Individual Prediction of Electric Field Induced by Deep-brain Magnetic Stimulation with CNN-Transformer.

Deep-brain Magnetic Stimulation (DMS) can improve the symptoms caused by Alzheimer's disease by inducing rhythmic electric field in the deep brain, and the induced electric field is rhythm-dependent. However, calculating the induced electric field requires building a voxel model of the brain for the stimulated object, which usually takes several hours. In order to obtain the rhythm-dependent electric field induced by DMS in real time, we adopt a CNN-Transformer model to predict it. A data set with a sample size of 7350 is established for the training and testing of the model. 10-fold cross validation is used to determine the optimal hyperparameters for training CNN-Transformer. The combination of 5-layer CNN and 6-layer Transformer is verified as the optimal combination of CNN-Transformer model. The experimental results show that the CNN-Transformer model can complete the prediction in 0.731s (CPU) or 0.042s (GPU), and the overall performance metrics of prediction can reach: MAE=0.0269, RMSE=0.0420, MAPE=4.61% and R2=0.9627. The prediction performance of the CNN-Transformer model for the hippocampal electric field is better than that of the brain grey matter electric field, and the stimulation rhythm has less influence on the model performance than the coil configuration. Taking the same dataset to train and test the separate CNN model and Transformer model, it is found that CNN-Transformer has better prediction performance than the separate CNN model and Transformer model in the task of predicting electric field induced by DMS.

Characterization of Quantitative Trait Loci for Leaf Rust Resistance from CI 13227 in Three Winter Wheat Populations.

Leaf rust is a widespread foliar wheat disease causing substantial yield losses worldwide. Slow-rusting is "adult plant" resistance that significantly slows epidemic development and thereby reduces yield loss. Wheat accession CI 13227 was previously characterized as having slow-rusting resistance. To validate the quantitative trait loci (QTL) and develop diagnostic markers for slow rusting resistance in CI 13227, a new population of recombinant inbred lines (RILs) of CI 13227 × Everest was evaluated for latent period (LP), final severity (FS), area under disease progress curve (AUDPC), and infection type (IT) in greenhouses and genotyped using genotyping-by-sequencing (GBS). Four QTL were identified on chromosome arms 2BL, 2DS, 3BS, and 7BL, explaining 6.82 to 28.45% of the phenotypic variance for these traits. Seven kompetitive allele specific polymorphism (KASP) markers previously reported to be linked to the QTL in two other CI 13227 populations were validated. In addition, the previously reported QLr.hwwg-7AL was remapped to 2BL (renamed QLr.hwwg-2BL) after adding new markers in this study. Phenotypic data showed that the RILs harboring two or three of the QTL had a significantly longer LP. QLr.hwwg-2DS on 2DS showed a major effect on all rust resistance traits and was finely mapped to a 2.7 Mb interval by two newly developed flanking markers from exome capture. Three disease-resistance genes and two transporter genes were identified as the putative candidates for QLr.hwwg-2DS. The validated QTL can be used as slow rusting resistance resources and the markers developed in this study will be useful for marker-assisted selection.

Enhancing the adsorption-photocatalytic efficiency of BiOBr for Congo red degradation by tuning the surface charge and bandgap via an Y3+-I- co-doping strategy.

Metal-ion doping and halogen substitution have been largely applied to tune the bandgap of bismuth oxybromide (BiOBr) to upgrade its photodegradation capacity. In this work, the adsorption capacity and photocatalytic behavior of solvothermally synthesized BiOBr photocatalysts can be optimized via the synergistic effect of Y3+- and I--doping. After an adsorption reaction in the dark and exposure for another 80 min to visible light, pure BiOBr can remove 46.5% of Congo red (CR) from water with an initial CR concentration of 50 mg L-1. Meanwhile, Bi0.8Y0.20OBr0.97I0.03, the co-doped catalyst, displays total degradation rates exceeding 98% and 92% with CR dosages of 50 and 100 mg L-1, respectively, demonstrating a doubled degradation capacity. With the co-doping solution, the negative charges on the catalysts reduce, more oxygen vacancies are generated, the bandgap remarkably narrows, and the photoabsorption range broadens for derivation of photoinduced electron-hole pairs. The mechanism for optimized photodegradation behavior and dramatically increased adsorption capacity are discussed based on analyses of the structural evolution, surface properties including the chemical state and surface charge, electrochemical performance and the yield/type of photogenerated species. Density functional theory (DFT) simulations were conducted to investigate the structural state, density of states (DOS) and electrostatic potential.

Understanding health education needs of pregnant women in China during public health emergencies: a qualitative study amidst the COVID-19 pandemic.

Background: Public health emergencies impose unique challenges on pregnant women, affecting their physiological, psychological, and social wellbeing. This study, focusing on the context of the corona virus disease in 2019 (COVID-19) pandemic in China, aims to comprehensively explore the experiences of pregnant women amidst diverse public health crises. Herein, we investigate the health education needs of pregnant Chinese women in regard to public health emergencies to provide a scientific foundation for the development of targeted health education strategies. Objective: The study described in this article aims to explore the health education needs of pregnant Chinese women in the context of public health emergencies specifying the types of emergencies of pandemics and to provide a scientific basis for targeted health education interventions. Methods: Thirteen pregnant women were purposively selected, and the rationale for this sample size lies in the qualitative nature of the study, seeking in-depth insights rather than generalizability. Data collection involved semi-structured interviews, and the Colaizzi, which is a structured qualitative technique used to extract, interpret, and organize significant statements from participant descriptions into themes, providing a comprehensive understanding of their lived experiences. Results: The analysis yielded six prominent themes encompassing the following areas: I. Personal protection and vaccine safety; II. Knowledge of maternal health; III. Knowledge of fetal health; IV. Knowledge of childbirth; V. Knowledge of postpartum recovery; and VI. Knowledge sources of health education for pregnant women and their expectations of healthcare providers. Theme I was analyzed with two sub-themes (needs for personal protection knowledge, vaccine safety knowledge needs); Theme II was analyzed with three sub-themes (nutrition and diet, exercise and rest, sexual life); Theme III was analyzed with three sub-themes (medications and hazardous substances, pregnancy check-ups, and fetal movement monitoring); Theme IV was analyzed with three sub-themes (family accompaniment, analgesia in childbirth, and choice of mode of delivery); Theme V was analyzed with one sub-theme (knowledge of postnatal recovery); Theme VI was analyzed with one sub-theme (expectations of Healthcare providers). Sub-themes within each main theme were identified, offering a nuanced understanding of the multifaceted challenges faced by pregnant women during public health emergencies. The interrelation between sub-themes and main themes contributes to a holistic portrayal of their experiences. Conclusion: The study emphasizes the need for healthcare professionals to tailor health education for pregnant women during emergencies, highlighting the role of the Internet in improving information dissemination. It recommends actionable strategies for effective health communication, ensuring these women receive comprehensive support through digital platforms for better health outcomes during public health crises.

Mg-Sr-Ca containing bioactive glass nanoparticles hydrogel modified mineralized collagen scaffold for bone repair.

The aim of this study is to explore the therapeutic effects of Mg-Sr-Ca containing bioactive glass nanoparticles sodium alginate hydrogel modified mineralized collagen scaffold (Mg-Sr-Ca-BGNs-SA-MC) on the repair of osteoporotic bone defect. During the study, Mg-Sr-Ca containing bioactive glass nanoparticles (Mg-Sr-Ca-BGNs) were synthesized using the sol-gel method, and the Mg-Sr-Ca-BGNs-SA-MC scaffold was synthesized by a simple method. The Mg-Sr-Ca-BGNs and the Mg-Sr-Ca-BGNs-SA-MC scaffold were observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The elements of Mg, Sr, Ca and Si were effectively integrated into Mg-Sr-Ca-BGNs. SEM analysis revealed the presence of Mg-Sr-Ca-BGNs on the scaffold's surface. Furthermore, the cytotoxicity of the scaffolds were assessed using a live/dead assay. The result of the live/dead assay demonstrated that the scaffold materials were non-toxic to cell growth. More importantly, the in vivo study indicated that implanted scaffold promoted tissue regeneration and integration with newly formed bone. Overall, the Mg-Sr-Ca-BGNs-SA-MC scaffold is suitable for guided bone regeneration and beneficial to repair of osteoporotic bone defects.

Characterization of a new greenbug resistance gene Gb9 in a synthetic hexaploid wheat.

Greenbug [Schizaphis graminum (Rondani)] is a serious insect pest that not only damages cereal crops, but also transmits several destructive viruses. The emergence of new greenbug biotypes in the field makes it urgent to identify novel greenbug resistance genes in wheat. CWI 76364 (PI 703397), a synthetic hexaploid wheat (SHW) line, exhibits greenbug resistance. Evaluation of an F2:3 population from cross OK 14319 × CWI 76364 indicated that a dominant gene, designated Gb9, conditions greenbug resistance in CWI 76364. Selective genotyping of a subset of F2 plants with contrasting phenotypes by genotyping-by-sequencing identified 25 SNPs closely linked to Gb9 on chromosome arm 7DL. Ten of these SNPs were converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers for genotyping the entire F2 population. Genetic analysis delimited Gb9 to a 0.6-Mb interval flanked by KASP markers located at 599,835,668 bp (Stars-KASP872) and 600,471,081 bp (Stars-KASP881) on 7DL. Gb9 was 0.5 cM distal to Stars-KASP872 and 0.5 cM proximal to Stars-KASP881. Allelism tests indicated that Gb9 is a new greenbug resistance gene which confers resistance to greenbug biotypes C, E, H, I, and TX1. TX1 is one of the most widely virulent biotypes and has overcome most known wheat greenbug resistance genes. The introgression of Gb9 into locally adapted wheat cultivars is of economic importance, and the KASP markers developed in this study can be used to tag Gb9 in cultivar development.

Accelerated dissemination of antibiotic resistant genes via conjugative transfer driven by deficient denitrification in biochar-based biofiltration systems.

Biofiltration systems harbored and disseminated antibiotic resistance genes (ARGs), when confronting antibiotic-contained wastewater. Biochar, a widely used environmental remediation material, can mitigate antibiotic stress on adjoining microbes by lowering the availability of sorbed antibiotics, and enhance the attachment of denitrifiers. Herein, bench-scale biofiltration systems, packed with commercial biochars, were established to explore the pivotal drivers affecting ARG emergence. Results showed that biofiltration columns, achieving higher TN removal and denitrification capacity, showed a significant decrease in ARG accumulation (p < 0.05). The relative abundance of ARGs (0.014 ± 0.0008) in the attached biofilms decreased to 1/5-folds of that in the control group (0.065 ± 0.004). Functional analysis indicated ARGs' accumulation was less attributed to ARG activation or horizontal gene transfer (HGT) driven by sorbed antibiotics. Most denitrifiers, like Bradyrhizobium, Geothrix, etc., were found to be enriched and host ARGs. Nitrosative stress from deficient denitrification was demonstrated to be the dominant driver for affecting ARG accumulation and dissemination. Metagenomic and metaproteomic analysis revealed that nitrosative stress promoted the conjugative HGT of ARGs mainly via increasing the transmembrane permeability and enhancing the amino acid transport and metabolism, such as cysteine, methionine, and valine metabolism. Overall, this study highlighted the risks of deficient denitrification in promoting ARG transfer and transmission in biofiltration systems and natural ecosystems.

Ensemble-Based Virtual Screening Led to the Discovery of Novel Lead Molecules as Potential NMBAs.

Neuromuscular blocking agents (NMBAs) are routinely used during anesthesia to relax skeletal muscle. Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels; NMBAs can induce muscle paralysis by preventing the neurotransmitter acetylcholine (ACh) from binding to nAChRs situated on the postsynaptic membranes. Despite widespread efforts, it is still a great challenge to find new NMBAs since the introduction of cisatracurium in 1995. In this work, an effective ensemble-based virtual screening method, including molecular property filters, 3D pharmacophore model, and molecular docking, was applied to discover potential NMBAs from the ZINC15 database. The results showed that screened hit compounds had better docking scores than the reference compound d-tubocurarine. In order to further investigate the binding modes between the hit compounds and nAChRs at simulated physiological conditions, the molecular dynamics simulation was performed. Deep analysis of the simulation results revealed that ZINC257459695 can stably bind to nAChRs' active sites and interact with the key residue Asp165. The binding free energies were also calculated for the obtained hits using the MM/GBSA method. In silico ADMET calculations were performed to assess the pharmacokinetic properties of hit compounds in the human body. Overall, the identified ZINC257459695 may be a promising lead compound for developing new NMBAs as an adjunct to general anesthesia, necessitating further investigations.

Assessing greenhouse gas emissions from the printing and dyeing wastewater treatment and reuse system: Potential pathways towards carbon neutrality.

The urgency of achieving carbon neutrality needs a reduction in greenhouse gas (GHG) emissions from the textile industry. Printing and dyeing wastewater (PDWW) plays a crucial role in the textile industry. The incomplete assessment of GHG emissions from PDWW impedes the attainment of carbon neutrality. Here, we firstly introduced a more standardized and systematic life-cycle GHG emission accounting method for printing and dyeing wastewater treatment and reuse system (PDWTRS) and proposed possible low-carbon pathways to achieve carbon neutrality. Utilizing case-specific operational data over 12 months, the study revealed that the PDWTRS generated 3.49 kg CO2eq/m3 or 1.58 kg CO2eq/kg CODrem in 2022. This exceeded the GHG intensity of municipal wastewater treatment (ranged from 0.58 to 1.14 kg CO2eq/m3). The primary contributor to GHG emissions was energy consumption (33 %), with the energy mix (sensitivity = 0.38) and consumption (sensitivity = 0.33) exerting the most significant impact on GHG emission intensity respectively. Employing prospective life cycle assessment (LCA), our study explored the potential of the anaerobic membrane bioreactor (AnMBR) to reduce emissions by 0.54 kg CO2eq/m3 and the solar-driven photocatalytic membrane reactor (PMR) to decrease by 0.20 kg CO2eq/m3 by 2050. Our projections suggested that the PDWTRS could achieve net-zero emissions before 2040 through an adoption of progressive transition to low-carbon management, with a GHG emission intensity of -0.10 kg CO2eq/m3 by 2050. Importantly, the study underscored the escalating significance of developing sustainable technologies for reclaimed water production amid water scarcity and climate change. The study may serve as a reminder of the critical role of PDWW treatment in carbon reduction within the textile industry and provides a roadmap for potential pathways towards carbon neutrality for PDWTRS.

Adaptive prediction for effluent quality of wastewater treatment plant: Improvement with a dual-stage attention-based LSTM network.

The accurate effluent prediction plays a crucial role in providing early warning for abnormal effluent and achieving the adjustment of feedforward control parameters during wastewater treatment. This study applied a dual-staged attention mechanism based on long short-term memory network (DA-LSTM) to improve the accuracy of effluent quality prediction. The results showed that input attention (IA) and temporal attention (TA) significantly enhanced the prediction performance of LSTM. Specially, IA could adaptively adjust feature weights to enhance the robustness against input noise, with R2 increased by 13.18%. To promote its long-term memory ability, TA was used to increase the memory span from 96 h to 168 h. Compared to a single LSTM model, the DA-LSTM model showed an improvement in prediction accuracy by 5.10%, 2.11%, 14.47% for COD, TP, and TN. Additionally, DA-LSTM demonstrated excellent generalization performance in new scenarios, with the R2 values for COD, TP, and TN increasing by 22.67%, 20.06%, and 17.14% respectively, while the MAPE values decreased by 56.46%, 63.08%, and 42.79%. In conclusion, the DA-LSTM model demonstrated excellent prediction performance and generalization ability due to its advantages of feature-adaptive weighting and long-term memory focusing. This has forward-looking significance for achieving efficient early warning of abnormal operating conditions and timely management of control parameters.

The association of stress perception on anxiety, depression and sleep quality in parents of children with burns: The moderating effect of social support.

OBJECTIVE: Few studies have explored the mental health status of parents of children with burns and the moderating effect of social support on them. METHODS: A survey was performed with parents of 112 burn-injured children at a burn center in China. Their perceived stress, anxiety, depression, sleep quality, and social support were measured by the Chinese Perceived Stress Scale, Hospital Anxiety and Depression Scale, Pittsburgh Sleep Quality Index, and Perceived Social Support Scale. RESULTS: ➀ The prevalence of anxiety (46.43%), depression (52.67%) and poor sleep quality (43.75%) of parents indicated that they experienced emotional and sleep disorders;➁ The perceived stress was positively correlated with sleep quality, anxiety and depression（P＜0.01), and negatively correlated with perceived social support (p＜0.05); ➂ Social support had a significant moderating effect on their perceived stress and anxiety, depression, but not on their sleep quality. With high social support, parental perceived stress had a significant positive association on anxiety and depression, while with low perceived social support, parental perceived stress had no significant association on anxiety and depression. CONCLUSION: Parents of burned children had increased stress, obvious symptoms of anxiety and depression, and poor sleep quality. Social support had a significant buffering effect on them under low pressure, and high pressure will hinder the buffering effect of social support on stress. Therefore, the ideal services to improve mental health should be provided for them to face different levels of stress.

Does the Sagittal Radiographic Morphology of Subtalar Joint Affect the Alignment of Foot?

OBJECTIVES: The etiology of flatfoot and cavus foot is multicausal and controversial. So far, no literature reports the relationship between the sagittal morphology of subtalar joint and the alignment of foot. The purpose of this study was to explore whether the subtalar alignment would influence the configuration of foot. METHODS: From January 2017 to January 2020, we included 109 feet in the flatfoot group, 95 feet in the cavus group, and 104 feet in the control group in this retrospective comparative study. The Gissane angle and calcaneal posterior articular surface inclination angle represented the sagittal morphology of the subtalar joint. Meary's angle, calcaneal pitch angle, and talar pitch angle reflected the alignment of foot. They were measured in the weightbearing foot X-rays. The angles in different groups were compared via Mann-Whitney U test. We calculated the correlation between the sagittal alignment of subtalar joint and the alignment of foot using Spearman's correlation analysis. Interobserver and intraobserver reliability were calculated. RESULTS: The Gissane angle, calcaneal posterior articular surface inclination angle, Meary's angle, talar pitch angle, and calcaneal pitch angle were significantly different in the three groups. The Gissane angle had an excellent correlation with the Meary's angle (r = 0.850, p < 0.0001), and the talar pitch angle (r = -0.825, p < 0.0001), and a good correlation with the calcaneal pitch angle (r = 0.638, p < 0.0001). The calcaneal posterior articular surface inclination angle had an excellent correlation with the Meary's angle (r = -0.902, p < 0.001), and the talar pitch angle (r = 0.887, p < 0.0001), and a good correlation with the calcaneal pitch angle (r = -0.702, p < 0.0001). The interobserver and intraobserver reliability for all radiographic measurements was good to excellent. CONCLUSION: A subtalar joint with a larger Gissane angle and a more horizontal calcaneal posterior articular surface angle tended to have a higher foot arch and vice versa. The inspiration from this study was that the deformities of flatfoot and cavus foot may relate to the subtalar deformity.

Association between metformin treatment and coronary artery inflammation based on pericoronary adipose tissue attenuation in type 2 diabetes mellitus patients.

Cardiovascular disease (CVD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. The role of metformin in reducing cardiovascular events is well-established, but its effect on coronary artery inflammation in T2DM patients is still unclear. In this study, we evaluated 547 T2DM patients who underwent coronary computed tomography angiography (CCTA) at Wuhan Central Hospital. Using propensity score matching, we compared the attenuation of pericoronary adipose tissue (PCAT), an imaging marker of coronary artery inflammation, between patients treated with and without metformin. Multiple linear regression models were used to analyze the influence of metformin on PCAT attenuation. The results of the propensity-matched analysis showed that patients on metformin therapy had significantly lower PCAT attenuation, indicating reduced coronary inflammation. Specifically, the PCAT attenuation in the left anterior descending artery (LAD) and right coronary artery (RCA) was lower in the metformin group compared to the non-metformin group. Metformin use was independently associated with decreased LAD-PCAT attenuation in the multivariate regression analysis. The association of metformin with PCAT attenuation differed significantly in populations analyzed in subgroups of patients with obesity and chronic kidney disease. In conclusion, our study shows a preliminary signal that metformin therapy may be associated with decreased coronary artery inflammation in T2DM patients, as indicated by PCAT attenuation on CCTA. And this correlation may vary depending on the patient population. This initial finding suggests that PCAT attenuation could be potentially used as an imaging biomarker to monitor the anti-inflammatory effects of medication.

Coronary inflammation based on pericoronary adipose tissue attenuation in type 2 diabetic mellitus: effect of diabetes management.

BACKGROUND: Coronary inflammation plays crucial role in type 2 diabetes mellitus (T2DM) induced cardiovascular complications. Both glucose-lowering drug interventions (GLDIS) and glycemic control (GC) status potentially correlate coronary inflammation, as indicated by changes in pericoronary adipose tissue (PCAT) attenuation, and thus influence cardiovascular risk. This study evaluated the impact of GLDIS and GC status on PCAT attenuation in T2DM patients. METHODS: This retrospective study collected clinical data and coronary computed tomography angiography (CCTA) images of 1,342 patients, including 547 T2DM patients and 795 non-T2DM patients in two tertiary hospitals. T2DM patients were subgroup based on two criteria: (1) GC status: well: HbA1c < 7%, moderate: 7 ≤ HbA1c ≤ 9%, and poor: HbA1c > 9%; (2) GLDIS and non-GLDIS. PCAT attenuations of the left anterior descending artery (LAD-PCAT), left circumflex artery (LCX-PCAT), and right coronary artery (RCA-PCAT) were measured. Propensity matching (PSM) was used to cross compare PCAT attenuation of non-T2DM and all subgroups of T2DM patients. Linear regressions were conducted to evaluate the impact of GC status and GLDIS on PCAT attenuation in T2DM patients. RESULTS: Significant differences were observed in RCA-PCAT and LCX-PCAT between poor GC-T2DM and non-T2DM patients (LCX: - 68.75 ± 7.59 HU vs. - 71.93 ± 7.25 HU, p = 0.008; RCA: - 74.37 ± 8.44 HU vs. - 77.2 ± 7.42 HU, p = 0.026). Higher PCAT attenuation was observed in LAD-PCAT, LCX-PCAT, and RCA-PCAT in non-GLDIS T2DM patients compared with GLDIS T2DM patients (LAD: - 78.11 ± 8.01 HU vs. - 75.04 ± 8.26 HU, p = 0.022; LCX: - 71.10 ± 8.13 HU vs. - 68.31 ± 7.90 HU, p = 0.037; RCA: - 78.17 ± 8.64 HU vs. - 73.35 ± 9.32 HU, p = 0.001). In the linear regression, other than sex and duration of diabetes, both metformin and acarbose were found to be significantly associated with lower LAD-PCAT (metformin: ß coefficient = - 2.476, p=0.021; acarbose: ß coefficient = - 1.841, p = 0.031). CONCLUSION: Inadequate diabetes management, including poor GC and lack of GLDIS, may be associated with increased coronary artery inflammation in T2DM patients, as indicated by PCAT attenuation on CCTA, leading to increased cardiovascular risk. This finding could help healthcare providers identify T2DM patients with increased cardiovascular risk, develop improved cardiovascular management programs, and reduce subsequent cardiovascular related mortality.

A comparative analysis of the levels and drivers of regional coordinated development in the Yangtze River Economic Belt and Yellow River Basin, China.

Positioned in the era of the transformation of China's primary social contradictions, this study delves into the new connotations of regional coordinated development(RCD) from the perspective of "factors" coordination within the region and constructs an RCD evaluation system from five subsystems of regional economic coordination(REC), urban-rural coordination(URC), economic and social coordination(EASC), resource and environmental coordination(RAEC), and material and spiritual civilization coordination(MASCC). Then, the Entropy weight-TOPSIS model is used to evaluate the RCD levels of the 19 provinces located in the Yangtze River Economic Belt(YREB) and Yellow River Basin(YRB) from 2010 to 2019, and the two-way fixed-effects model is employed to illustrate the driving mechanisms of various influencing factors on the RCD in YRB and YREB. The results show that:(1)the RCD levels of YRB and YREB show a fluctuating upward trend during 2010 and 2019, however, both regions have low RCD levels, as seen by the mean RCD indices for YREB and YRB, which are only 0.433 and 0.309, respectively. (2) The RCD level of YREB is higher than that of YEB. In 2019, the "coordinated" provinces in YRB and YREB account for 37.50% and 81.82% of the total number of provinces in the basins, respectively, the "uncoordinated" and "low coordinated" provinces all located in YRB. (3) The RCD of YRB and YREB is significantly improved by REC, URC and RAEC, but not significantly positively by MASCC or EASC, and insufficient development of MASCC is the main contradiction limiting the increase in the RCD level of YRB, while the low level of EASC has become the main obstacle limiting the RCD of YREB. (4)Finally, based on the varying impact degrees and directions of different influencing factors on the RCD in YRB and YREB, the recommendations to promote RCD are proposed.

Assessing NH300094, a novel dopamine and serotonin receptor modulator with cognitive enhancement property for treating schizophrenia.

Background: Schizophrenia is a serious psychiatric disorder that significantly affects the quality of life of patients. The objective of this study is to discover a novel antipsychotic candidate with highly antagonistic activity against both serotonin and dopamine receptors, demonstrating robust efficacy in animal models of positive, negative, and cognitive symptoms of schizophrenia. Methods: In the present study, we examined the activity of antipsychotic drug (NH300094) on 5-HT2A, 5-HT2C, 5-HT1A, 5-HT1B, 5-HT7, H1, M1, Alpha1A, D2L, D2S, Alpha2A, D3 receptor functional assay in vitro. In addition, multiple animal models, including dizocilpine (MK-801) induced hyper-locomotion; APO induced climbing; Conditioned Avoidance Response (CAR); DOI-Induced Head Twitch; Forced swimming test; Scopolamine induced cognitive impairment model, were used to verify the antipsychotic activity of NH300094 in preclinical. Results: In vitro functional assays have indicated that NH300094 is a potent antagonist of 5-HT receptors and dopamine receptors, with higher relative antagonistic activity against 5-HT2A receptor (5-HT2A IC50 = 0.47 nM) than dopamine receptors (D2L IC50 = 1.04 nM; D2S IC50 = 11.71 nM; D3 IC50 = 31.55 nM). Preclinical in vivo pharmacological study results showed that NH300094 was effective in multiple models, which is more extensive than the clinic drug Risperidone. Furthermore, the safety window for extrapyramidal side effects of NH300094 is significantly wider than that of Risperidone (For NH300094, mice catalepsy model ED50/ Mice MK-801 model ED50 = 104.6-fold; for Risperidone, mice catalepsy model ED50/ Mice MK-801 model ED50 = 12.9-fold), which suggests a potentially better clinical safety profile for NH300094. Conclusion: NH300094 is a novel potent serotonin and dopamine receptors modulator, which has good safety profile and therapeutic potential for the treatment of schizophrenia with cognition disorders.

Magnetite alleviating calcification of anaerobic granular sludge (AnGS): Electron transfer enhancement and ion competition.

Calcification accompanied by deactivation of anaerobic granular sludge (AnGS) is a continuing challenge for high calcium wastewater treatment. The interaction between Ca2+ and extracellular polymeric substances (EPS) is a precondition for this problem. In this study, magnetite for activity recovery and calcification alleviation simultaneously of AnGS under high calcium stress was investigated. The results showed that, in the presence of magnetite, the relative biogas production increased by 13.2 % with the higher activities of key enzymes involved in methanogenesis. Methanosarcina turned into the dominant methanogens, and syntrophic bacteria such as Chloroflexi, Synergistota were enriched, which indicated the enhancement of electron transfer by magnetite, supported by an 18 % increase of the electron transfer system (ETS) activity. Further characterizations of AnGS suggested that the granule calcification was alleviated with a final decrease of 13-40 % calcium content of AnGS with particle size of 1-2.5 mm. Besides, calcium was partially substituted by iron in the EPS, and the secretion of EPS especially proteins decreased. Batch tests demonstrated the competition between Fe2+ dissolved from magnetite and Ca2+, which interfered the interaction between Ca2+ and EPS, so the granule calcification was prevented. Therefore, magnetite played a pluripotent role in the alleviation of granule calcification and deactivation in situ via (1) enhancing electron transfer, and (2) blocking the complex between Ca2+ and EPS. This study provides a novel insight into the application of conductive metal materials in biological wastewater treatment systems suffering from high calcium attack.

Characterization of Quantitative Trait Loci for Leaf Rust Resistance in the Uzbekistani Wheat Landrace Teremai Bugdai.

Leaf rust, caused by Puccinia triticina, is a major cause of wheat yield losses globally, and novel leaf rust resistance genes are needed to enhance wheat leaf rust resistance. Teremai Bugdai is a landrace from Uzebekistan that is highly resistant to many races of P. triticina in the United States. To unravel leaf rust resistance loci in Teremai Bugdai, a recombinant inbred line (RIL) population of Teremai Bugdai × TAM 110 was evaluated for response to P. triticina race Pt54-1 (TNBGJ) and genotyped using single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). Quantitative trait loci (QTL) analysis using 5,130 high-quality GBS-SNPs revealed three QTLs, QLr-Stars-2DS, QLr-Stars-6BL, and QLr.Stars-7BL, for leaf rust resistance in two experiments. QLr-Stars-2DS, which is either a new Lr2 allele or a new resistance locus, was delimited to an ∼19.47-Mb interval between 46.4 and 65.9 Mb on 2DS and explained 31.3 and 33.2% of the phenotypic variance in the two experiments. QLr-Stars-6BL was mapped in an ∼84.0-kb interval between 719.48 and 719.56 Mb on 6BL, accounting for 33 to 36.8% of the phenotypic variance in two experiments. QLr.Stars-7BL was placed in a 350-kb interval between 762.41 and 762.76 Mb on 7BL and explained 4.4 to 5.3% of the phenotypic variance. Nine GBS-SNPs flanking these QTLs were converted to kompetitive allele specific PCR (KASP) markers, and these markers can be used to facilitate their introgression into locally adapted wheat lines.

Spinal Cord Injury: From MicroRNAs to Exosomal MicroRNAs.

Spinal cord injury (SCI) is an unfortunate experience that may generate extensive sensory and motor disabilities due to the destruction and passing of nerve cells. MicroRNAs are small RNA molecules that do not code for proteins but instead serve to regulate protein synthesis by targeting messenger RNA's expression. After SCI, secondary damage like apoptosis, oxidative stress, inflammation, and autophagy occurs, and differentially expressed microRNAs show a function in these procedures. Almost all animal and plant cells release exosomes, which are sophisticated formations of lipid membranes. These exosomes have the capacity to deliver significant materials, such as proteins, RNAs and lipids, to cells in need, regulating their functions and serving as a way of communication. This new method offers a fresh approach to treating spinal cord injury. Obviously, the exosome has the benefit of conveying the transported material across performing regulatory activities and the blood-brain barrier. Among the exosome cargoes, microRNAs, which modulate their mRNA targets, show considerable promise in the pathogenic diagnosis, process, and therapy of SCI. Herein, we describe the roles of microRNAs in SCI. Furthermore, we emphasize the importance of exosomal microRNAs in this disease.

An Automated Instance Segmentation Method for Crack Detection Integrated with CrackMover Data Augmentation.

Crack detection plays a critical role in ensuring road safety and maintenance. Traditional, manual, and semi-automatic detection methods have proven inefficient. Nowadays, the emergence of deep learning techniques has opened up new possibilities for automatic crack detection. However, there are few methods with both localization and segmentation abilities, and most perform poorly. The consistent nature of pavement over a small mileage range gives us the opportunity to make improvements. A novel data-augmentation strategy called CrackMover, specifically tailored for crack detection methods, is proposed. Experiments demonstrate the effectiveness of CrackMover for various methods. Moreover, this paper presents a new instance segmentation method for crack detection. It adopts a redesigned backbone network and incorporates a cascade structure for the region-based convolutional network (R-CNN) part. The experimental evaluation showcases significant performance improvements achieved by these approaches in crack detection. The proposed method achieves an average precision of 33.3%, surpassing Mask R-CNN with a Residual Network 50 backbone by 8.6%, proving its effectiveness in detecting crack distress.