Effects of an Early Intensive Blood Pressure-lowering Strategy Using Remifentanil and Dexmedetomidine in Patients with Spontaneous Intracerebral Hemorrhage: A Multicenter, Prospective, Superiority, Randomized Controlled Trial.

BACKGROUND: Although it has been established that elevated blood pressure and its variability worsen outcomes in spontaneous intracerebral hemorrhage, antihypertensives use during the acute phase still lacks robust evidence. A blood pressure-lowering regimen using remifentanil and dexmedetomidine might be a reasonable therapeutic option given their analgesic and antisympathetic effects. The objective of this superiority trial was to validate the efficacy and safety of this blood pressure-lowering strategy that uses remifentanil and dexmedetomidine in patients with acute intracerebral hemorrhage. METHODS: In this multicenter, prospective, single-blinded, superiority randomized controlled trial, patients with intracerebral hemorrhage and systolic blood pressure (SBP) 150 mmHg or greater were randomly allocated to the intervention group (a preset protocol with a standard guideline management using remifentanil and dexmedetomidine) or the control group (standard guideline-based management) to receive blood pressure-lowering treatment. The primary outcome was the SBP control rate (less than 140 mmHg) at 1 h posttreatment initiation. Secondary outcomes included blood pressure variability, neurologic function, and clinical outcomes. RESULTS: A total of 338 patients were allocated to the intervention (n = 167) or control group (n = 171). The SBP control rate at 1 h posttreatment initiation in the intervention group was higher than that in controls (101 of 161, 62.7% vs. 66 of 166, 39.8%; difference, 23.2%; 95% CI, 12.4 to 34.1%; P < 0.001). Analysis of secondary outcomes indicated that patients in the intervention group could effectively reduce agitation while achieving lighter sedation, but no improvement in clinical outcomes was observed. Regarding safety, the incidence of bradycardia and respiratory depression was higher in the intervention group. CONCLUSIONS: Among intracerebral hemorrhage patients with a SBP 150 mmHg or greater, a preset protocol using a remifentanil and dexmedetomidine-based standard guideline management significantly increased the SBP control rate at 1 h posttreatment compared with the standard guideline-based management.

High photoresponsivity MoS2phototransistor through enhanced hole trapping HfO2gate dielectric.

Phototransistor using 2D semiconductor as the channel material has shown promising potential for high sensitivity photo detection. The high photoresponsivity is often attributed to the photogating effect, where photo excited holes are trapped at the gate dielectric interface that provides additional gate electric field to enhance channel charge carrier density. Gate dielectric material and its deposition processing conditions can have great effect on the interface states. Here, we use HfO2gate dielectric with proper thermal annealing to demonstrate a high photoresponsivity MoS2phototransistor. When HfO2is annealed in H2atmosphere, the photoresponsivity is enhanced by an order of magnitude as compared with that of a phototransistor using HfO2without annealing or annealed in Ar atmosphere. The enhancement is attributed to the hole trapping states introduced at HfO2interface through H2annealing process, which greatly enhances photogating effect. The phototransistor exhibits a very large photoresponsivity of 1.1 × 107A W-1and photogain of 3.3 × 107under low light illumination intensity. This study provides a processing technique to fabricate highly sensitive phototransistor for low optical power detection.

Global Neural Network Potential with Explicit Many-Body Functions for Improved Descriptions of Complex Potential Energy Surface.

The high dimensional machine learning potential (MLP) that has developed rapidly in the past decade represents a giant step forward in large-scale atomic simulation for complex systems. The long-range interaction and the poor description of chemical reactions are typical problems of high dimensional MLP, which are mainly caused by the poor structure discrimination of the atom-centered ML model. Herein, we propose a low-cost neural-network-based MLP architecture for fitting global potential energy surface data, namely, G-MBNN, that can offer improved energy and force resolution on a complex potential energy surface. In G-MBNN, a set of many-body energy terms based on the local atomic environment are explicitly included in computing the total energy─the total energy of the system is written as the sum of atomic energy and many-body energy contributions. These extra many-body energy terms are computationally low-cost and, importantly, can provide easy access to delicate energy terms in complex systems such as very short repulsion, long-range attractions, and sensitive angular-dependent covalent interactions. We implement G-MBNN in the LASP code and demonstrate the improved accuracy of the new framework in representative systems, including ternary-element energy materials LiCoOx, TiO2 with defects, and a series of organic reactions.

Highly Active NiO-Ni(OH)2 -Cr2 O3 /Ni Hydrogen Evolution Electrocatalyst through Synergistic Reaction Kinetics.

High activity catalysts for hydrogen evolution reaction (HER) play a key role in converting renewable electricity to storable hydrogen fuel. Great effort has been devoted to the search for noble metal free catalysts to make electrolysis viable for practical applications. Here, a non-precious metal oxide/metal catalyst with high intrinsic activity comparable to Pt/C was reported. The electrocatalyst consisting of NiO, Ni(OH)2 , Cr2 O3 , and Ni metal exhibits a low overpotential of 27, 103, and 153 mV at current densities of 10, 100, and 200 mA cm-2 , respectively, in a 1.0 m NaOH electrolyte. The activity is much higher than that of NiOx /Ni or Cr2 O3 alone, showing the synergistic effect of NiOx /Ni and Cr2 O3 on catalyzing HER. Density functional theory calculations shows that NiO and Cr2 O3 on Ni surface lower the disassociation energy barrier for breaking H-OH bond, while Ni(OH)2 and Cr2 O3 create preferred sites on Ni surface with near-zero H* adsorption free energy to promote H* to gaseous H2 evolution. These synergistic effects of multiple-oxides/metal composition enhance the disassociation of H-OH and the evolution of H* to gaseous H2 , thus achieving high activity and demonstrating a promising composition design for noble metal free catalyst.

The effect of dietary carbohydrate and calorie restriction on weight and metabolic health in overweight/obese individuals: a multi-center randomized controlled trial.

BACKGROUND: Both low-carbohydrate (LC) and calorie-restricted (CR) diets have been shown to have metabolic benefits. However, the two regimens have yet to be thoroughly compared. We conducted a 12-week randomized trial to compare the effects of these diets separately and in combination on both weight loss and metabolic risk factors in overweight/obese individuals. METHODS: A total of 302 participants were randomized to LC diet (n = 76), CR diet (n = 75), LC + CR diet (n = 76), or normal control (NC) diet (n = 75) using a computer-based random number generator. The primary outcome was the change in body mass index (BMI). The secondary outcomes included body weight, waist circumference, waist-to-hip ratio, body fat, and metabolic risk factors. All participants attended health education sessions during the trial. RESULTS: A total of 298 participants were analyzed. BMI change over 12 weeks was - 0.6 (95% CI, - 0.8 to - 0.3) kg/m2 in NC, - 1.3 (95% CI, - 1.5 to - 1.1) kg/m2 in CR, - 2.3 (95% CI, - 2.6 to - 2.1) kg/m2 in LC, and - 2.9 (95% CI, - 3.2 to - 2.6) kg/m2 in LC + CR. LC + CR diet was more effective than LC or CR diet alone at reducing BMI (P = 0.001 and P < 0.001, respectively). Furthermore, compared with the CR diet, the LC + CR diet and LC diet further reduced body weight, waist circumference, and body fat. Serum triglycerides were significantly reduced in the LC + CR diet group compared with the LC or CR diet alone. Plasma glucose, homeostasis model assessment of insulin resistance, and cholesterol concentrations (total, LDL, and HDL) did not change significantly between the groups during the 12-week intervention. CONCLUSIONS: The reduction of carbohydrate intake without restricting caloric intake is more potent to achieve weight loss over 12 weeks when compared to a calorie-restricted diet in overweight/obese adults. The combination of restricting carbohydrate and total calorie intake may augment the beneficial effects of reducing BMI, body weight, and metabolic risk factors among overweight/obese individuals. TRIAL REGISTRATION: The study was approved by the institutional review board of Zhujiang Hospital of Southern Medical University and registered at the China Clinical Trial Registration Center (registration number: ChiCTR1800015156).

Imaging analysis of 1 138 supernumerary teeth by using cone-beam computed tomography.

OBJECTIVES: This study aims to analyze and summarize the characteristics of supernumerary teeth by using cone-beam computed tomography (CBCT). METHODS: A total of 718 patients with 1 138 supernumerary teeth were retrospectively collected. Age, gender, number, location, morphology, eruption status, and accompanying symptoms of the supernumerary teeth were statistically analyzed. The relationship relative to jaws, gender, and eruption status were analyzed and discussed. RESULTS: The average age of the patients was 9.54±5.32 years, and the male to female ratio was 2.88∶1. About 77.02% of the patients sought medical advice during the mixed dentition period, and 50.70% had one supernumerary tooth. These supernumeraries were most commonly conical in shape, and 85.76% of them were in the incisor region, 92.09% in the upper jaw, 46.75% in inverted position, and 86.20% unerupted. Overall, 65.29% of them had fully developed roots, and 60.63% had an impact on adjacent structures. Significant differences were found in eruption status, morphology, zoning, direction, root development, and impact on adjacent structures between the supernumerary teeth located in the upper and lower jaws (P<0.05). Significant differences were also detected in gender, morphology, zoning, orientation, root development, and impact on adjacent structures between erupted and unerupted teeth (P<0.05). The incidence of supernumerary teeth in the incisor region was higher in males than that in females. Moreover, the root of supernumeraries was more completely developed in males than in females (P<0.05). CONCLUSIONS: For supernumerary teeth, CBCT images can provide accurate three-dimensional radiographic data and are valuable for clinical diagnosis and treatment planning.

[The Mechanism of Resveratrol on Acute T-Lymphocyte Leukemia through IL-7-Mediated JAK / STAT Signaling Pathway].

OBJECTIVE: To explore the roles and relative mechanism of resveratrol against T-ALL through detecting the signaling molecules in IL-7 and JAK/STAT pathway. METHODS: In vitro experiments, Molt4 cells were divided into 3 groups, including the control group, the DMSO group and resveratrol-treated group (Res group). The control group cells without any treatment, the DMSO group cells treated with 0.05% DMSO for 48 hours, the Res group cells treated with 200 µmol/L resveratrol for 48 hours. In vivo experiments, female C57BL/6J mice (6-8 weeks) were randomly divided into the control group, the T-ALL model group (T-ALL group), and Res treatment group (Res group). The control group mice treated with 0.05% DMSO by intragastric treatment, the T-ALL group mice treated with 0.05% DMSO by intragastric treatment, and the Res group mice treated with 10 mg/ml resveratrol. Expression of IL-7, IL-7R and Pim1 mRNA in the cells and mice spleen tissues were detected by RT-qPCR. Cell proliferation ability was detected by CCK-8. The expression of JAK1, JAK3, STAT5, phosphorylated JAK1 (p-JAK1), phosphorylated JAK3 (p-JAK3), phosphorylated STAT5 (p-STAT5) and Pim1 were detected by Western blot. ELISA was used to detect the IL-7 and IL-7R in the cells and mice serum of each groups. RESULTS: Resveratrol could inhibit the proliferation ability of Molt4 cells, decrease the relative levels of p-JAK1, p-JAK3, p-STAT5, Pim1 protein, and the expression levels of Pim1, IL-7 and IL-7R mRNA in cells and mice spleens, reduce the IL-7 and IL-7R in Molt4 cells and mice serum. CONCLUSION: Resveratrol may inhibite IL-7-medicated JAK/STAT signaling pathway to reduce the expression of target protein Pim1 to further exert its anti-T-ALL effects.

Artificial intelligence pathway search to resolve catalytic glycerol hydrogenolysis selectivity.

The complex interaction between molecules and catalyst surfaces leads to great difficulties in understanding and predicting the activity and selectivity in heterogeneous catalysis. Here we develop an end-to-end artificial intelligence framework for the activity prediction of heterogeneous catalytic systems (AI-Cat method), which takes simple inputs from names of molecules and metal catalysts and outputs the reaction energy profile from the input molecule to low energy pathway products. The AI-Cat method combines two neural network models, one for predicting reaction patterns and the other for providing the reaction barrier and energy, with a Monte Carlo tree search to resolve the low energy pathways in a reaction network. We then apply AI-Cat to resolve the reaction network of glycerol hydrogenolysis on Cu surfaces, which is a typical selective C-O bond activation system and of key significance for biomass-derived polyol utilization. We show that glycerol hydrogenolysis features a huge reaction network of relevant candidates, containing 420 reaction intermediates and 2467 elementary reactions. Among them, the surface-mediated enol-keto tautomeric resonance is a key step to facilitate the primary C-OH bond breaking and thus selects 1,2-propanediol as the major product on Cu catalysts. 1,3-Propanediol can only be produced under strong acidic conditions and high surface H coverage by following a hydrogenation-dehydration pathway. AI-Cat further discovers six low-energy reaction patterns for C-O bond activation on metals that is of general significance to polyol catalysis. Our results demonstrate that the reaction prediction for complex heterogeneous catalysis is now feasible with AI-based atomic simulation and a Monte Carlo tree search.

Performance of the EuroSCORE II Model in Predicting Short-Term Mortality of General Cardiac Surgery: A Single-Center Study in Taiwan.

Background: The latest European System for Cardiac Operative Risk Evaluation (EuroSCORE) II is a well-accepted risk evaluation system for mortality in cardiac surgery in Europe. Objectives: To determine the performance of this new model in Taiwanese patients. Methods: Between January 2012 and December 2014, 657 patients underwent cardiac surgery at our institution. The EuroSCORE II scores of all patients were determined preoperatively. The short-term surgical outcomes of 30-day and in-hospital mortality were evaluated to assess the performance of the EuroSCORE II. Results: Of the 657 patients [192 women (29.22%); age 63.5 ± 12.68 years], the 30-day mortality rate was 5.48%, and the in-hospital mortality rate was 9.28%. The discrimination power of this new model was good in all populations, regardless of 30-day mortality or in-hospital mortality. Good accuracy was also noted in different procedures related to coronary artery bypass grafting, and good calibration was noted for cardiac procedures (p value > 0.05). When predicting surgical death within 30 days, the EuroSCORE II overestimated the risk (observed to expected: 0.79), but in-hospital mortality was underestimated (observed to expected: 1.33). The predictive ability [area under the curve (AUC) of the receiver operating characteristic (ROC) curve] and calibration of the EuroSCORE II for 30-day mortality (0.792) and in-hospital mortality (0.825) suggested that in-hospital mortality is a better endpoint for the EuroSCORE II. Conclusions: The new EuroSCORE II model performed well in predicting short-term outcomes among patients undergoing general cardiac surgeries. For short-term outcomes, in-hospital mortality was better than 30-day mortality as an indicator of surgical results, suggesting that it may be a better endpoint for the EuroSCORE II.

Methanol Synthesis from CO2/CO Mixture on Cu-Zn Catalysts from Microkinetics-Guided Machine Learning Pathway Search.

Methanol synthesis on industrial Cu/ZnO/Al2O3 catalysts via the hydrogenation of CO and CO2 mixture, despite several decades of research, is still puzzling due to the nature of the active site and the role of CO2 in the feed gas. Herein, with the large-scale machine learning atomic simulation, we develop a microkinetics-guided machine learning pathway search to explore thousands of reaction pathways for CO2 and CO hydrogenations on thermodynamically favorable Cu-Zn surface structures, including Cu(111), Cu(211), and Zn-alloyed Cu(211) surfaces, from which the lowest energy pathways are identified. We find that Zn decorates at the step-edge at Cu(211) up to 0.22 ML under reaction conditions with the Zn-Zn dimeric sites being avoided. CO2 and CO hydrogenations occur exclusively at the step-edge of the (211) surface with up to 0.11 ML Zn coverage, where the low coverage of Zn (0.11 ML) does not much affect the reaction kinetics, but the higher coverages of Zn (0.22 ML) poison the catalyst. It is CO2 hydrogenation instead of CO hydrogenation that dominates methanol synthesis, agreeing with previous isotope experiments. While metallic steps are identified as the major active site, we show that the [-Zn-OH-Zn-] chains (cationic Zn) can grow on Cu(111) surfaces under reaction conditions, which suggests the critical role of CO in the mixed gas for reducing the cationic Zn and exposing metal sites for methanol synthesis. Our results provide a comprehensive picture on the dynamic coupling of the feed gas composition, the catalyst active site, and the reaction activity in this complex heterogeneous catalytic system.

Changing the pattern of the back-muscle flexion-relaxation phenomenon through flexibility training in relatively inflexible young men.

Although several studies have investigated the back-muscle flexion-relaxation phenomenon (FRP), the effect of individual flexibility on the FRP has been discussed infrequently, with very limited data on the influence of flexibility training on the FRP. This study thus examined the effect of flexibility training on the change of back-muscle FRP pattern in relatively inflexible young men. We collected and analyzed the valid data from 20 male participants (10 each with high and low flexibility included in the control and trained groups, respectively) when flexing their trunks at seven trunk flexion positions (0°-90°, in increments of 15°); their erector spinae and hamstring activation, pelvic tilt, and lumbosacral angle were then recorded. After 7 weeks of flexibility training for the low-flexibility group, no difference in flexibility was discovered between this group and the control (originally high-flexibility) group. The trunk flexion experiment was then repeated. The results showed that before the training stage, the low-flexibility group had lower erector spinae and higher hamstring activation, a larger pelvic tilt, and a smaller lumbosacral angle. By contrast, after training, the erector spinae and hamstring activation, pelvic tilt, and lumbosacral angle were significantly changed, and no intergroup differences were observed in FRP patterns. The study results suggest that flexibility training changes lumbopelvic movement and thereby reduces the degree of the back-muscle FRP when trunk flexion is performed.

Evans blue staining to detect deep blood vessels in peripheral retina for observing retinal pathology in early-stage diabetic rats.

AIM: To observe and compare the statistical significance of superficial and deep vascular leakage in the pathological changes of the diabetic rats retina after the Evans blue (EB) perfusion, and utilize the modified whole-retina spreading method to make the slides while protecting the periphery of the retina. METHODS: The Sprague-Dawley (SD) rats were randomly divided into 6 groups. Each group named as the normal groups for 4, 8, and 12wk and the diabetic groups for 4, 8, and 12wk. The EB was injected into the cardiovascular system of the rats at the different time points. The retina of each group was obtained for observation. RESULTS: The superficial vascular leakage was found in all 6 groups. The size of leakage area of superficial retinal blood vessels was (0.54±0.23)%, (0.65±0.11)%, and (0.58±0.10)% in normal group. No notable leakage was found in the deep blood vessels [(0.03±0.04)%, (0.03±0.05)%, and (0.03±0.05)%]. The deep retinal vascular leakage was found in the peripheral retina of diabetic rats. The size of leakage area of superficial retinal blood vessels in diabetic group were (0.53±0.22)%, (0.69±0.16)%, and (0.52±0.11)%. The leakage areas of deep blood vessels were (0.54±0.50)%, (1.42±0.16)%, and (1.80±0.07)% at 4, 8, and 12wk, respectively. There was a statistically difference of the leakage area between the 8th week and the 4th week of diabetes group (P=0.003). The statistically significant difference between the diabetes and the control groups was noted at 4wk and 8wk (P<0.001). CONCLUSION: The main retinal pathological changes of early-stage diabetic rats are the vascular leakage of the periphery of deep retina. Diabetic rats modeled after 8wk have semi-quantitative statistical difference compared with the normal rats, thus early intervention treatment research can start at this time point.

Recent advance in the discovery of tyrosinase inhibitors from natural sources via separation methods.

Tyrosinase (TYR) inhibitors are in great demand in the food, cosmetic and medical industrials due to their important roles. Therefore, the discovery of high-quality TYR inhibitors is always pursued. Natural products as one of the most important sources of bioactive compounds discovery have been increasingly used for TYR inhibitors screening. However, due to their complex compositions, it is still a great challenge to rapid screening and identification of biologically active components from them. In recent years, with the help of separation technologies and the affinity and intrinsic activity of target enzymes, two advanced approaches including affinity screening and inhibition profiling showed great promises for a successful screening of bioactive compounds from natural sources. This review summarises the recent progress of separation-based methods for TYR inhibitors screening, with an emphasis on the principle, application, advantage, and drawback of each method along with perspectives in the future development of these screening techniques and screened hit compounds.

Relationship of an adherence score with blood pressure control status among patients with hypertension and their determinants: Findings from a nationwide blood pressure screening program.

This study aimed to examine the relationship of adherence with blood pressure (BP) control and its associated factors in hypertensive patients. This cross-sectional nationwide BP screening study was conducted in Malaysia from May to October 2018. Participants with self-declared hypertension completed the Hill-Bone Compliance to High Blood Pressure Therapy Scale (Hill-Bone CHBPTS) which assesses three important domains of patient behavior to hypertension management namely medication taking, appointment keeping and reduced salt intake. Lower scores indicate better compliance while higher scores indicate otherwise. Participant's body mass index and seated BP were measured based on standard measurement protocol. Determinants of adherence to treatment were analyzed using multiple linear regression. Out of 5167 screened subjects, 1705 were known hypertensives. Of these, 927 (54.4%) answered the Hill-Bone CHBPTS and were entered into analysis. The mean age was 59.0 ± 13.2 years, 55.6% were female and 42.2% were Malays. The mean Hill-Bone CHBPTS score was 20.4 ± 4.4 (range 14-47), and 52.1% had good adherence. The mean systolic BP and diastolic BP were 136.4 ± 17.9 and 80.6 ± 11.6 mmHg, respectively. BP was controlled in 58.3% of those with good adherence compared to 50.2% in those with poor adherence (p = .014). Based on multiple linear regression analysis, female gender (ß = -0.72, 95% confidence interval [CI] -1.30, -0.15, p = .014), older age (ß = -0.05, 95% CI -0.07, -0.03, p < .001), and individuals with primary or lower educational level (ß = -0.91, 95% CI -1.59, -0.23, p = .009) had better adherence to BP management. Interventional programs targeted at the less adherent groups are needed in order to improve their adherence and BP control.

Reaction prediction via atomistic simulation: from quantum mechanics to machine learning.

It is an ultimate goal in chemistry to predict reaction without recourse to experiment. Reaction prediction is not just the reaction rate determination of known reactions but, more broadly, the reaction exploration to identify new reaction routes. This review briefly overviews the theory on chemical reaction and the current methods for computing/estimating reaction rate and exploring reaction space. We particularly focus on the atomistic simulation methods for reaction exploration, which are benefited significantly by recently emerged machine learning potentials. We elaborate the stochastic surface walking global pathway sampling based on the global neural network (SSW-NN) potential, developed in our group since 2013, which can explore complex reactions systems unbiasedly and automatedly. Two examples, molecular reaction and heterogeneous catalytic reactions, are presented to illustrate the current status for reaction prediction using SSW-NN.

Large-Scale Atomic Simulation via Machine Learning Potentials Constructed by Global Potential Energy Surface Exploration.

Atomic simulations based on quantum mechanics (QM) calculations have entered into the tool box of chemists over the past few decades, facilitating an understanding of a wide range of chemistry problems, from structure characterization to reactivity determination. Due to the poor scaling and high computational cost intrinsic to QM calculations, one has to either sacrifice accuracy or time when performing large-scale atomic simulations. The battle to find a better compromise between accuracy and speed has been central to the development of new theoretical methods.The recent advances of machine-learning (ML)-based large-scale atomic simulations has shown great promise to the benefit of many branches of chemistry. Instead of solving the Schrödinger equation directly, ML-based simulations rely on a large data set of accurate potential energy surfaces (PESs) and complex numerical models to predict the total energy. These simulations feature both a high speed and a high accuracy for computing large systems. Due to the lack of a physical foundation in numerical models, ML models are often frustrated in their predictivity and robustness, which are key to applications. Focusing on these concerns, here we overview the recent advances in ML methodologies for atomic simulations on three key aspects. Namely, the generation of a representative data set, the extensity of ML models, and the continuity of data representation. While global optimization methods are the natural choice for building a representative data set, the stochastic surface walking method is shown to provide the desired PES sampling for both minima and transition regions on the PES. The current ML models generally utilize local geometrical descriptors as an input and consider the total energy as the sum of atomic energies. There are many flavors of data descriptors and ML models, but the applications for material and reaction predictions are still limited, not least because of the difficulty to train the associated vast global data sets. We show that our recently designed power-type structure descriptors together with a feed-forward neural network (NN) model are compatible with highly complex global PES data, which has led to a large family of global NN (G-NN) potentials.Two recent applications of G-NN potentials in material and reaction simulations are selected to illustrate how ML-based atomic simulations can help the discovery of new materials and reactions.

May Measurement Month 2018: an analysis of blood pressure screening results from Malaysia.

Hypertension continues to be the top global killer, contributing to over 10 million deaths annually. As prevalence and unawareness of hypertension remain high in Malaysia, this study was aimed to screen more individuals to identify those with undiagnosed hypertension. Respondents aged ≥18 years were recruited through opportunistic sampling at various screening sites including health clinics, hospitals, student health centres, universities, community halls, shopping malls, as well as through other health screening campaigns. Each respondent completed a questionnaire on socio-demographic, environmental, and lifestyle data. Anthropometric measurements as well as three blood pressure (BP) measurements were obtained from all participants. Hypertension was defined as a systolic BP ≥140 mmHg and/or diastolic BP ≥90 mmHg or taking antihypertensive medication. The total number of participants was 4866. The mean age of the participants was 39.8 (17.6) years with 61.1% female participants. Of the 4866 participants, 1405 (28.9%) had hypertension. The proportion of those aware of their hypertension status was 76.3% (1073/1405). The proportion of those with hypertension on medication was 71% (998/1405). Of those receiving antihypertensive treatment, 62.4% (623/998) had controlled BP. The proportion of hypertension in this study was 28.9%. The awareness rate of 76.3% compares favourably to a previously reported national level of 43.2%. Hence, BP screening programmes may be effective at increasing awareness and should be conducted annually.

[Application of conditional inference forest in time-to-event data analysis].

OBJECTIVE: To explore the application and advantages of conditional inference forest in survival analysis. METHODS: We used simulated experiment and actual data to compare the predictive performance of 4 models, including Coxproportional hazards model, accelerated failure time model, random survival forest model and conditional inference forest model based on their Brier scores. RESULTS: Simulation experiment suggested that both of the two forest models had more accurate and robust predictive performance than the other two regression models. Conditional inference forest model was superior to the other models in analyzing time-to-event data with polytomous covariates, collinearity or interaction, especially for a large sample size and a high censoring rate. The results of actual data analysis demonstrated that conditional inference forest model had the best predictive performance among the 4 models. CONCLUSIONS: Compared with the commonly used survival analysis methods, conditional inference forest model performs better especially when the data contain polytomous covariates with collinearity and interaction.

Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019.

BACKGROUND: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity. METHODS: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively. FINDINGS: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed. INTERPRETATION: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions. FUNDING: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).

A Facile Fabrication of Biodegradable and Biocompatible Cross-Linked Gelatin as Screen Printing Substrates.

This study focuses on preparation and valuation of the biodegradable, native, and modified gelatin film as screen-printing substrates. Modified gelatin film was prepared by crosslinking with various crosslinking agents and the electrode array was designed by screen-printing. It was observed that the swelling ratio of C-2, crosslinked with glutaraldehyde and EDC/NHS (1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide) was found to be lower (3.98%) than that of C-1 (crosslinked with only glutaraldehyde) (8.77%) and C-0 (without crosslinking) (28.15%). The obtained results indicate that the swelling ratios of both C-1 and C-2 were found to be lower than that of C-0 (control one without crosslinking). The Young's modulus for C-1 and C-2 was found to be 8.55 ± 0.57 and 23.72 ± 2.04 kPa, respectively. Hence, it was conveyed that the mechanical strength of C-2 was found to be two times higher than that of C-l, suggesting that the mechanical strength was enhanced upon dual crosslinking in this study also. The adhesion study indicates that silver ink adhesion on the gelation surface is better than that of carbon ink. In addition, the electrical response of C-2 with a screen-printed electrode (SPE) was found to be the same as the commercial polycarbonate (PC) substrate. The result of MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay suggested that the silver SPE on C-2 was non-cytotoxic toward L929 fibroblast cells proliferation. The results indicated that C-2 gelatin is a promising material to act as a screen-printing substrate with excellent biodegradable and biocompatible properties.