Browse Articles

Characterizing the content and quality of internet resources on exercise training in Ehlers-Danlos Syndromes and generalized hypermobility spectrum disorder

Background Individuals with Ehlers-Danlos Syndromes (EDS) and Generalized Hypermobility Spectrum Disorder (G-HSD) experience musculoskeletal joint instability, cardiopulmonary manifestations, and functional limitations with online exercise resources commonly utilized. This study characterizes and assesses the content, quality, and readability of websites addressing exercise training for individuals with EDS/G-HSD. Methods The first 350 English websites were Googled using search terms “Ehlers-Danlos Syndrome and exercise” and “Ehlers-Danlos Syndrome and physical activity,” targeting educational/instructional sites on exercise training for adults with EDS/G-HSD. Content was assessed using scientific consensus criteria, quality using Modified DISCERN, Global Quality Scale (GQS), and the Patient Education Materials Assessment Tool (PEMAT), and readability using Flesch-Kincaid Grade Level (FKGL) and Flesh-Reading Ease Scores (FRES). Results 78/350 unique websites were included, most from industry organizations (37%) and personal commentary (24%). The mean content score was moderate 13.8 ± 4.4/25. The content most discussed included: short/long-term benefits of muscle strength, resistance training, and generalized exercise safety considerations. Median modified DISCERN and GQS scores were 4/5 IQR [3–4] and 3/5[2.3–4], respectively. Mean PEMAT understandability and actionability scores were 85% ± 12% and 69% ± 23%, respectively. Average FKGL was 11.0 ± 2.7 and FRES was 43.6 ± 7.2. Moderate-strong Spearman correlations were observed between total content scores and GQS (rho = 0.76) and DISCERN (rho = 0.52), p < 0.001 for both. Conclusion Website content varied, most addressing general safety recommendations and multiple training modalities. While quality was moderate-to-good, future resources should focus on simplified language, actionable guidance, and visual aids. Incorporating practical examples of daily activities, injury prevention strategies, broader benefits like cardiovascular health, and psychological support can empower safe and confident exercise training.

Autologous Transplantation of the Entire Bulbar Ocular Surface

The cytological analysis of crossing over in armadillos supports the existence of a phylogenetic component of recombination rates in mammals

In mammals rates of recombination are well predicted by the phylogenetic relationship between species, with lower recombination rates in more basal clades. In this regard, there is currently insufficient evidence for Xenarthra, one of the earliest branches of eutherian mammals. Here we estimated the average recombination rates in four species of armadillos (Cingulata, Xenarthra) using immunodetection of the protein MLH1, a reporter of reciprocal recombination, in pachytene. The recombination rates of the examined species are strikingly similar; despite the fact that they split more than 40 million years ago, suggesting that this may be a conserved trait in other Xenarthra. We provide evidence that armadillos have lower recombination rates than the average for eutherian mammals, and that they approach those of rodents more closely than those of early mammalian clades like Afrotheria.

Cerebral Embolic Protection during TAVI — The Failed Promise

Human umbilical cord mesenchymal stem cells decellular matrix alleviates chondrocyte senescence by inhibiting the STING-NF-κB pathway

Osteoarthritis (OA), characterized by synovial inflammation, articular cartilage degeneration, and structural changes of subchondral bone and periarticular tissues, represents a major unmet clinical challenge. Targeting senescent chondrocytes has emerged as a promising therapeutic strategy of OA. Human umbilgratical cord mesenchymal stem cells (hUCMSCs) have shown potential in OA treatment through paracrine mechanisms, but their clinical translation is limited by challenges in cell viability control and safety concerns. hUCMSCs decellular extracellular matrix (hUCMSCs-dECM) can target senescent chondrocytes to alleviate senescence in OA. Stimulator of interferon gene (STING) can promote chondrocyte senescence in OA through the activation of NF-κB signaling, and inhibition of STING may provide a novel approach for OA treatment. Here, we demonstrated that hUCMSCs-dECM attenuated chondrocyte senescence in vivo and in vitro by inhibiting the STING-NF-κB pathway, which would provide a novel approach for OA treatment.

Boerhaave Syndrome

Serratia sp. traits distinguish the lung microbiome of patients with tuberculosis and non-tuberculous mycobacterial lung diseases

Background Pathogenic mycobacteria, such as Mycobacterium tuberculosis complex (Mtbc), and non-tuberculous mycobacteria (NTMs) can cause severe chronic pulmonary infections. However, not all infected patients develop active disease, and it remains unclear whether key lung microbiome taxa play a role in the pathogenesis of tuberculosis (TB) and NTM lung diseases (LD). Here, we aim to further define the lung microbiome composition in TB, and NTM-LD prior to the initiation of therapy. Study design We employed 16S rRNA amplicon sequencing to characterize the baseline microbiome in bronchoalveolar lavage fluid (BALF) from patients diagnosed with TB (n = 23), NTM-LD (n = 19), or non-infectious inflammatory disease (n = 4). We applied depletion of human cells, removal of extracellular DNA, implementation of a decontamination strategy, and exploratory whole-metagenome sequencing (WMS) of selected specimens. Results Genera Serratia and unclassified Yersiniaceae dominated the lung microbiome of most patients with a mean relative abundance of >15% and >70%, respectively. However, at the sub-genus level, as determined by amplicon sequence variants (ASVs), TB-patients exhibited increased community diversity, and distinct signatures of ASV_7, ASV_21 abundances which resulted in a significant association with disease state. Exploratory WMS, and ASV similarity analyses suggested the presence of Serratia liquefaciens, Serratia grimesii, Serratia myotis and/or Serratia quinivorans in TB and NTM-LD patients. Conclusions The lung microbiome of TB-patients harbored a distinct, and heterogenous structure, with specific occurrences of certain Serratia traits. Some of these traits may play a role in understanding the microbial interactions in the lung microbiome of patients infected with Mtbc.

Gene Therapy for Infantile-Onset Pompe’s Disease

Differences in the incidence of cirrhosis-associated complications between MASLD, MetALD and ALD among patients with decompensated liver cirrhosis

Background Recently, the new definition of steatotic liver disease (SLD) has been introduced, which not only differentiates MASLD (Metabolic Dysfunction-Associated steatotic liver disease) from alcohol-related steatotic liver disease (ALD), but also introduces the concept of metabolic and alcohol-related SLD (MetALD). However, potential differences of the new etiologies regarding the clinical phenotype of patients with advanced liver cirrhosis still remain undetermined. Therefore, we analyzed survival and the incidence of cirrhosis-related complications in SLD-patients with advanced liver cirrhosis. Methods A number of 416 consecutive patients with MASLD, MetALD- and ALD-associated decompensated liver cirrhosis were investigated. Overall survival, infections, hepatic encephalopathy, portal-hypertensive bleeding, rehospitalization and development of hepatocellular carcinoma were retrospectively analyzed within one year of follow-up. Cox regression analyses were performed for survival, competing risk analyses for the cirrhosis-specific complications. MASLD was used as reference group. Results ALD was associated with a lower risk of infections (HR = 0.55; p < 0.001) compared to MASLD. This remained significant after adjustment for age, sex, Model for End-Stage Liver Disease (MELD), serum-sodium, serum-cholinesterase, diabetes, body mass index and norfloxacin (HR = 0.59; p = 0.02) in the multivariable competing risk model. Notably, the incidence of infections in MetALD patients was in between both groups (MetALD: 68.7%, ALD: 56.1%, MASLD: 87.3%). However, there were no differences in survival (MetALD: HR = 1.03; p = 0.93; ALD: HR = 0.79; p = 0.49) and the other complications studied here. Conclusion The risk of infections is increased in MASLD-associated cirrhosis compared to other SLD-phenotypes. Thus, the role of a metabolic risk profile should not be neglected even in patients with decompensated liver cirrhosis.

The application of artificial intelligence techniques in predicting game outcomes of professional basketball league: A systematic review

Background Predicting basketball game outcomes is a critical area in sports science and data analysis, providing concrete benefits for optimizing coaching strategies, improving team management, and informing betting decisions. Objective This methodological review systematically evaluates the effectiveness of specific artificial intelligence technologies in predicting professional basketball game outcomes over the past five years from 2019 to 2024, providing detailed insights into current methodologies and identifying emerging trends and challenges in this domain. Methods Following PRISMA-SCR guidelines, a comprehensive keyword search was conducted across four electronic bibliographic databases: PubMed, Web of Science, Scopus, and EBSCO. Studies were included if they utilized artificial intelligence techniques, focused on professional leagues, and aimed to predict game outcomes. Results This review incorporated 34 studies that met the predefined eligibility criteria, examining various artificial intelligence techniques used to predict professional basketball game outcomes over the past five years. The findings reveal that artificial intelligence models, particularly the multilayer perceptron neural network, achieved a high prediction accuracy of 98.90%. The random forest model, based on four factors, reached an accuracy of 93.81%, while the voting regression ensemble model achieved 93.3%. The studies underscore the importance of effective data processing and feature selection in enhancing model performance. Additionally, dynamic prediction models that adapt to real-time changes in the game were shown to be particularly useful for tactical decisions and betting strategies. Conclusions Artificial intelligence significantly improves the accuracy of predicting outcomes in professional basketball games. Future research should include diverse basketball leagues and employ more advanced validation techniques to enhance model robustness and applicability. Integrating real-time data and exploring transfer learning will likely improve prediction accuracy and decision-making support.

Osteoporosis is associated with increased CVD mortality and all-cause mortality in alcohol-consuming individuals: A cohort study using data from NHANES

Background Osteoporosis, a skeletal disorder characterized by reduced bone density and increased fracture risk, imposes a significant global health burden, particularly in aging populations. Previous studies have highlighted the negative impact of alcohol consumption on bone health, but the interplay between osteoporosis and mortality risk in alcohol-consuming individuals remains underexplored. This study aimed to investigate the association between osteoporosis and cardiovascular disease (CVD) mortality and all-cause mortality in U.S. adults who consume alcohol. Methods This prospective cohort study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning five cycles (2005–2010, 2013–2014, and 2017–2018). A total of 12,178 alcohol-consuming participants aged 20 years and older were included after excluding those with missing data or non-drinking status. Bone density was measured using dual-energy X-ray absorptiometry (DXA), and osteoporosis was defined using World Health Organization (WHO) T-score criteria (T-score ≤ −2.5). Mortality data were obtained through linkage with the National Death Index (NDI). Multivariable Cox proportional hazards regression models were employed to assess the relationship between osteoporosis and mortality outcomes, adjusting for demographic, socioeconomic, and clinical covariates. Results Kaplan-Meier survival analysis revealed higher all-cause and CVD mortality rates in participants with osteoporosis compared to those without (Log-rank test P < 0.001 for both). After adjusting for potential confounders, osteoporosis was associated with a 1.60-fold increased risk of all-cause mortality (HR = 1.60, 95% CI = 1.26–2.03, P < 0.001) and a 1.55-fold increased risk of CVD mortality (HR = 1.55, 95% CI = 1.06–2.28, P = 0.025). Stratified analyses across age, sex, smoking status, and cardiovascular risk factors showed consistent results, with no significant interaction effects (P > 0.05). Sensitivity analyses confirmed the robustness of these findings. Conclusion Osteoporosis is positively associated with increased risks of all-cause and CVD mortality in alcohol-consuming individuals. These findings underscore the need for further research to elucidate the underlying mechanisms and inform preventive strategies targeting this high-risk population.

A dose scaling antivenin protocol in treatment of Daboia palaestinae envenomation may reduce morbidity and costs

Background Daboia palaestinae is a leading cause of snakebite envenomation in the eastern Mediterranean, with substantial mortality in the absence of antivenin. Current recommended antivenin dose is 50 ml; however, antivenin is costly, may be difficult to obtain and is associated with substantial side effects. Thus, this study was designed to define the minimal effective antivenin dose and identify patients who can be safely managed without antivenin. Methods This retrospective single-center study was conducted in adults with suspected or confirmed D. palaestinae envenomation. Patients were treated via our previously developed envenomation protocol: no antivenin use for local symptoms and dose scaling for mild or severe systemic symptoms – initially 10 ml antivenin, with repeat dosing for ongoing systemic symptoms. The main outcomes measured were morbidity and mortality associated with this protocol. Secondary outcomes included assessing the demographics and clinical effects of snake envenomation and comparing between those who received antivenin and those who did not. Results In total, 101 patients were included. A median of 45 minutes [interquartile range: 30–61 minutes] elapsed between snakebite and hospital admission, with no differences between groups. Among 52 patients receiving antivenin, 119 [60–237] minutes elapsed between snakebite and initial antivenin administration, with a maximum of 1073 minutes to initial antivenin administration. Maximum until last antivenin was 3860 minutes. Median antivenin dose was 15 [10–22.5] ml, with 26/52 (50.0%) requiring only 10 ml. Two (2) patients developed an early antivenin immune reaction, with one developing anaphylaxis requiring invasive ventilation. Both received a single 10 ml dose of antivenin prior to allergic reaction. Neither patient had a known history of exposure to serum or relevant allergic reaction. No patients died during hospitalization. Conclusions This cohort demonstrates that a dose-scaling antivenin protocol can be safely employed, reducing morbidity and costs. We recommend a randomized control trial comparing fixed dose regimen to an escalation protocol and development of similar protocols for envenomations due to other snake species.

Thorax temperature and niche characteristics as predictors of abundance of Amazonian Odonata

Environmental architecture and body temperature drive the distribution of ectothermic species, especially those with specific ecophysiological requirements or narrow ecological niches. In this study, we evaluated the connection between thorax temperature and niche specialization concerning the abundance and species contribution to the beta diversity of adult Odonata in Amazonian streams, employing the Species Contribution to Beta Diversity (SCBD). Our hypotheses were (i) Odonata species’ thorax temperature is positively correlated with both morphology (thorax width) and air temperature and differ between suborders. (ii) The thorax temperature of the Odonata assemblage serves as a more influential predictor than niche specialization in determining species abundance and SCBD. We sampled 46 streams in an anthropized landscape in the Northeastern and Southeastern regions of Pará state, Brazil. Notably, niche breadth emerged as the variable influencing the abundance and SCBD of the Odonata assemblage. Niche position is negatively related with abundance only for Zygoptera. Anisoptera exhibited a negative relationship between abundance and thoracic temperature. On the other hand, Zygoptera had positive relationship between abundance and thoracic temperature. In summary, our results underscore the necessity of considering both niche and ecophysiological predictors to comprehensively assess the Odonata assemblage in Amazonian streams. This holistic approach has implications for conservation efforts and bioassessment practices, offering valuable insights into the collective response of Odonata as a group.

Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines

Recent advancements in quantum computing suggest the potential to revolutionize computational algorithms across various scientific domains including oceanography and atmospheric science. The field is still relatively young and quantum computation is so different from classical computation that suitable frameworks to represent oceanic and atmospheric dynamics are yet to be explored. Quantum annealing (QA), one of the major paradigms, focuses on combinatorial optimization tasks. Given its potential to excel in NP-hard problems, QA may significantly accelerate the calculation of ocean and atmospheric systems described by the Navier-Stokes equations in the future. In this paper, we apply both QA and simulated annealing (SA), its classical counterpart, to a simplified ocean model known as the Stommel problem. We use the Stommel problem, which is not an NP problem and therefore does not benefit from QA today, just as an example, a first step in exploring QA for more intricate problems governed by the Navier-Stokes equations. We cast the linear partial differential equation governing the Stommel model into an optimization problem by the least-squares method and discretize the cost function in two ways: finite difference and truncated basis expansion. In either case, SA successfully reproduces the expected solution when appropriate parameters are chosen. In contrast, QA using the D-Wave quantum annealing machine fails to obtain good solutions for some cases owing to hardware limitations; in particular, the highly limited connectivity graph of the machine limits the size of the solvable problems, at least under currently available algorithms. Either expanding the machine’s connectivity graph or improving the graph-embedding algorithms would probably be necessary for quantum annealing machines to be usable for oceanic and atmospheric dynamics problems.

Barriers to conducting implementation science research in Asia: An online survey

Background Implementation science (IS) has importance in Asia to facilitate effective delivery of evidence-based interventions to bridge disease prevention and management gaps. However, IS research conducted in Asia are slower compared to the Western region. Purpose This study aims to assess barriers to conducting IS research in Asia. Methods This study adopted a cross-sectional online survey design. Researchers who had conducted IS research in Asian settings completed a questionnaire which examined socio-demographic characteristics, IS research practices, and yes or no items on the various barriers to conducting IS research. An open-ended question was provided to gather additional barriers. Results The response rate for this study was 40.1% (113/282). More than half of the participants has PhD level education (68.1%, n = 77), and 46.0% (n = 52) were academic lecturers. The most common barrier to conducting IS research was the lack of funding (86.7%, n = 98) followed by the lack of awareness (59.5%, n = 67), the lack of time (56.6%, n = 64), and the lack of organisational support (48.7%, n = 55). The open-ended responses elicited additional barriers: the lack of commitment and involvement from stakeholders other than researchers, perceived low value of IS research, the lack of scientific rigour as a field, existing knowledge, system and practices challenge, the lack of capacity or training support, and the lack of academic progression indicators. Conclusions To facilitate the increase of IS research in Asia, more support are needed in terms of availability of funding, capacity building and training in the region, and effective ways to build constructive long-term collaborations with stakeholders.

Constructing a domain-specific sentiment lexicon for agricultural product reviews using BERT and SO-PMI

The absence of a sentiment lexicon tailored to agricultural product reviews presents significant challenges for accurate sentiment analysis in this domain. Existing general-purpose lexicons, such as NTUSD, HOWNET, and BosonNLP, fail to capture the unique linguistic features of agricultural reviews, leading to suboptimal classification performance. To address this gap, this study constructs the BSTS sentiment lexicon, using a dataset of 19,843 preprocessed reviews from JD.com. Positive and negative seed words were extracted through BERT-based Term Frequency (TF) analysis, and the SO-PMI algorithm was applied to calculate sentiment scores for candidate words. By determining an optimal threshold, a balanced and effective lexicon was developed. Experimental results demonstrate that the BSTS lexicon outperforms existing lexicons in sentiment classification, achieving precision, recall, and F1 scores of 85.21%, 91.92%, and 88.44%, respectively. Furthermore, additional experiments on Taobao’s agricultural product reviews confirmed the lexicon’s robustness, with performance metrics of 93.28% precision and 87.34% F1 score, highlighting its effectiveness across different e-commerce platforms. The BSTS lexicon significantly improves sentiment classification in the agricultural domain, offering a reliable and domain-specific tool for sentiment analysis in agricultural product reviews.

Dynamic antenna clustering along with low RF complexity digital beamforming

This paper presents a digital beamforming technique with low radio frequency (RF) complexity that can preserve antenna weights between the antenna aperture and the digital baseband processing unit. Each antenna subarray connects a separate RF chain and it can only transmit one data stream. The RF chain is made to keep the beamforming weights of subarray antenna elements in a TDM fashion. In this paper, two dynamic clustering algorithms are proposed. Using the first algorithm, the actual number of required RF chains can be identified. By using the second algorithm, it is possible to comprehend the antennas in each subarray for a specific number of RF chains. RF circuit designers can utilize the proposal from this paper to determine the exact number of RF chains in a given scenario and the corresponding digital-to-analogue converter (DAC) and its associated components. Our findings show that, with a much lower RF complexity, the suggested digital beamforming scheme can successfully deliver almost the same spectral efficiency as a full-complexity DBF system.

Social context in political stance detection: Impact and extrapolation

Stance detection is an important task with a wide range of high-impact social applications, including opinion polling and detecting propaganda, misinformation, and hate speech. In this work, we explore the performance and extrapolation power of political stance-detection models using an existing large-scale weakly-labeled Twitter dataset collected around the 2019 South American Protests. We construct transformer-based user and tweet encoders to embed users in a low-dimensional space using their posts and interactions. We then train heterogeneous graph attention networks to predict user stances and contrast their ability to extrapolate stance predictions to different country contexts and to future events. We find that leveraging users’ ego-network in political stance detection improves in-country model performance for every country we examine. More notably, we find that leveraging a user’s social context greatly enhances the ability of our stance detection models to extrapolate to new country contexts and future data.

Origins of the ‘vampire fungus’ that causes white-nose syndrome in bats

Utility of PLUS CYCLE to measure physical activity and sleep duration and detect postoperative sleep disturbances in hospitalized dogs

Sleep is essential for animal health and welfare. In humans, postsurgical sleep disturbances can delay postoperative recovery. However, objective sleep evaluation in dogs and studies of postoperative sleep disturbances in animals have not been reported. This study aimed to determine whether activity monitors (PLUS CYCLE®; JARMeC, Kanagawa, Japan) can accurately monitor the condition of hospitalized dogs and postoperative sleep disturbances. First, the activity data collected by PLUS CYCLE® were compared with the observation data in a video of hospitalized dogs (n = 9). We determined the correlation between the total hours of physical activity, Sleeping/Resting time and amount of physical activity collected by PLUS CYCLE®, and the time when body movements could not be confirmed (inactive time) recorded by video. There was a strong correlation between the inactive time observed in the videos and the Sleeping/Resting time in PLUS CYCLE® (p < 0.0001, r = 0.95). Thereafter, six hospitalized dogs (n = 6) that underwent phacoemulsification and aspiration surgery for cataracts at the Veterinary Teaching Hospital of the Okayama University of Science were monitored to compare pre- and postoperative amounts of physical activity and Sleeping/Resting time between two groups: the Colorado State University Acute Pain Scale (APS) = 0 group (n = 3) and the APS = 1 group (n = 3). A significant decrease in postoperative sleep duration was observed in the APS = 1 group (p = 0.0224). This prospective study suggested that PLUS CYCLE® can accurately assess the condition of hospitalized dogs and that it has the potential to detect postoperative sleep disturbance. Thus, PLUS CYCLE® may help manage postoperative hospitalization and pain management.