Browse Articles

Selection of optimal human myoblasts based on patient related factors influencing proliferation and differentiation capacity

Abstract Human myoblasts (hMb) are a promising source for engineering skeletal muscle tissue. But sample-specific variabilities make research with human cells challenging. For the purpose of selecting hMb with adequate proliferation and differentiation properties, the influence of various patient related factors, including age, gender, BMI, anatomical sampling site and previous radio-/chemotherapy on hMb behavior was investigated in this study. Immunofluorescence staining and proliferation periods were analysed for proliferation capacity, while creatine kinase and cell viability assay, immunofluorescence staining and PCR were used to determine differentiation capacity. Using desmin expression, a multiple linear regression (MLR) model was established based on the above-mentioned patient related factors. Higher age and BMI, female gender and chemotherapy had a negative impact on desmin expression. Muscle type specific differences could also be seen. Previous radiotherapy led to senescence of hMb in large parts. Differentiation was mainly influenced by gender in a time-dependent manner, as well as by the anatomical collecting site. We were able to demonstrate the importance of analyzing patient characteristics for the purpose of hMb isolation. Using MLR, these patient characteristics can be used to predict the proliferation capacity of hMb as a step further towards translational application of skeletal muscle engineering and regeneration.

The mediating role of intrinsic capacity in balance and falls among older adults

Trends in prevalence of spine fractures and risk factors in spine fractures among US adults, 1999–2018

Dietary patterns derived by Gaussian graphical models and metabolic profiles among overweight and obese individuals

A transfer triage tool for COVID-19 mass critical care surges

The association between loneliness, suicidal ideation, and psychological distress considering family compositions: a cross-sectional study in a Japanese rural area

Federated deep reinforcement learning-based urban traffic signal optimal control

Terahertz microscopy through complex media

Abstract Manipulating broadband fields in scattering media is a modern challenge across photonics and other wave domains. Recent studies have shown that complex propagation in scattering media can be harnessed to manipulate broadband light wave packets in space-time for focusing, imaging, and computing applications. Interestingly, while many proposed methodologies operate on intensity-based assessment of scattered fields, often in the spectral domain, from a pure transmission-function perspective, scattering operates as a linear field-level combinatory process, i.e., the superposition of transformation of unit excitations. As a result, we recently demonstrated that gaining experimental access to instantaneous scattered fields, as available through time-domain spectroscopy in the terahertz (THz) spectral range, in conjunction with sparse light excitation typical of ghost imaging, provides a key advantage in enabling the functionalisation of scattering, exposing a novel modelling paradigm. In this paper, we provide experimental proof of reconstructing 1-dimensional object features through a scattering medium using a fully broadband THz time-domain approach.

Exercise enhances cardiomyocyte mitochondrial homeostasis to alleviate left ventricular dysfunction in pressure overload induced remodelling

Exome sequencing reveals low-frequency and rare variant contributions to multiple sclerosis susceptibility in Turkish families

Effectiveness of exercise therapy on chronic ankle instability: a meta-analysis

Abstract Lateral ankle sprains are one of the most common musculoskeletal injuries. Up to 70% of individuals who sustain lateral ankle sprains develop chronic ankle instability (CAI). Exercise therapy is considered an effective treatment for patients with CAI. This meta-analysis investigated the efficacy of exercise therapy in CAI patients by reviewing 15 randomized controlled trials (RCTs) involving 586 participants. Databases including PubMed, EMBASE, Cochrane Library, and Web of Science were searched from inception to September 13, 2024. The Cochrane Risk of Bias Tool was used to assess study quality. Meta-analysis, sensitivity analysis, and publication bias analysis were conducted using RevMan 5.3.0 and Stata 18.0 software. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach was applied to evaluate the quality of evidence. Main outcomes were assessed using the Foot and Ankle Ability Measure (FAAM) and the Star Excursion Balance Test (SEBT). The results demonstrated that exercise therapy significantly improved FAAM-S (MD = 7.98, CI: 4.11 to 11.86, p < 0.0001, I² = 30%). Long-term exercise therapy (over 4 weeks) significantly enhanced FAAM-A (MD = 10.95, CI: 6.60 to 15.29, p < 0.00001, I² = 0%) and dynamic balance ability of ankle joint (SBET-A: MD = 4.83, CI: 1.04 to 8.63, p = 0.01, I² = 62%; SEBT-PM: MD = 6.93, CI: 2.37 to 11.48, p = 0.003, I² = 69%; and SEBT-PL: MD = 8.98, CI: 2.66 to 15.29, p = 0.005, I² = 86%). After categorizing by exercise type, the results indicated that strength training was more effective in improving SEBT-PL (MD = 8.15, CI: 6.09 to 10.21, p < 0.00001, I² = 0%), joint mobilization was more effective in improving SEBT-A (MD = 7.65, CI: 4.93 to 10.37, p < 0.00001, I² = 0%), and proprioceptive training was more effective in improving SEBT-PM (MD = 10.46, CI: 5.27 to 15.65, p < 0.0001, I² = 33%). In conclusion, long-term, multifaceted exercise therapy demonstrates superior rehabilitation efficacy for patients with CAI. Personalized treatment plans, informed by SEBT assessment results, should prioritize targeted interventions such as joint mobilization, strength training, or proprioceptive training. This approach holds significant theoretical and practical value for optimizing CAI treatment strategies and enhancing patient outcomes.

Transcriptomic analysis of the anti-tumor effects of leflunomide in prolactinoma

Study on the phenomenon of the ultra-large drilling cuttings quantity in rockburst coal seam

Later midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke

Sodium propionate protects against bronchopulmonary dysplasia by inhibiting IL-17-mediated apoptosis of alveolar epithelial cells

A machine learning approach for corrosion rate modeling in Patna water distribution network of Bihar

Metabolomic profiling of biphenyl-induced stress response of Brucella anthropi MAPB-9

Abstract The exposure of bacteria to toxic compounds such as polychlorinated biphenyl (PCB) and biphenyl induces an adaptive response at different levels of cell morphology, biochemistry, and physiology. PCB and biphenyl are highly toxic compounds commercially used in the industry. In our previous study, Brucella anthropi MAPB-9 efficiently degraded PCB-77 and biphenyl at a high concentration. In this study, we used metabolomic analyses to understand the metabolic processes occurring in MAPB-9 during exposure to biphenyl. A combination of analytical techniques such as GC-MS/MS and HR-MS study confirmed the complete biphenyl degradation pathway. The intermediate metabolic products identified were cis-2, 3-dihydro-2, 3-dihydroxy biphenyl, 2,3-dihydroxy biphenyl, and 4-dihydroxy-2-oxo-valerate. Further, benzoic acid and 2,3-dihydroxy benzoic acid metabolites identified in the extract revealed the interconnection of biphenyl and benzoic degradation pathways. In addition, the variations in the functioning of the major biochemical pathways in the cells were revealed through changes in the profile of metabolites belonging to glyoxylate, tricarboxylic acid (TCA) cycle, and fatty acid pathways. The exposure to biphenyl inhibited metabolic activity leading to changes in the morphology and metabolism. Despite many adverse changes, the MAPB-9 was able to adapt and grow in the toxic environment undergoing upper and lower biphenyl degradation pathways.

ML techniques increasing the power factor of a compression ignition engine that is powered by Annona biodiesel using SATACOM

Effect of different types of exercise on bone mineral density in postmenopausal women: a systematic review and network meta-analysis

Service recommendation method based on text view and interaction view

Abstract With the increasing prosperity of web service-sharing platforms, more and more software developers are integrating and reusing Web services when developing applications. This approach not only meets the needs of developers but also is cost-effective and widely used in the field of software development. Usually, software developers can browse, evaluate, and select corresponding Web services from a web service-sharing platform to create various applications with rich functionality. However, a large number of candidate Web services have placed a heavy burden on the selection decisions of software developers. Existing web service recommendation systems often face two challenges. Firstly, developers discover services by inputting development requirements, but the user’s input is arbitrary and can not fully reflect the user’s intention. Secondly, the application service interaction record is too sparse, reaching 99.9%, making it particularly difficult to extract services that meet the requirements. To address the above challenges, in this paper, we propose a service recommendation method based on text and interaction views (SRTI). Firstly, SRTI employs graph neural network algorithms to deeply mine the historical records, extract the features of applications and services, and calculate their preferences. Secondly, SRTI uses Transformer to analysis develop requirements and uses fully connected neural networks to deeply mine the matching degree between candidate services and development requirements. Finally, we integrate the above two to obtain the final service list. Extensive experiments on real-world datasets have shown that SRTI outperforms several state-of-the-art methods in service recommendation.