Search Results (620)

Background/Objectives: Strengthening antimicrobial stewardship (AMS) programs is an invaluable intervention in the ongoing efforts to contain the threat of antimicrobial resistance (AMR), particularly in low-resource settings. This study evaluates the impact of the Telementoring, Education, and Advocacy Collaboration initiative for Health through Antimicrobial Stewardship (TEACH AMS), which uses the virtual Extension for Community Healthcare Outcomes (ECHO) learning model to enhance AMS capacity in Kenya, Ghana, and Malawi. Methods: A mixed-methods approach was used, which included attendance data collection, facility-level assessments, post-session and follow-up surveys, as well as focus group discussions. Results: Between September 2023 and February 2025, 77 virtual learning sessions were conducted, engaging 2445 unique participants from hospital-based AMS committees and health professionals across the three countries. Participants reported significant knowledge gain, and data showed facility improvements in two core AMS areas, including the implementation of multidisciplinary ward-based interventions/communications and enhanced monitoring of antibiotic resistance patterns. Along those lines, participants reported that the program assisted them in improving prescribing and culture-based treatments, and also evidence-informed antibiotic selection. The evidence of implementing ward-based interventions was further stressed in focus group discussions, as well as other strengthened practices like point-prevalence surveys, and development or revision of stewardship policies. Substantial improvements in microbiology services were also shared by participants, particularly in Malawi. Other practices mentioned were strengthened multidisciplinary communication, infection prevention efforts, and education of patients and the community. Conclusion: Our findings suggest that a virtual case-based learning educational intervention, providing structured and tailored AMS capacity building, can drive behavior change and strengthen healthcare systems in low resource settings. Future efforts should aim to scale up the engagements and sustain improvements to further strengthen AMS capacity. Full article

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R² = 0.86; Q²_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC₅₀ > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. Full article

The current proceedings summarize the presentations delivered during the third International Electronic Conference on Microbiology (ECM 2025), which was held online from 1 to 3 April 2025, via the SciForum platform. This virtual event brought together researchers from around the world to share recent advances in microbiological sciences. The ECM 2025 highlighted recent developments across a broad spectrum of microbiological research, including antimicrobial resistance, gut microbiota, infectious diseases, and environmental microbiomes. Participants shared their work through online presentations and abstracts, with selected submissions invited for full publication. The event fostered global collaboration, promoted open-access science, and showcased innovative tools for studying and managing microbial systems in health, agriculture, and industry. The multidisciplinary program was organized into several thematic sessions: S1. Gut Microbiota and Health Disease. S2. Foodborne Pathogens and Food Safety. S3. Antimicrobial Agents and Resistance. S4. Emerging Infectious Diseases. S5. Microbiome and Soil Science. S6. Microbial Characterization and Bioprocess. S7. Microbe–Plant Interactions. This conference report presents summaries of the contributions made by participating authors over the three-day event. Full article

Burn injuries result in complex physiological and psychological sequelae, including hypermetabolism, muscle wasting, mobility impairment, scarring, and disrupted body image. While advances in acute care have improved survival, comprehensive rehabilitation strategies are critical for restoring function, appearance, and psychosocial well-being. Structured physical activity, including resistance and aerobic training, plays a central role in counteracting muscle atrophy, improving cardiovascular function, enhancing scar quality, and promoting psychological resilience and body image restoration. This narrative review synthesizes the current evidence on the effects of exercise-based interventions on post-burn recovery, highlighting their therapeutic mechanisms, clinical applications, and implementation challenges. In addition to physical training, emerging technologies such as virtual reality, aquatic therapy, and compression garments offer promising adjunctive benefits. Notably, artificial intelligence (AI) is gaining traction in burn rehabilitation through its integration into wearable biosensors and telehealth platforms that enable real-time monitoring, individualized feedback, and predictive modeling of recovery outcomes. These AI-driven tools have the potential to personalize exercise regimens, support remote care, and enhance scar assessment and wound tracking. Overall, the integration of exercise-based interventions with digital technologies represents a promising, multimodal approach to burn recovery. Future research should focus on optimizing exercise prescriptions, improving access to personalized rehabilitation tools, and advancing AI-enabled systems to support long-term recovery, functional independence, and positive self-perception among burn survivors. Full article

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0. Full article

Virtual fencing (VF) offers a promising alternative to conventional or electrified fences for managing livestock grazing distribution. This study evaluated the behavioral responses of 25 Rarámuri Criollo cows fitted with Nofence^® collars in Pine Valley, CA, USA. The VF system was deployed in chaparral rangeland pastures. The study included a 14-day training phase followed by an 18-day testing phase. The collar-recorded variables, including audio warnings and electric pulses, animal movement, and daily typical behavior patterns of cows classified into a High or Low virtual fence response group, were compared using repeated-measure analyses with mixed models. During training, High-response cows (i.e., resistant responders) received more audio warnings and electric pulses, while Low-response cows (i.e., active responders) had fewer audio warnings and electric pulses, explored smaller areas, and exhibited lower mobility. Despite these differences, both groups showed a time-dependent decrease in the pulse-to-warning ratio, indicating increased reliance on audio cues and reduced need for electrical stimulation to achieve similar containment rates. In the testing phase, both groups maintained high containment with minimal reinforcement. The study found that Rarámuri Criollo cows can effectively adapt to virtual fencing technology, achieving over 99% containment rate while displaying typical diurnal patterns for grazing, resting, or traveling behavior. These findings support the technical feasibility of using virtual fencing in chaparral rangelands and underscore the importance of accounting for individual behavioral variability in behavior-based containment systems. Full article

Phosphatidylinositol 3-kinase alpha (PI3Kα) is frequently mutated in head and neck squamous cell carcinoma (HNSCC), leading to the constitutive activation of the PI3K/Akt pathway, which promotes tumor cell proliferation, survival, and metastasis. PI3Kα allosteric inhibitors demonstrate therapeutic potential as both monotherapy and combination therapy, particularly in patients with PIK3CA mutations or resistance to immunotherapy, through the precise targeting of mutant PI3Kα. Compared to ATP-competitive PI3Kα inhibitors such as Alpelisib, the allosteric inhibitor RLY-2608 exhibits enhanced selectivity for mutant PI3Kα while minimizing the inhibition of wild-type PI3Kα, thereby reducing side effects such as hyperglycemia. To date, no allosteric PI3Kα inhibitors have been approved for clinical use. To develop novel PI3Kα inhibitors with improved safety and efficacy, we employed a scaffold hopping approach to structurally modify RLY-2608 and constructed a compound library. Based on the structural information of the PI3Kα allosteric site, we conducted the systematic virtual screening of 11,550 molecules from databases to identify lead compounds. Through integrated approaches, including molecular docking studies, target validation, druggability evaluation, molecular dynamics simulations, and metabolic pathway and metabolite analyses, we successfully identified a promising novel allosteric PI3Kα inhibitor, H-18 (3-(2-chloro-5-fluorophenyl)isoindolin-1-one). H-18 has not been previously reported as a PI3Kα inhibitor, and provides an excellent foundation for subsequent lead optimization, offering a significant starting point for the development of more potent PI3Kα allosteric inhibitors. Full article

This paper proposes an anti-disturbance model predictive fault-tolerance control strategy for open-circuit faults of five-phase flux intensifying fault-tolerant interior permanent magnet (FIFT-IPM) motors. This strategy is applicable to electric agricultural equipment that has an open winding failure. Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. This results in high harmonic distortion in the phase current. Hence, this paper innovatively proposes a multi-plane virtual vector model predictive fault-tolerant control strategy that can achieve rapid and effective control of both the fundamental and harmonic planes while ensuring good dynamic stability performance. Additionally, considering that electric agricultural equipment is usually in a multi-disturbance working environment, this paper introduces an adaptive gain sliding-mode disturbance observer. This observer estimates complex disturbances and feeds them back into the control system, which possesses good resistance to complex disturbances. Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental results. Full article

Aiming at the transient overcurrent problem faced by doubly-fed induction generators (DFIGs) during continuous voltage fault ride-through, a segmented control strategy based on the rotor side converter (RSC) is proposed. First, through theoretical analysis of the relationship between stator current and transient induced electromotive force (EMF) in each stage of continuous faults, a feedforward control strategy based on the transient component of stator current is proposed. The observable stator current is extracted for its transient component, which is used as a rotor voltage compensation term to effectively counteract the influence of transient EMF. Meanwhile, a fuzzy control algorithm is introduced during the low voltage ride-through (LVRT) stage to dynamically adjust the virtual resistance value, enhancing the system’s damping characteristics. Studies show that this strategy significantly suppresses rotor current spikes in all stages of voltage ride-through. Finally, simulation results verify that the proposed method improves the ride-through performance of DFIG under continuous voltage faults. Full article

Background and Clinical Significance: Avatar Therapy (AT) for individuals with treatment-resistant auditory verbal hallucinations (AVHs) in schizophrenia aims to address emotional responses, beliefs about voices, self-perception, and coping strategies. This study focuses on three participants who, during AT, shifted their belief about the origin of their most distressing voice from an external source to a self-generated one. Case Presentation: The objective of this study was to explore the evolution of the reattribution of the participants’ most distressing voice to oneself during AT and the patients’ perception of this reattribution. Immersive sessions and semi-structured interviews were transcribed and qualitatively described to provide a session-by-session account of the evolution of each participant’s AVH reattribution to themselves during the course of AT, along with their perceptions of this reattribution. This process led to the recognition that initially perceived as external voices were internally generated thoughts, reflecting how participants viewed themselves. Two participants reported a reduction in AVH severity. All three described positive changes in how they related to their voices and self-perception. Additional improvements were observed in emotional regulation, social functioning, and engagement in personal projects. Conclusions: This reassignment of the voice from an external source to an internal one suggests that AT can modify how individuals relate to their voices and may empower them to regain control over their hallucinations. However, given the exploratory nature of this study, the results should be interpreted as examples. Full article

Background/Objectives: Telehealth enhances access to specialty care, but stakeholder perspectives are often overlooked. The objective was to evaluate participant and provider satisfaction with a novel telehealth-enabled home safety program. Methods: This is a sub-investigation of a non-randomized pilot study of a novel telehealth-enabled home safety program that enrolled 23 persons with Parkinson’s Disease (PwPs) at risk for falls and their respective care partners (CPs). Dyads participated in four to six televisits over three months, where they performed “virtual home tours” using a mobile platform (tablet mounted on a rolling stand) with a physical therapist to identify and mitigate environmental fall hazards. Satisfaction was assessed using PI-developed surveys and open feedback. Mobile platform usability was assessed with the System Usability Scale (SUS). Results: A total of 95.65% of dyads were very to extremely satisfied with the entire program overall, and the therapist indicated the same for 73.91% of the dyads. Additionally, 95.65% of dyads reported gaining new awareness of home fall hazards. Difficulties maneuvering the mobile platform, using a tablet, and connectivity issues were common challenges noted. The mean score on SUS for the mobile platform was 65, indicating poor perceived usability, and most dyads indicated they would have preferred using a smartphone for the program. Other priorities, including competing health and personal obligations, along with resistance to change, were the primary barriers to implementing program recommendations. Conclusions: Our novel telehealth-enabled home safety program was well-received by patients and the study therapist. Using a smartphone and troubleshooting connectivity issues might help further improve the usability and accessibility of this program. Full article

With the increasing penetration of distributed generation and the diversification of electrical equipment, distribution networks face issues like three-phase unbalance and harmonic currents, while the voltage stability and inertia of the grid-connected system also decrease. A certain amount of energy storage is needed in a Distribution Static Synchronous Compensator (DSTATCOM) to manage power quality and actively support voltage and inertia in the network. This paper first addresses the limitations of traditional $dq0$ compensation algorithms in effectively filtering out negative-sequence twice-frequency components. An improved $dq0$ compensation algorithm is proposed to reduce errors in detecting positive-sequence fundamental current under unbalanced three-phase conditions. Second, considering the impedance ratio characteristics of the distribution network, while reactive power voltage regulation is common, active power regulation is more effective in high-resistance distribution networks. A grid-forming model-based active and reactive power coordinated voltage regulation method is proposed. This method uses synchronous control to establish a virtual three-phase voltage internal electromotive force, forming a comprehensive compensation strategy that combines power quality improvement and active voltage support, exploring the potential of energy storage DSTATCOM applications in distribution networks. Finally, simulation and experimental results demonstrate the effectiveness of the proposed control method. Full article

Epilepsy remains a widespread neurological disorder, with approximately 30% of patients showing resistance to current antiepileptic therapies. To address this unmet need, a series of 2-(isoindolin-2-yl) esters derived from natural amino acids were designed and evaluated for their potential interaction with the GABA_A receptor. Sixteen derivatives were subjected to in silico assessments, including physicochemical and ADMET profiling, virtual screening–ensemble docking, and enhanced sampling molecular dynamics simulations (metadynamics calculations). Among these, compounds derived from the aromatic amino acids, phenylalanine, tyrosine, tryptophan, and histidine, exhibited superior predicted affinity, attributed to π–π stacking interactions at the benzodiazepine binding site of the GABA_A receptor. Based on computational performance, the tyrosine and tryptophan derivatives were synthesized and further assessed in vivo using the pentylenetetrazole-induced seizure model in zebrafish (Danio rerio). The tryptophan derivative produced comparable behavioral seizure reduction to the reference drug diazepam at the tested concentrations. The results implies that aromatic amino acid-derived isoindoline esters are promising anticonvulsant candidates and support the hypothesis that π–π interactions may play a critical role in modulating GABA_A receptor binding affinity. Full article

Plasmodium falciparum is the causative agent of malaria, a parasitic disease that affects millions of people in terms of prevalence and is associated with hundreds of thousands of deaths. Current antimalarial medications, in addition to exhibiting moderate to serious adverse reactions, are not efficacious enough due to factors such as drug resistance. In silico approaches can speed up the discovery and design of new molecules with wide-spectrum antimalarial activity. Here, we report a unified computational methodology combining a perturbation theory machine learning model based on multilayer perceptron networks (PTML-MLP) and the fragment-based topological design (FBTD) approach for the prediction and design of novel molecules virtually exhibiting versatile antiplasmodial activity against diverse P. falciparum strains. Our PTML-MLP achieved an accuracy higher than 85%. We applied the FBTD approach to physicochemically and structurally interpret the PTML-MLP, subsequently extracting several suitable molecular fragments and designing new drug-like molecules. These designed molecules were predicted as multi-strain antiplasmodial inhibitors, thus representing promising chemical entities for future synthesis and biological experimentation. The present work confirms the potential of combining PTML modeling and FBTD for early antimalarial drug discovery while opening new horizons for extended computational applications for antimicrobial research and beyond. Full article

Background: Chronic musculoskeletal disorders (CMDs) represent a leading cause of global disability and diminished quality of life, and they are often resistant to conventional physiotherapy. Emerging technologies such as virtual reality (VR), augmented reality (AR), and exergaming are increasingly used to enhance rehabilitation outcomes, yet their comparative effectiveness remains unclear. Objective: To systematically evaluate the effectiveness of VR, AR, and exergaming interventions in improving pain, function, balance, and psychological outcomes among adults with CMDs. Methods: This systematic review and exploratory meta-analysis followed PRISMA 2020 guidelines and was prospectively registered (PROSPERO: CRD42024589007). A structured search was conducted in PubMed, Cochrane CENTRAL, Scopus, and PEDro (up to 1 May 2025). Eligible studies were randomized controlled trials (RCTs) involving adults (≥18 years) with CMDs receiving VR, AR, or exergaming-based rehabilitation. Risk of bias was assessed using the PEDro scale and the Downs and Black checklist. Where feasible, standardized mean differences (SMDs) for pain outcomes were pooled using a random-effects model. Results: Thirteen RCTs (n = 881 participants) met the inclusion criteria. Interventions spanned immersive VR, AR overlays, exergaming platforms (e.g., Kinect, Wii), and motion-tracking systems. Pain, function, and quality of life improved in most studies. An exploratory meta-analysis of eight RCTs (n = 610) yielded a significant pooled effect favoring VR/AR interventions for pain reduction (SMD = −1.14; 95% CI: −1.63 to −0.75; I² = 0%). Exergaming showed consistent improvements in physical performance, while immersive VR was more effective for kinesiophobia and psychological outcomes. AR was underrepresented, with only one study. Risk of bias was generally low; however, publication bias could not be excluded due to limited funnel plot power (n < 10). Conclusions: VR, AR, and exergaming are effective adjuncts to conventional rehabilitation for CMDs, improving pain and function with high patient adherence. Nevertheless, gaps in long-term data, economic evaluation, and modality comparison persist. Future RCTs should address these limitations through standardized, inclusive, and longitudinal design. Full article