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Ethylene plays an important role in plant development and stress resistance. The rate-limiting enzyme in ethylene biosynthesis is 1-aminocyclopropane-1-carboxylic acid synthase (ACS). C. quinoa (Chenopodium quinoa) is an important food crop known for its strong tolerance to abiotic stresses. However, knowledge regarding the ACS gene family in C. quinoa remains restricted. In this study, we successfully identified 12 ACS genes (CqACSs) from the C. quinoa genome. Through thorough analysis of their sequences and phylogenetic relationships, it was verified that 8 out of these 12 CqACS isozymes exhibited substantial resemblance to ACS isozymes possessing ACS activity. Furthermore, these eight isozymes could be categorized into three distinct groups. The four remaining CqACS genes grouped under category IV displayed notable similarities with AtACS10 and AtACS12, known as amido transferases lacking ACS activity. The CqACS proteins bore resemblance to the AtACS proteins and had the characteristic structural features typically observed in plant ACS enzymes. Twelve CqACS genes were distributed across 8 out of the 18 chromosomes of C. quinoa. The CqACS genes were expanded from segment duplication. Many cis-regulatory elements related with various abiotic stresses, phytohormones, and light were found. The expression patterns of ACS genes varied across different tissues of C. quinoa. Furthermore, the analysis of gene expression patterns under abiotic stress showed that CqACS genes can be responsive to various stresses, implying their potential functions in adapting to various abiotic stresses. The findings from this research serve as a foundation for delving deeper into the functional roles of CqACS genes.

In recent years, the application of artificial intelligence-based methods to engineering problems has received consistent praise for their high predictive accuracy. This paper utilizes a BP neural network to predict the strength of steel–concrete composite beam shear connectors with high-strength friction-grip bolts (HSFGBs). These connectors are widely used in bridge and building construction due to their superior strength and stiffness compared to traditional beams. A validated finite element model was used to predict the strength of HSFGB shear connectors. A reliable database was created by analyzing 208 models with different characteristics for machine learning modeling. Previous studies have identified issues with result variation and overestimation or underestimation of shear connection strength. Among the machine learning methods evaluated, the backpropagation neural network model performed the best. It achieved a goodness of fit of over 93% in both the training and testing sets, with a low coefficient of variation of 6.50%. Concrete strength, bolt diameter, and bolt tensile strength were found to be important variables influencing the strength of shear connectors. Other variables showed a proportional or inverse relationship with compressive strength, except for concrete strength and bolt pretension. This study presents an accurate machine learning approach for predicting the strength of HSFGB shear connectors in steel–concrete composite beams. The study offers valuable insights into the effects of various variables on the performance of shear connection strength, providing support for structural design and analysis.

Biodiversity monitoring is an important means by which to evaluate management effectiveness and develop sound conservation plans. In this study, 52 cameras were installed in the study area of Tianzhushan to assess wildlife diversity and elevational patterns from 2018 to 2019. In total, 9 541 independent photos were collected within 26 565 camera-days. We analysed the relative abundance index (RAI), activity patterns and seasonal activity rhythms of the five most abundant species at 200-m elevational intervals throughout the study area (elevation range 1 400–2 000 m a.s.l.). Based on RAI results, the activity patterns of the five most abundant species (i.e. Sus scrofa, Naemorhedus griseus, Muntiacus reevesi, Arctonyx collaris and Capricornis milneedwardsii) were analysed. Amongst the detected wild mammals, Sus scrofa had the highest RAI value of 9.91, while the occurrence of Tamiops swinhoei had the lowest RAI at 0.004. In addition, there were significant differences in species activity during the daytime and night-time. RAI of the ungulate community peaked at the 1 600–1 800 m a.s.l. elevational range, thus showing a mid-elevational peak pattern. Differences in vertical distribution patterns were detected for the five most abundant species. Mainland serows and wild boars preferred mid-elevation habitats (1 600–1 800 m a.s.l.), long-tailed gorals preferred mid- and high altitudes (1 600–2 000 m a.s.l.) elevation habitats and Chinese muntjacs and hog badgers preferred low elevation habitats (1 400–1 600 m a.s.l.). Taken together, this is the first study to reveal the five dominant species activity patterns in Tianzhushan, which is of importance for wildlife conservation.

The insulation performance of ethylene propylene diene monomers (EPDMs) subjected to multi-stresses in the field is always obscure. To understand the effects of temperature and pressure on the performance of the EPDMs used as insulators for power cables, in this work, focuses were on the dielectric losses of EPDMs under the temperature range of 30– $120^{\circ }\text{C}$ and pressure range of 2–8 bar. The polarization and depolarization currents and the dielectric loss factor of EPDMs under the above conditions have been first measured. The relationship between the depolarization current and dielectric loss factor has been studied based on the correlation of the depolarization charge and the dielectric loss factor at low-frequency. The experimental results showed that the conduction currents and the dielectric loss factor increase with the increase in temperature, but the effect of pressure on the dielectric properties of EPDM is more complicated. There is a strong correlation between the depolarization charge and low-frequency dielectric loss factor, both of which can reflect the change law of the EPDMs’ performance. Moreover, the asymmetry coefficient of the dielectric loss factor at low-frequency can be a supplement with regard to describing the deterioration degree of EPDM insulation. The evaluation chart of the insulation performance of the EPDMs has been advanced according to the asymmetry coefficient and the total dielectric loss calculated by the polarization and depolarization currents.

ObjectiveTo compare the treatment effect of five electrical stimulation methods commonly used in the treatment of stroke patients with lower limb dysfunction.MethodsWe implemented a systematic search of 3915 studies published up to January 2023 from eight databases and two clinical trial registries. First, two independent reviewers critically evaluated trial eligibility according to the inclusion and exclusion criteria. Next, they selected and extracted data. Then, they assessed the risk of bias. Pairwise meta-analysis and Bayesian network meta-analysis were conducted to estimate the effectiveness and ranking of the five electrical stimulation methods.ResultsA total of 33 trials with a final total of 2246 subjects were included in the analysis. By combining the comprehensive Rehabilitation Treatment (RT), the treatment effects of using five electrical stimulation methods were surperior to those of using RT only. In the meantime, RT+transcranial Direct Current Stimulation(tDCS) and RT+Functional Electrical Stimulation(FES) could be the optimal electric stimulation schemes for restoring lower limb motor function(SMD 8.35, 95%CI [3.05, 13.34]/ SMD 5.64, 95%CI [3.68, 7.56]), improving balance (SMD 9.80, 95%CI [0.67, 20.93]/ SMD 6.54, 95%CI [3.85, 10.95]) and activities of daily living(SMD 18.95, 95%CI [0.401, 36.9]/ SMD 15.47, 95%CI [7.89, 22.75]), and the treatment effects would be even better using RT+FES+tDCS combination.ConclusiontDCS and FES superior to other electrical stimulation methods based on RT in the treatment of lower limb dysfunction after stroke.

Hypomyelination with brainstem and spinal cord involvement and leg spasticity (HBSL), caused by aspartyl-tRNA synthetase (DARS1) gene mutations, is extremely rare, with only a few cases reported worldwide; thus, reports on HBSL treatment are few. In this review, we summarized the clinical manifestations, imaging features, treatment methods, and gene mutations responsible for HBSL based on relevant studies and cases.

Ischemic stroke (IS) has been associated with an impairment in glymphatic function. Xuefu Zhuyu Decoction (XFZYD) is widely used in the prevention and treatment of ischemic stroke. We hypothesized that Xuefu Zhuyu decoction pretreatment could attenuate early neurological deficits after ischemic stroke by enhancing the function of the glymphatic system. To prove our hypothesis, we carried out temporary middle cerebral artery occlusion and reperfusion surgery on C57BL/6 mice and then measured neurological score, infarct size and performed hematoxylin-eosin staining to assess stroke outcomes after 24 h of reperfusion. Subsequently, we injected fluorescent tracers in to the cisterna magna and evaluated tracer distribution in coronal brain sections. The polarization of aquaporin-4 (AQP4), colocalization of aquaporin-4, α-dystroglycan, β-dystroglycan and agrin were determined by immunofluorescence. Our research showed that pretreatment with Xuefu Zhuyu decoction significantly alleviated neurological scores, neurological deficits and pathological abnormalities in a mouse model of ischemic stroke. Importantly, Xuefu Zhuyu decoction pretreatment enhanced cerebrospinal fluid influx, protected aquaporin-4 depolarization and promoted the colocalization of aquaporin-4 with its anchoring proteins in the brain. Our findings highlight novel mechanisms underlying the neuroprotective effect of Xuefu Zhuyu decoction pretreatment on ischemic stroke-induced brain damage through the glymphatic system. Xuefu Zhuyu decoction pretreatment may offer a promising approach to slow the onset and progression of ischemic stroke.

Introduction Perfusion imaging according to the DEFUSE 3 or DAWN criteria has been applied to select patients with large vascular occlusive stroke undergo endovascular therapy (EVT) in the extended time window. Emerging studies have shown that collateral blood flow-based criteria may be as effective as DEFUSE 3 and DAWN criteria for the evaluation of EVT eligibility beyond 6 hours. We will conduct a meta-analysis to compare collateral status-based criteria with DEFUSE 3 or DAWN criteria.Methods and analysis We will conduct a search for the studies comparing collateral blood flow-based imaging with CT perfusion using the DEFUSE 3 or DAWN criteria in selecting patients with acute ischaemic stroke undergo EVT in the Web of Science, PubMed, EMBASE and the Cochrane Library databases between November 2017 and November 2021. We will also search the sources of grey literature, the reference lists of included studies and the newly published studies during the review period. Two investigators will independently screen the eligible studies and extract data. The study quality will be assessed by using the Newcastle-Ottawa Scale or the Cochrane risk bias tool. Stata V.17 will be used to conduct data analysis.Ethics and dissemination Patient informed consent and ethics approval are not necessary as this study uses only published studies. The finding of this meta-analysis will be propagated through committee conferences or peer-reviewed journals.PROSPERO registration number CRD42021281928.

AbstractThe Lower Cretaceous Tengger Formation located in the Baiyinchagan Sag of the Erlian Basin comprises mainly deeply buried tight sandstone. The identification of high-quality reservoirs in these thickly stacked and heterogeneous units requires a comprehensive understanding of the diagenetic environmental history of the rocks. This paper reports an integrated study involving thin-section petrography, scanning electron microscopy, X-ray diffraction, fluid-inclusion analysis, and vitrinite reflectance analysis of Tengger Formation sandstones with the aim of characterizing the diagenetic conditions of the reservoir rocks and providing guidance for future petroleum exploration. Observed mineral assemblages, the distribution of authigenic minerals, and the distribution and nature of pores suggest the presence of two types of diagenetic environment, acidic and alkaline, which have varied over time and vertically through the rock column. Acidic conditions are indicated by quartz overgrowths and dissolution of both feldspar and carbonate cement. In contrast, alkaline conditions are indicated by the precipitation of carbonate cement, feldspar overgrowths, quartz dissolution, and occurrences of authigenic illite and chlorite. Changes in pore fluid chemistry controlled the evolution of the diagenetic environment. The early diagenetic environment from 110 Ma to 107 Ma was syndepositional and thus controlled by the chemistry of water in depositional centers, which is interpreted to have been weakly alkaline. Significant burial that occurred at 107 Ma induced pulses of hydrothermal fluids and petroleum into the reservoir rocks, which caused a shift to an acidic diagenetic environment. From 103 Ma to 70 Ma, subsequent episodes of uplift and burial caused periodic alternation between acidic and alkaline diagenetic environments. Three distinct episodes of oil and gas charging interpreted from petrography and the homogenization temperatures of fluid inclusions played a critical role in the enhancement of porosity through time. From 70 Ma to the present, acidic diagenesis gradually weakened because of the consumption of organic acids during the process of interaction between rocks and fluids. This study demonstrates the importance of understanding the diagenetic history of reservoir rocks and provides the basis for improved reservoir characterization and optimized hydrocarbon exploration of the Tengger Formation.

Objective: To investigate how Hydroxysafflor yellow A (HSYA) effects acute liver injury (ALI) and what transcriptional regulatory mechanisms it may employ.Methods: Rats were randomly divided into five groups (n = 10): Control, Model, HSYA-L, HSYA-M, and HSYA-H. In the control and model groups, rats were intraperitoneally injected with equivalent normal saline, while in the HSYA groups, they were also injected with different amounts of HSYA (10, 20, and 40 mg/kg/day) once daily for eight consecutive days. One hour following the last injection, the control group was injected into the abdominal cavity with 0.1 ml/100 g of peanut oil, and the other four groups got the same amount of a peanut oil solution containing 50% CCl4. Liver indexes were detected in rats after dissection, and hematoxylin and eosin (HE) dyeing was utilized to determine HSYA’s impact on the liver of model rats. In addition, with RNA-Sequencing (RNA-Seq) technology and quantitative real-time PCR (qRT-PCR), differentially expressed genes (DEGs) were discovered and validated. Furthermore, we detected the contents of anti-superoxide anion (anti-O2−) and hydrogen peroxide (H2O2), and verified three inflammatory genes (Icam1, Bcl2a1, and Ptgs2) in the NF-kB pathway by qRT-PCR.Results: Relative to the control and HSYA groups, in the model group, we found 1111 DEGs that were up-/down-regulated, six of these genes were verified by qRT-PCR, including Tymp, Fabp7, Serpina3c, Gpnmb, Il1r1, and Creld2, indicated that these genes were obviously involved in the regulation of HSYA in ALI model. Membrane rafts, membrane microdomains, inflammatory response, regulation of cytokine production, monooxygenase activity, and iron ion binding were significantly enriched in GO analysis. KEGG analysis revealed that DEGs were primarily enriched for PPAR, retinol metabolism, NF-kB signaling pathways, etc. Last but not least, compared with the control group, the anti-O2− content was substantially decreased, the H2O2 content and inflammatory genes (Icam1, Bcl2a1, and Ptgs2) levels were considerably elevated in the model group. Compared with the model group, the anti-O2− content was substantially increased, the H2O2 content and inflammatory genes (Icam1, Bcl2a1, and Ptgs2) levels were substantially decreased in the HSYA group (p < 0.05).Conclusion: HSYA could improve liver function, inhibit oxidative stress and inflammation, and improve the degree of liver tissue damage. The RNA-Seq results further verified that HSYA has the typical characteristics of numerous targets and multiple pathway. Protecting the liver from damage by regulating the expression of Tymp, Fabp7, Serpina3c, Gpnmb, Il1r1, Creld2, and the PPAR, retinol metabolism, NF-kappa B signaling pathways.

Dazomet (3,5-dimethyl-1,3,5-thiadiazinane-2-thione) is widely used as a soil fumigant for controlling soil-borne diseases and pests in China and other agricultural countries. The active ingredient of dazomet is its degradation product, methyl isothiocyanate. Little is known about the environmental conditions that affect the degradation of dazomet in soil. In this study, we conducted laboratory incubation experiments to test the effects of several environmental factors, including soil texture, water content, temperature, pH, and soil amendments, such as chicken manure or urea fertilizer, on the decomposition of dazomet. Results showed that dazomet degradation in soil is an abiotic process strongly dependent on soil texture, water content, temperature, and pH. Decomposition rates differed greatly in various soils, depending mainly on soil physicochemical properties such as pH and organic matter content. The degradation rate increased by 15 to 24 times and by 16 to 37 times when soil temperature increased from 5 to 45°C, and water content increased from 10 to 30%, respectively. Dazomet degraded faster in alkaline versus acidic soil. Both chicken manure and urea fertilizer moderately slowed dazomet degradation. Dazomet was degraded in soil mainly by hydrolysis. The results of our study contribute to a better understanding of the environmental behavior of dazomet, potentially leading to its more efficient, safe, profitable, and effective use by farmers. [ABSTRACT FROM AUTHOR]

This paper focuses on the compressive strength of Glass fiber reinforced polymer (GFRP)-confined reinforced concrete columns. Data from 114 sets of GFRP-confined reinforced concrete columns were collected to evaluate the researchers’ and proposed model. A data-driven machine learning model was used to model the compressive strength of the GFRP-confined reinforced concrete columns and investigate the importance and sensitivity of the parameters affecting the compressive strength. The results show that the researchers’ model facilitates the study of the compressive strength of confined columns but suffers from a large coefficient of variation and too high or conservative estimation of compressive strength. The back propagation (BP) neural network has the best accuracy and robustness in predicting the compressive strength of the confined columns, with the coefficient of variation of only 14.22%, and the goodness of fit for both the training and testing sets above 0.9. The parameters that have an enormous influence on compressive strength are the concrete strength and FRP thickness, and all the parameters, except the fracture strain of FRP, are positively or inversely related to the compressive strength.

Abstract Background Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment. Conclusions The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

BackgroundThe pathogenic mechanisms underlying the autonomic nervous system (ANS) dysfunction in patients with chronic migraine (CM) remain unclear. This study investigated the pathogenesis of ANS dysfunction in this population.MethodsA total of 60 patients diagnosed with CM and 60 healthy subjects were recruited to participate in this study. The pupil diameter, pupil contraction velocity, latency, amplitude, and the maximum gradient recovery time were examined before, at 2 min and at 5 min after the cold pressor test, which was combined with the pupillary light reflex method. A brain 3D T1-weighted structural imaging scan, resting-state functional magnetic resonance imaging scan, and diffusion tensor imaging (DTI) scan were also acquired.ResultsPatients with CM exhibited a longer recovery time to the maximum gradient at 2 min and at 5 min after cold pressing compared with the control group (P < 0.01 and P < 0.05, respectively). There was no significant difference in the pupil diameter, pupillary contraction velocity, latency, amplitude, blood pressure, or heart rate between the two groups (all P > 0.05). In the CM group, the regional homogeneity (ReHo) values of the left amygdala and left lateral hypothalamic area were significantly higher than those of other brain areas (P < 0.001, Alphasim corrected). The DTI scan of the whole brain area showed a lack of significant difference in DTI indices, including FA, MD, AD, and RD values between the two groups (P > 0.05, Alphasim corrected).ConclusionThe dysfunction of the left amygdala and left lateral hypothalamic area may be related to ANS dysfunction in patients with CM.

Objective: Hypomyelination with brain stem and spinal cord involvement and leg spasticity (HBSL) is a rare form of leukodystrophy presenting with varying clinical and imaging features. We report a case of HBSL to investigate the clinical and radiological characteristics of HBSL resulting from cytoplasmic aspartyl-tRNA synthetase gene (DARS) mutations.Subjects: We report a patient of HBSL with compound heterozygous mutations in DARS1. To study the potential genetic variations of the patient, targeted next-generation sequencing, whole-exome sequencing, and Sanger sequencing were used. We reviewed the clinical and radiological features of the patient. The literature was thoroughly evaluated.Results: The patient suffered from developmental regression associated with lower limbs spasticity, developmental delay, and paralysis of the lower limbs since childhood. Decreased T1 and increased T2 signals were observed on the bilateral basal, centrum ovale, frontal lobe, parietal lobe, and ganglia in cervical cord magnetic resonance imaging (MRI). The patient had two compound heterozygous mutations (NM_001349:c.1363T > C and NM_001349:c.821C > G) in the DARS1 gene.Conclusion: Two mutations in DARS1 were found to be associated with HBSL, one of them being reported for the first time. These findings can be valuable for diagnosing and providing genetic counseling to HBSL patients in the future.

Biochar (BC) is increasingly applied in agriculture; however, due to its adsorption and degradation properties, biochar may also affect the efficacy of fumigant in amended soil. Our research is intended to study the effects of two types of biochars (BC-1 and BC-2) on the efficacy and emission of methyl isothiocyanate (MITC) in biochar amendment soil. Both types of biochars can significantly reduce MITC emission losses, but, at the same time, decrease the concentration of MITC in the soil. The efficacy of MITC for controlling soil-borne pests (Meloidogyne spp., Fusarium spp. Phytophthora spp., Abutilon theophrasti and Digitaria sanguinalis) was reduced when the biochar (BC-1 and BC-2) was applied at a rate of higher than 1% and 0.5% (on a weight basis) (on a weight basis), respectively. However, increased doses of dazomet (DZ) were able to offset decreases in the efficacy of MITC in soils amended with biochars. Biochars with strong adsorption capacity (such as BC-1) substantially reduced MITC degradation rate by 6.2 times, and increased by 4.1 times following amendment with biochar with high degradability (e.g., BC-2), compared to soil without biochar amendment. This is due to the adsorption and degradation of biochar that reduces MITC emission losses and pest control. [ABSTRACT FROM AUTHOR]

For the diversification and individuality of customers' requirements, the multi-specification and small batch production is becoming the primary production model. More new technologies are adopted to enhance the intelligence and flexibility in traditional manufacturing environment. However, incompatibility between hardware and software architectures from different vendors, as well as high integration costs, hinder the application of such new technology. A flexible production line prototype is presented with the integration of 3D printer, industrial robot and machine vision. Firstly, a low-cost and open-source 3D printer was fabricated based on the fused deposition modeling technique. Meanwhile, a grasper was designed to automatically remove the printed part from the positioning platform. Secondly, an industrial robot picked the printed part and placed it into the storing box under the guidance of a machine vision camera. The whole system control depended on a programmable logic controller. Finally, an experiment was conducted to verify that this intelligent solution could enable highly flexible work cells and innovative manufacturing processes. [ABSTRACT FROM AUTHOR]

Abstract Multidrug resistance (MDR) based on ATP-dependent efflux transporters (p-glycoprotein (p-gp)) remains a major obstacle in successful chemotherapy treatment. Herein, we have investigated the potential of PD-L1 mAb-conjugated nanoliposome to serve as a targeted delivery platform for the co-delivery of paclitaxel (PTX) and p-gp specific transport inhibitor (TQD, tariquidar) in drug-resistant gastric cancers. Two drugs, PTX and TQD, were co-loaded in a single vehicle in a precise ratio to enhance the prospect of combination chemotherapeutic effect. Cellular uptake study indicated that PD-PTLP had higher internalization efficiency in PD-L1 receptor overexpressing SGC7901/ADR cells than non-targeted PTLP. Highest synergy was observed at a weight fraction of 1/0.5 (PTX/TQD) and the combination of PTX and TQD resulted in obvious synergistic effect compared to that of individual drugs alone. Our in vitro results showed that TQD was effective in reversing the multidrug resistance in SGC7901/ADR cells. The IC50 value of PD-PTLP was 0.76 μg/ml compared to 6.58 μg/ml and 7.64 μg/ml for PTX and TQD, respectively. PD-TPLP triggered significantly higher levels of reactive oxygen species (ROS) and cell apoptosis compared to that of free PTX or TQD. Furthermore, the in vivo antitumor study showed that the combination chemotherapy of PD-PTLP displayed a significant inhibition of tumor burden of drug-resistant xenograft tumors with significantly higher terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL)-positive cells. Furthermore, free PTX resulted in significant increase in the levels of AST and ALT while PD-PTLP insignificantly different compared to that of control indicating the safety index. Overall, we believe that combination of anticancer drug with a p-gp inhibitor could provide a potential direction toward the treatment of drug-resistant gastric tumors.

This paper studies the application of machine learning in the analysis and diagnosis of electromyography data. Firstly, 2,352 electromyography examination reports have been recorded from Sichuan Provincial Hospital of Traditional Chinese Medicine for ten months. The data cleaning has been conducted based on the specific-designed inclusion criteria. Next, two data sets have been established, containing 575 facial motor nerve conduction study reports and 233 auditory brainstem response reports, respectively. And then, four machine learning algorithms including random forest, linear regression, support vector machine and logistic regression have been employed to the data sets. The performance comparisons of accuracy and recall rate among different algorithms indicate that the random forest algorithm has the optimal performance over the other two in both data sets. Moreover, the comparisons have been carried out in the cases with and without deviation standardization for each algorithm, and the results demonstrate that the deviation standardization has a certain effect on the accuracy improvement. Additionally, it is found that the random forest algorithm can present the ranking of the features in order of importance. Consequently, the random forest is proven to be an optimal algorithm for computer-aided diagnosis systems. Furthermore, it is worth mentioning that the feature ranking in order of importance can facilitate clinical diagnosis and has a certain clinical potential in diagnosis and diagnostic assessment.

The deformation characteristics and instability patterns of rotational landslides are complicated. Such landslides are large and occur continuously, seriously threatening people’s lives. We used interferometry synthetic aperture radar (InSAR), digital elevation models of difference (DODs), numerical simulations, and other techniques for analyzing the topographic changes, surface deformation and movement process before, during and after a landslide. Based on the high-resolution terrain data before and after the landslide, the topographic changes were analyzed, and the active zone of the landslide was identified. The areas of the topographic changes were mainly located on the main scarp, toe and secondary landslides. The topographic changes were influenced by rainfall and rill erosion. The geomorphologically-guided InSAR interpretation method was applied to explore the displacement pattern. The deformation area in the middle of the landslide coincided with the secondary landslides. A time-series InSAR analysis revealed the dynamic evolution of the deformation before and after the landslide. Based on its evolution, the simulated landslide process included the main landslide and three secondary landslides. Based on the displacement of the longitudinal ground surface profiles, the displacement characteristics and kinematic behavior were summarized and compared with those of a single rotational landslide and multiple rotational landslides. The single rotational landslide had obvious secondary and progressive characteristics, developing into multiple rotational landslides triggered by conditions such as rainfall.

Aurora-A kinase is frequently over-expressed in tumours. Here, the authors show that it modulates the activity of lactate dehydrogenase B, resulting in enhanced glycolysis, bio-synthesis and tumour growth.

Introduction COVID-19 has spread with high morbidity and mortality worldwide. Many inactivated SARS-CoV-2 vaccines are being tested at various clinical trial stages for the control and prevention of COVID-19. We aim to comprehensively and objectively evaluate the safety and immunogenicity of inactivated SARS-CoV-2 vaccines in healthy individuals through a systematic review and meta-analysis of randomised controlled trials (RCTs).Methods and analysis We will search electronic databases of PubMed, the Cochrane Library, Web of Science and EMBASE for RCTs from inception to 31 December 2021. We will also search conference abstracts, reference lists, and grey literature of all available records. Two reviewers will independently screen and extract information from the literature. Bias and the quality of included studies will be evaluated with the risk-bias assessment tool provided by the Cochrane Collaboration. Statistical analysis will be performed using Cochrane’s Review Manager (RevMan), V.5.3.Ethics and dissemination Ethics approval and patient informed consent are not required because we will be including published literature only. The findings of this research will be disseminated in a peer-reviewed journal and likely through other scientific events such as conferences, seminars and symposia.PROSPERO registration number CRD42021266285.

Rainfall-induced shallow landslides are widespread throughout the world, and vegetation is frequently utilized to control them. However, in recent years, shallow landslides have continued to frequently occur during the rainy season on the vegetated slopes of the Loess Plateau in China. To better probe this phenomenon, we considered vegetation cover in the sensitivity analysis of landslide hazards and used the transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model to quantitatively describe the impacts of different types of vegetation cover on slope stability. Based on the rainfall information for landslide events, the spatiotemporal distributions of the pore water pressure and the factor of safety of the vegetated slopes were inverted under the driving changes in the soil properties under different vegetation types, and the average prediction accuracy reached 79.88%. It was found that there was a strong positive correlation between the cumulative precipitation and the proportion of landslide-prone areas in woodland covered by tall trees, grassland covered by shrubs and grasses, and cultivated land. The highest landslide susceptibility, which has the greatest potential to hasten the occurrence of rainfall-induced landslides, is found in woodland with tall trees. Therefore, this paper proposes the promoting relationship between vegetation and landslide erosion, which provides a new scientific perspective on watershed management to prevent shallow landslide disasters and manage and develop watershed vegetation.

Residential areas comprise more than 30% of the urban built-up zones of China. High-density residential areas and high proportions of impervious surfaces make residential areas prone to severe flooding. Low-impact development practices are broadly applied to solve these problems, and as a main component of low-impact development practices, green spaces have also drawn attention because of their capacity to control rainwater. However, the effects of green space spatial characteristics on hydrological processes have been overlooked. In this study, to determine how to optimize the layout of the green space system to improve the capacity of stormwater management, data from Tianjin were analyzed using a FRAGSTATs model and a SWMM model to identify how the layout of green spaces affects the process of rainwater generation and concentration in terms of three typical residential area layouts. The results show that (1) when it is possible to increase the amount of green space, maintaining a high patch density is the best way to achieve runoff treatment; (2) when newly built green space is limited, increasing connectivity between existing green spaces is the best way to control rainwater, especially in enclosed and axial modes; (3) when comparing the efficiency of the three modes, the axial mode presents the best performance in terms of promotion rate. These results will provide those developing urban residential areas with more economical, practical, and suitable layout strategies for green space systems in terms of planning, design, and optimization aimed at stormwater management.

Alzheimer's disease (AD) is an age-related irreversible neurodegenerative disorder characterized by extracellular β Amyloid(Aβ) deposition, intracellular neurofibrillary tangles and neuronal loss. The dysfunction of neurogenesis and increased degeneration of neurons contribute to the pathogenesis of AD. We now report that miR-211-5p, a small non-coding RNA, can impair neurite differentiation by directly targeting NUAK1, decrease neuronal viability and accelerate the progression of Aβ-induced pathologies. In this study, we observed that during embryonic development, the expression levels of miR-211-5p were down-regulated in the normal cerebral cortexes of mice. However, in APPswe/PS1ΔE9 double transgenic adult mice, it was up-regulated from 9 months of age compared to that of the age-matched wild type mice. Studies in primary cortical neuron cultures demonstrated that miR-211-5p can inhibit neurite growth and branching via NUAK1 repression and decrease mature neuron viability. The impairments were more obvious under the action of Aβ. Our data showed that miR-211-5p could inhibit cortical neuron differentiation and survival, which may contribute to the synaptic failure, neuronal loss and cognitive dysfunction in AD. [ABSTRACT FROM AUTHOR]

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. To date, among medications used to treat PD, only levodopa exhibits a limited disease-modifying effect on early-onset PD, but it cannot delay the progression of the disease. In 2018, for the first time, the World Health Organization included traditional Chinese medicine (TCM) in its influential global medical compendium. The use of TCM in the treatment of PD has a long history. At present, TCM can help treat and prevent PD. Iron metabolism is closely associated with PD. Ferroptosis, which is characterized by the accumulation of lipid peroxides, is a recently discovered form of iron-dependent cell death. The research literature indicates that ferroptosis in dopaminergic neurons is an important pathogenetic mechanism of PD. TCM may thus play unique roles in the treatment of PD and provide new ideas for the treatment of PD by regulating pathways associated with ferroptosis.

Aiming at the problem of not enough influencing factors were considered in traditional methods,a much more realistic stochastic model was built.In which error corrections were introduced into the geometry-based function model,an improved least squares variance component estimation (LS-VCE) algorithm with space-for-time was used to solve the model,two sets of real GPS data were collected to evaluate the performance of the model,and with which the carrier phase integer ambiguity was solved.The experimental results show that the proposed methods are superior to the traditional methods in terms of model accuracy,model solution complexity and integer ambiguity resolution.

Gas composition has a significant impact on the dispersion behavior and accumulation characteristics of blowout gas. However, few public studies has investigated the corresponding effect of gas composition. Therefore, this study firstly builds the FLACS-based numerical model about an offshore drilling platform. Then several scenarios by varying the composition of blowout gas are simulated while the scenario with the composition of “Deepwater Horizon” accident is regarded as the benchmark. Furthermore, the effects of the gas composition on the flammable cloud volume, the influenced area of flammable cloud, the influenced area of hydrogen sulfide and the critical time of the hydrogen sulfide spreading to the living area are analyzed. The results demonstrate that gas composition is a driving factor for dispersion characteristics of blowout gas. All the results can give support to reduce the risk of the similar accidents incurred by real blowouts. Keywords: Blowout accident, Gas composition, Offshore platform, Hydrocarbon, Hydrogen sulfide

This paper quantitatively examines the effects of slope height and slope gradient on landslide size distributions. We developed a loess slide inventory by using field survey data. Statistical analysis shows that most landslides are concentrated in areas with slope heights less than 60 m, and approximately 30% of the loess slides occurred on slopes with a gradient between 30° and 40°. However, high and steep slopes are rare in nature. We calculated the relative density of landslides, and the results showed that the relative density of landslides is greater on higher slopes with steeper slope gradients. Moreover, landslide size is correlated with slope height and slope gradient. The results demonstrate that landslide size increases as slope height increases and decreases as slope gradient increases. Furthermore, we determined the probability density of landslide area using kernel density estimation. The results showed that the landslide size distribution exhibits power law scaling above a certain size threshold, and the size threshold differs for different slope heights and slope gradients. The exponential scalings are influenced by slope height and slope gradient. Our results indicate that the exponential scaling decreases with increasing slope height and increases with increasing slope gradient. Large landslides are more frequent with a higher slope height and gentler slope gradient.

The spatial and temporal distributions of landslides can be used to assess the potential future impacts of landslides over large scales. However, quantitatively characterizing the spatial and temporal distributions of landslides and their causes remains a critical challenge. In this work, a typical landslide-prone region (the Qinba Mountains) is selected to identify this spatial and temporal trend. Information on 295 landslides spanning ten years from 2005 to 2014 was collected. The results revealed that landslide occurrences were clustered in time and space. Approximately 81% of the total landslides occurred from July to October. Moreover, a power law relationship between the cumulative frequency and number of landslides per day was discovered. Notably, the probability density of the time interval decreased as the time interval between landslide events increased, and this relationship was well described by a negative power-law correlation. Furthermore, the spatial and temporal distribution pattern of most landslides were influenced by rainfall events and earthquakes. There were several clustered centers in the study area, and the mean centers of the landslide distribution varied among years.

Metabolites have been reported as the main factor that influences the fruit flavor of watermelon. But the comprehensive study on the dynamics of metabolites during the development of watermelon fruit is not up-to-date. In this study, metabolome and transcriptome datasets of ‘Crimson’ watermelon fruit at four key developmental stages were generated. A total of 517 metabolites were detected by ultrahigh-performance liquid chromatography–electrospray ionization–tandem mass spectrometry and gas chromatography–solid-phase microextraction–mass spectrometry. Meanwhile, by K-means clustering analysis, the total differentially expressed genes were clustered in six classes. Integrating transcriptome and metabolome data revealed similar expression trends of sugars and genes involved in the glycolytic pathway, providing molecular insights into the formation of taste during fruit development. Furthermore, through coexpression analysis, we identified five differentially expressed ADH (alcohol dehydrogenase) genes (Cla97C01G013600, Cla97C05G089700, Cla97C01G001290, Cla97C05G095170, and Cla97C06G118330), which were found to be closely related to C9 alcohols/aldehydes, providing information for the formation of fruit aroma. Our findings establish a metabolic profile during watermelon fruit development and provide insights into flavor formation.

Background and Purpose: Prehospital delay is the major factor limiting intravenous thrombolysis and mechanical thrombectomy in acute ischemic stroke (AIS). This study aimed to: (1) identify factors related to prehospital delay and (2) determine the impact of recognition and behavior of family members on patient delay.Methods: A cross-sectional, multicenter study was conducted at six teaching hospitals in China between December 1, 2018 and November 30, 2019. Patients who experienced AIS within 7 days of onset were interviewed.Results: Of 1,782 consecutive patients (male, 57.97%; mean age, 66.3 ± 9.65 years) who had an AIS, 267 (14.98%) patients arrived within 4.5 h and 722 (40.52%) patients arrived within 6 h of stroke onset. Among patients who arrived within 4.5 h, 103 (38.6%) received thrombolysis. Age over 65 years (OR, 2.009; 95% CI, 1.014–3.982), prior stroke (OR, 3.478; 95% CI, 1.311–9.229), blurred vision (OR, 3.95; 95% CI, 1.71–9.123), and patients deciding to seek medical help (OR, 3.097; 95% CI, 1.417–6.769) were independently associated with late arrival. In contrast, sudden onset of symptoms (OR, 0.075; 95% CI, 0.028–0.196), the National Institutes of Health Stroke Scale 7–15 (OR, 0.093; 95% CI, 0.035–0.251), consciousness disturbance (OR, 0.258; 95% CI, 0.091–0.734), weakness (OR, 0.265; 95% CI, 0.09–0.784), arrival by ambulance (OR, 0.102; 95% CI, 0.049–0.211), decision time

Abstract The appraisal of tectonic‐geomorphic features is the basis for the development and management of land, the selection of road routes, and the site selection and construction process of hydropower projects. However, properly evaluating tectonic‐geomorphic features and revealing the relationships among geomorphic evolution, landslides, and tectonic activity remain major challenges in geography and geomorphology. We take the core area of the planned Diamer‐Bhasha Dam as a study area. On the strength of digital elevation models (DEMs), geomorphic indices are extracted to evaluate the tectonic activity and geomorphic evolution. Landslide cataloging by field investigation is used to reveal the relationships between geomorphic evolution, landslides, and tectonic activity. We found that the tectonic activity and geomorphic evolution of the sub‐basin where the Diamer‐Bhasha Dam is planned and the sub‐basin along the Indus are in the stable and old stage, respectively. In contrast, the tectonic‐geomorphic features in the marginal sub‐basins far from the Indus are still active. The correlations among lithology, AF, Vf, HI, SL, and landslide indicate that tectonic activity can influence geomorphic evolution and induce landslides, whereas changes in lithology do not. In addition, landslides can exacerbate geomorphic evolution.