The Spatiotemporal Pattern and Its Determinants of Hemorrhagic Fever With Renal Syndrome in Northeastern China: Spatiotemporal Analysis.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease mainly transmitted by rodents. However, the determinants of its spatiotemporal patterns in Northeast China remain unclear. OBJECTIVE: This study aimed to investigate the spatiotemporal dynamics and epidemiological characteristics of HFRS and detect the meteorological effect of the HFRS epidemic in Northeastern China. METHODS: The HFRS cases of Northeastern China were collected from the Chinese Center for Disease Control and Prevention, and meteorological data were collected from the National Basic Geographic Information Center. Times series analyses, wavelet analysis, Geodetector model, and SARIMA model were performed to identify the epidemiological characteristics, periodical fluctuation, and meteorological effect of HFRS in Northeastern China. RESULTS: A total of 52,655 HFRS cases were reported in Northeastern China from 2006 to 2020, and most patients with HFRS (n=36,558, 69.43%) were aged between 30-59 years. HFRS occurred most frequently in June and November and had a significant 4- to 6-month periodicity. The explanatory power of the meteorological factors to HFRS varies from 0.15 ≤ q ≤ 0.01. In Heilongjiang province, mean temperature with a 4-month lag, mean ground temperature with a 4-month lag, and mean pressure with a 5-month lag had the most explanatory power on HFRS. In Liaoning province, mean temperature with a 1-month lag, mean ground temperature with a 1-month lag, and mean wind speed with a 4-month lag were found to have an effect on HFRS, but in Jilin province, the most important meteorological factors for HFRS were precipitation with a 6-month lag and maximum evaporation with a 5-month lag. The interaction analysis of meteorological factors mostly showed nonlinear enhancement. The SARIMA model predicted that 8,343 cases of HFRS are expected to occur in Northeastern China. CONCLUSIONS: HFRS showed significant inequality in epidemic and meteorological effects in Northeastern China, and eastern prefecture-level cities presented a high risk of epidemic. This study quantifies the hysteresis effects of different meteorological factors and prompts us to focus on the influence of ground temperature and precipitation on HFRS transmission in future studies, which could assist local health authorities in developing HFRS-climate surveillance, prevention, and control strategies targeting high-risk populations in China.

Spatiotemporal dynamics and environmental determinants of scrub typhus in Anhui Province, China, 2010-2020.

This study aims to describe the epidemiological characteristics of scrub typhus, detect the spatio-temporal patterns of scrub typhus at county level, and explore the associations between the environmental variables and scrub typhus cases in Anhui Province. Time-series analysis, spatial autocorrelation analysis, and space-time scan statistics were used to explore the characteristics and spatiotemporal patterns of the scrub typhus in Anhui Province. Negative binomial regression analysis was used to explore the association between scrub typhus and environmental variables. A total of 16,568 clinically diagnosed and laboratory-confirmed cases were reported from 104 counties of 16 prefecture-level cities. The number of female cases was higher than male cases, with a proportion of 1.32:1. And the proportion of cases over 65 years old was the highest, accounting for 33.8% of the total cases. Two primary and five secondary high-risk clusters were detected in the northwestern, northeastern, and central-eastern parts of Anhui Province. The number of cases in primary and secondary high-risk clusters accounted for 60.27% and 3.00%, respectively. Scrub typhus incidence in Anhui Province was positively correlated with the population density, normalized difference vegetation index, and several meteorological variables. The mean monthly sunshine duration with 3 lags (SSD_lag3), mean monthly ground surface temperature with 1 lag (GST_lag1), and mean monthly relative humidity with 3 lags (RHU_lag3) had the most significant association with increased cases of scrub typhus. Our findings indicate that public health interventions need to be focused on the elderly farmers in north of the Huai River in Anhui Province.

Body mass index and death by cognitive impairment.

BACKGROUND: Epidemiological studies have reported that among participants with impaired cognitive, overweight and mild obesity are associated with substantially improved survival, this finding has been termed the "obesity paradox" and has led to uncertainty about secondary prevention. AIMS: To explore whether the association of BMI with mortality differed in different MMSE score, and whether the obesity paradox in patient with cognitive impairment (CI) is real. METHODS: The study used data from CLHLS, a representative prospective population-based cohort study in China, which included 8348 participants aged ≥ 60 years between 2011 and 2018. The independent association between BMI and mortality in differed MMSE score by calculating hazard ratios (HRs) in multivariate Cox regression analysis. RESULTS: During a median (IQR) follow-up of 41.18 months, a total of 4216 participants died. In the total population, underweight increased the risk of all-cause mortality (HRs, 1.33; 95% CI 1.23-1.44), compared with normal weight, and overweight was associated with a decreased risk of all-cause mortality (HR 0.83; 95% CI 0.74-0.93). However, compared to normal weight, only underweight was associated with increased mortality risk among participants with MMSE scores of 0-23, 24-26, 27-29, and 30, and the fully-adjusted HRs (95% CIs) for mortality were 1.30 (1.18, 1.43), 1.31 (1.07, 1.59), 1.55 (1.34, 1.80) and 1.66 (1.26, 2.20), respectively. The obesity paradox was not found in individuals with CI. Sensitivity analyses carried out had hardly any impact on this result. CONCLUSION: We found no evidence of an obesity paradox in patients with CI, compared with patients of normal weight. But underweight individuals may have increased mortality risk whether in the population with CI or not. And overweight/obese people with CI should continue to aim for normal weight.

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study.

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.

Cognitive impairment assessed by Mini-Mental State Examination predicts all-cause and CVD mortality in Chinese older adults: A 10-year follow-up study.

Objective: Cognitive impairment (CI) has been demonstrated as a useful proxy measure of mortality in Western populations. However, the predictive value of CI in Chinese populations is unknown. We aimed to explore whether CI is independently associated with increased long-term all-cause and cardiovascular disease (CVD) mortality in Chinese older adults and the association of performance in specific MMSE sub-domains to subsequent mortality. Methods and results: A total of 4,499 older adults [mean (SD) age, 70.3(6.7) years] who received a sample investigation from 2011 to 2014 were followed up till 2021 for mortality. The Mini-Mental State Examination was used to assess cognitive function, and Cox's proportional hazard models were used to evaluate the effects of cognitive function on the risk of all-cause and CVD mortality. Demographic characteristics, lifestyle, and health status were included as covariates. During a 10-year follow-up, a total of 667 (14.8%) died. In the fully adjusted model, compared with cognitively normal participants with CI had a 1.33-fold [HR, 1.33; (95% CI, 1.10-1.61)] greater risk of all-cause mortality and a 1.45-fold [HR, 1.45; (95% CIs, 1.11-1.92)] greater risk of CVD mortality. After a similar multivariable adjustment, a per-SD increase in MMSE scores was associated with a reduced risk of all-cause mortality [HR, 0.85; (95% CI, 0.78-0.93)] and CVD mortality [HR, 0.74; (95% CI, 0.65-0.84)]. In the unadjusted model, MMSE sub-domains (apart from immediate recall) were associated with mortality. But only orientation and calculation and attention were still independently associated with all-cause and CVD mortality in a multivariable model. Conclusion: These findings confirmed that CI is a marker of all-cause and CVD mortality risk in Chinese older adults, independently of other commonly assessed risk factors, and some sub-domains of the MMSE may have stronger associations with mortality. Further research is needed to identify the mechanisms underlying the observed associations.

Synergistic impact of diabetes and cognitive impairment on all-cause and cause-specific mortality in Chinese older adults: A prospective population-based cohort study.

Background: Diabetes mellitus (DM) or cognitive impairment (CI) is known to be strongly associated with mortality. DM commonly coexists with CI and proportionally increases with age. However, little is known about the combined effect of cognitive function and diabetes on mortality. This study aimed to evaluate the combined effects of DM and CI on all-cause and cause-specific mortality in Chinese older adults. Methods: This prospective population-based cohort study was based on the Beijing Elderly Comprehensive Health Cohort Study. A total of 4,499 older adults were included. Cox's proportional hazard models were utilized to calculate the effect of DM and CI on all-cause, cardiovascular disease (CVD) mortality and cancer mortality, and a multiplicative term was introduced to study a potential interaction between DM and CI on outcomes. Results: During a median follow-up of 6.8 years (ranging from 6.6 to 11.7 years), 667 (14.8%) participants died from all causes, 292 from CVD, and 215 from cancer. In the fully adjusted model, participants with coexisting DM and CI had the highest risk of all-cause mortality [hazard ratios (HRs), 3.08; 95% confidence intervals (CIs), 2.30,4.11] and CVD mortality (HRs, 3.85; 95% CIs, 2.60,5.71) compared with individuals with normal cognition and non-DM. We also found a multiplicative interaction between DM and CI in respect to all-cause (HRs, 2.46; 95% CI, 1.87,3.22) and CVD mortality (HRs, 3.15 95% CI, 2.19,4.55). In the diabetic population, CI was associated with an increased risk of all-cause mortality (HRs, 2.09; 95% CIs, 1.51,2.89) and CVD mortality (HRs, 3.16; 95% CIs, 2.02,5.05) compared with the normal cognition group. Restricted cubic spline revealed a linear inverse association between Mini-Mental State Examination (MMSE) score and all-cause, CVD mortality in the total sample and participants without diabetes. However, a nearly reverse J association was observed between MMSE and mortality from all causes and CVD in the diabetes group. Conclusion: The findings highlighted that cognitive impairment concomitant with diabetes further increases the risk of mortality. In addition to strengthening routine screening of cognitive functioning in older adults with early-stage diabetes, more extensive assessment of prognostic risks has high clinical value for developing comprehensive treatment plans.

Climate and socio-economic factors drive the spatio-temporal dynamics of HFRS in Northeastern China.

Background: Hemorrhagic fever with renal syndrome (HFRS) occurs widely in Northeastern China, but the mechanism and interactions of meteorological and socio-economic factors on the transmission of HFRS are still largely unknown. Objective: We explored the effects of socioeconomic-environmental factors on the spatio-temporal variation of HFRS incidence from 2001 to 2019 in Northeastern China. Specifically, the relative importance and contribution rates (CR) of determinants of HFRS were identified by boosted regression tree and variance partitioning analysis, respectively. Structural equation models (SEMs) were used to explain the roles of climatic and socio-economic factors in the transmission of HFRS. And a negative binomial regression was used to identify the risk effect between monthly meteorological variables and HFRS with 0-6 months lags in Northeastern China. Results: Over the past decades, the high-risk areas of HFRS were mainly concentrated in the northern and eastern areas of Northeastern China. Additionally, HFRS mainly presented a decreasing trend from 2001 to 2019 in most areas of Northeastern China, but slightly increased in the cities of Daqing, Songyuan, Baicheng, and Tonghua. The temporal dynamics of the incidence of HFRS were primarily explained by the variations in population density (CR = 27.30%), climate (CR = 13.30%), and economic condition(CR = 1.90%). The spatial variations of HFRS were medicated by the climate (CR = 16.95%) and population density (CR = 9.45%) and medical health care (CR = 2.25%). The SEM models indicated that humid and warm climates were conducive to the incidence and increase of HFRS, but the improvement in education and an increase in population density reduced the transmission of HFRS. Conclusion: Climate and population density appeared to mediate the spatio-temporal variation of HFRS in Northeastern China. These findings may provide valuable empirical evidence for the management of HFRS in endemic areas.

Prediction and analysis of COVID-19 daily new cases and cumulative cases: times series forecasting and machine learning models.

BACKGROUND: COVID-19 poses a severe threat to global human health, especially the USA, Brazil, and India cases continue to increase dynamically, which has a far-reaching impact on people's health, social activities, and the local economic situation. METHODS: The study proposed the ARIMA, SARIMA and Prophet models to predict daily new cases and cumulative confirmed cases in the USA, Brazil and India over the next 30 days based on the COVID-19 new confirmed cases and cumulative confirmed cases data set(May 1, 2020, and November 30, 2021) published by the official WHO, Three models were implemented in the R 4.1.1 software with forecast and prophet package. The performance of different models was evaluated by using root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). RESULTS: Through the fitting and prediction of daily new case data, we reveal that the Prophet model has more advantages in the prediction of the COVID-19 of the USA, which could compose data components and capture periodic characteristics when the data changes significantly, while SARIMA is more likely to appear over-fitting in the USA. And the SARIMA model captured a seven-day period hidden in daily COVID-19 new cases from 3 countries. While in the prediction of new cumulative cases, the ARIMA model has a better ability to fit and predict the data with a positive growth trend in different countries(Brazil and India). CONCLUSIONS: This study can shed light on understanding the outbreak trends and give an insight into the epidemiological control of these regions. Further, the prediction of the Prophet model showed sufficient accuracy in the daily COVID-19 new cases of the USA. The ARIMA model is suitable for predicting Brazil and India, which can help take precautions and policy formulation for this epidemic in other countries.

A dramatic conformational effect of multifunctional zwitterions on zeolite crystallization.

Carnitine functions as a mesoporogen in LTA zeolite synthesis whereas its structural analogue acetylcarnitine acts as a crystal growth modifier. An array of experimental and theoretical studies reveal a remarkable effect of molecular conformation on the actual roles of organic functional groups during zeolite crystallization.

In situ templating synthesis of mesoporous Ni-Fe electrocatalyst for oxygen evolution reaction.

Low-cost and efficient electrocatalysts with high dispersion of active sites and high conductivity are of high importance for oxygen evolution reaction (OER). Herein, we use amorphous mesoporous fumed silica (MFS) as a skeleton material to disperse Ni2+ and Fe3+ through a simple impregnation strategy. The MFS is in situ etched away during the OER process in 1 M KOH to prepare a stable mesoporous Ni-Fe electrocatalyst. The high specific surface area and abundant surface silanol groups in the mesoporous fumed silica afford rich anchor sites for fixing metal atoms via strong chemical metal-oxygen interactions. Raman and XPS investigations reveal that Ni2+ formed covalent bonds with surface Si-OH groups, and Fe3+ inserted into the framework of fumed silica forming Fe-O-Si bonds. The mesoporous Ni-Fe catalysts offer high charge transfer abilities in the OER process. When loaded on nickel foam, the optimal 2Ni1Fe-MFS catalyst exhibits an overpotential of 270 mV at 10 mA cm-2 and a Tafel slope of 41 mV dec-1. Notably, 2Ni1Fe-MFS shows a turnover frequency value of 0.155 s-1 at an overpotential of 300 mV, which is 80 and 190 times higher than that of the state-of-the-art IrO2 and RuO2 catalysts. Furthermore, 2Ni1Fe-MFS exhibits 100% faradaic efficiency, large electrochemically active surface area, and good long-term durability, confirming its outstanding OER performance. Such high OER efficiency can be ascribed to the synergistic effect of high surface area, dense metal active sites and interfacial conductive path. This work provides a promising strategy to develop simple, cost-effective, and highly efficient porous Ni-Fe based catalysts for OER.

A zeolite-based ship-in-a-bottle route to ultrasmall carbon dots for live cell labeling and bioimaging.

Fluorescent carbon quantum dots (CQDs) are a new class of carbon nanomaterials that have excellent biocompatibility and low toxicity, useful for cell labeling and bioimaging. However, it is challenging to reproducibly create CQDs that are uniform and small in size with controlled toxicity and fluorescence properties, and this status quo hinders the practical application of CQDs, especially in vivo. In this report, CQDs with a uniform size of ∼1.53 ± 0.42 nm are synthesized via in situ pyrolysis of organics confined in the smallest-pore zeolite SAPO-20 with a micropore aperture of 0.28 nm. The ultrasmall fluorescent CQDs show a bright green fluorescence with a quantum yield (QY) of 16%, higher than that of most of the bare CQDs without any functionalization and maximum emission at 523 nm under the irradiation of xenon-light at an excitation wavelength of 470 nm. X-ray photoelectron spectroscopy (XPS) characterization confirms the presence of rich carboxyl and hydroxyl groups on the CQD surface containing N- and O-based functional groups. The synthesized CQDs with high QY and low cytotoxicity have been successfully used for cellular imaging with excellent biocompatibility.

Direct synthesis of core-shell MFI zeolites with spatially tapered trimodal mesopores via controlled orthogonal self-assembly.

Manipulating pore hierarchy in porous materials is an attractive, yet difficult challenge in crystalline zeolites. Here, we report core-shell MFI zeolites having trimodal mesopores with size gradually decreasing from the surface to the core, synthesized through a one-pot approach via controlled orthogonal self-assembly. The novel spatially resolved mesopore structures are ascribed to the nanoscale phase separation between mutually coupled interactions of organosilane supramolecular assembly and zeolite framework ordering. The highly hierarchical zeolite architecture with tapered mesopore distribution allowed for spatially resolved adsorption of florescent molecules, improved catalytic performance in condensation reactions, and an enhanced nanoreactor for coupling reactions due to alleviated diffusion limitations. The successful synthesis of fine-tuned zeolites with larger mesopores gradually subdivided into smaller mesopores (hierarchy-type I) may open up possibilities for emergent new porous structures exhibiting a higher degree of hierarchies that are currently inaccessible to many crystalline oxide or related materials.

Organosilicon modification to enhance the stability of black phosphorus nanosheets under ambient conditions.

Thanks to its tunable direct band gap, high charge-carrier mobility, and unique in-plane anisotropic structure, black phosphorus (BP) has become a rising star among post-graphene two-dimensional (2D) nanomaterials. However, BP is unstable under ambient conditions, which largely limits its application. In this paper, an organosilicon agent, TMSCl, was used for the surface coordination of BP nanosheets to generate TMSCl@BP, which could maintain its surface morphology and properties for 24 h under ambient conditions and has no cytotoxicity at a concentration of 200 ppm as per previous reports. Our study is the first evidence that bare BP can coordinate with organosilicon to generate the more stable TMSCl@BP. Notably, the photothermal effect of TMSCl@BP was maintained after exposure to ambient conditions for over 24 hours.