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Background: The collaboration between pharmacists and veterinarians plays a crucial role in ensuring optimal animal healthcare. Understanding the willingness of veterinarians to collaborate with pharmacists and analyzing the prescribing trends by veterinarians are essential factors in improving the quality of veterinary care. By analyzing these aspects, valuable insights can be gained to enhance interprofessional collaboration and optimize medication management in veterinary practice. Objectives: To examine the willingness of veterinarians towards interprofessional collaboration with community pharmacist. Methods: A cross-sectional study was conducted among 40 veterinary clinics in Klang Valley, Malaysia. Data was collected via online using Google Forms from registered veterinarians working in private veterinary clinics in Klang Valley, Malaysia. Descriptive statistics and statistical analysis were performed using SPSS version 27. Results: The overall willingness of veterinarians to collaborate with community pharmacists was measured with a median score of 51 out of 75. The results indicated that 55 % of veterinarians demonstrated high willingness to collaborate. Specifically, 52.5 % of veterinarians had a positive attitude towards collaboration, 55 % recognized the roles of pharmacists positively, and 57.5 % identified barriers to collaboration. These findings highlight a generally positive inclination towards interprofessional collaboration among veterinarians. Conclusion: More veterinarians demonstrated a positive willingness to collaborate with pharmacists for optimal patient care. However, several constraints were identified, including a lack of face-to-face communication, concerns about pharmacists' knowledge or skills in veterinary medicine, and financial interests. Addressing these issues could further enhance collaboration between veterinarians and pharmacist.

Abstract Background Biliary atresia (BA) is a severe neonatal disease with progressive intra- and extra-hepatic bile ducts inflammation and hepatic fibrosis. Characterization of gut microbiome profiles in infants with biliary atresia can provide valuable information and potential disease biomarkers. Our study aims to explore the relationship between gut microbiota and biliary atresia. Methods 16 S ribosomal RNA (rRNA) gene sequencing was carried out to identify the differences in composition and diversity of gut microbiota between infants with BA and healthy subjects. A total of 31 infants with biliary atresia and 20 healthy subjects were recruited. Results The composition of gut microbiota in BA group was significantly different with the normal control group (P

Acute ischemic stroke (AIS), a neurological injury resulting from blood clots, is the second most common cause of death worldwide. Novel therapeutics are urgently needed. Rapid developments in instrumentation and bioinformatics have resulted in increased use of mass spectrometry-based proteomics as an effective tool for the in-depth study of AIS. This review focuses on proteomics investigations of AIS in animal models. We highlight the study findings in system-wide protein abundance changes and molecular mechanisms underlying AIS with or without therapeutic intervention, as well as prestroke prognosis investigations. This review reveals that common molecular pathways related to ischemic injury and spontaneous recovery have been uncovered and part of AIS-changed proteins have been repeatedly identified, indicating the promise of proteomics in generating novel therapeutic targets and biomarker candidates. We also discuss challenges, alleviating strategies, and perspectives of mass spectrometry-based proteomics in AIS research and call for a broad application of systems-level investigations on preclinical AIS molecular mechanism elucidation, target discovery and validation, and therapeutics development.

In order to improve the prediction accuracy of photovoltaic output power， this paper proposes a prediction method using AFSA （artificial fish swarm algorithm） to optimize BP （back-propagation） neural network. Based on the cleaned data， the paper takes highly correlative meteorological data as input， and photovoltaic output power data as output. It uses the global optimization capabilities and inherent parallel computing capabilities of AFSA to optimize the weights and thresholds of the BP neural network. The photovoltaic output power prediction model based on the AFSA-BP neural network is obtained after training. The simulation analysis of a photovoltaic power station shows that compared with using BP neural networks, genetic algorithm optimized BP neural network， and PSO-BP network， the prediction results of this method are more accurate, the degree of fitting to the original data curve is better， the corresponding error evaluation index is lower, and the training is less time-consuming; the method can rapidly and accurately predict the photovoltaic output power.

The impact of CEOs' psychological traits on firms' decision-making has been explored by many psychological researchers. What's more, the CEO hometown identity, as one of the most fundamental psychological traits, has drawn increasing attention from the psychological literature. Firms' adoption of blockchain technology plays an innovative and efficient role in firms' strategic transformation. Thus, it is necessary to investigate the relationship between CEOs' psychological traits and firms' adoptions of blockchain technology from the perspective of hometown identity. To examine the impact of the CEO hometown identity on firms' adoption of blockchain technology, this paper manually collects information about the CEO hometown identity and constructs the index of firms' adoption of blockchain technology based on the textual analysis of firms' annual reports. Based on the theory about the psychology of identity, this paper constructs the theoretical hypothesis about the relationship between CEO hometown identity and firms' adoption of blockchain technology. Then, this paper uses a two-way fixed effect regression model to estimate the impact of the CEO hometown identity on firms' adoption of blockchain technology based on the panel data of Chinese A-share non-financial listed firms during 2008–2019. The research results show that: (1) the CEO hometown identity has a positive effect on firms' adoption of blockchain technology. (2) For firms with severe financing constraints and State-owned enterprises (SOEs), the positive effect of the CEO hometown identity on firms' adoption of blockchain technology is more prominent. (3) Our benchmark results still hold after a series of robustness checks, including altering the measurement of the CEO hometown identity, altering the sample, adding CEO-specific control variables, and altering the logit regression model. Based on the above-mentioned findings, this paper not only sheds new light on the power of CEOs' psychological trait but also deepens the understanding about theories of the psychology of identity.

Abstract Background Camptocormia is common in patients with multiple system atrophy (MSA). The current study was aimed at assessing the frequency of camptocormia and its related factors in MSA patients with different disease durations. Also, the impact of camptocormia on disability was evaluated. Methods A total of 716 patients were enrolled in the study. They were classified into three groups based on disease duration (≤ 3, 3–5, ≥ 5 years). Specific scales were used to evaluate the motor and non-motor symptoms. Disease severity was assessed using the Unified Multiple System Atrophy Rating Scale (UMSARS). The binary logistic regression model was used to explore the factors related to camptocormia. To analyze the impact of camptocormia on disability in patients with disease duration less than 5 years, propensity score matching (PSM) and stratified Cox regression analysis were used. Results In the current study, we found that the frequency of camptocormia was 8.9, 19.7 and 19.2% when the disease duration was ≤3, 3–5, ≥ 5 years, respectively. In the disease duration ≤3 years group, we found that MSA-parkinsonian subtype (MSA-P) (OR = 2.043, P = 0.043), higher total UMSARS score (OR = 1.063, P

Abstract Background Epidemiological and clinical studies have suggested comorbidity between amyotrophic lateral sclerosis (ALS) and autoimmune disorders. However, little is known about their shared genetic architecture. Methods To examine the relation between ALS and 10 autoimmune diseases, including asthma, celiac disease (CeD), Crohn’s disease (CD), inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), and ulcerative colitis (UC), and identify shared risk loci, we first estimated the genetic correlation using summary statistics from genome-wide association studies, and then analyzed the genetic enrichment leveraging the conditional false discovery rate statistical method. Results We identified a significant positive genetic correlation between ALS and CeD, MS, RA, and SLE, as well as a significant negative genetic correlation between ALS and IBD, UC, and CD. Robust genetic enrichment was observed between ALS and CeD and MS, and moderate enrichment was found between ALS and UC and T1D. Thirteen shared genetic loci were identified, among which five were suggestively significant in another ALS GWAS, namely rs3828599 (GPX3), rs3849943 (C9orf72), rs7154847 (G2E3), rs6571361 (SCFD1), and rs9903355 (GGNBP2). By integrating cis-expression quantitative trait loci analyses in Braineac and GTEx, we further identified GGNBP2, ATXN3, and SLC9A8 as novel ALS risk genes. Functional enrichment analysis indicated that the shared risk genes were involved in four pathways including membrane trafficking, vesicle-mediated transport, ER to Golgi anterograde transport, and transport to the Golgi and subsequent modification. Conclusions Our findings demonstrate a specific genetic correlation between ALS and autoimmune diseases and identify shared risk loci, including three novel ALS risk genes. These results provide a better understanding for the pleiotropy of ALS and have implications for future therapeutic trials.

Abstract Background Spastic paraplegia type 11 (SPG11) mutations are the most frequent cause of autosomal recessive hereditary spastic paraplegia (ARHSP). We are aiming to identify the causative mutations in SPG11 among families referred to our center with ARHSP in a Chinese population. Methods Targeted next-generation sequencing was performed on the patients to identify disease-causing mutations. Variants were analyzed according to their predicted pathogenicity and their relevance to the clinical phenotypes. The segregation in the family members was validated by Sanger sequencing. Results A total of 12 mutations in SPG11 gene from 9 index cases were identified, including 6 frameshift mutations, 3 missense mutations, 1 nonsense mutation, 1 splicing mutation, and 1 intron deletion mutation. In 6 of these patients, the mutations were homozygous, and the other 3 patients carried two compound heterozygous mutations. Six mutations were novel; 2 were classified as pathogenic, 1 were considered as likely pathogenic, and the other 3 were variants of unknown significance. Additionally, 1 missense heterozygous variant we found was also carried by amyotrophic lateral sclerosis (ALS) patient. Clinically and electrophysiologically, some of our ARHSP patients partially shared various features of autosomal-recessive juvenile amyotrophic lateral sclerosis (ARJALS), including combination of both UMN and LMN degeneration. Conclusions The results contribute to extending of the SPG11 gene mutation spectrum and emphasizing a putative link between ARHSP and ARJALS.

Relational keyword search (R-KWS) systems provide users with a convenient means in relational database queries. There exist two main types of R-KWS: those based on Data Graphs and those based on Schema Graphs. In this paper, we focus on the latter, R-KWS based on Schema Graphs. Most existing methods are typically inefficient due to the large number of repetitive operation caused by overlapping candidate networks and the execution of lots of complex queries. We present the R-KWS approach based on combined candidate network evaluation to improve the query efficiency. The proposed Combined Candidate Network (CCN) can efficiently share the overlapping part between candidate networks, and then avoid the repetitive operation during the evaluation of candidate networks. Meanwhile, CCN possesses another important characteristic that candidate networks within a CCN are still identifiable after candidate networks being compressed into a CCN. We design an algorithm based on this characteristic to evaluate CCN for the generation of final query results. This algorithm is able to eliminate the execution of a large number of complex queries required by most existing approaches, and thus significantly improve the efficiency of keyword search. Experiments on real datasets show that our approach can improve query efficiency without any loss of the quality of query results with respect to existing approaches.

Acetylation of tau protein is dysregulated in Alzheimer's Disease (AD). It has been proposed that acetylation of specific sites in the KXGS motif of tau can regulate phosphorylation of nearby residues and reduce the propensity of tau to aggregate. Histone deacetylase 6 (HDAC6) is a cytoplasmic enzyme involved in deacetylation of multiple targets, including tau, and it has been suggested that inhibition of HDAC6 would increase tau acetylation at the KXGS motifs and thus may present a viable therapeutic approach to treat AD. To directly test the contribution of HDAC6 to tau pathology, we intracerebroventricularly injected an antisense oligonucleotide (ASO) directed against HDAC6 mRNA into brains of P301S tau mice (PS19 model), which resulted in a 70% knockdown of HDAC6 protein in the brain. Despite a robust decrease in levels of HDAC6, no increase in tau acetylation was observed. Additionally, no change of tau phosphorylation or tau aggregation was detected upon the knockdown of HDAC6. We conclude that HDAC6 does not impact tau pathology in PS19 mice.

To date, microglia subsets in the healthy CNS have not been identified. Utilizing autofluorescence (AF) as a discriminating parameter, we identified two novel microglia subsets in both mice and non-human primates, termed autofluorescence-positive (AF+) and negative (AF−). While their proportion remained constant throughout most adult life, the AF signal linearly and specifically increased in AF+ microglia with age and correlated with a commensurate increase in size and complexity of lysosomal storage bodies, as detected by transmission electron microscopy and LAMP1 levels. Post-depletion repopulation kinetics revealed AF− cells as likely precursors of AF+ microglia. At the molecular level, the proteome of AF+ microglia showed overrepresentation of endolysosomal, autophagic, catabolic, and mTOR-related proteins. Mimicking the effect of advanced aging, genetic disruption of lysosomal function accelerated the accumulation of storage bodies in AF+ cells and led to impaired microglia physiology and cell death, suggestive of a mechanistic convergence between aging and lysosomal storage disorders.

Abstract Background There are inconsistences regarding the correlation between diabetes or fasting blood glucose concentrations and the risk and survival of amyotrophic lateral sclerosis (ALS) in the previous studies. Moreover, the association between hemoglobin A1c (HbA1c) levels, which reflect long-term glycemic status, and ALS survival was not examined. Methods A prospective cohort study including 450 Chinese sporadic ALS patients (254 men and 196 women; mean age: 55.4 y). We identified 223 deaths during average 1.6 years of follow-up. We assessed levels of fasting HbA1c (primary exposure) and glucose (secondary exposure) via ion exchange high-performance liquid chromatography and hexokinase/glucose-6-pgosphate dehydrogenase methods, respectively. Multivariate Cox proportional hazards regression model was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of ALS mortality across the exposures. Results Our results indicated that, higher levels of HbA1c, but not fasting blood glucose concentrations, were significantly associated with higher risks of mortality. The adjusted HR was 1.40 (95% confidence interval (95% CI): 1.02–1.99) for HbA1c of 5.7–6.4%, and 2.06 (95% CI: 1.07–3.96) for HbA1c ≥6.5%, relative to HbA1c 0.05 for all). Conclusion In this prospective study, we observed that individuals with higher HbA1c levels at the baseline had higher risk of mortality, which is independent of other known risk factors.

A rapid series of synchronous cell divisions initiates embryogenesis in many animal species, including the frog Xenopus laevis. After many of these cleavage cycles, the nuclear to cytoplasmic ratio increases sufficiently to somehow cause cell cycles to elongate and become asynchronous at the mid-blastula transition (MBT). We have discovered that an unanticipated remodeling of core metabolic pathways occurs during the cleavage cycles and the MBT in X. laevis, as evidenced by widespread changes in metabolite abundance. While many of the changes in metabolite abundance were consistently observed, it was also evident that different female frogs laid eggs with different levels of at least some metabolites. Metabolite tracing with heavy isotopes demonstrated that alanine is consumed to generate energy for the early embryo. dATP pools were found to decline during the MBT and we have confirmed that maternal pools of dNTPs are functionally exhausted at the onset of the MBT. Our results support an alternative hypothesis that the cell cycle lengthening at the MBT is triggered not by a limiting maternal protein, as is usually proposed, but by a decline in dNTP pools brought about by the exponentially increasing demands of DNA synthesis.

Shexiang Tongxin Dropping Pill (STP) is a composite formula of traditional Chinese medicine that is widely used for the treatment of cardiovascular diseases. It consists of seven medicinal extracts thereof or materials, including Bufonis venenum , synthetic Moschus, Panax ginseng , Bovis calculus artifactus , Bear bile powder, Salvia miltiorrhiza Bge and synthetic borneol. However, it is considerably difficult to evaluate the quality of STP due to its complex chemical compositions. This paper was designed to explore a comprehensive and systematic method combining fingerprints and chemical identification for quality assessment of STP samples. Twenty batches of STP samples were analyzed by high-performance liquid chromatography (HPLC) and high-performance liquid chromatography–quadrupole time-of-flight tandem mass spectrometry. Ten common peaks were detected by HPLC fingerprint similarity evaluation system. Meanwhile, 100 compounds belonging to 4 structural characteristics, including 23 bufadienolides, 36 organic acids, 34 saponins and 7 other types, were systematically identified as the basic components in STP. This study could be used for clarifying the multiple bioactive substances and developing a comprehensive quality evaluation method of STP. [ABSTRACT FROM AUTHOR]