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Purpose: Low back pain (LBP) has a significant impact on the general population, especially on military personnel. This study aimed to systematically review the relevant literature to determine the prevalence and risk factors of low back pain among military personnel from different military occupational categories. Methods: For this systematic review, we searched Embase, PubMed, and Cochrane. We performed study selection, data extraction, and assessed the quality of the evidence using the adapted risk of bias assessment tool by Hoy et al. This review process was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This study is registered on the Center for Open Science, registration DOI: 10.17605/OSF.IO/HRGE8. Results: Out of 860 papers, 19 studies met the inclusion criteria. More than 360 000 military people with lumbar pain situation were considered for inclusion in this systematic review. The 1-year prevalence of LBP could be up to 81.7% in the Army, 5.2% in the Marines, and 48.1% in the Air Force. Age (OR = 0.494–2.89), history of LBP (OR = 2.2–8.91), and sedentary position (OR = 0.55–3.63) were the most common physical, sociodemographic, and occupational risk factors, respectively. Conclusions: Low back pain was prevalent among military personnel. There was heterogeneity in studies and a significant difference in prevalence and incidence across various occupational categories. Physical, sociodemographic, and occupational risk factors were researched more than psychological risk factors in the military.

Abstract Background The impact of acrylamide (ACR) on learning and memory has garnered considerable attention. However, the targets and mechanisms are still unclear. Results Elongation factor 2 (eEF2) was significantly upregulated in the results of serum proteomics. Results from in vitro and in vivo experiments indicated a notable upregulation of Eukaryotic elongation factor 2 kinase (eEF2K), the sole kinase responsible for eEF2 phosphorylation, following exposure to ACR (P

Abstract One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Purpose: In the military, neck pain is second to low back pain among musculoskeletal disorders. However, the prevalence and related factors of neck pain in military personnel have not been systematically investigated, which may lead to the lack of neck pain prevention and the generation of additional medical expenses, posing challenges to medical care. This review aimed to obtain the prevalence and related factors for neck pain in military personnel in an attempt to provide directions for prevention and intervention. Methods: We searched PubMed, Embase, and Cochrane databases in December 2021. Two researchers independently screened studies according to eligibility criteria and assessed study quality. Results: We screened titles and abstracts of 503 articles, and 17 articles met the inclusion criteria. Sixteen articles received moderate to high-quality evaluations. Neck pain is common in the military, with 1-year prevalence as high as 83% and lifetime prevalence as high as 78%. Old age (OR = 5.0), poor neck mobility (OR = 3.61), shoulder pain (OR = 4.9), low back pain (OR = 2.3), high-G pilots (OR = 1.6), longer flight time (OR = 2.53), type of aircraft (OR = 3.93), and use of helmets and night vision systems (OR = 1.9) may be associated with the prevalence of neck pain. Conclusion: Neck pain is highly prevalent in military personnel and exhibits a substantial lifetime prevalence rate. The high prevalence rate of neck pain in the military is related to many individual-related factors and work-related factors. The in-depth assessment and prevention of specific factors is an important direction of future research.

Abstract Background Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication, restricted interests that can be accompanied by repetitive behavior, and disturbances in social behavior. This study investigated brain mechanisms that contribute to sociability deficits and sex differences in an ASD animal model. Methods Sociability was measured in C58/J and C57BL/6J mice using the 3-chamber social choice test. Bulk RNA-Seq and snRNA-Seq identified transcriptional changes in C58/J and C57BL/6J amygdala within which DMRseq was used to measure differentially methylated regions in amygdala. Results C58/J mice displayed divergent social strata in the 3-chamber test. Transcriptional and pathway signatures revealed immune-related biological processes differ between C58/J and C57BL/6J amygdala. Hypermethylated and hypomethylated genes were identified in C58/J versus C57BL/6J amygdala. snRNA-Seq data in C58/J amygdala identified differential transcriptional signatures within oligodendrocytes and microglia characterized by increased ASD risk gene expression and predicted impaired myelination that was dependent on sex and sociability. RNA velocity, gene regulatory network, and cell communication analysis showed diminished oligodendrocyte/microglia differentiation. Findings were verified using Bulk RNA-Seq and demonstrated oxytocin’s beneficial effects on myelin gene expression. Limitations Our findings are significant. However, limitations can be noted. The cellular mechanisms linking reduced oligodendrocyte differentiation and reduced myelination to an ASD phenotype in C58/J mice need further investigation. Additional snRNA-Seq and spatial studies would determine if effects in oligodendrocytes/microglia are unique to amygdala or if this occurs in other brain regions. Oxytocin’s effects need further examination to understand its’ potential as an ASD therapeutic. Conclusions Our work demonstrates the C58/J mouse model’s utility in evaluating the influence of sex and sociability on the transcriptome in concomitant brain regions involved in ASD. Our single-nucleus transcriptome analysis elucidates potential pathological roles of oligodendrocytes and microglia in ASD. This investigation provides details regarding regulatory features disrupted in these cell types, including transcriptional gene dysregulation, aberrant cell differentiation, altered gene regulatory networks, and changes to key pathways that promote microglia/oligodendrocyte differentiation. Our studies provide insight into interactions between genetic risk and epigenetic processes associated with divergent affiliative behavior and lack of positive sociability.

We investigate the feasibility of measuring the proton charge radius through dimuon photoproduction off a proton target. Our findings indicate that the Bethe-Heitler mechanism, which dominates at small momentum transfers, allows for an extraction of the proton electromagnetic form factors in the extremely low Q2 region below 10−3 GeV2 in the spacelike region, when the incident photon beam energy exceeds several hundred MeV. The optimal kinematical region and a sensitivity study of the proton charge radius from dimuon photoproduction are presented. Such a measurement is expected to provide an alternative to the elastic muon-proton scattering measurements such as MUSE at PSI and AMBER at CERN.

This study seeks to identify core housing bubble predictors and empirically investigate a novel model for detecting housing bubbles in Malaysia. We engender new insights based on the extraction of real-time opinions of market players about housing bubble formation and collapse. We employ a practical approach using a comprehensive survey of opinions from relevant walks of life via the survey data analysis software, SmartPLS3. Results indicate that housing demand, economic growth outlook, and buyers’ expectations positively impact the housing bubble. This study’s present housing market condition, foreign investment, and government policies are otherwise insignificant. We found that the present housing condition, government policies, and economic growth outlook do not influence the impact of housing demand, buyers’ expectations, and foreign investment on the housing bubble. We employed a cross-sectional research design in this study to obtain our findings. This might have indirectly suppressed more robust findings, which may have been otherwise obtained in the case of a longitudinal study. We advocate that policymakers should not overlook the significant roles of housing demand, economic growth outlook, and buyers’ expectations of the housing bubble. We show that the present housing market condition has no significant moderating effect on the impact of buyers’ expectations, foreign investment, and housing demand on housing bubbles.

Abstract Furin primarily localizes to the trans‐Golgi network (TGN), where it cleaves and activates a broad range of immature proproteins that play critical roles in cellular homeostasis, disease progression, and infection. Furin is retrieved from endosomes to the TGN after being phosphorylated, but it is still unclear how furin exits the TGN to initiate the post‐Golgi trafficking and how its activity is regulated in the TGN. Here three membrane‐associated RING‐CH finger (MARCHF) proteins (2, 8, 9) are identified as furin E3 ubiquitin ligases, which catalyze furin K33‐polyubiquitination. Polyubiquitination prevents furin from maturation by blocking its ectodomain cleavage inside cells but promotes its egress from the TGN and shedding. Further ubiquitin‐specific protease 32 (USP32) is identified as the furin deubiquitinase in the TGN that counteracts the MARCHF inhibitory activity on furin. Thus, the furin post‐Golgi trafficking is regulated by an interplay between polyubiquitination and phosphorylation. Polyubiquitination is required for furin anterograde transport but inhibits its proprotein convertase activity, and phosphorylation is required for furin retrograde transport to produce fully active furin inside cells.

BackgroundAreca nut (AN) is a traditional Chinese herbal medicine used for centuries to treat gastrointestinal (GI) disorders. Charred AN (CAN) is a processed product of AN with similar therapeutic effects. This study aimed to investigate the therapeutic mechanisms of AN and CAN for constipation via metabolomics and gut microbiota analysis.MethodsIn this study, the rats were randomly divided into 5 groups (n = 6): control, constipation model, positive drug, AN treatment, and CAN treatment groups. Constipation was induced by intragastric administration of loperamide hydrochloride, followed by 14-day treatment with mosapride, AN, or CAN. The efficacy difference between AN and CAN was assessed by evaluating the weight gain, fecal water content, GI transit rate, colonic histopathology, serum levels of GI hormones, gut microbiota, and fecal metabolites.ResultsThe results demonstrated that both AN and CAN could alleviate loperamide-induced constipation. Furthermore, they significantly elevated the serum levels of motilin, vasoactive intestinal peptide, substance P, and acetylcholine. 16S rRNA analysis revealed that AN regulated the relative abundance of Bacillus, UCG-005, norank_f_Muribaculaceae, Candidatus_Saccharimonas, and Ruminococcus, whereas CAN modulate the relative abundance of Lactobacillus, Bacillus, norank_f_Muribaculaceae, Ruminococcus, unclassified_f_Oscillospiraceae, and unclassified_f_Prevotellaceae. Moreover, the metabolic profile of AN- and CAN-treated rats was also different, where AN treatment involved pathways of citrate cycle (TCA) and tyrosine, alanine, aspartate, and glutamate metabolisms. Whereas CAN treatment involved pathways of steroid and primary bile acid biosynthesis, as well as pyrimidine and purine metabolisms. Spearman correlation analysis indicated a close relationship between gut microbiota and fecal metabolites.ConclusionIn summary, this study revealed that AN may protect GI mucosa, enhance GI motility, and alleviate constipation symptoms by regulating the relative abundance of specific gut microbiota (Bacillus, UCG-005, norank_f_Muribaculaceae, Candidatus_Saccharimonas, Ruminococcus) as well as citrate cycle or tyrosine, alanine, aspartate, and glutamate metabolic pathways. Furthermore, CAN was observed to promote gastric emptying and intestinal propulsion, thereby alleviating constipation, by modulating the relative abundance of specific gut microbiota (Lactobacillus, Bacillus, norank_f_Muribaculaceae, Ruminococcus, unclassified_f_Oscillospiraceae, unclassified_f_Prevotellaceae) as well as steroid and primary bile acid biosynthesis, as well as pyrimidine and purine metabolic pathways.

We propose a novel method for measuring the charge radii of charged stable hadrons, with which the first measurement of the charge radii of the Σ+ and the Ξ− is foreseen. The method explores the facts that the Dalitz decay ψ(2S)→YY¯e+e− contains the hyperon form factors and the lowest measurable four-momentum transfer squared can be as low as ∼4me2=1.05×10−6GeV2 in the time-like region. We identify a kinematic region where the hyperon form factors are essential and propose a method for subtracting the background from the data. It is estimated that the hyperon charge radii can be measured to a precision of about 0.2 fm with the BESIII experiment and one order of magnitude better at the future Super τ-Charm Facility. Moreover, the same method can be used to measure the charge radius of the proton, which provides an independent cross-check on the extraction of proton radius from elastic ep scattering or leptonic hydrogen spectroscopy.

Summary: Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3-mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We apply an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in humans and mice. We unexpectedly discover an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts are altered in Shank3-mutant mice and postmortem brain tissues from individuals with autism spectrum disorder. The enhanced SHANK3 transcriptome significantly improves the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest that both deterministic and stochastic transcription of the genome is associated with SHANK family genes.

Genetic markers for acne are being studied to create personalized treatments based on an individual’s genes, and the field is benefiting from the application of artificial intelligence (AI) techniques. One such AI tool, the Q-learning algorithm, is increasingly being utilized by medical researchers to delve into the genetics of acne. In contrast to previous methods, our research introduces a Q-learning model that is adaptable to diverse sample groups. This innovative approach involves preprocessing data by identifying differentially expressed genes and constructing gene-gene connectivity networks. The key advantage of using the Q-learning model lies in its ability to transform acne gene data into Markovian domains, which are essential for selecting relevant genetic markers. Performance evaluations of our Q-learning model have shown high accuracy and specificity, although there may be some sensitivity variations. Notably, this research has identified specific genes, such as CD86, AGPAT3, TMPRSS11D, DSG3, TNFRSF1B, PI3, C5AR1, and KRT16, as being acne-related through biological verification and text data mining. These findings underscore the potential of AI-driven Q-learning models to revolutionize the study of acne genetics. In conclusion, our Q-learning model offers a promising approach for the selection of acne-related genetic markers, despite minor sensitivity fluctuations. This research highlights the transformative potential of Q-learning in advancing our understanding of the genetics underlying acne, paving the way for more personalized and effective treatments in the future.