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The rolling restraint system between two space rigid bodies is a typical non-holonomic system. The incomplete characteristics can be used to simplify the mechanical structure and improve the reliability of the system. Aimed at the problems that the state variables of the pure rolling constraint non-holonomic system are difficult to control, the existing control methods are limited to specific models, and there is a lack of online control research, a solution method suitable for the online motion planning of the general rolling constraint system is established based on the rolling constraint first-order motion model. First, the offline motion planning is achieved by using the collocation method to obtain the reference trajectory. Then, the sequential action control (SAC) algorithm is used in real-time control combined with the rolling optimization framework to realize the online motion planning of the rolling system. The algorithm is applied to the real-time motion planning of the ball-plane rolling model and the rolling model between two spheres. The simulation results show that the method has a practical application value in broadening the control of the spherical robot and the operation of the dexterous manipulator.

Dual-ion batteries (DIBs) have attracted immense interest as a new generation of energy storage device due to their low cost, environmental friendliness and high working voltage. However, developing DIBs using organic compounds as active electrode materials is in its infancy. Herein, we first report a bipolar and self-polymerized Cu phthalocyanine (CuTAPc) as an electrode material for sodium-based DIBs (SDIBs). Benefitting from the bipolar property, CuTAPc could serve as the cathode or anode material to construct metal sodium-based or metal sodium-free SDIB (cell 1 or 2) by coupling with sodium anode or graphite cathode, respectively. As a result, cell 1 displays a high discharge capacity of 195.7 mAh g−1 at 50 mA g−1 and a high reversible capacity of 57 mAh g−1 over 2500 cycles at 1 A g−1, and cell 2 shows a high energy density of 324 Wh kg−1 and a high power density of 7481 W kg−1. Subsequently, the proposed binding mechanism and the bipolar reactivity of CuTAPc have been revealed by the detailed reaction kinetic analysis and ex-situ techniques as well as the density functional theory (DFT) calculations. This work could open a pathway to develop the advanced SDIBs constructed by elemental abundant and environmentally friendly organic materials.

To study the alterations of sleep quality and circadian rhythm genes expressions upon elderly thyroid nodule patients, the risk factors associated with thyroid malignancies, and the potential relationship involved. The elderly people enrolled in our study were divided into three groups according to the thyroid histopathology: malignant nodule group, benign nodule group, and normal group, and the clinical data and sleep quality were collected. Among the patients of surgery, 56 fresh thyroid tissues were collected for real-time PCR, immunohistochemistry and western blotting analysis of CLOCK, BMAL1, CRYs and PERs. Poor sleep quality, sleep latency and daytime dysfunction were the independent risk factors of malignant nodule after adjusted by other impacts. The expression levels of CLOCK, BMAL1 and PER2 in thyroid malignant group were significantly higher than benign and normal groups, while CRY2 was decreased, p

An acidic mixture of sulfuric and fluosilicic acid (H2SO4+H2SiF6) was employed as lixiviant to enhance leaching of lithium from lepidolite. The H2SiF6 was obtained as a byproduct of anhydrous hydrofluoric acid production, aiming to provide HF molecules. It was found that the HF molecules were the main reaction component and played a key role in strengthening the dissolution of lepidolite. Different factors, including mass ratio of ore/H2SO4/H2SiF6, concentrations of H2SO4 and H2SiF6, leaching temperatures (40−80 °C) and time (15−75 min), were investigated. Moreover, an efficient tubular reactor was employed to improve this acid leaching system. Under the optimal conditions (ore/H2SO4/H2SiF6 mass ratio of 1:0.8:1.6, 80 wt.% H2SO4, 15 wt.% H2SiF6, 80 °C, 15 min), 97.9% of Li, 96.4% of K, 97.6% of Rb, 96.7% of Cs and 81.4% of Al (mass fraction) were leached. Additionally, a two-step thermal process was proposed to remove fluorine of leaching slurry. This acid treatment using an acidic mixture of H2SO4 and H2SiF6 in a continuous tubular reactor shows potential as an alternative process to extract lithium from lepidolite.

Cannabinoids (CBs) are psychoactive compounds, with reported anticancer, anti-inflammatory, and anti-neoplastic properties. The study was aimed at assessing the hepatoprotective effects of CB against ethanol (EtOH)-induced liver toxicity in rats. The animals were divided into seven groups: control (Group I) and Group II were treated with 50% ethanol (EtOH 5 mg/kg). Groups III, IV, and VI were treated with (EtOH + CB 10 mg/kg), (EtOH + CB 20 mg/kg), and (EtOH + CB 30 mg/kg), respectively. Groups V and VII consisted of animals treated with 20 and 30 mg/kg, of CB, respectively. Biochemical analysis revealed that Group IV (EtOH + CB 20 mg/kg) had reduced levels of ALT-alanine transferase, AST-aspartate aminotransferase, ALP-alanine peroxidase, MDA-malondialdehyde and increased levels of GSH-reduced glutathione. Histopathological analysis of liver and kidney tissues showed that EtOH + CB (20 and 30 mg/kg) treated animal groups exhibited normal tissue architecture similar to that of the control group. ELISA revealed that the inflammatory markers were reduced in the animal groups that were treated with EtOH + CB 20 mg/kg, in comparison to the animals treated only with EtOH. The mRNA expression levels of COX-2, CD-14, and MIP-2 showed a remarkable decrease in EtOH + CB treated animal groups to control groups. Western blot analysis revealed that CB downregulated p38/JNK/ERK thereby exhibiting its hepatoprotective property by inhibiting mitogen-activated protein kinase pathways. Thus, our findings suggest that CB is a potential candidate for the treatment of alcohol-induced hepatotoxicity.

Background: Blastocystis sp. is a widespread anaerobic eukaryotic protist found in both human and animal gastrointestinal tracts, which can causes diarrhea in individuals with reduced immunity and endangers health. In China, however, there have been fewer studies of Blastocystis sp. infections in alpacas. This study aim at investigate the influence of Blastocystis sp. in alpacas in china.Methods: 484 fresh faecal samples were gathered from individual alpacas in nine different locations across China. Total genomic DNA was extracted, and Blastocystis sp. was identified using nested PCR amplification based on the SSU-rDNA gene. The phylogenetic tree was construct by MEGA7, which included one outgroup and 47 reference sequences downloaded from Genbank along with the 13 representative sequences found in the current study.Results: Blastocystis sp. was detected in 27.5% (133/484) of the alpaca’s fecal samples. In this study, however, no Blastocystis-positive was found in younger alpaca’s fecal samples. The SSU-rDNA sequence analysis revealed seven Blastocystis sp. subtypes in alpacas. The dominant subtype was ST10, which was found in 40.6% (54/133), followed by ST14 (30.8%, 41/133), and the remaining subtypes ST24, ST21, ST30, ST25, ST23, ST26, were detected in 11.3% (15/133), 7.5% (10/133), 3.8% (5/133), 3.0% (4/133), 2.3% (3/133) and 1.5% (2/133), respectively. The phylogenetic analysis clearly showed that the sequences of the eight subtypes (ST10, ST14, ST21, ST23, ST24, ST25, ST26, and ST30) clustered with the reference subtype sequences. Conclusion: This study revealed the geographic distribution and genetic diversity of Blastocystis from alpaca in China. Furthermore, ST21, ST23 to ST26 and ST30 were firstly reported in Chinese alpacas. It provides the fundamental molecular data for the study of Blastocystis sp. in Chinese animals.

Water and fertilizer supply can affect the processes of assimilate production (source) and assimilate accumulation (sink), thereby causing differences in potato yield. However, little is known about the coupling effects of irrigation amount and potassium rate on potato tuber yield and its potential source-sink relationships. The objective of this study was to quantify how water and potassium supplies affected the source-sink relationships of drip-fertigated potato after tuber emergence. A two-year field experiment was conducted during the potato growing seasons of 2019 and 2020, with three irrigation levels (W1: 60% ETc, W2: 80% ETc and W3: 100% ETc, where ETc is the crop water requirements) and four potassium rates (K0: 0 kg ha-1, K1: 135 kg ha-1, K2: 270 kg ha-1 and K3: 405 kg ha-1). The results showed that compared with K0, the treatments viz., K1, K2 and K3 increased average tuber yield by 1.3%, 17.3% and 15.5% in 2019 and 10.7%, 24.0% and 19.3% in 2020, respectively. However, compared with W3, the treatments viz., W1 and W2 reduced the average tuber yield by 8.0% and 12.9% in 2019 and 8.9% and 14.7% in 2020, respectively. The beta sigmoid growth function well fitted the relationship of source capacity and sink capacity. The source capacity and source activity increased with the increase of potassium rate under W2 and W3 in 2019 and under W3 in 2020, while the sink capacity and sink activity first increased and then declined with the increasing potassium rate. Increasing water and potassium supply generally increased the vegetative growth and tuber growth time. The tuber growth rate first increased and then decreased with the increase of potassium rate, while it increased with the increasing irrigation amount. The sink-source ratio decreased with the increase of potassium rate, but there was no significant difference between K1 and K2, and the sink-source ratio under K3 was significantly lower than that in the other potassium treatments. It was concluded that potato was in source-sink balance under K1 and K2, but not under K3. The quantitative approach produced parameters that characterized the differences of source and sink capacity in response to various water and potassium supplies. Sufficient irrigation (W3) with moderate potassium application (K2) increased potato yield mainly by maintaining its source-sink balance.

HIV incidence in sub-Saharan Africa declined substantially between 2000 and 2015. In this analysis, we consider the relative associations of nine structural and individual determinants with this decline. A linear mixed effects model of logged HIV incidence rates versus determinants was used. The data were from mathematical modelling as part of the 2019 Global Burden of Disease Study in 43 sub-Saharan African countries. We used forwards selection to determine a single final model of HIV incidence rate. The association of economic variables and HIV knowledge with incidence was found to be driven by education, while ART coverage had the largest impact on other determinants’ coefficients. In the final model, education years per capita contributed the most to explaining variation in HIV incidence rates; a 1-year increase in mean education years was associated with a 0.39 (− 0.56; − 0.2, t = − 4.48 p

The orthogonal basis functions (OBFs) method is a viable approach for magnetic target signal detection under the Gaussian white noise. However, its performance would degrade overtly under the Gaussian color noise with the power spectral density of $1/f^{\alpha }$ , which is the common environmental magnetic noise. In this letter, based on the linear constrained minimum variance criterion and the generalized likelihood ratio test, respectively, an alternative detection scheme is proposed through the optimization of the basis functions by considering both the signal and noise information. Experiment results using both the simulated data and the measured data show that the present approach can significantly improve the detection performance when compared to the original OBFs method.

Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.National Key Research and Development Program.

Differential single-beam saturated-absorption spectroscopy (DSSAS) is proposed to stabilize lasing frequency and suppress Doppler-broadened background and common-mode optical noise. The spectral first-derivative demodulated signal of metastable He4 atoms is used as an error signal to stabilize a fiber laser around 1083 nm. Experimental results show that, compared with existing non-DSSAS frequency stabilization, DSSAS stabilization produces better stability and lower fluctuations, especially for frequency-noise-corrupted lasers. In DSSAS stabilization, for data acquired over 7000 s, the root mean square frequency fluctuation of the fiber laser is 16.4 kHz, and the frequency stability described by the modified Allan deviation is 4.1 × 10

High crop water productivity (WPc) and fertilizer use efficiency are the key to ensuring the sustainable development of agriculture in water-deficient areas, such as the northwest China. In order to determine the irrigation amount and potassium rate for optimizing potato yield, plant potassium accumulation and WPc of drip-irrigated potato, a two-year field experiment was conducted on the Loess Plateau of northwest China, with three irrigation levels (W1: 60% ETc, W2: 80% ETc and W3: 100% ETc, where ETc is the crop evapotranspiration) and four potassium levels (K0: kg ha−1, K1: 135 kg ha−1, K2: 270 kg ha−1 and K3: 405 kg ha−1). The results showed that leaf area index, chlorophyll content, aboveground dry matter, tuber yield, starch, vitamin C content and WPc generally increased with the increase of irrigation amount, while they first increased and then decreased with the increasing potassium rate. The trends of reducing sugar and potassium use efficiency were contrary to the above trends. The residue of available potassium in the soil increased with the increase of potassium rate, but decreased with the increase of irrigation amount. Irrigation amount and potassium rate had interaction effects on chlorophyll content, dry matter, tuber yield, reducing sugar, plant potassium accumulation and potassium use efficiency. To ensure high-yield, high-quality, water-saving and fertilizer-saving potato production, a water input (irrigation plus effective rainfall) range of 498–520 mm combined with a potassium rate range of 201–393 kg ha−1 was recommended. These results can provide a theoretical basis for the rational application of irrigation water and potassium fertilizer to improve tuber yield, quality and soil environment of drip-irrigated potato in northwest China.

Superhydrophobicity has only ever been achieved by a combination of chemical hydrophobicity and surface topography due to our inability to attain complete non-wetting on the smooth surface of any known material. Here, we report extreme non-wetting of condensation-induced droplets with contact angles approaching 180° on a smooth surface using suspended monolayers of graphene experimentally. Such extreme non-wetting droplets are reported exclusively on suspended monolayer graphene open to the water vapour saturated environment on both sides. Simultaneous observations of droplets condensing on monolayer and multilayer supported and suspended graphene demonstrates that this extreme non-wetting behaviour is unique to suspended monolayer graphene. These results anticipate that interactions between liquid molecules across a suspended monolayer isolated from a bulk substrate may induce extreme non-wetting beyond that possible on smooth hydrophobic or atomically flat supported monolayer surfaces.

Urea electrooxidation with favorable thermodynamic potential is highly anticipated but suffering from sluggish kinetics. Deciphering the activity origin and achieving rational structure design are pivotal for developing highly efficient electrocatalyst for urea oxidation reaction (UOR). Herein, nitrogen penetrated nickel nanoparticles confined in carbon nanotubes (Ni-NCNT) is successfully achieved to drive UOR. Active origin of Ni-NCNT is decoded to be the in-situ generated Ni

The present study was conducted to investigate the effects of supranutritional selenium nanoparticles (SeNPs) on immune and antioxidant capacity in rats. Forty male Sprague-Dawley (SD) rats were randomly divided into four groups and given intragastric administration of SeNPs at doses of 0, 0.2, 0.4, and 0.8 mg Se/kg BW, respectively, for 2 weeks. Serum immune parameters, serum and organic tissues (liver, heart, kidney) antioxidant indices, and liver mRNA expression of glutathione peroxidase 1 (GPx1) and glutathione peroxidase 4 (GPx4) were examined. The results showed that supranutritional doses of 0.4 and 0.8 mg Se/kg BW SeNPs promoted the immune responses in serum. SeNPs administration improved antioxidant capacity in the liver and kidney, and the best improvement on antioxidant capacity was found in the kidney. Furthermore, intragastric administration of SeNPs upregulated mRNA expression of GPx1 and GPx4 in the liver. The results obtained indicated that SeNPs administration at supranutritional levels had beneficial effects on immune and antioxidant capacity and supplemental SeNPs at dose of 0.4 mg Se/kg BW exhibited the best response in SD rats.

Botanical garden greenhouses typically use solar radiation as an important heat source and meanwhile provide light for plants to survive. However, in the summertime, when the solar radiation is too strong, overheating will occur in the greenhouse and natural ventilation assisted with shading is used to cool it down. The modulation strategy of shading is very important not only to indoor temperature but also to the growth of plants. In order to determine the control strategy of the shading area in the design and installation stage, a CFD model of an exhibition greenhouse in Shanghai is established. During summer conditions, under the worst-case scenario of a windless day, the minimum shading area needed under different outdoor comprehensive temperatures is studied, and the correlation curve is fitted to guide the control of the shading to maintain appropriate thermal conditions. The decrease in indoor temperature under different shading areas is also explored when the outdoor comprehensive temperature is 34 °C. The annual carbon emission reduction of the greenhouse is about 500 t CO2, by adopting shading and natural ventilation. This study provides a reference value for shading control and energy saving and emission reduction of a botanical garden greenhouse.

Summary Background Vision loss is an important public health issue in China, but a detailed understanding of national and regional trends in its prevalence and causes, which could inform health policy, has not been available. This study aimed to assess the prevalence, causes, and regional distribution of vision impairment and blindness in China in 1990 and 2019. Methods Data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were used to estimate the prevalence of moderate and severe vision impairment and blindness in China and compare with other Group of 20 (G20) countries. We used GBD methodology to systematically analyse all available demographic and epidemiological data at the provincial level in China. We compared the age-standardised prevalences across provinces, and the changes in proportion of vision loss attributable to various eye diseases in 1990 and 2019. We used two different counterfactual scenarios with respect to population structure and age-specific prevalence to assess the contribution of population growth and ageing to trends in vision loss. Findings In 2019, the age-standardised prevalence was 2·57% (uncertainty interval [UI] 2·28–2·86) for moderate vision impairment, 0·25% (0·22–0·29) for severe vision impairment, and 0·48% (0·43–0·54) for blindness in China, which were all below the global average, but the prevalence of moderate and severe vision impairment had increased more rapidly than in other G20 countries from 1990 to 2019. The prevalence of vision loss increased with age, and the main causes of vision loss varied across age groups. The leading causes of vision impairment in China were uncorrected refractive error, cataract, and macular degeneration in both 1990 and 2019 in the overall population. From 1990 to 2019, the number of people with moderate vision impairment increased by 133·67% (from 19·65 to 45·92 million), those with severe vision impairment increased by 147·14% (from 1·89 to 4·67 million), and those with blindness increased by 64·35% (from 5·29 to 8·69 million); in each case, 20·16% of the increase could be explained by population growth. The contributions to these changes by population ageing were 87·22% for moderate vision impairment, 116·06% for severe vision impairment, and 99·22% for blindness, and the contributions by age-specific prevalence were 26·29% for moderate vision impairment, 10·91% for severe vision impairment, and −55·04% for blindness. The prevalence and specific causes of vision loss differed across provinces. Interpretation Although a comprehensive national policy to prevent blindness is in place, public awareness of visual health needs improving, and reducing the prevalence of moderate and severe vision impairment should be prioritised in future work. Funding China National Key Research and Development Programme and Beijing Municipal Special Funds for Medical Research on Public Welfare Development and Reform.

This study was aimed to explore magnetic resonance imaging (MRI) based on deep learning belief network model in evaluating serum bile acid profile and adverse perinatal outcomes of intrahepatic cholestasis of pregnancy (ICP) patients. Fifty ICP pregnant women diagnosed in hospital were selected as the experimental group, 50 healthy pregnant women as the blank group, and 50 patients with cholelithiasis as the gallstone group. Deep learning belief network (DLBN) was built by stacking multiple restricted Boltzmann machines, which was compared with the recognition rate of convolutional neural network (CNN) and support vector machine (SVM), to determine the error rate of different recognition methods on the test set. It was found that the error rate of deep learning belief network (7.68%) was substantially lower than that of CNN (21.34%) and SVM (22.41%) ( P < 0.05 ). The levels of glycoursodeoxycholic acid (GUDCA), glycochenodeoxycholic acid (GCDCA), and glycocholic acid (GCA) in the experimental group were dramatically superior to those in the blank group ( P < 0.05 ). Both the experimental group and the blank group had notable clustering of serum bile acid profile, and the experimental group and the gallstone group could be better distinguished. In addition, the incidence of amniotic fluid contamination, asphyxia, and premature perinatal infants in the experimental group was dramatically superior to that in the blank group ( P < 0.05 ). The deep learning confidence model had a low error rate, which can effectively extract the features of liver MRI images. In summary, the serum characteristic bile acid profiles of ICP were glycoursodeoxycholic acid, glycochenodeoxycholic acid, and glycocholic acid, which had a positive effect on clinical diagnosis. The toxic effects of high concentrations of serum bile acids were the main cause of adverse perinatal outcomes and sudden death.

Injury-induced fibroblast-to-myofibroblast differentiation is a key event of renal fibrosis. Yes-associated protein (YAP), a transcriptional coactivator, plays an important role in fibroblast activation and Smad transcriptional activity to promote transforming growth factor-β (TGF-β)-induced differentiation from fibroblasts to myofibrolasts. Macrophage stimulating 1/2 (MST1/2), a negative regulator of YAP, also increases in fibroblasts by TGF-β stimulation. Here, we examined whether MST1/2, as a negative regulator, attenuated YAP and TGF-β/Smad signaling in fibroblasts to reduce fibrosis. MST1/2 and YAP expression levels increased in platelet-derived growth factor receptor-α (PDGFRα)

Ovarian cancer (OC) is known to be the most malignant gynecologic cancers.

Although statins are the cornerstone of lipid management, hardly any of the existing studies on statin treatment of dyslipidemia in nephrotic syndrome (NS) addressed patient-centered outcomes of cardiovascular events.To evaluate whether statin treatment impacts the outcomes of cardiovascular events in patients with NS.A single-center, retrospective, nested case-control study analyzed data from the First Affiliated Hospital of Army Medical University.Patients diagnosed with NS from January 1, 1999, to November 30, 2014, were selected and followed up for 5 years.A total of 2706 patients with NS were enrolled in this study cohort. Among these, 115 patients diagnosed with cardiovascular disease (CVD) at the end of the observational period and 235 CVD-free controls enrolled by 1:2 matching with gender, age, and index time were included in the study. Propensity score matching was used to match (1:1) the baseline characteristics of the cases and controls. The chi-square test was performed based on whether the patient used a statin as an exposure factor, and binary logistic regression analysis of the association between cardiovascular events and statin therapy duration was conducted. Subgroup analyses for relevant variables were also performed. The chi-square test showed that statin therapy was significantly associated with a reduction in CVD risk in patients with NS (p = 0.002). Furthermore, the risk of cardiovascular events in patients with NS decreased as the length of statin treatment increased (OR = 0.82 [95% CI 0.73-0.89], p 0.001).For NS patients with dyslipidemia, statin therapy may be used to decrease CVD risk, and extended treatment was associated with more significant risk reduction.

In recent years, sensing technology based on nanopores has become one of the trustworthy options for characterization and even identification of a single biomolecule. In nanopore based DNA sequencing technology, the DNA strand in the electrolyte solution passes through the nanopore under an applied bias electric field. Commonly, the ionic current signals carrying the sequence information are difficult to detect effectively due to the fast translocation speed of the DNA strand, so that slowing down the translocation speed is expected to make the signals easier to distinguish and improve the sequencing accuracy. Modifying the nanopore structure is one of the effective methods. Through all-atom molecular dynamics simulations, we designed an asymmetric double-layer graphene nanopore structure to regulate the translocation speed of a single carbon chain. The structure consists of two nanopores with different sizes located on two layers. The simulation results indicate that the asymmetric nanopore structure will affect the chain's translocation speed and the ionic current value. When the single carbon chain passes from the smaller pore to the larger pore, the translocation time is significantly prolonged, which is about three times as long as the chain passing from the larger pore to the smaller pore. These results provide a new idea for designing more accurate and effective single-molecule solid-state nanopore sensors.

Restenosis is a severe complication after percutaneous transluminal coronary angioplasty which limits the long-term efficacy of the intervention. In this study, we investigated the efficiency of exosomes derived from AT2R-overexpressing bone mesenchymal stem cells on the prevention of restenosis after carotid artery injury. Our data showed that AT2R-EXO promoted the proliferation and migration of vascular endothelial cells and maintained the ratio of eNOS/iNOS. On the contrary, AT2R-EXO inhibited the proliferation and migration of vascular smooth muscle cells. In vivo study proved that AT2R-Exo were more effectively accumulated in the injured carotid artery than EXO and Vehicle-EXO controls. AT2R-EXO treatment could improve blood flow of the injured carotid artery site more effectively. Further analysis revealed that AT2REXO prevents restenosis after carotid artery injury by attenuating the injury-induced neointimal hyperplasia. Our study provides a novel and more efficient exosome for the treatment of restenosis diseases after intervention.

In Northwest China, the sediment concentration of the Yellow River is high. A project to investigate the operation of a pumping station shows that the flow patterns in the forebay and inlet tank are disordered, and there is sediment deposition that endangers the normal operation and safety of the pumping station. To solve this problem, the three-dimensional two-phase water-sediment flow in the forebay of the pumping station is modeled by using fluid simulation software, and diagrams of the sediment volume fraction content and vector distribution in the flow layers of different sections are obtained. Combined with the multiphase flow theory of mixtures and the realizable turbulent kinetic energy equation, the location and formation mechanism of each vortex, as well as the area and degree of sediment deposition in the forebay, are analyzed. The actual engineering and numerical simulation results are compared to verify the accuracy of the simulation. The results show that the main reason for sediment deposition is the high sediment concentration of the Yellow River, but the flow pattern disorder is affected by a specific design defect of the forebay, which makes the sediment deposition worse. The results of this study provide specific guidance and methods for the construction and transformation of the forebay of the pump station in the future; construction to weaken the return area to a certain extent can reduce the degree of sedimentation.

Structural manipulation at the nanoscale breaks the intrinsic correlations among different energy carrier transport properties, achieving high thermoelectric performance. However, the coupled multifunctional (phonon and electron) transport in the design of nanomaterials makes the optimization of thermoelectric properties challenging. Machine learning brings convenience to the design of nanostructures with large degree of freedom. Herein, we conducted comprehensive thermoelectric optimization of isotopic armchair graphene nanoribbons (AGNRs) with antidots and interfaces by combining Green's function approach with machine learning algorithms. The optimal AGNR with ZT of 0.894 by manipulating antidots was obtained at the interfaces of the aperiodic isotope superlattices, which is 5.69 times larger than that of the pristine structure. The proposed optimal structure via machine learning provides physical insights that the carbon-13 atoms tend to form a continuous interface barrier perpendicular to the carrier transport direction to suppress the propagation of phonons through isotope AGNRs. The antidot effect is more effective than isotope substitution in improving the thermoelectric properties of AGNRs. The proposed approach coupling energy carrier transport property analysis with machine learning algorithms offers highly efficient guidance on enhancing the thermoelectric properties of low-dimensional nanomaterials, as well as to explore and gain non-intuitive physical insights.

Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021.All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification.Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5·94 million worldwide, we estimate that 18·2 million (95% uncertainty interval 17·1-19·6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120·3 deaths (113·1-129·3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4·07 million [3·71-4·36]), the USA (1·13 million [1·08-1·18]), Russia (1·07 million [1·06-1·08]), Mexico (798 000 [741 000-867 000]), Brazil (792 000 [730 000-847 000]), Indonesia (736 000 [594 000-955 000]), and Pakistan (664 000 [498 000-847 000]). Among these countries, the excess mortality rate was highest in Russia (374·6 deaths [369·7-378·4] per 100 000) and Mexico (325·1 [301·6-353·3] per 100 000), and was similar in Brazil (186·9 [172·2-199·8] per 100 000) and the USA (179·3 [170·7-187·5] per 100 000).The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic.BillMelinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.