Browse Articles

Correction: Functional characterization of a novel plant growth-promoting rhizobacterium enhancing root growth and salt stress tolerance

Secondary analysis of a randomised controlled trial on reducing sedentary behaviour and its effects on quality of life and wellbeing

Abstract High sedentary behaviour (SB) associates with poorer wellbeing among adults at increased cardiovascular risk. The aim of this study was to investigate the effects of reducing SB on perceived quality of life, depressive symptoms, stress, and workability among physically inactive adults with metabolic syndrome. Sixty-four sedentary, inactive adults [58 (SD 7) years old, 58% women, BMI 32 (4) kg/m 2 ] with metabolic syndrome were randomised into the intervention ( n  = 33) and control ( n  = 31) groups. The 6-month intervention aimed at reducing SB by 1 h/day without adding exercise, while the control group kept their usual SB. All participants wore accelerometers throughout the study to monitor SB and physical activity. Health-related quality of life, stress, depressive symptoms and workability were assessed at baseline, at three months, and after the intervention using the RAND-36, perceived stress questionnaire (PSQ), general health questionnaire (GHQ-12), and the workability score. Main intervention effects were analysed using linear mixed models for repeated measurements. The RAND-36 vitality score decreased in the control group [-2.9 (95% CI -7.7, 1.9) and -1.0 (-5.9, 4.0) from baseline to three and six months, respectively] and increased in the intervention group [+5.7 (1.1, 10.4) and +5.3 (0.4, 10.3) from baseline to three and six months, respectively; between-group difference at three months p  = 0.012 and at six months p  = 0.079]. The PSQ index increased among all participants [+0.03 (-0.01, 0.06) from baseline to six months; time p  = 0.033, no significant between-group differences p  = 0.143]. Among all participants, the change in SB correlated negatively with the change in RAND-36 social functioning score, and the change in light physical activity correlated negatively with the change in PSQ index. Moreover, the change in SB breaks correlated negatively with the RAND-36 physical and social functioning scores. Aiming to reduce SB by 1 h/day may increase perceived vitality among physically inactive adults with metabolic syndrome. The study was pre-registered at Clinicaltrials.gov (5/4/2017, NCT03101228).

Tofogliflozin ameliorates cardiotoxin induced skeletal muscle injury and fibrosis in obesity

Abstract Obesity impairs muscle function through effects on lipid metabolism, systemic inflammation, and insulin resistance, leading to muscle loss and reduced regeneration. Tofogliflozin (Tofo), a sodium-glucose cotransporter 2 inhibitor (SGLT2i), exclusively inhibits SGLT2 and is used to treat hyperglycemia in patients with diabetes. The mechanism by which Tofo promotes myogenic potential in an injury model remains elusive. This study investigated Tofo’s role in skeletal muscle repair in diet-induced obesity. C57BL/6 J male mice were fed a high-fat diet (HFD) with or without Tofo for 12 weeks. Cardiotoxin (CTX) was used to induce acute injury. We showed that Tofo administration during HFD alleviates obesity-induced disruption in glucose metabolism and upregulates Pax7 and MyoG expression in skeletal muscle, thereby promoting myogenesis following acute injury. Tofo activates fibro-adipogenic progenitors (FAPs) in skeletal muscle, leading to upregulated follistatin ( Fst ) expression and boosting the recovery process after acute injury. Mechanistically, Tofo prevented the obesity-induced decline in AMPK phosphorylation, rescued the impairment of lipid metabolism, and improved skeletal muscle function, which led to increased exercise tolerance, activation of FAPs, facilitation of skeletal muscle repair, and reduction of fibrosis.

Trend analysis of medical expenses under DRG payment reform in China

Strategic Fermi Level Engineering of Donor–Acceptor Self-Assembled Monolayer toward Ultrahigh Paired-Pulse Facilitations in Photosynaptic Transistors

Analysis of kinematic factors influencing performance in the Chinese men’s 4 × 100 m relay team

Digital marketing tools and digital transformation capability as a factor in enhancing business performance in China and Kazakhstan

Partially coherent Mathieu–Gauss beams

Examining the impact of augmented reality on students’ learning outcomes

A computer vision-based framework for objective evaluation of sunken upper eyelid

A short-term load forecasting framework for air conditioning system based on model stacking

Development of Balangu seed mucilage nanoparticles fabricated through ultrasonication-antisolvent method for encapsulation of gallic acid

Classifying polish in use-wear analysis with convolutional neural networks

Abstract Lithic use-wear analysis examines micro- and macroscopic traces on tool surfaces resulting from human use and post-depositional processes. Polish, formed through surface abrasion with different materials, is a key diagnostic feature that is increasingly analyzed using machine learning to enhance automation and standardization. However, further research is needed to explore whether deep learning approaches, in particular, can be effectively applied to use-wear analysis and to determine the optimal surface area size (e.g., patch size and microscope objectives) and model architecture (custom vs. pre-trained) for achieving the best results. This study employs convolutional neural networks (CNNs) to classify experimental polish based on contact material (wood, hide, bone) and use intensity, while also assessing optimal imaging and analytical parameters. The results of this exploratory study suggest that CNNs may effectively identify polish from bone and hide but perform less effectively with wood. The models also successfully distinguish between polish formed by short- and long-term use. Custom models outperformed pre-trained ones, particularly when using images that captured smaller areas of the tool’s surface, suggesting that bigger surface areas may lack the necessary information for optimal results. These findings underscore the need to expand use-wear datasets in terms of size and variability and optimize CNN architectures and workflows.

Breastfeeding knowledge and body image affect breastfeeding attitude of pregnant women: a cross-sectional study

Endothelial soluble guanylate cyclase enzyme inhibitors as a novel target for the treatment of sepsis-related hypotension

Lumbar stabilization exercise with and without real-time ultrasound imaging biofeedback in chronic low back pain patients: a randomized controlled trial

Mapping of potential storages and rainwater harvesting sites in arid region of Indus basin using analytical hierarchy technique

Theoretical investigation of the electronic structure and magnetic properties of Ru doped LiFeAs

Abstract This study performed first-principles calculations using Density Functional Theory (DFT) and DFT+ U within the Quantum-Espresso package. . The electronic structure and magnetic properties of Ru-doped LiFeAs were systematically analyzed at doping concentrations of 25%, 50%, and 100%, revealing significant modifications induced by Ru substitution. The optimized lattice parameter of pristine LiFeAs is 3.767 Å, in excellent agreement with the experimental value of 3.77 Å. Upon 25% Ru substitution, the lattice parameter expands slightly to 3.786 Å, reflecting the structural response to partial Ru incorporation. The computed electronic structure and magnetic properties of LiFe 1−x Ru x As confirm its metallic nature, with no detectable band gaps. Density of States (DOS) calculations reveal that the conduction band near the Fermi level is primarily dominated by Fe-3 d and Ru-4 d orbitals, while the valence band is largely influenced by As- p states. With 25% Ru substituted, the electronic band structure shows a strong buildup of states close to the Fermi level, suggesting that the material is becoming more metallic. This elevated electronic density at the Fermi surface is likely to have a substantial impact on the material’s superconducting behavior and charge transport properties, potentially enhancing its conductivity and modifying the electron pairing interactions. In the ferromagnetic (FM) configuration, Ru doping enhances both spin polarization and metallicity, whereas the antiferromagnetic (AFM) state exhibits a suppressed DOS near the Fermi level. The inclusion of the Hubbard U correction provides improved insight into localized electron interactions, particularly in the Fe 3 d orbitals. This study contributes to a deeper understanding of the interplay between doping, electronic correlation, and magnetism in iron-based superconductors. The pristine, 25, and 50% Ru-doped LiFeAs systems retain AFM coupling, while full (100%) Ru substitution induces a transition to a nonmagnetic state. The magnetic moments of Fe atoms decrease progressively with increasing Ru concentration, indicating a suppression of magnetism.

Erdafitinib suppresses pathological retinal angiogenesis via dual targeting of FGFR and VEGFR2 signaling

Anti-VEGF neutralizing antibody delays osteomucosal healing by reducing collagen formation in mice

Abstract Medication-related osteonecrosis of the jaw (MRONJ) is a detrimental side effect in patients undergoing treatment with antiresorptive agents. The anti-angiogenic agent, bevacizumab (anti-VEGF antibody (Ab)), has also been reported to be associated with MRONJ. However, the role of anti-VEGF Ab in MRONJ development, especially under conditions of pre-existing inflammation, remains elusive. This study examined anti-VEGF Ab effects on bone necrosis and osteomucosal healing, with or without pre-inflammation. Forty mice received biweekly i.p. injections of anti-VEGF Ab (10 mg/kg) or saline (Veh). For the tooth extraction (TE) model ( n = 10), maxillary first molars were extracted. For the ligature-induced periodontitis and tooth extraction (LIP-TE) model ( n = 10), maxillary second molars were ligated with 5−0 silk for 8 weeks before extraction. Mice were euthanized after 3 weeks of post-extraction healing. In both TE and LIP-TE models, anti-VEGF Ab-treated mice showed delayed osteomucosal healing with diminished bone formation, lower CD31 and collagen III expression, and increased osteoclast numbers than Veh-treated mice. There was no significant difference in necrotic bone areas. IL-23- or IL-17-producing cell numbers remained unchanged in both Veh- and anti-VEGF Ab-treated mice. Anti-VEGF Ab delayed osteomucosal healing by reducing collagen production in the presence or absence of pre-inflammatory conditions, without causing bone necrosis. Our data suggest anti-VEGF Ab delays osteomucosal wound healing but does not cause bone necrosis alone.