasting phase (training set: RMSE = 1424.40 and MAE = 812.55; test set: RMSE = 2107.83, MAE = 1494.41), so this model has the best performance. The optimal model was used to further predict the incidence numbers of HFMD in 2020 and then compared with the reported cases. And, for analysis, 2020 was divided into two periods. The predicted incidence numbers followed the same trend as the reported cases of HFMD before the COVID-19 outbreak; while after the COVID-19 outbreak, the reported cases have been greatly reduced than expected, with an average of only about 103 cases per month, and the incidence peak has also been delayed, which has led to significant changes in the seasonality of HFMD. Overall, the AutoML algorithm is an applicable and ideal method to predict the epidemic trend of the HFMD. Furthermore, it was found that the countermeasures of COVID-19 have a certain influence on suppressing the spread of HFMD during the period of COVID-19. The findings are helpful to health administrative departments.

A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA

This prevalence of coronavirus disease 2019 (COVID-19) has become one of the most serious public health crises. Tree-based machine learning methods, with the advantages of high efficiency, and strong interpretability, have been widely used in predicting diseases. A data-driven interpretable ensemble framework based on tree models was designed to forecast daily new cases of COVID-19 in the USA and to determine the important factors related to COVID-19. Based on a hyperparametric optimization technique, we developed three machine learning algorithms based on decision trees, including random forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), and three linear ensemble models were used to integrate these outcomes for better prediction accuracy. Finally, the SHapley Additive explanation (SHAP) value was used to obtain the feature importance ranking. Our outcomes demonstrated that, among the three basic machine learners, the prediction accuracy was the following in descending order: LightGBM, XGBoost, and RF. The optimized LAD ensemble was the most precise prediction model that reduced the prediction error of the best base learner (LightGBM) by approximately 3.111%, while vaccination, wearing masks, less mobility, and government interventions had positive effects on the control and prevention of COVID-19.

Transcriptome analysis reveals the molecular mechanism of cinnamaldehyde against Bacillus cereus spores in ready-to-eat beef

The purpose of this study was to investigate the antibacterial effect and mechanism of cinnamaldehyde on Bacillus cereus spores in ready-to-eat beef. The colour difference and texture of the ready-to-eat beef supplemented with cinnamaldehyde did not differ greatly from the colour and texture of the blank beef. However, cinnamaldehyde has an effective antibacterial effect on the total number of bacterial colonies and B. cereus spores in ready-to-eat beef. Transmission electron microscopy (TEM) analysis revealed that the cell membrane of B. cereus was disrupted by cinnamaldehyde, leading to leakage of intracellular components. Transcriptome sequencing (RNA-seq) indicated that the B. cereus spore resistance regulation system (sigB, sigW, rsbW, rsbV, yfkM and yflT) and phosphoenolpyruvate phosphotransferase system (PTS) (ptsH, ptsI and ptsG) respond positively to cinnamaldehyde in an adverse environment. Intracellular disorders due to damage to the cell membrane involve some transporters (copA, opuBA and opuD) and some oxidative stress systems (ywrO, scdA and katE) in the regulation of the body. However, downregulation of K⁺ transport channels (kdpD and kdpB), osmotic pressure regulation (opuE) and some oxidative stress (norR and srrA)-related genes may accelerate spore apoptosis. In addition, cinnamaldehyde also effectively inhibits the spore germination-related genes (smc, mreB and gerE). This study provides new insights into the molecular mechanism of the antibacterial effect of cinnamaldehyde on B. cereus spores in ready-to-eat beef.

Rational design of 2D/2D ZnIn2S4/C3N4 Heterojunction Photocatalysts for Enhanced Photocatalytic H2 production

Development of close contact two-dimensional (2D) heterojunction photocatalysts for hydrogen evolution performance possesses great significance. In this work, we reported the design and photocatalytic activity of the 2D ZnIn2S4 nanosheets...

Mendelian randomization analyses in ocular disease: a powerful approach to causal inference with human genetic data

Ophthalmic epidemiology is concerned with the prevalence, distribution and other factors relating to human eye disease. While observational studies cannot avoid confounding factors from interventions, human eye composition and structure are unique, thus, eye disease pathogenesis, which greatly impairs quality of life and visual health, remains to be fully explored. Notwithstanding, inheritance has had a vital role in ophthalmic disease. Mendelian randomization (MR) is an emerging method that uses genetic variations as instrumental variables (IVs) to avoid confounders and reverse causality issues; it reveals causal relationships between exposure and a range of eyes disorders. Thus far, many MR studies have identified potentially causal associations between lifestyles or biological exposures and eye diseases, thus providing opportunities for further mechanistic research, and interventional development. However, MR results/data must be interpreted based on comprehensive evidence, whereas MR applications in ophthalmic epidemiology have some limitations worth exploring. Here, we review key principles, assumptions and MR methods, summarise contemporary evidence from MR studies on eye disease and provide new ideas uncovering aetiology in ophthalmology.

Epidemiology, health policy and public health implications of visual impairment and age-related eye diseases in mainland China

The prevalence of visual impairment (VI) and age-related eye diseases has increased dramatically with the growing aging population in mainland China. However, there is limited comprehensive evidence on the progress of ophthalmic epidemiological research in mainland China to enhance our awareness of the prevention of eye diseases to inform public health policy. Here, we conducted a literature review of the population-based epidemiology of VI and age-related eye diseases in mainland China from the 1st of January 1946 to the 20th of October 2021. No language restrictions were applied. There was significant demographic and geographic variation in the epidemic of VI and age-related eye diseases. There are several factors known to be correlated to VI and age-related eye diseases, including age, gender, family history, lifestyle, biological factors, and environmental exposures; however, evidence relating to genetic predisposition remains unclear. In addition, posterior segment eye diseases, including age-related macular degeneration and diabetic retinopathy, are amongst the major causes of irreversible visual impairments in the senile Chinese population. There remains a significant prevention gap, with only a few individuals showing awareness and achieving optimal medical care with regards to age-related eye diseases. Multiple challenges and obstacles need to be overcome, including the accelerated aging of the Chinese population, the lack of structured care delivery in many underdeveloped regions, and unequal access to care. Despite the progress to date, there are few well-conducted multi-center population-based studies following a single protocol in mainland China, which findings can hopefully provide valuable cues for governmental decision-making and assist in addressing and halting the incidence of VI and age-related eye diseases in China.

The correlation between temperature and the incidence of COVID-19 in four first-tier cities of China: a time series study

The COVID-19 outbreak emerged in Wuhan, China, and was declared a global pandemic in March 2020. This study aimed to explore the association of daily mean temperature with the daily counts of COVID-19 cases in Beijing, Shanghai, Guangzhou, and Shenzhen, China. Data on daily confirmed cases of COVID-19 and daily mean temperatures were retrieved from the 4 first-tier cities in China. Distributed lag nonlinear models (DLNMs) were used to assess the association between daily mean temperature and the daily cases of COVID-19 during the study period. After controlling for the imported risk index and long-term trends, the distributed lag nonlinear model showed that there were nonlinear and lag relationships. The daily cumulative relative risk decreased for every 1.0 °C change in temperature in Shanghai, Guangzhou, and Shenzhen. However, the cumulative relative risk increased with a daily mean temperature below - 3 °C in Beijing and then decreased. Moreover, the delayed effects of lower temperatures mostly occurred within 6-7 days of exposure. There was a negative correlation between the cumulative relative risk of COVID-19 incidence and temperature, especially when the temperature was higher than - 3 °C. The conclusions from this paper will help government and health regulators in these cities take prevention and protection measures to address the COVID-19 crisis and the possible collapse of the health system in the future.

[Comparison of QuantiFERON-TB Gold Plus and QuantiFERON-TB Gold In Tube in the diagnosis of pulmonary tuberculosis]

Objective: To compare the screening value of QuantiFERON-TB Gold Plus (QFT-Plus) and QuantiFERON®-TB Gold in tube (QFT-GIT) in the auxiliary diagnosis of pulmonary tuberculosis (TB). Methods: A screening test was performed. Patients who were hospitalized in Guangzhou Chest Hospital and underwent QFT-GIT testing from October to December 2020 were prospectively included as research subjects, QFT-Plus testing was added. And the basic information, clinical manifestations, laboratory test results, imaging examinations and other data of these patients were collected. A total of 207 patients were included and divided into tuberculosis group and non-tuberculosis group according to these data. There were 124 cases in the tuberculosis group (94 confirmed patients and 30 clinically diagnosed patients), including 90 males and 34 females, aged 18-93 years, with a median age of 57 (38, 67) years. The non-tuberculosis group included 83 patients (16 patients with non-tuberculous Mycobacteria and 67 patients with other lung diseases), including 49 males and 34 females, with a median age of 60 (51, 68) years. The confirmed patients were subdivided into three grades of low, medium and high Mycobacteriam tuberculosis (MTB) bacterial load, and three grades of mild, moderate and severe pulmonary tuberculosis. The results of QFT-Plus and QFT-GIT were compared, and the levels of IFN-γ in different antigen tubes were compared. Differences between different groups were compared using Mann-Whitney U test and Kruskal-Wallis H test. Results: The QFT-Plus showed a high degree of agreement with the QFT-GIT (κ=0.786, 95%CI: 0.740-0.832), while the main discordant result was QFT-GIT negative/QFT-Plus positive, accounting for 15/17. The sensitivity of QFT-GIT was 80.7%(95%CI: 0.706-0.880), the specificity was 76.3%(95%CI: 0.649-0.850), the positive predictive value was 79.8%(95%CI: 0.697-0.873), and the negative predictive value was 77.3%(95%CI: 0.659-0.859), repectively. QFT-Plus showed a sensitivity of 84.3%(95%CI: 0.743-0.910), a specificity of 78.8% (95%CI: 0.679-0.868), and a positive predictive value of 80.5%(95%CI: 0.703-0.879), the negative predictive value being 82.9%(95%CI: 0.721-0.902), slightly improved to that of the QFT-GIT. Also, this study found that there were significant differences in IFN-γ values between different MTB load or disease severity (P<0.05). Conclusions: There is a good consistency between the QFT-Plus test and the QFT-GIT test, both of which show good application value in the auxiliary diagnosis of pulmonary tuberculosis. Moreover, because of the addition of tuberculosis-specific CD8 cell antigen, the QFT-Plus test has higher sensitivity, lower uncertainty and more application value. This study also found that the bacterial load and disease severity of patients with pulmonary tuberculosis may have a certain correlation with the measured value of IFN-γ.

SKA3 is a prognostic biomarker and associated with immune infiltration in bladder cancer

BACKGROUND

Spindle and kinetochore‑associated complex subunit 3 (SKA3) has recently been considered a key regulator of carcinogenesis. However, the connection between SKA3 and immune cell infiltration remains unknown.

METHODS

The current study investigated the expression mode, prognostic effect, and functional role of SKA3 in different tumors, particularly bladder cancer using numerous databases, comprising TIMER, GEPIA, HPA, UALCAN, PrognoScan, and Kaplan-Meier Plotter. Differentially expressed gene and enrichment analyses were implemented on SKA3 using R packages "edgR" and "clusterProfiler". Immunohistochemistry was further used to validate the expression of SKA3 gene in bladder cancer. Following that, the relevance of SKA3 expression to immune infiltration level in bladder cancer was evaluated using TIMER.

RESULTS

Overall, the level of SKA3 expression in tumor tissue significantly increased than in normal tissue. In bladder cancer and other tumors, patients with high SKA3 expression levels had worse overall survival (OS) (p = 0.016), disease-specific survival (DSS) (p = 0.00004), and disease-free survival (DFS) (p = 0.032). Additionally, the major molecular functions for SKA3 included nuclear division, mitotic nuclear division, mitotic sister chromatid segregation, humoral immune response, and cell chemotaxis. Additionally, SKA3 expression was found to be positively associated with enhanced M2 macrophage and T helper (Th) 2 cell infiltration in bladder cancer.

CONCLUSIONS

Our study implies that SKA3 contributes to M2 macrophage and Th2 cell polarization by acting as an oncogene in bladder cancer. SKA3 might be a novel biomarker for evaluating prognosis and immune infiltration in bladder cancer.

Therapeutic Potential of Astragaloside IV Against Adriamycin-Induced Renal Damage in Rats via Ferroptosis

Adriamycin (ADR) has been utilized to treat cancer for several decades. However, ADR-induced renal injury is one of the most common side effects accompanying ADR therapy. In the present study, we revealed that astragaloside IV (ASIV) was beneficial for renal injury caused by Adriamycin. We demonstrated that ASIV significantly ameliorated kidney injury, improved renal dysfunction, reduced oxidative stress, alleviated iron accumulation, and inhibited the induction of ferroptosis by ADR. ASIV also rescued the intracellular levels of nuclear factor-erythroid-2-related factor 2 (Nrf2) and promoted nuclear translocation of Nrf2. These protective effects of ASIV on renal injury might be attained through the ASIV-induced activation of the Pi3K/Akt signaling pathway. In vitro, the treatment of the HK-2 cells with fer-1 or deferoxamine mesylate obviously improved cell viability during Adriamycin administration. On the other hand, the protective role of ASIV can be abrogated by RSL3 to some extent. Moreover, ASIV lowered the expression of transferrin receptor 1 and divalent metal transporter 1 while enhancing the expression of ferropotin 1 and glutathione peroxidase 4 in ADR administrated cells, the effects of which were akin to those of deferoxamine mesylate. Furthermore, ASIV increased the phosphorylation of Pi3K, Akt, and the expression of Nrf2 and glutathione peroxidase 4 compared to HK-2 cells stimulated by ADR. However, Pi3K inhibitor LY294002 abrogated these activations. In conclusion, ferroptosis may involve in ADR-induced nephrotoxicity, and ASIV might protect nephrocytes against ADR-induced ferroptosis, perhaps via activations of the Pi3K/Akt and Nrf2 signaling pathways.

Poloxamer-linked prodrug of a topoisomerase I inhibitor SN22 shows efficacy in models of high-risk neuroblastoma with primary and acquired chemoresistance

High‐risk solid tumors continue to pose a tremendous therapeutic challenge due to multidrug resistance. Biological mechanisms driving chemoresistance in high‐risk primary and recurrent disease are distinct: in newly diagnosed patients, non‐response to therapy is often associated with a higher level of tumor “stemness” paralleled by overexpression of the ABCG2 drug efflux pump, whereas in tumors relapsing after non‐curative therapy, poor drug sensitivity is most commonly linked to the dysfunction of the tumor suppressor protein, p53. In this study, we used preclinical models of aggressive neuroblastoma featuring these characteristic mechanisms of primary and acquired drug resistance to experimentally evaluate a macromolecular prodrug of a structurally enhanced camptothecin analog, SN22, resisting ABCG2‐mediated export, and glucuronidation. Together with extended tumor exposure to therapeutically effective drug levels via reversible conjugation to Pluronic F‐108 (PF108), these features translated into rapid tumor regression and long‐term survival in models of both ABCG2‐overexpressing and p53‐mutant high‐risk neuroblastomas, in contrast to a marginal effect of the clinically used camptothecin derivative, irinotecan. Our results demonstrate that pharmacophore enhancement, increased tumor uptake, and optimally stable carrier‐drug association integrated into the design of the hydrolytically activatable PF108‐[SN22]₂ have the potential to effectively combat multiple mechanisms governing chemoresistance in newly diagnosed (chemo‐naïve) and recurrent forms of aggressive malignancies. As a macromolecular carrier‐based delivery system exhibiting remarkable efficacy against two particularly challenging forms of high‐risk neuroblastoma, PF108‐[SN22]₂ can pave the way to a robust and clinically viable therapeutic strategy urgently needed for patients with multidrug‐resistant disease presently lacking effective treatment options.

Nanocarrier-Based Delivery of SN22 as a Tocopheryl Oxamate Prodrug Achieves Rapid Tumor Regression and Extends Survival in High-Risk Neuroblastoma Models

Despite the use of intensive multimodality therapy, the majority of high-risk neuroblastoma (NB) patients do not survive. Without significant improvements in delivery strategies, anticancer agents used as a first-line treatment for high-risk tumors often fail to provide clinically meaningful results in the settings of disseminated, recurrent, or refractory disease. By enhancing pharmacological selectivity, favorably shifting biodistribution, strengthening tumor cell killing potency, and overcoming drug resistance, nanocarrier-mediated delivery of topoisomerase I inhibitors of the camptothecin family has the potential to dramatically improve treatment efficacy and minimize side effects. In this study, a structurally enhanced camptothecin analog, SN22, reversibly coupled with a redox-silent tocol derivative (tocopheryl oxamate) to allow its optimally stable encapsulation and controlled release from PEGylated sub-100 nm nanoparticles (NP), exhibited strong NB cell growth inhibitory activity, translating into rapid regression and durably suppressed regrowth of orthotopic, MYCN-amplified NB tumors. The robust antitumor effects and markedly extended survival achieved in preclinical models recapitulating different phases of high-risk disease (at diagnosis vs. at relapse with an acquired loss of p53 function after intensive multiagent chemotherapy) demonstrate remarkable potential of SN22 delivered in the form of a hydrolytically cleavable superhydrophobic prodrug encapsulated in biodegradable nanocarriers as an experimental strategy for treating refractory solid tumors in high-risk cancer patients.

Spatiotemporal cluster analysis of COVID-19 and its relationship with environmental factors at the city level in mainland China

This study sought to identify the spatial, temporal, and spatiotemporal clusters of COVID-19 cases in 366 cities in mainland China with the highest risks and to explore the possible influencing factors of imported risks and environmental factors on the spatiotemporal aggregation, which would be useful to the design and implementation of critical preventative measures. The retrospective analysis of temporal, spatial, and spatiotemporal clustering of COVID-19 during the period (January 15 to February 25, 2020) was based on Kulldorff's time-space scanning statistics using the discrete Poisson probability model, and then the logistic regression model was used to evaluate the impact of imported risk and environmental factors on spatiotemporal aggregation. We found that the spatial distribution of COVID-19 cases was nonrandom; the Moran's I value ranged from 0.017 to 0.453 (P < 0.001). One most likely cluster and three secondary likely clusters were discovered in spatial cluster analysis. The period from February 2 to February 9, 2020, was identified as the most likely cluster in the temporal cluster analysis. One most likely cluster and seven secondary likely clusters were discovered in spatiotemporal cluster analysis. Imported risk, humidity, and inhalable particulate matter PM_2.5 had a significant impact on temporal and spatial accumulation, and temperature and PM₁₀ had a low correlation with the spatiotemporal aggregation of COVID-19. The information is useful for health departments to develop a better prevention strategy and potentially increase the effectiveness of public health interventions.

Comparing ameliorative effects of biomass ash and alkaline slag on an acidic Ultisol under artificial Masson pine: A field experiment

Forest soil acidification caused by acid deposition is a serious threat to the forest ecosystem. To investigate the liming effects of biomass ash (BA) and alkaline slag (AS) on the acidic topsoil and subsoil, a three-year field experiment under artificial Masson pine was conducted at Langxi, Anhui province in Southern China. The surface application of BA and AS significantly increased the soil pH, and thus decreased exchangeable acidity and active Al in the topsoil. Soil exchangeable Ca²⁺ and Mg²⁺ in topsoil were significantly increased by the surface application of BA and AS, while an increase in soil exchangeable K⁺ was only observed in BA treatments. The soil acidity and active Al in subsoil were decreased by the surface application of AS. Compared with the control, soluble monomeric and exchangeable Al in the subsoil was decreased by 38.0% and 29.4% after 3 years of AS surface application. There was a minimal effect on soluble monomeric and exchangeable Al after the application of BA. The soil exchangeable Ca²⁺ and Mg²⁺ in the subsoil increased respectively by 54% and 141% after surface application of 10 t ha^-1 AS. The decrease of soil active Al and increase of base cations in subsoil were mainly attributed to the high migration capacity of base cations in AS. In conclusion, the effect of surface application of AS was superior to BA in ameliorating soil acidity and alleviating soil Al toxicity in the subsoil of this Ultisol.

Analysis of canopy phenology in man-made forests using near-earth remote sensing

BACKGROUND

Forest canopies are highly sensitive to their growth, health, and climate change. The study aims to obtain time sequence images in mix foresters using a near-earth remote sensing method to track the seasonal variation in the color index and select the optimal color index. Three different regions of interest (RIOs) were defined and six color indexes (GRVI, HUE, GGR, RCC, GCC, and GEI) were calculated to analyze the microenvironment difference. The key phenological phase was identified using the double logistic model and the derivative method, and the phenology forecast of color indexes was performed based on the long short-term memory (LSTM) model.

RESULTS

The results showed that the same color index in different RIOs and different color indexes in the same RIO present a slight difference in the days of growth and the days corresponding to the peak value, exhibiting different phenological phases; the mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of the LSTM model was 0.0016, 0.0405, 0.0334, and 12.55%, respectively, indicating that this model has a good forecast effect.

CONCLUSIONS

In different areas of the same forest, differences in the micro-ecological environment in the canopies were prevalent, with their internal growth mechanism being affected by different cultivation ways and the external environment. Besides, the optimal color index also varies with species in phenological response, that is, different color indexes are used for different forests. With the data of color indexes as the training set and forecast set, the feasibility of the LSTM model in phenology forecast is verified.

Controlling Photoluminescence and Photocatalysis Activities in Lead-Free Cs2 Ptx Sn1-x Cl6 Perovskites via Ion Substitution

Lead-free halide perovskites have triggered interest in the field of optoelectronics and photocatalysis because of their low toxicity, and tunable optical and charge-carrier properties. From an application point of view, it is desirable to develop stable multifunctional lead-free halide perovskites. We have developed a series of Cs₂ Pt_x Sn_1-x Cl₆ perovskites (0≤x≤1) with high stability, which show switchable photoluminescence and photocatalytic functions by varying the amount of Pt⁴⁺ substitution. A Cs₂ Pt_x Sn_1-x Cl₆ solid solution with a dominant proportion of Pt⁴⁺ shows broadband photoluminescence with a lifetime on the microsecond timescale. A Cs₂ Pt_x Sn_1-x Cl₆ solid solution with a small amount of Pt⁴⁺ substitution exhibits photocatalytic hydrogen evolution activity. An optical spectroscopy study reveals that the switch between photoluminescence and photocatalysis functions is controlled by sub-band gap states. Our finding provides a new way to develop lead-free multifunctional halide perovskites with high stability.

Feedback mechanisms of periphytic biofilms to ZnO nanoparticles toxicity at different phosphorus levels

The increasing use of nanoparticles (NPs) has raised concerns about their potential environmental risks. Many researches on NPs focused on the toxicity mechanism to microorganisms, but neglect the toxicity effects in relation to nutritional conditions. Here, we evaluated the interactive effects of zinc oxide (ZnO) NPs and phosphorus (P) levels on the bacterial community and functioning of periphytic biofilms. Results showed that long-term exposure to ZnO NPs significantly reduced alkaline phosphatase activity (APA) of periphytic biofilms just in P-limited conditions. Co-occurrence network analysis indicated that ZnO NPs exposure reduced network complexity between bacterial taxa in P-limited conditions, while the opposite trend was observed in P-replete conditions. Correlation analysis and random forest modeling suggested that excessive Zn²⁺ released and high reactive oxygen species (ROS) production might be mainly responsible for the inhibition of APA induced by ZnO NPs under P-limited conditions, while adjustment of bacterial diversity and improvement of keystone taxa cooperation were the main mechanisms in maintaining APA when subjected to weak toxicity of ZnO NPs in P-replete conditions. Taken together, our results provide insights into the biological feedback mechanism involved in ZnO NPs exposure on the ecological function of periphytic biofilms in different P nutritional conditions.

A New Strategy to Quantitatively Identify Hot-Spot Areas in Growth of New HIV Infections for Targeted Interventions

Background: Previous geographic studies of HIV infection have usually used prevalence data, which cannot indicate the hot-spot areas of current transmission. To develop quantitative analytic measures for accurately identifying hot-spot areas in growth of new HIV infection, we investigated the geographic distribution features of recent HIV infection and long-term HIV infection using data from a whole-population physical examination in four key counties in Liangshan prefecture, which are most severely affected by HIV in China. Methods: Through a whole-population physical examination during November 2017- June 2018 in the four key counties, a total of 5,555 HIV cases were diagnosed and 246 cases were classified as recently infected by laboratory HIV recency tests. The geospatial patterns of recent and long-term HIV infected cases were compared using ordinary least squares regression and Geodetector. Further, geospatial-heterogeneity was quantified and indicated using a residual map to visualize hot-spot areas where new infection is increasing. Results: The geographic location of HIV cases showed an uneven distribution along major roads and clustered at road intersections. The geographic mapping showed that several areas were clustered with more recently infected HIV cases than long-term infected cases. The quantitative analyses showed that the geospatial asymmetry between recent and long-term HIV infection was 0.30 and 0.31 in ordinary least squares regression and Geodetector analysis, respectively. The quantitative analyses found twenty-three townships showing an increase in the number of recent infections. Conclusions: Quantitative analysis of geospatial-heterogeneous areas by comparing between recent and long-term HIV infections allows accurate identification of hot-spot areas where new infections are expanding, which can be used as a potent methodological tool to guide targeted interventions and curb the spread of the epidemic.

Astragaloside IV Attenuates the Myocardial Injury Caused by Adriamycin by Inhibiting Autophagy

Astragaloside IV (ASIV) is the main active component of Astragalus, and can ameliorate cardiomyocyte hypertrophy, apoptosis and fibrosis. In this experiment, we studied how ASIV reduces the cardiotoxicity caused by adriamycin and protects the heart. To this end, rats were randomly divided into the control, ADR, ADR + ASIV and ASIV groups (n = 6). Echocardiography was used to observe cardiac function, HE staining was used to observe myocardial injury, TUNEL staining was used to observe myocardial cell apoptosis, and immunofluorescence and Western blotting was used to observe relevant proteins expression. Experiments have shown that adriamycin can damage heart function in rats, and increase the cell apoptosis index, autophagy level and oxidative stress level. Further results showed that ADR can inhibit the PI3K/Akt pathway. ASIV treatment can significantly improve the cardiac function of rats treated with ADR and regulate autophagy, oxidative stress and apoptosis. Our findings indicate that ASIV may reduce the heart damage caused by adriamycin by activating the PI3K/Akt pathway.

3-D Multi-Component Reverse Time Migration Method for Tunnel Seismic Data

Migration imaging is a key step in tunnel seismic data processing. Due to the limitation of tunnel space, tunnel seismic data are small-quantity, multi-component, and have a small offset. Kirchhoff migration based on the ray theory is limited to the migration aperture and has low migration imaging accuracy. Kirchhoff migration can no longer meet the requirements of high-precision migration imaging. The reverse time migration (RTM) method is used to realize cross-correlation imaging by reverse-time recursion principle of the wave equation. The 3-D RTM method cannot only overcome the effect of small offset, but also realize multi-component data imaging, which is the most accurate migration method for tunnel seismic data. In this paper, we will study the 3-D RTM method for multi-component tunnel seismic data. Combined with the modeled data and the measured data, the imaging accuracy of the 3-D Kirchhoff migration and 3-D RTM is analyzed in detail. By comparing single-component and multi-component Kirchhoff migration and RTM profile, the advantages of the multi-component RTM method are summarized. Compared with the Kirchhoff migration method, the 3-D RTM method has the following advantages: (1) it can overcome the effect of small offset and expand the range of migration imaging; (2) multi-component data can be realized to improve the energy of anomalous interface; (3) it can make full use of multiple waves to realize migration imaging and improve the resolution of the anomalous interface. The modeled data and the measured data prove the advantages of the 3-D multi-component RTM method.

Nursing Scheduling Mode and Experience from the Medical Teams in Aiding Hubei Province During the COVID-19 Outbreak: A Systematic Scoping Review of 17 Studies

Introduction

Due to COVID-19 outbreak, since January 24, 2020, national medical teams from across the country and the armed forces have been dispatched to aid Hubei. The present review was designed to timely summarize the existing frontline information about nursing scheduling mode with special focus on the length of shifts with the aim to contribute to improve the nurses' job satisfaction and the quality of nursing services.

Methods

Articles from Jan 2020 to October 2020 were retrieved from China National Knowledge Infrastructure, Wanfang Data and Weipu Information, with the terms "COVID-19", "designated hospital", "Hubei-assisted", "makeshift hospital", "nursing", "nursing shift", "whole-system takeover" and variations of these, in the title and abstract fields and the Boolean combinations of these words as the retrieval strategy.

Results

Seventeen journal articles have been included in the target field, from the nurses in aiding Hubei Province, four kinds of shift length, 2-hour (h), 3-h, 4-h and 6-h shift have been considered, the main nursing scheduling mode adopted in designated hospitals for COVID-19 patients was dynamic scheduling based on workload, flexible scheduling based on working hours, workload and the number of critically ill patients admitted, humanized scheduling based on the daily reported health status of the nurses, and professional-integrated scheduling according to the professional distribution of nurses on the basis of four-hour shift length, and in makeshift hospitals for mild patients, the scheduling mode was 6-h based correspondingly.

Conclusion

The descriptive results of the present systematic review shed light on the challenges and practical solutions of nursing scheduling mode in the context of cross-regional medical assistance. Additionally, the present systematic review could provide the academic community of nurses, nurse managers and administrators with baseline information and scientific productions from the content's points of view in the target field.

Recent progress in agents targeting polo-like kinases: Promising therapeutic strategies

Polo-like kinases (PLKs) play important roles in regulating multiple aspects of cell cycle and cell proliferation. In many cancer types, PLK family members are often dysregulated, which can lead to uncontrolled cell proliferation and aberrant cell division and has been shown to associate with poor prognosis of cancers. The key roles of PLK kinases in cancers lead to an enhanced interest in them as promising targets for anticancer drug development. In consideration of PLK inhibitors and some other anticancer agents, such as BRD4, EEF2K and Aurora inhibitors, exert synergy effects in cancer cells, dual-targeting of PLK and other cancer-related targets is regarded as an rational and potent strategy to enhance the effectiveness of single-targeting therapy for cancer treatment. This review introduces the PLK family members at first and then focuses on the recent advances of single-target PLK inhibitors and summarizes the corresponding SARs of them. Moreover, we discuss the synergisms between PLK and other anti-tumor targets, and sum up the current dual-target agents based on them.

Cloning of PCS gene (TpPCS1) from Tagetes patula L. and expression analysis under cadmium stress

Phytochelatins (PCs) constitute an important mechanism for plants to resist heavy metal stress. Widely found in higher plants, they are small heavy metal binding peptides, synthesized through catalysis of phytochelatin synthase (PCS). We speculate that there may be PCS genes in Peacock grass (Tagetes patula L., Asteraceae), which is an important reason for its rich cadmium. In order to obtain the full-length cDNA sequence of the PCS gene from T. patula L. used rapid amplification of cDNA ends (RACE). Meanwhile, Relative expression of TpPCS1 under different concentrations of cadmium (Cd) stress was analysed using quantitative real-time polymerase chain reaction (qRT-PCR). Results found ORF of TpPCS1 genes with a length of 1970 bp, a gene coding area length of 1764 bp, coding for 587 amino acids. Expression of TpPCS1 under Cd stress was tissue specific. TpPCS1 in the root showed higher expression, while expression in the leaf and seed was relatively low. This research demonstrates that expression of TpPCS1 enhanced the enrichment of cadmium in T. patula L. roots and could be used to construct a plant hyperexpression carrier that would provide new avenues for plant restoration technology.

Sirt1 suppresses MCP-1 production during the intervertebral disc degeneration by inactivating AP-1 subunits c-Fos/c-Jun

OBJECTIVE

The anti-inflammatory effect of Sirtuin 1 (Sirt1) during intervertebral disc degeneration (IDD) has been widely confirmed. Monocyte chemoattractant protein-1 (MCP-1) activation is the initiating inflammatory response associated with the IDD. However, whether Sirt1 suppresses MCP-1 in the intervertebral disc is unclear.

PATIENTS AND METHODS

The MCP-1 and Sirt1 protein expression in the degenerated and non-degenerated NP tissues were compared by immunohistochemistry (IHC). We induced nucleus pulposus (NP) cell degeneration by IL-1β and mediated cellular Sirt1 expression through the Sirt1 activator resveratrol (Res) or inhibitor Nicotinamide (Nico). In addition, the inhibitors of MCP-1 and Activator protein 1 (AP-1) were also used in cell culture. The function of NP cells was determined by the type II collagen and Cell Counting Kit-8 (CCK-8) assay. We assessed the Sirt1 and MCP-1 expression by the Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR). The AP-1 activity was valued by the phosphorylation of its components c-Fos, and c-Jun.

RESULTS

Both in vivo and in vitro experimental results indicated that MCP-1 was upregulated in the degenerated condition, which was opposite to Sirt1 expression. Res suppressed AP-1, the phosphorylation of c-Fos/c-Jun, and the MCP-1 expression. On the contrary, Sirt1 downregulation by Nico aggravated the phosphorylation of c-Fos/c-Jun and MCP-1 expression. However, the MCP-1 suppression did not affect the Sirt1 and AP-1 levels. The destruction of AP-1 activation also inhibited MCP-1 expression but not Sirt1. The upregulation of Sirt1 and suppression of MCP-1 improved the type II collagen expression and cell viability, which was injured by IL-1β.

CONCLUSIONS

Sirt1 suppresses the MCP-1 production in the degenerated NP cells by suppressing the phosphorylation of the AP-1 subunits c-Fos and c-Jun.

Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach

OBJECTIVE

Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain infectious diseases to effectively control their prevalence and outbreak potential. Compared to the use of one base model, model stacking can often produce better forecasting results. In this study, we fitted the monthly reported cases of HFRS in mainland China with a model stacking approach and compared its forecasting performance with those of five base models.

METHOD

We fitted the monthly reported cases of HFRS ranging from January 2004 to June 2019 in mainland China with an autoregressive integrated moving average (ARIMA) model; the Holt-Winter (HW) method, seasonal decomposition of the time series by LOESS (STL); a neural network autoregressive (NNAR) model; and an exponential smoothing state space model with a Box-Cox transformation; ARMA errors; and trend and seasonal components (TBATS), and we combined the forecasting results with the inverse rank approach. The forecasting performance was estimated based on several accuracy criteria for model prediction, including the mean absolute percentage error (MAPE), root-mean-squared error (RMSE) and mean absolute error (MAE).

RESULT

There was a slight downward trend and obvious seasonal periodicity inherent in the time series data for HFRS in mainland China. The model stacking method was selected as the best approach with the best performance in terms of both fitting (RMSE 128.19, MAE 85.63, MAPE 8.18) and prediction (RMSE 151.86, MAE 118.28, MAPE 13.16).

CONCLUSION

The results showed that model stacking by using the optimal mean forecasting weight of the five abovementioned models achieved the best performance in terms of predicting HFRS one year into the future. This study has corroborated the conclusion that model stacking is an easy way to enhance prediction accuracy when modeling HFRS.

Astragaloside IV inhibits adriamycin-induced cardiac ferroptosis by enhancing Nrf2 signaling

Astragaloside IV (AsIV), an active ingredient isolated from traditional Chinese medicine astragalus membranaceus, is beneficial to cardiovascular health. This study aimed to characterize the functional role of AsIV against adriamycin (ADR)-induced cardiomyopathy. Here, healthy rats were treated with ADR and/or AsIV for 35 days. We found that AsIV protected the rats against ADR-induced cardiomyopathy characterized by myocardial fibrosis and cardiac dysfunction. Meanwhile, ADR increased type I and III collagens, TGF-β, NOX2, and NOX4 expression and SMAD2/3 activity in the left ventricles of rats, while those effects were countered by AsIV through suppressing oxidative stress. Moreover, ADR was found to promote cardiac ferroptosis, whereas administration of AsIV attenuated the process via activating Nrf2 signaling pathway and the subsequent GPx4 expression increasing. These results suggest that AsIV might play a protective role against ADR-induced myocardial fibrosis, which may partly attribute to its anti-ferroptotic action by enhancing Nrf2 signaling.

Natural Polyphenols as Targeted Modulators in Colon Cancer: Molecular Mechanisms and Applications

Colon cancer commonly develops from long-term chronic inflammation in the intestine and seriously threatens human health. Natural polyphenols have been valued as a crucial regulator of nutrient metabolism and metabolic diseases, owing to their anti-inflammatory and antioxidant functions and the ability to maintain a balance between gut microbes and their hosts. Notably, experimental and clinical evidence has shown that natural polyphenols could act as a targeted modulator to play a key role in the prevention or treatment of colon cancer. Thus, in this review, we summarized recent advances in the possible regulatory mechanism and the potential application of natural polyphenols in colon cancer, which might be regarded as a novel platform for the colon cancer management.

Sub-multiplicative interaction between polygenic risk score and household coal use in relation to lung adenocarcinoma among never-smoking women in Asia

We previously identified 10 lung adenocarcinoma susceptibility loci in a genome-wide association study (GWAS) conducted in the Female Lung Cancer Consortium in Asia (FLCCA), the largest genomic study of lung cancer among never-smoking women to date. Furthermore, household coal use for cooking and heating has been linked to lung cancer in Asia, especially in Xuanwei, China. We investigated the potential interaction between genetic susceptibility and coal use in FLCCA. We analyzed GWAS-data from Taiwan, Shanghai, and Shenyang (1472 cases; 1497 controls), as well as a separate study conducted in Xuanwei (152 cases; 522 controls) for additional analyses. We summarized genetic susceptibility using a polygenic risk score (PRS), which was the weighted sum of the risk-alleles from the 10 previously identified loci. We estimated associations between a PRS, coal use (ever/never), and lung adenocarcinoma with multivariable logistic regression models, and evaluated potential gene-environment interactions using likelihood ratio tests. There was a strong association between continuous PRS and lung adenocarcinoma among never coal users (Odds Ratio (OR) = 1.69 (95% Confidence Interval (CI) = 1.53, 1.87), p=1 × 10^-26). This effect was attenuated among ever coal users (OR = 1.24 (95% CI: 1.03, 1.50), p = 0.02, p-interaction = 6 × 10^-3). We observed similar attenuation among coal users from Xuanwei. Our study provides evidence that genetic susceptibility to lung adenocarcinoma among never-smoking Asian women is weaker among coal users. These results suggest that lung cancer pathogenesis may differ, at least partially, depending on exposure to coal combustion products. Notably, these novel findings are among the few instances of sub-multiplicative gene-environment interactions in the cancer literature.

Effects of straw decayed products of four crops on the amelioration of soil acidity and maize growth in two acidic Ultisols

Variable charge soils have low agricultural productivity associated with low pH, low cation exchange capacity (CEC), and low pH buffering capacity (pHBC). As a result of rapid acidification rates, these soils are prone to infertility resulting from Al phytotoxicity and deficiency of P, Ca, Mg, and K, and thus require amendments that can ameliorate soil acidity and enhance soil CEC and pHBC. A 30-day pot experiment was carried out using a clay Ultisol and a sandy Ultisol amended with straw decayed products (SDPs) of peanut, pea, canola, and rice. The results showed that applying SDPs increased the soil CEC, organic matter content, and exchangeable base cations in the two Ultisols. The ameliorative effects of the SDPs were superior for the sandy Ultisol than for the clay Ultisol. The addition of SDPs significantly increased soil pH and pHBC of the two Ultisols, and simultaneously decreased soil exchangeable Al³⁺. Among them, the greatest effect was found in the treatment with pea straw decayed products (PeaSD). The soil pHs of clay Ultisol and sandy Ultisol treated with PeaSD were respectively 5.70 and 7.37 and were 1.26 and 2.63 pH units higher than those of control. Also, applying SDPs increased maize seedling biomass in both soils and the most significant effect was found in the treatment with PeaSD, which were 0.97 (clay Ultisol) and 2.5 (sandy Ultisol) times higher than in the respective controls. The results of this study demonstrated that carefully selected straws for SDP production can effectively improve soil chemical properties, enhanced soil pHBC, and thus promote agricultural sustainability.

The Triglyceride-Glucose Index is Associated with Diabetic Retinopathy in Chinese Patients with Type 2 Diabetes: A Hospital-Based, Nested, Case-Control Study

BACKGROUND

This study aimed to investigate the association between the triglyceride-glucose (TyG) index and diabetic retinopathy (DR) in Chinese patients with type 2 diabetes.

METHODS

In this nested case-control study, all diabetic participants were registered hospitalizations during 2012-2018, including 596 with DR as cases and three matching controls per case. DR was assessed using Early Treatment Diabetic Retinopathy Study criteria. The TyG index was calculated: Ln (fasting blood glucose [mg/dL] × fasting triglycerides [mg/dL] ÷ 2). Multivariate logistic regression, a receiver-operating characteristic (ROC) curve, linear regression models, and mediation analysis were used to explore associations.

RESULTS

The TyG index was lower in DR and decreased as its severity advanced among 2,112 subjects (P=0.005). After confounders (sex, duration of diabetes, use of antidiabetic agents, heart rate, systolic blood pressure, pulse pressure, height, weight, body-mass index, and glycated hemoglobin) had been accounted for, there were significant associations between the TyG index and any-severity DR (OR 0.83, 95% CI 0.73-0.95; P=0.006), as well as vision-threatening DR (VTDR; OR 0.53, 95% CI 0.36-0.76; P=0.001). ROC analysis indicated that the TyG index showed significant discriminatory ability in any-severity DR (area under curve [AUC] 0.534, P=0.015) and VTDR (AUC 0.624, P=0.001).

CONCLUSION

The TyG index was associated with the presence and severity of DR. Our findings suggest that the TyG index may become a useful biomarker in evaluating and following the presence of DR and VTDR.

Comparison of ARIMA model and XGBoost model for prediction of human brucellosis in mainland China: a time-series study

OBJECTIVES

Human brucellosis is a public health problem endangering health and property in China. Predicting the trend and the seasonality of human brucellosis is of great significance for its prevention. In this study, a comparison between the autoregressive integrated moving average (ARIMA) model and the eXtreme Gradient Boosting (XGBoost) model was conducted to determine which was more suitable for predicting the occurrence of brucellosis in mainland China.

DESIGN

Time-series study.

SETTING

Mainland China.

METHODS

Data on human brucellosis in mainland China were provided by the National Health and Family Planning Commission of China. The data were divided into a training set and a test set. The training set was composed of the monthly incidence of human brucellosis in mainland China from January 2008 to June 2018, and the test set was composed of the monthly incidence from July 2018 to June 2019. The mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to evaluate the effects of model fitting and prediction.

RESULTS

The number of human brucellosis patients in mainland China increased from 30 002 in 2008 to 40 328 in 2018. There was an increasing trend and obvious seasonal distribution in the original time series. For the training set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)₁₂ model were 338.867, 450.223 and 10.323, respectively, and the MAE, RSME and MAPE of the XGBoost model were 189.332, 262.458 and 4.475, respectively. For the test set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)₁₂ model were 529.406, 586.059 and 17.676, respectively, and the MAE, RSME and MAPE of the XGBoost model were 249.307, 280.645 and 7.643, respectively.

CONCLUSIONS

The performance of the XGBoost model was better than that of the ARIMA model. The XGBoost model is more suitable for prediction cases of human brucellosis in mainland China.

MiRNA-206 suppresses the metastasis of osteosarcoma via targeting Notch3

To investigate the role of microRNA-206 (miRNA-206) in the malignant progression of osteosarcoma and the underlying mechanism, expression pattern of miRNA-206 in osteosarcoma tissues and cell lines was determined by quantitative real-time polymerase chain reaction (qRT-PCR). Correlation between miRNA-206 level and prognosis of osteosarcoma patients was analyzed. Regulatory effects of miRNA-206 on the proliferation and metastasis of U2OS and MG63 cells were evaluated by cell counting kit-8 (CCK-8), Transwell and wound healing assay. Through dual-luciferase reporter gene assay, the target gene of miRNA-206 was verified. A series of rescue experiments were conducted to explore the role of miRNA-206/Notch3 in regulating the malignant progression of osteosarcoma. MiRNA-206 was downregulated in osteosarcoma tissues and cell lines, and its level was correlated to poor prognosis and distant metastasis of osteosarcoma patients. Overexpression of miRNA-206 attenuated the proliferative and metastatic abilities of osteosarcoma cells, and miRNA-206 knockdown obtained the opposite trends. Notch3 was verified to be the target gene of miRNA-206, which was upregulated in osteosarcoma and accelerated osteosarcoma cells to proliferate and metastasize. Finally, rescue experiments showed that Notch3 overexpression partially reversed the regulatory effects of miRNA-206 on cellular behaviors of osteosarcoma cells. MiRNA-206 is downregulated in osteosarcoma. Overexpression of miRNA-206 accelerates osteosarcoma cells to proliferate and metastasize by targeting Notch3, thus accelerating the malignant progression of osteosarcoma.

Integrating Unified Medical Language System and Kleinberg's Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder

Background

The treatment of post-traumatic stress disorder (PTSD) has long been a challenge because the symptoms of PTSD are multifaceted. PTSD is primarily treated with psychotherapy and medication, or a combination of psychotherapy and medication. The present study was designed to analyze the literature on medications for PTSD and explore high-frequency common drugs and low-frequency burst drugs by burst detection algorithm combined with Unified Medical Language System (UMLS) and provide references for developing new drugs for PTSD.

Methods

Publications related to medications for PTSD from 2010 to 2019 were identified through PubMed, Web of Science Core Collection, and BIOSIS Previews. SemRep and SemRep semantic result processing system were performed to extract the set of drug concepts with therapeutic relationship according to the semantic relationship of UMLS. Kleinberg’s burst detection algorithm was applied to calculate the burst weight index of drug concepts by a Java-based program. These concepts were sorted according to the frequency and the burst weight index.

Results

Four hundred and fifty-nine treatment-related drug concepts were extracted. The drug with the highest burst weight index was “Psilocybine”, a hallucinogen, which was more likely to be a hotspot for the pharmacotherapy of PTSD. The highest frequency concept was “prazosin”, which was more likely to be the focus of research in the medications for PTSD.

Conclusion

The present study assessed the medication-related literature on PTSD treatment, providing a framework of burst words detection-based method, a baseline of information for future research and the new attempt for the discovery of textual knowledge. The bibliometric analysis based on the burst detection algorithm combined with UMLS has shown certain feasibility in amplifying the microscopic changes of a specific research direction in a field, it can also be used in other aspects of disease and to explore the trends of various disciplines.