Colquhounia Root Tablet Promotes Autophagy and Inhibits Apoptosis in Diabetic Nephropathy by Suppressing CD36 Expression In Vivo and In Vitro.

Methods: Rat models of DN were established using streptozotocin (STZ). The primary metabolic parameters were assessed. The pathological changes of the rat kidney were investigated, and RNA sequencing was performed for each group. Renal tissue apoptosis was detected using the TUNEL assay. In rats and high glucose- (Hg-) induced HK-2 cells, RT-qPCR and western blot were used to analyze the expression of related genes and proteins. Hg medium was used to establish the diabetic kidney environment. The CCK-8 assay and flow cytometry were used to assess cell viability and apoptosis, respectively. Transmission electron microscopy was used to evaluate autophagy in vitro. Results: CRT treatment significantly reduced albuminuria and renal tissue damage in DN rats. Furthermore, CRT administration inhibited apoptosis and promoted autophagy in DN rat kidney tissues. CRT downregulated CD36 expression and activated the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway in DN rat kidney tissues. CRT intervention inhibited Hg-induced apoptosis and reversed autophagy in HK-2 cells. Moreover, overexpression of CD36 suppressed the beneficial effects of CRT. Conclusions: Our study is the first to report that CRT inhibited apoptosis and promoted autophagy in vivo and in vitro, which was achieved by reducing CD36 expression and activating the AMPK pathway. Therefore, CRT may be an effective drug to treat DN.

Comparison of physicochemical characteristics, antioxidant and immunomodulatory activities of polysaccharides from wine grapes.

In this study, an efficient ultrasonic-assisted extraction method was used for the extraction and optimization of four wine grape polysaccharides. A three-level, three-factor Box Behnken Design combined with the response surface approach was used to optimize the extraction conditions. Their physicochemical properties, molecular structure, antioxidant activity, immunomodulatory activity and hepatoprotective effects were examined and compared. These findings suggest that the four wine grape polysaccharides share similar basic structural features and monosaccharide composition. Furthermore, four wine grape polysaccharides exhibited antioxidant and immunomodulatory activities in a concentration-dependent manner. Moldova (MD) polysaccharide displayed better antioxidant activity and immunomodulatory ability. Furthermore, MD polysaccharide has a significant therapeutic effect on CCl4-induced rat liver injury by improving the antioxidant defense system and inhibiting oxidative stress, indicating that MD has a hepatoprotective effect. Taken together, the MD wine grape polysaccharide may have potential applications in prevention of liver disease in the functional food and pharmaceutical industries.

C4orf19 inhibits colorectal cancer cell proliferation by competitively binding to Keap1 with TRIM25 via the USP17/Elk-1/CDK6 axis.

Colorectal cancer (CRC) is one of the most common malignant tumors in the gastrointestinal tract, and has been attracted a great deal attention and extensive investigation due to its high morbidity and mortality rates. The C4orf19 gene encodes a protein with uncharacterized function. Our preliminary exploration of the TCGA database indicated that C4orf19 is markedly downregulated in CRC tissues in comparison to that observed in normal colonic tissues, suggesting its potential association with CRC behaviors. Further studies showed a significant positive correlation between C4orf19 expression levels and CRC patient prognosis. Ectopic expression of C4orf19 inhibited the growth of CRC cells in vitro and tumorigenic ability in vivo. Mechanistic studies showed that C4orf19 binds to Keap1 at near the Lys615, which prevents the ubiquitination of Keap1 by TRIM25, thus protecting the Keap1 protein from degradation. The accumulated Keap1 results in USP17 degradation and in turn leading to the degradation of Elk-1, further attenuates its regulated CDK6 mRNA transcription and protein expression, as well as its mediated proliferation of CRC cells. Collectively, the present studies characterize function of C4orf19 as a tumor suppressor for CRC cell proliferation by targeting Keap1/USP17/Elk-1/CDK6 axis.

Physicochemical characteristics and biological activities of grape polysaccharides collected from different cultivars.

In this study, four wine grape polysaccharides were extracted and optimized by using an efficient ultrasound-assisted extraction. A three-level, three-factor Box Behnken Design (BBD) combining with response surface methodology (RSM) was employed to optimize the extraction conditions including ultrasonic power, ultrasonic time and liquid-to-solid ratio. Furthermore, their physicochemical structures, antioxidant and liver protective activity were investigated and compared. Results revealed that the functional groups and monosaccharide compositions of these grape polysaccharides collected from different varieties were similar. Nevertheless, their molecular weights, molar ratios of monosaccharide compositions and surface morphological features were different. And the antioxidant activities of these polysaccharides were screened by free radical scavenging test. 'Beichun' (BC) and 'Benni fuji' (BF) polysaccharides possessed better antioxidant function. Further, the in vivo evaluation indicated that the polysaccharides of BC and BF have a protective effect against myocardial I/R injury in mice by inhibiting myocardial necroptosis mediated by mitochondrial ROS generation. Therefore, BC and BF grapes have potential applications in the medical and food industries.

Differentiation of Lung Metastases Originated From Different Primary Tumors Using Radiomics Features Based on CT Imaging.

RATIONALE AND OBJECTIVES: To explore the feasibility of differentiating three predominant metastatic tumor types using lung computed tomography (CT) radiomics features based on supervised machine learning. MATERIALS AND METHODS: This retrospective analysis included 252 lung metastases (LM) (from 78 patients), which were divided into the training (n = 176) and test (n = 76) cohort randomly. The metastases originated from colorectal cancer (n = 97), breast cancer (n = 87), and renal carcinoma (n = 68). An additional 77 LM (from 35 patients) were used for external validation. All radiomics features were extracted from lung CT using an open-source software called 3D slicer. The least absolute shrinkage and selection operator (LASSO) method selected the optimal radiomics features to build the model. Random forest and support vector machine (SVM) were selected to build three-class and two-class models. The performance of the classification model was evaluated with the area under the receiver operating characteristic curve (AUC) by two strategies: one-versus-rest and one-versus-one. RESULTS: Eight hundred and fifty-one quantitative radiomics features were extracted from lung CT. By LASSO, 23 optimal features were extracted in three-class, and 25, 29, and 35 features in two-class for differentiating every two of three LM (colorectal cancer vs. renal carcinoma, colorectal cancer vs. breast cancer, and breast cancer vs. renal carcinoma, respectively). The AUCs of the three-class model were 0.83 for colorectal cancer, 0.79 for breast cancer, and 0.91 for renal carcinoma in the test cohort. In the external validation cohort, the AUCs were 0.77, 0.83, and 0.81, respectively. Swarmplot shows the distribution of radiomics features among three different LM types. In the two-class model, high accuracy and AUC were obtained by SVM. The AUC of discriminating colorectal cancer LM from renal carcinoma LM was 0.84, and breast cancer LM from colorectal cancer LM and renal carcinoma LM were 0.80 and 0.94, respectively. The AUCs were 0.77, 0.78, and 0.84 in the external validation cohort. CONCLUSION: Quantitative radiomics features based on Lung CT exhibited good discriminative performance in LM of primary colorectal cancer, breast cancer, and renal carcinoma.

Downregulation of TEX11 promotes S-Phase progression and proliferation in colorectal cancer cells through the FOXO3a/COP1/c-Jun/p21 axis.

Colorectal cancer (CRC) is the most common digestive tract malignancy, attributing to approximately 9.4% of global cancer-related deaths. However, the pathogenesis of CRC is poorly understood. The testis-expressed 11 (TEX11) gene is located on the X chromosome and is required for spermatogenesis, and is reported might serve as a biomarker for early onset CRC according to database analysis. However, the role played by TEX11 in cancer progression remains to be investigated. In this study, we show that TEX11 expression is significantly downregulated in CRC cell lines and clinical CRC tissue samples, and TEX11 expression correlates with poor prognosis in CRC patients. We further demonstrate that TEX11 can significantly inhibit the proliferative capacity of CRC cells in vitro and in vivo. Mechanistically, we demonstrate that TEX11 promotes transcription of COP1 by upregulating FOXO3a expression. This enhanced COP1 expression subsequently accelerates the degradation of the negative transcriptional regulator c-Jun, which, in turn, enhances p21 transcription inhibiting CRC cell cycle progression and proliferation. Overall, our findings suggest that TEX11 may be a valuable therapeutic target for the treatment of CRC.

Clinical-radiomics nomogram for identifying HER2 status in patients with breast cancer: A multicenter study.

Purpose: To develop and validate a clinical-radiomics nomogram based on radiomics features and clinical risk factors for identification of human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer (BC). Methods: Two hundred and thirty-five female patients with BC were enrolled from July 2018 to February 2022 and divided into a training group (from center I, 115 patients), internal validation group (from center I, 49 patients), and external validation group (from centers II and III, 71 patients). The preoperative MRI of all patients was obtained, and radiomics features were extracted by a free open-source software called 3D Slicer. The Least Absolute Shrinkage and Selection Operator regression model was used to identify the most useful features. The radiomics score (Rad-score) was calculated by using the radiomics signature-based formula. A clinical-radiomics nomogram combining clinical factors and Rad-score was developed through multivariate logistic regression analysis. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 2,553 radiomics features were extracted, and 21 radiomics features were selected as the most useful radiomics features. Multivariate logistic regression analysis indicated that Rad-score, progesterone receptor (PR), and Ki-67 were independent parameters to distinguish HER2 status. The clinical-radiomics nomogram, which comprised Rad-score, PR, and Ki-67, showed a favorable classification capability, with AUC of 0.87 [95% confidence internal (CI), 0.80 to 0.93] in the training group, 0.81 (95% CI, 0.69 to 0.94) in the internal validation group, and 0.84 (95% CI, 0.75 to 0.93) in the external validation group. DCA illustrated that the nomogram was useful in clinical practice. Conclusions: The nomogram combined with Rad-score, PR, and Ki-67 can identify the HER2 status of BC.

Catalytic Effect of Ferrocenyl Energetic Catalysts for N-Guanylurea Dinitramide (GUDN or FOX-12) Decomposition.

Four N,N-dimethylaminomethylferrocene polynitrogen catalysts were applied to the thermal decomposition of FOX-12, and their catalytic effect on FOX-12 was investigated by TG-DSC. The kinetic parameters and kinetic model of the mixed system were revealed by the Kissinger method, Freidman method, and combined kinetic analysis. The results showed that MAFcTAZ is the catalyst with the strongest effect on FOX-12, the decomposition peak temperature of FOX-12 is reduced, and the decomposition weight loss is higher than those for other catalysts, which prove that the decomposition of FOX-12 is more thorough under the catalysis of MAFcTAZ. The introduction of the four catalysts reduced the thermal decomposition peak temperature of FOX-12. MAFcTAZ was the most active catalyst for the decomposition of FOX-12, and the maximum heat release of catalyzing the decomposition of FOX-12 can reach 1236.76 J·g-1. The activation energy (E a) of FOX-12 decomposition decreased from 217.91 to 128.19, 137.85, 157.65, and 151.91 kJ·mol-1 under the effect of MAFcNO3, MAFcPA, MAFcNTO, and MAFcTAZ. The Freidman analysis illustrated that MAFcTAZ reduced the activation energy during the entire decomposition process of FOX-12. The physical model of the decomposition reaction of FOX-12 transformed from the random nucleation and two-dimensional growth of nuclei model (A2) to the random scission model (L2) in the presence of MAFcNO3 and two-dimensional diffusion (D2) under the effect of MAFcPA, MAFcNTO, and MAFcTAZ. By analyzing the molecular structures, MAFcTAZ has a higher iron content and nitrogen content, which are the essence of its excellent catalytic performance. From the perspective of interaction energy, the strong catalytic effect of MAFcTAZ is attributed to its large interaction energy with FOX-12 by energy decomposition analysis.

Study on the effect of solvent on cocrystallization of CL-20 and HMX through theoretical calculations and experiments.

Cocrystallization is a helpful method for explosives design. However, lack of understanding of the cocrystallization mechanism leads to inefficiency in cocrystal preparation. Therefore, studying the effects of solvent on cocrystal is of great importance for the efficient application of 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20). In this paper, the effect of solvent on cocrystallization is investigated by the CL-20/HMX cocrystal/solvent cluster model, the CL-20/HMX/solvent mixture model, the CL-20/HMX cocrystal/solvent interface model combined with quantum chemistry and molecular dynamic methods. The authors find that the hydrogen bond between CL-20 and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) is the strongest and the binding energy of cocrystal and solvent molecules is the weakest in ethyl acetate (EA) solvent, indicating that CL-20 and HMX tend to be combined together and there is less hindrance by solvent molecules. Analysis of the CL-20/HMX/solvent mixture and mass density distribution studies show that the solvent effect has a great influence on the crystal faces and the cocrystallization rate of CL-20 and HMX is the highest in EA solvent. The XRD and SEM characterization results are consistent with the theoretical calculations. The present work on the effects of solvent on CL-20/HMX cocrystals is beneficial for understanding the mechanism of the growth of energetic cocrystal materials. It is helpful in selecting more suitable theoretical and experimental conditions and makes access to excellent cocrystals more efficient.

CT perfusion-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease.

Purpose: To build CT perfusion (CTP)-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease (MMD). Methods: Fifty-three MMD patients who underwent CTP and digital subtraction angiography (DSA) examination were retrospectively enrolled. Patients were divided into good and poor groups based on postoperative DSA. CTP parameters, such as mean transit time (MTT), time to drain (TTD), time to maximal plasma concentration (Tmax), and flow extraction product (FE), were obtained. CTP efficacy in evaluating surgical treatment were compared between the good and poor groups. The changes in the relative CTP parameters (ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE) were calculated to evaluate the differences between pre- and postoperative CTP values. CTP parameters were selected to build delta-radiomics models for identifying collateral vessel formation. The identification performance of machine learning classifiers was assessed using area under the receiver operating characteristic curve (AUC). Results: Of the 53 patients, 36 (67.9%) and 17 (32.1%) were divided into the good and poor groups, respectively. The postoperative changes of ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE in the good group were significantly better than the poor group (p < 0.05). Among all CTP parameters in the perfusion improvement evaluation, the ΔrTTD had the largest AUC (0.873). Eleven features were selected from the TTD parameter to build the delta-radiomics model. The classifiers of the support vector machine and k-nearest neighbors showed good diagnostic performance with AUC values of 0.933 and 0.867, respectively. Conclusion: The TTD-based delta-radiomics model has the potential to identify collateral vessel formation after the operation.

Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers.

Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.

Succumbing to the COVID-19 Pandemic-Healthcare Workers Not Satisfied and Intend to Leave Their Jobs.

Healthcare workers are under such a tremendous amount of pressure during the COVID-19 pandemic that many have become concerned about their jobs and even intend to leave them. It is paramount for healthcare workers to feel satisfied with their jobs and lives during a pandemic. This study aims to examine the predictors of job satisfaction, life satisfaction, and turnover intention of healthcare workers during the COVID-19 pandemic. Between 10 and 30 April 2020, 240 healthcare workers in Bolivia completed a cross-sectional online survey, which assessed their job satisfaction, life satisfaction, and turnover intention in the ongoing COVID-19 pandemic. The results revealed that their number of office days predicted job satisfaction, life satisfaction, and turnover intention, but the relationships varied by their age. For example, healthcare workers' office days negatively predicted job satisfaction for the young (e.g., at 25 years old: b = - 0.21; 95% CI: - 0.36 to - 0.60) but positively predicted job satisfaction for the old (e.g., at 65 years old: b = 0.25; 95% CI: 0.06 to 0.44). These findings provide evidence to enable healthcare organizations to identify staff concerned about job satisfaction, life satisfaction, and turnover intention to enable early actions so that these staffs can remain motivated to fight the prolonged COVID-19 pandemic.

Correction to: Succumbing to the COVID-19 Pandemic-Healthcare Workers Not Satisfied and Intend to Leave Their Jobs.

[This corrects the article DOI: 10.1007/s11469-020-00418-6.].

Preparation, Characterization and Application of Nano-Graphene-Based Energetic Materials.

Nano-graphene-based energetic materials, as a new type of composite energetic materials such as desensitizer and combustion catalyst, have attracted extensive attention from energetic researchers. In this paper, the preparation of nano-graphene-based energetic materials, the desensitization effect of nano-graphene-based on energetic compounds, the thermal decomposition and combustion behavior of the materials are reviewed. Meanwhile, the existing problems and future development of nano-graphene-based energetic compounds are discussed.

Individual-Level Heterogeneity in Mask Wearing during the COVID-19 Pandemic in Malaysia.

Wearing a face mask has been a key approach to contain or slow down the spread of COVID-19 in the ongoing pandemic. However, there is huge heterogeneity among individuals in their willingness to wear face masks during an epidemic. This research aims to investigate the individual heterogeneity to wear face masks and its associated predictors during the COVID-19 pandemic when mask-wearing was not mandatory. Based on a survey of 708 Malaysian adults and a multivariate least-squares fitting analysis, the results reveal a significant variance among individuals in wearing masks, as 34% of the individual adults did not always wear masks in public places. Female individuals, individuals who wash their hands more frequently, and those who reported more availability of personal protective equipment were more likely to practice mask-wearing. The identification of less-compliant groups of mask wearing has critical implications by enabling more specific health communication campaigns.

Time Series Analysis and Forecasting of the Hand-Foot-Mouth Disease Morbidity in China Using An Advanced Exponential Smoothing State Space TBATS Model.

OBJECTIVE: The high morbidity, complex seasonality, and recurring risk of hand-foot-and-mouth disease (HFMD) exert a major burden in China. Forecasting its epidemic trends is greatly instrumental in informing vaccine and targeted interventions. This study sets out to investigate the usefulness of an advanced exponential smoothing state space framework by combining Box-Cox transformations, Fourier representations with time-varying coefficients and autoregressive moving average (ARMA) error correction (TBATS) method to assess the temporal trends of HFMD in China. METHODS: Data from January 2009 to December 2019 were drawn, and then they were split into two segments comprising the in-sample training data and out-of-sample testing data to develop and validate the TBATS model, and its fitting and forecasting abilities were compared with the most frequently used seasonal autoregressive integrated moving average (SARIMA) method. RESULTS: Following the modelling procedures of the SARIMA and TBATS methods, the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.024, {1,1}, 0.855, {<12,4>}) specifications were recognized as being the optimal models, respectively, for the 12-step ahead forecasting, along with the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.062, {1,3}, 0.86, {<12,4>}) models as being the optimal models, respectively, for the 24-step ahead forecasting. Among them, the optimal TBATS models produced lower error rates in both 12-step and 24-step ahead forecasting aspects compared to the preferred SARIMA models. Descriptive analysis of the data showed a significantly high level and a marked dual seasonal pattern in the HFMD morbidity. CONCLUSION: The TBATS model has the capacity to outperform the most frequently used SARIMA model in forecasting the HFMD incidence in China, and it can be recommended as a flexible and useful tool in the decision-making process of HFMD prevention and control in China.

Predictors of Depression and Anxiety Symptoms in Brazil during COVID-19.

The COVID-19 pandemic in Brazil is extremely severe, and Brazil has the third-highest number of cases in the world. The goal of the study is to identify the prevalence rates and several predictors of depression and anxiety in Brazil during the initial outbreak of COVID-19. We surveyed 482 adults in 23 Brazilian states online on 9-22 May 2020, and found that 70.3% of the adults (n = 339) had depressive symptoms and 67.2% (n = 320) had anxiety symptoms. The results of multi-class logistic regression models revealed that females, younger adults, and those with fewer children had a higher likelihood of depression and anxiety symptoms; adults who worked as employees were more likely to have anxiety symptoms than those who were self-employed or unemployed; adults who spent more time browsing COVID-19 information online were more likely to have depression and anxiety symptoms. Our results provide preliminary evidence and early warning for psychiatrists and healthcare organizations to better identify and focus on the more vulnerable sub-populations in Brazil during the ongoing COVID-19 pandemic.

Epidemiological Characteristics and Drug Resistance Analysis of Cerebrospinal Fluid Microbial Infections in Wenzhou Area.

OBJECTIVE: Central nervous system infections (CNSI) are serious diseases that endanger human health. Identifying pathogens and their susceptibility to antibiotics, and promptly using antibiotics under this guidance is essential for treatment. The purpose of this study is to investigate the pathogen characteristics of CNSI patients, which can help clinicians choose appropriate empiric antibiotic . METHODS: We retrospectively collected data on CNSI patients with cerebrospinal fluid (CSF) culture positive from 2012 to 2020, including demographic characteristics, laboratory data, pathogenic bacteria, and antimicrobial susceptibility test results. RESULTS: A total of 166 patients with 168 isolates out of 8188 patients were available for data analysis. Among the isolates, Gram-positive bacteria, Gram-negative bacteria and fungi accounted for 59.5%, 36.3%, and 4.2%, respectively. Among newborns, children under 12, and patients over 12, the most isolated strains were Streptococcus agalactiae (24/46, 52.2%), Streptococcus pneumoniae (21/68, 30.9%) and Staphylococcus epidermidis (10/54, 18.5%), respectively. Streptococcus agalactiae is more sensitive to linezolid and vancomycin. Streptococcus pneumoniae is more sensitive to vancomycin. Staphylococcus epidermidis is more sensitive to clindamycin and rifampicin. The sugar content in the CSF of Gram-negative bacteria of children ≤12 years old was significantly lower than that of Gram-positive bacteria (P<0.05). CONCLUSION: We comprehensively studied the etiological characteristics and antimicrobial resistance patterns of positive cerebrospinal fluid cultures in Wenzhou City, Zhejiang Province from 2012 to 2020, which can provide valuable strategies for preventing pathogens and improving evidence-based treatment.

Forecasting the Tuberculosis Incidence Using a Novel Ensemble Empirical Mode Decomposition-Based Data-Driven Hybrid Model in Tibet, China.

OBJECTIVE: The purpose of this study is to develop a novel data-driven hybrid model by fusing ensemble empirical mode decomposition (EEMD), seasonal autoregressive integrated moving average (SARIMA), with nonlinear autoregressive artificial neural network (NARNN), called EEMD-ARIMA-NARNN model, to assess and forecast the epidemic patterns of TB in Tibet. METHODS: The TB incidence from January 2006 to December 2017 was obtained, and then the time series was partitioned into training subsamples (from January 2006 to December 2016) and testing subsamples (from January to December 2017). Among them, the training set was used to develop the EEMD-SARIMA-NARNN combined model, whereas the testing set was used to validate the forecasting performance of the model. Whilst the forecasting accuracy level of this novel method was compared with the basic SARIMA model, basic NARNN model, error-trend-seasonal (ETS) model, and traditional SARIMA-NARNN mixture model. RESULTS: By comparing the accuracy level of the forecasting measurements including root-mean-square error, mean absolute deviation, mean error rate, mean absolute percentage error, and root-mean-square percentage error, it was shown that the EEMD-SARIMA-NARNN combined method produced lower error rates than the others. The descriptive statistics suggested that TB was a seasonal disease, peaking in late winter and early spring and a trough in autumn and early winter, and the TB epidemic indicated a drastic increase by a factor of 1.7 from 2006 to 2017 in Tibet, with average annual percentage change of 5.8 (95% confidence intervals: 3.5-8.1). CONCLUSION: This novel data-driven hybrid method can better consider both linear and nonlinear components in the TB incidence than the others used in this study, which is of great help to estimate and forecast the future epidemic trends of TB in Tibet. Besides, under present trends, strict precautionary measures are required to reduce the spread of TB in Tibet.

Real-time detection and imaging of exogenous and endogenous Zn2+ in the PC12 cell model of depression with a NIR fluorescent probe.

Depression is closely related to overactivation of N-methyl-d-aspartic acid (NMDA) receptors, and Zn2+ is a vital NMDA receptor modulator involved in the pathophysiological and physiological processes of depression. Therefore, quantitative and real-time detection of Zn2+ is very important for understanding the pathogenesis of depression. In this work, a near-infrared (NIR) fluorescent probe ISO-DPA was designed and synthesized for Zn2+ detection with a large Stokes shift (185 nm), high quantum yield (up to 44%), high sensitivity (LOD = 0.106 µM) and good pH stability. The probe showed rapid response within 10 s, accompanied by a distinct fluorescence change from faint to bright pink with the fluorescence intensity increasing 4.5-fold. Moreover, the sensing mechanism of ISO-DPA towards Zn2+ was supported by MALDI-TOF-MS and Job's plot. The probe ISO-DPA could detect instantaneous variation of exogenous and endogenous Zn2+ in PC12 cells. The bioimaging results reveal the increase of the endogenous Zn2+ concentration in PC12 cells under the oxidative stress induced by glutamate and confirm that overactivation of NMDA receptors results in an increase of the Zn2+ level. All the results proved that ISO-DPA is an excellent probe for detecting Zn2+ in solution and living cells and could help us better understand Zn2+ associated pathogenesis of depression.