Histamine H4 receptor and TRPV1 mediate itch induced by cadaverine, a metabolite of the microbiome.

Cadaverine is an endogenous metabolite produced by the gut microbiome with various activity in physiological and pathological conditions. However, whether cadaverine regulates pain or itch remains unclear. In this study, we first found that cadaverine may bind to histamine 4 receptor (H4R) with higher docking energy score using molecular docking simulations, suggesting cadaverine may act as an endogenous ligand for H4R. We subsequently found intradermal injection of cadaverine into the nape or cheek of mice induces a dose-dependent scratching response in mice, which was suppressed by a selective H4R antagonist JNJ-7777120, transient receptor potential vanilloid 1 (TRPV1) antagonist capsazepine and PLC inhibitor U73122, but not H1R antagonist or TRPA1 antagonist or TRPV4 antagonist. Consistently, cadaverine-induced itch was abolished in Trpv1-/- but not Trpa1-/- mice. Pharmacological analysis indicated that mast cells and opioid receptors were also involved in cadaverine-induced itch in mice. scRNA-Seq data analysis showed that H4R and TRPV1 are mainly co-expressed on NP2, NP3 and PEP1 DRG neurons. Calcium imaging analysis showed that cadaverine perfusion enhanced calcium influx in the dissociated dorsal root ganglion (DRG) neurons, which was suppressed by JNJ-7777120 and capsazepine, as well as in the DRG neurons from Trpv1-/- mice. Patch-clamp recordings found that cadaverine perfusion significantly increased the excitability of small diameter DRG neurons, and JNJ-7777120 abolished this effect, indicating involvement of H4R. Together, these results provide evidences that cadaverine is a novel endogenous pruritogens, which activates H4R/TRPV1 signaling pathways in the primary sensory neurons.

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.

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).

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.

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.

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.

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.

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.

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.

Glucose to 5-Hydroxymethylfurfural: Origin of Site-Selectivity Resolved by Machine Learning Based Reaction Sampling.

Glucose pyrolysis, a model system in biomass utilization, is renowned for its great complexity, deep in reaction network hierarchy and rich in reaction patterns. The selectivity in glucose pyrolysis, e.g., the high yield of 5-hydroxymethylfurfural (HMF), a value-added platform product, remains an intriguing puzzle even after 60 years of experimental study. Here we resolve the whole reaction network of glucose pyrolysis using a global-to-global technique for reaction pathway sampling. This is achieved by establishing the first organic chemistry reaction database via stochastic surface walking (SSW) global optimization, building the global neural network (G-NN) potential via machine learning and extensively exploring the reaction network of glucose pyrolysis. In total, 6407 elementary reactions, screened out from more than 150 000 reaction pairs in glucose pyrolysis, are collected in our reaction database. The established reaction network from SSW-NN, further validated by first-principles calculations, reveals that for glucose to HMF, the lowest energy reaction pathway involves fructose and 3-deoxyglucos-2-ene (3-DGE) as key intermediates and a site-selective reaction type, retro-Michael-addition, for three consecutive dehydration steps. The overall barrier is determined to be 1.91 eV, being at least 0.19 eV lower than all previously proposed mechanisms, which assumes direct ß-H elimination dehydration. The lowest pathways to the other two major products, furfural (FF) and hydroxyacetaldehyde (HAA), are also discovered with a similar barrier 1.95 eV, which exhibit a competing nature by sharing the same key intermediate, 3-ketohexose. Since chemical reactions occurring in fast glucose pyrolysis are generally present in biomass chemistry, containing essentially all reaction patterns of C-H-O elements, the methodology designed and the results presented would help to advance reaction design and mechanistic modeling in renewable fuels from biomass.

May Measurement Month 2017 blood pressure screening: findings from Malaysia-South-East Asia and Australasia.

Elevated blood pressure (BP) is a growing burden worldwide, leading to over 10 million deaths each year. However there are still many individuals, particularly in many countries in Asia, who have poor BP control. In Malaysia, less than two-fifths have achieved BP control. We participated in BP screening in Malaysia in conjunction with the May Measurement Month 2017 (MMM17), a global initiative by the International Society of Hypertension (ISH) aimed at screening more individuals for earlier detection of hypertension. A nationwide screening of adults aged ≥18 was carried out through health campaigns at clinics, hospitals, during family day events, and charity runs from 1 April 2017 to 31 May 2017 in 42 centres. We used the detailed protocol provided by ISH for data collection. A total of 4116 individuals were screened during MMM17. After multiple imputation, 32.4% (n = 1317/4059) had hypertension. Out of this, 63.9% (842/1317) of those with hypertension were on treatment. Of individuals receiving antihypertensive medication with an imputed BP, 59.5% (n = 496/834) of them had controlled BP. MMM17 was the largest organized BP screening campaign undertaken by health professionals in Malaysia. This study identified that 32.4% of screened individuals had hypertension and 59.5% individuals with treated hypertension had achieved BP control.

Enhancement of erythritol production by Trichosporonoides oedocephalis ATCC 16958 through regulating key enzyme activity and the NADPH/NADP ratio with metal ion supplementation.

Erythritol, a well-known natural sweetener, is mainly produced by microbial fermentation. Various metal ions (Al3+, Cu2+, Mn2+, and Ni2+) were added to the culture medium of Trichosporonoides oedocephalis ATCC 16958 at 30 mg/L in shake flask cultures. Compared with controls, Cu2+ increased the erythritol content by 86% and decreased the glycerol by-product by 31%. After 48 hr of shake flask culture, sodium dodecyl sulfate polyacrylamide gel electrophoresis showed that expression levels of erythrose reductase (ER) in the presence of 30 mg/L CuSO4 · 5H2O were higher than those obtained after treatment with other examined metal ions. Furthermore, after 108 hr of batch culture in a 5-L bioreactor, supplementation with 30 mg/L of CuSO4 · 5H2O increased the specific erythritol content by 27%. Further studies demonstrated that ER activity under 30 mg/L CuSO4 · 5H2O supplementation in a fermentor was overtly increased compared with the control after 60 hr, while glycerol-3-phosphate dehydrogenase activity was clearly reduced in most of the fermentation process. Furthermore, the NADPH/NADP ratio was slightly lower in T. oedocephalis cells treated with Cu2+ compared with control cells. These results provide further insights into Cu2+ effects on erythritol biosynthesis in T. oedocephalis and should improve the industrial production of erythritol by biological processes.

Association between serum 25-hydroxyvitamin D levels and carotid atherosclerosis in chronic kidney disease patients.

BACKGROUND: Epidemiological studies have shown an inverse relationship between vitamin D levels and cardiovascular diseases. However, this does not infer a causal relationship between the two. Chronic kidney disease (CKD) patients have a high prevalence of vitamin D deficiency and carotid atherosclerosis. Therefore, in this study we have aimed to determine the association between serum 25-hydroxyvitamin D levels and carotid atherosclerosis in the CKD population. METHODS: 100 CKD stage 3-4 patients were included in the study. Direct chemiluminesent immunoassay was used to determine the level of serum 25-hydroxyvitamin D. All subjects underwent a carotid ultrasound to measure common carotid artery intima-media thickness (CCA-IMT) and to assess the presence of carotid plaques or significant stenosis (≥50 %). Vitamin D deficiency was defined as serum 25-hydroxyvitamin D < 25 nmol/L. Abnormal CCA-IMT was defined as CCA-IMT ≥ 0.8 mm. Plaque was defined as a focal structure that encroaches into the arterial lumen of ≥ 0.5 mm or 50 % of the surrounding IMT value. Significant stenosis was defined as peak-systolic velocities ≥ 125 cm/s and end-diastolic velocities ≥ 40 cm/s. RESULTS: The vitamin D deficiency and non-deficiency groups did not differ significantly in terms of abnormal CCA-IMT (P = 0.443), carotid plaque (P = 0.349), and carotid stenosis (P = 0.554). No significant correlation between serum 25-hydroxyvitamin D levels and CCA-IMT (P = 0.693) was found. On a backward multiple linear regression model, serum 25-hydroxyvitamin D levels was not associated with CCA-IMT, abnormal CCA-IMT, or plaque presence. CONCLUSIONS: No important association between serum 25-hydroxyvitamin levels and carotid atherosclerosis was found in CKD patients.

Increased riboflavin production by knockout of 6-phosphofructokinase I and blocking the Entner-Doudoroff pathway in Escherichia coli.

OBJECTIVES: To construct an Escherichia coli strain capable of producing riboflavin with high titer and yield. RESULTS: A low copy number plasmid pLS01 containing a riboflavin operon under the control of a constitutive promoter was constructed and introduced into Escherichia coli MG1655. Subsequently, the pfkA, edd and ead genes were disrupted, and the resulting strain LS02T produced 667 mg riboflavin/l in MSY medium supplied with 10 g glucose/l in flask cultivation. In a fed-batch process, riboflavin production of the strain reached 10.4 g/l with a yield of 56.8 mg riboflavin/g glucose. CONCLUSION: To our knowledge, this is the first report of engineered E. coli strains that can produce more than 10 g riboflavin/l in fed-batch cultivation, indicating that E. coli has potential for riboflavin production.

Young Adult Patent Ductus Arteriosus Treated with Endovascular Stent Grafting.

Endovascular stent-grafting is an alternative treatment for adult patent ductus arteriosus (PDA), especially in elderly patients. Regarding young adults, endovascular therapy is a reasonable choice if the landing zone is sufficient. In this study, we report on a young adult with PDA successfully treated with endovascular stent-grafting.

Many-Body Function Corrected Neural Network with Atomic Attention (MBNN-att) for Molecular Property Prediction.

Recent years have seen a surge of machine learning (ML) in chemistry for predicting chemical properties, but a low-cost, general-purpose, and high-performance model, desirable to be accessible on central processing unit (CPU) devices, remains not available. For this purpose, here we introduce an atomic attention mechanism into many-body function corrected neural network (MBNN), namely, MBNN-att ML model, to predict both the extensive and intensive properties of molecules and materials. The MBNN-att uses explicit function descriptors as the inputs for the atom-based feed-forward neural network (NN). The output of the NN is designed to be a vector to implement the multihead self-attention mechanism. This vector is split into two parts: the atomic attention weight part and the many-body-function part. The final property is obtained by summing the products of each atomic attention weight and the corresponding many-body function. We show that MBNN-att performs well on all QM9 properties, i.e., errors on all properties, below chemical accuracy, and, in particular, achieves the top performance for the energy-related extensive properties. By systematically comparing with other explicit-function-type descriptor ML models and the graph representation ML models, we demonstrate that the many-body-function framework and atomic attention mechanism are key ingredients for the high performance and the good transferability of MBNN-att in molecular property prediction.

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.

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.

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.

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.