Abstract:

Brown spot on the leaf sheath is an emerging disease of sweet corn (Zea mays L.) in Sinaloa, Mexico, with an unknown etiology. This study aimed to identify the causal agent of the disease and assess its pathogenicity on commercial sweet corn hybrids. Bacterial strains were isolated from symptomatic leaf sheaths collected from commercial fields. Identification was performed through biochemical profiling (API 50CHB/E), pathogenicity tests on alternative hosts (potato, onion, celery), and molecular analysis (16S rRNA gene sequencing and phylogenetic reconstruction). Pathogenicity and virulence were confirmed by inoculating four sweet corn hybrids in a greenhouse. The strains were Gram-negative rods, identified as Burkholderia gladioli based on biochemical profiles and molecular data (99.8% 16S rRNA similarity; phylogenetic clustering within the B. gladioli clade). In greenhouse trials, the strains induced brown spot lesions on the leaf sheaths of all tested hybrids, replicating field symptoms fulfilling Koch’s postulates. This is the first report of B. gladioli as the causal agent of brown spot on the leaf sheath of sweet corn in Mexico. The pathogen’s broad host range highlights its potential as an emerging threat to horticultural crops in the region.

Abstract: Background. NOTCH receptors play a pivotal role in carcinogenesis. Upon ligand binding, a cascade of proteolytic cleavages mediated by ADAM proteases and the γ‑secretase complex activates the receptor, ultimately releasing the NOTCH intracellular domain (NICD). NICD translocates to the nucleus, where it regulates gene expression. This review mainly aims to evaluate γ‑secretase inhibitors (GSIs) as anticancer agents in preclinical and clinical settings, with a focus on their ability to block tumor progression, target cancer stem cells, and overcome resistance to standard therapies. Methods. A systematic search was conducted in the ISI Web of Science, PubMed, and Scopus databases, following PRISMA guidelines. The review included preclinical in vitro and in vivo studies, as well as clinical trials, investigating GSIs, either as monotherapy or in combination with other treatments, in TNBC, metastatic melanoma, PDAC, gastric cancer, and NSCLC. Exclusion criteria included duplicates, non‑English articles, studies published before 2010, studies on non‑cancer conditions, research unrelated to NOTCH signaling, and studies outside the selected cancer types. 69 articles were included and categorized into the five types of cancer analyzed (20 on NSCLC, 22 on TNBC, 11 on metastatic melanoma, 7 on GC, and 9 on PDAC). Of these, 60 studies correspond to preclinical research in the types of cancer and 9 studies correspond to clinical trials in the types of cancer except for GC (Figure 7). Two independent authors screened and extracted relevant data, with disagreements resolved by the corresponding author. Findings were synthesized qualitatively across cancer types under study. Results. This review summarizes therapeutic advances involving GSIs in cancers driven by oncogenic NOTCH signaling, based on the 69 articles included. Preclinical studies show that GSIs synergize with chemotherapy and radiotherapy, particularly in NSCLC, melanoma, and TNBC, and block EMT, overcome therapeutic resistance, and improve prognosis. Commonly used GSIs include DAPT and RO4929097, which enhance the efficacy of agents such as gemcitabine (PDAC), paclitaxel, osimertinib, erlotinib, and crizotinib (NSCLC), and 5‑FU (gastric cancer, TNBC). Promising strategies include combining GSIs with SAHA, ATRA, CB‑103, and other NOTCH signaling targeting molecules, either alone or with chemo‑ and radiotherapy. Clinical trials with GSIs, however, remain limited. RO4929097 is the most extensively tested GSI in clinical settings. PDAC trials combining GSIs with gemcitabine showed no benefit; melanoma trials yielded modest outcomes; and TNBC trials demonstrated partial responses to GSIs but overall low efficacy and significant adverse events. Discussion and Conclusion. Despite encouraging preclinical evidence, clinical trials with GSIs have underperformed, largely due to tumor heterogeneity, dosing limitations, and the non‑selective nature of γ‑secretase inhibition. Other NOTCH inhibitors such as DLL4 antibodies also resulted in partial responses and secondary effects. Future strategies should prioritize receptor‑specific NOTCH inhibitors, patient stratification based on NOTCH pathway activation, and optimized combination regimens. Emerging approaches include integrating immunotherapy with advanced technologies such as CRISPR, CAR‑T cells, and bispecific antibodies, as well as targeted delivery systems to enhance efficacy and reduce toxicity. Additional research directions include addressing the tumor microenvironment and EMT‑driven resistance, elucidating mechanisms of immune evasion, and inhibiting tumor angiogenesis. Finally, leveraging artificial intelligence and big‑data‑driven personalized medicine, including sex‑specific considerations, will be essential for improving patient outcomes.

Abstract: Background/Objectives: Biventricular volume (BVV) can be measured from non-contrast-enhanced CT images in patients undergoing coronary artery calcium (CAC) scoring. BVV correlates with left ventricular mass and may predict mortality risk in type 2 diabetes mellitus patients. This study examines the relationships among body size, age, and BVV using the Standard Human Index (SHI), which combines height and bodyprint (BP = k*height – body surface area, h-BSA; k=1 for females, 1.1 for males). We hypothesize that this novel indexing method enhances the discrimination of increased BVV in over-weight and obese patients and assesses the relevance of age in interpreting BVV changes. Methods: We analyzed CT data from 2,466 patients (1,606 women, 860 men; mean age 64 ± 11 years) referred for CAC scoring. Fatless BVV was measured semi-automatically, and we compared raw BVV values and BVV normalized for height, body surface area (BSA), and SHI across sex, age, and body mass index (BMI) categories. Results: BVV was signifi-cantly higher in males (414±97 ml) than females (297±66 ml) (p< 0.001). BVV decreased non-linearly with age, stabilizing in older patients. Normal-weight males had higher BVV than females (p< 0.001). Normalization for height, BSA, and SHI indicated that BSA did not effectively distinguish BVV changes in overweight and obese patients. Conclusions: The proposed index effectively diagnosed BVV increases in overweight individuals, while BSA indexing may be misleading. Age dependence of BVV challenges the validity of standards based on younger populations for detecting ventricular enlargement in older adults.

Abstract: Plants exhibit complex internal dynamics in response to environmental conditions, yet whether these dynamics reflect structured affective regimes remains unclear. This study investigates whether internal plant signals encode information about affective states defined relationally by sustained environmental conditions. Valence and arousal were operationalised using temperature, humidity, and residualised light. Using only internal plant measurements—including bioelectrical activity and volatile gas emissions—we evaluated whether machine learning models could decode affective structure without access to environmental variables. Binary classification revealed that valence was reliably decoded over longer temporal windows, whereas arousal required shorter windows, suggesting distinct underlying timescales. Direct multiclass quadrant classification proved unstable, but an Echo State Network capturing temporal dependencies achieved improved performance. These results indicate that plant internal dynamics carry a learnable, temporally extended signature of environmentally defined affective regimes, supporting an interpretation of plant affect as embodied environmental engagement.

Abstract: Strategic decision-making (SDM) has traditionally been viewed as a human activity based on judgment, experience, and negotiation among senior managers. These decisions are limited by attention constraints, incomplete information, and bounded rationality. Today, many firms embed artificial intelligence (AI) and algorithmic decision-making systems into strategic processes. In some cases, algorithms do more than support managers. They filter options, rank priorities, and strongly shape final decisions. This article asks when SDM remains meaningfully human and when it becomes effectively algorithmic in algorithmically mediated enterprises. The study uses a theory-building integrative review of 62 contributions from strategy, information systems, behavioural research, and governance. It compares human and algorithmic decision-making across five dimensions: interpretive authority, search structure, time orientation, accountability, and scalability. Based on this analysis, it develops a framework of human–AI decision structures. The framework identifies three main forms: human-dominant, sequential hybrid (AI-to-human or human-to-AI), and aggregated human–AI governance structures. Each form affects not only decision accuracy but also power, learning, agency, and accountability. The key challenge is not to defend purely human strategy. It is to design governance systems where decision rights, oversight, and contestability remain strong when algorithms act as active decision participants.

Abstract:

Uropathogenic Escherichia coli (UPEC) is a leading cause of urinary tract infections (UTIs) in companion animals. This study characterized 42 UPEC isolates recovered from dogs and cats at the University of Florida, College of Veterinary Medicine Diagnostic Laboratories between 2023 and 2024, focusing on antimicrobial resistance (AMR), virulence gene profiles, biofilm-forming ability, and phylogroup distribution of the isolates. Antimicrobial susceptibility testing (AST) showed that 40.48% of the isolates were resistant to at least one of the tested antibiotics, and 9.52% exhibited multidrug resistance (MDR). Phylogroup B2 was predominant (69.05%), and 61.90% of isolates demonstrated strong biofilm formation in artificial human urine. Virulence gene analysis revealed the presence of genes mediating adhesion (fim, pap, sfa), iron acquisition (fyuA, iro), biofilm formation (csg, bcs, pga, ycg/ymg), motility (fli, mot, flh), and stress response (oxyR, soxR/S, kat). Multiple plasmids carrying AMR and virulence determinants were also identified. The co-occurrence of the traits underscores the potential for persistent and recurrent infections, which can complicate therapeutic outcomes and facilitate horizontal gene transfer (HGT). The detection of antimicrobial-resistant, highly virulent UPEC strains possessing human UPEC traits in companion animals suggests the risk of zoonotic and reverse-zoonotic transmission, particularly in households with close pet–owner interactions. These findings emphasize the importance of judicious antimicrobial use, routine molecular surveillance, and integrated One Health strategies to mitigate the veterinary and public health threats associated with UPEC infections in companion animals.

Abstract: We show that Quantum Mechanical Hilbert space can be paradoxical under some group action and explore its physical consequences. (1) Is there a more natural way of resolving the paradox of Wigner’s friend without invoking the Heisenberg’s cut?; (2) We notice the qualitative similarities between the paradox and paradoxical sets and use it as a motivation to rigorously prove that the Hilbert space H of the harmonic oscillator is paradoxical under the group action induced by SO(2, 1); (3) This paradoxical nature of the Hilbert space H provides the natural resolution for the paradox by using the Axiom of Choice instead of the Heisenberg’s cut; (4) Finally, we show that due to the very same paradoxical nature of H, certain class of quantum gravities naturally emerge from Quantum Mechanics that mediates a self-decoherence of the system.

Abstract: The valorization of agricultural by-products as functional feed additives represents a promising strategy for sustainable aquaculture. This study evaluated the effects of dietary fermented longan peel (FLP), produced through enzymatic hydrolysis and Lactiplanti-bacillus plantarum fermentation, on growth performance, digestive physiology, gut morphology, innate immunity, and gene expression in Nile tilapia (Oreochromis niloticus) cultured under a biofloc system. Five experimental diets were formulated with graded FLP levels (0, 5, 10, 20, and 40 g kg-1) and fed to fish for eight weeks. Growth indices, including final weight, weight gain, and specific growth rate, improved significantly in fish receiving 20 g kg-1 FLP, following a strong quadratic response pattern. In vitro di-gestibility assays showed enhanced carbohydrate and protein digestibility, coinciding with increased intestinal amylase and protease activities. Histological analysis indicated that moderate FLP inclusion (10–20 g kg-1) promoted villus height, crypt depth, and epithelial organization. Innate immune parameters, including lysozyme, peroxidase, and alternative complement activity, were markedly elevated in serum and mucus, partic-ularly at 20–40 g kg-1 after eight weeks. Gene expression profiling revealed significant up-regulation of growth-related (IGF-1, GH, NPY-α, Galanin), immune-related (TLR-7, TNF-α, NFκB), and antioxidant-related (hsp70, Keap-1, nrf-2, GST-α) genes in fish fed higher FLP levels, with responses plateauing beyond 20 g kg-1. Overall, FLP supple-mentation at 20 g kg-1 optimally enhanced growth, digestive efficiency, intestinal health, and innate immune status. These findings demonstrate the potential of fermented longan peel as a cost-effective, bioactive, and sustainable functional feed ingredient for tilapia and other warm-water aquaculture species.

Abstract: (1) Background: Flavored craft beer is favored for its diverse and distinctive aroma compounds; however, traditional fermentation processes are often plagued by poor yeast flocculation, which leads to substantial beer losses and compromised production efficiency. Yeast immobilization technology has emerged as a promising strategy to improve fermentation performance, shorten the primary fermentation period, and mitigate beer loss. (2) Methods: In this study, a natural material–based carrier was developed for the immobilization of yeast, and its application in mango craft beer fermentation was systematically investigated. The optimal fermentation conditions were screened, and the physicochemical properties, nutritional composition, and volatile flavor profiles of the resulting mango craft beer were comprehensively evaluated. (3) Results: The results showed that the maximum mass gain of yeast after immobilization on the natural carrier reached 13.3%. Compared with free yeast, the immobilized yeast exhibited 1.58-fold higher average extract consumption rate and 1.39-fold higher alcohol production rate, while the primary fermentation period was shortened by approximately 33%. Under the optimized fermentation conditions, the mango craft beer achieved a sensory score of 81 points, with a β-carotene retention rate of 91.25%. Furthermore, the mango craft beer exhibited a more diverse profile of volatile flavor compounds and enhanced nutritional composition compared with the control. (4) Conclusions: Overall, the natural immobilization carrier developed in this study effectively enhanced yeast fermentation efficiency, shortened the primary fermentation cycle. These findings demonstrate its significant potential for cost reduction and efficiency enhancement in the production of flavored craft beer, providing a practical technical support for the industrial application of natural carrier-based yeast immobilization technology.

Abstract: Diabetic kidney disease (DKD) is one of the most serious complications of diabetes and the leading cause of end-stage renal disease worldwide. Recently, renin-angiotensin system inhibitors, non-steroidal mineralocorticoid receptor antagonists, sodium-glucose cotransporter 2 inhibitors, and glucagon-like peptide-1 receptor agonists have been proposed as the four pillars for treating DKD. To understand the molecular mechanisms by which these drugs improve DKD, we described the histological and molecular changes due to diabetes. Based on our understanding of the molecular changes in DKD, we present evidence on the efficacy of these drugs in improving DKD and discuss why such drugs improve the prognosis of DKD. In addition to diabetes and hypertension, insulin resistance, dyslipidemia and hyperuricemia are risk factors for DKD. Metformin, fibrates, and febuxostat have been reported to improve DKD, however, caution is required when administering these drugs to patients with renal impairment due to concerns about the onset of lactic acidosis, rhabdomyolysis, and deterioration of renal function, respectively. Imeglimin, pemafibrate, and dotinurad have similar chemical structures or effects to metformin, fibrates, and febuxostat, respectively, but are safer in patients with renal impairment. Furthermore, they have specific mechanisms to improve DKD and may offer new options for its treatment.

Abstract: This research examines the relationship between energy generation, electricity produc-11 tion, energy consumption, and economic welfare across countries classified by income 12 level: high-income, upper-middle-income, lower-middle-income, and low-income. It uses 13 annual panel data from 2000 to 2023 sourced from the World Bank’s World Development 14 Indicators (WDI). Based on the World Bank’s income classifications and data availability 15 during the study period, 152 countries were selected, including 49 high-income, 35 upper-16 middle-income, 43 lower-middle-income, and 26 low-income economies. Pedroni cointe-17 gration tests indicate a long-term equilibrium relationship among energy generation, elec-18 tricity production, energy consumption, and economic welfare across all income groups, 19 with Kao cointegration tests confirming these results as robustness checks. The study uti-20 lizes panel dynamic differenced and system Generalized Method of Moments (GMM) to 21 estimate the model. Results reveal a significant positive long-term relationship among the 22 main energy and welfare variables across all income categories. However, when broken 23 down by income class, high-income and upper-middle-income countries show positive 24 associations between energy metrics and economic welfare. In contrast, lower-middle-in-25 come and low-income nations exhibit negative associations. The study recommends poli-26 cies focused on improving living standards and overall economic welfare, especially 27 through providing consistent, affordable, and clean energy.

Abstract: Matrix mechanics describes the spectral emissions of hydrogen gas, but quantum mechanics concerns the emission and absorption of radiation by a single atom. To obtain the spectral emissions of a single hydrogen atom we introduce thermal energy in infinitesimal increments registering the spectral lines one by one until a complete spectrum is obtained. We describe the gradual increase of the internal quantum mechanical energy in a non-conservative system by integrating between two specific endpoints, the atomic orbitals, and two specific times, the period τ, which are the conditions necessary for Hamilton’s principle. Wave mechanics is shown to be limited to conservative systems. A complete quantum mechanics is formulated using energy-time conjugate variables as the time integral of a Lagrangian independently of Hamiltonian formulations that use position-momentum conjugate variables.

Abstract: Childhood obesity is a globally pervasive condition driven not only by lifestyle and environmental factors but also by complex molecular mechanisms. These mechanisms involve genetic predisposition, epigenetic regulation, hormonal signaling pathways, adipose tissue biology, immuno-inflammatory responses, and interactions with environmental endocrine disruptors. This review synthesizes current evidence from scientific articles, systematic reviews, and mechanistic studies to elucidate how molecular processes shape the development, onset, and progression of obesity in children. Understanding these pathways is critical for developing precise prevention strategies and targeted interventions.

Abstract: Background: Generative artificial intelligence (GenAI) is rapidly permeating healthcare; yet, U.S. clinicians still report mixed feelings about its reliability, impact on workflow, and ethical implications. Current data on provider sentiment are needed to guide safe, patient-centered AI implementation in healthcare. Objective: To assess U.S. healthcare providers’ perceptions of GenAI adoption, perceived usefulness, training needs, barriers, and strategies for safe integration. Methods: A nationwide, IRB-approved, cross-sectional survey was administered to healthcare professionals using Qualtrics. A convenience sample of clinicians was recruited via professional listservs and e-mail invitations. The 20-page questionnaire captured demographics, GenAI exposure, organizational adoption status, perceived usefulness (5-point scale), barriers, and mitigation strategies. SPSS v27 and Microsoft Excel were used for statistical analysis. Results: Of 130 respondents, 109 completed the core survey (completion rate 83.8 %). Participants were 38.5 % physicians, 16.5 % nurses, 12.8 % allied professionals, and 32.2% other providers; 54.2 % were women, and 64.8 % were ≥50 years. Overall, 86.9 % agreed that GenAI is useful in current patient care, rising to 92.9 % when asked about future usefulness. Only 42.4 % had received formal GenAI training, and just 23.2 % reported that their organization had begun adopting AI. The top perceived benefits were improved documentation/clerking (57.0 %) and error reduction (49.4 %). Dominant barriers included limited AI knowledge (24.7 %) and fear of job loss (16.9 %). Despite concerns, 72 % expressed willingness to support broader GenAI adoption, favoring human oversight (67.1 %) and staff training (60.8 %) as key safeguards. There were statistically significant findings in perceived AI usefulness by gender (χ²= 29.2; P&lt;.001); organizational adoption of AI (χ²= 31.6.2; P=.047) and where AI is most useful (χ²=101.1; P&lt;.001) by qualifications; and support for AI adoption by age (χ²= 18.0; P=.02). Conclusions: U.S. clinicians in our survey viewed GenAI positively but lacked the training and organizational infrastructure needed for confident use. Structured education programs and transparent, provider-led implementation strategies may accelerate responsible GenAI assimilation while addressing ethical and workforce concerns. Also, health administrators should use the efficiency gains to improve provider-patient relationships and clinicians' work-life balance while reducing clinician burnout rates.

Abstract: Text-attributed graph node classification is still a challenge since it needs to reason about the topology structure simultaneously with the free-text semantics. Although graph neural network can perform well on structural propagation,they tend to be blind for the details in the text associated with nodes. On the other hand, LLMs have excellent NLU skills and are weak on structured,multi-hop reasoning over network agents.To address the above gap, in this work we propose FinSCRA, a novel LLM-powered multi-chain reasoning framework to inject domain-aware reasoning capability into a financial LLM with parameters efficient fine-tuning. Specifically, our framework designs a hierarchy of structured reasoning chains (single-hint,parallel, cascaded, and hybrid methods to extract and fuse the semantic signals like sentiment, correlation, and risk signals in the nodes’ text.A fusion layer based on fuzzy logic fuses the results of different reasoning lines for better robustness and explainability.While FinSCRA is generic and can be applied to other types of text-attributed graphs, here we assess its performance on credit risk analysis in supply chain networks,on the task of entity relation extraction, in which entities are related through their financial relation and described with rich text reports; we show experimentally on realworld datasets that our model FinSCRA greatly outperforms graphbased as well as LLM-based baselines,as an accurate and explainable technique to perform node classification over complex networked systems.We release our code and models for further research on LLM-grap.

Abstract: We propose a causal-diamond formulation of semiclassical gravity where a finite-resolution boundary regulator (Coherency Screen) supplies the edge structure for a local Wheeler--DeWitt description. Dynamics are defined by an informational principle: for each diamond \( O \), the action is the relative entropy \( S_{\mathrm{rel}}(\rho_O\|\sigma_O[\lambda]) \) between the physical state and a reference family on a fixed algebra. In the modular/KMS regime, the vacuum is at entanglement equilibrium; the leading dynamics become a linear-response problem governed by the Hessian of relative entropy (Kubo--Mori metric). This Hessian organizes deformations into tensor, vector and scalar sectors, yielding Einstein stiffness, Yang--Mills susceptibilities and mass gaps. The resulting local EFT is organized by a heat-kernel expansion (identifying the leading \( R^2 \) operator) and is compatible with a spinorial transport structure. Edge-mode counting and Newton's constant \( G \) fix the resolution scale at \( M_s \sim 3\times 10^{13}\,\mathrm{GeV} \). Identifying \( M_s \) with stiffness saturation places the high-curvature regime in a plateau universality class, predicting a tensor-to-scalar ratio \( r \sim 10^{-3} \). We further discuss how this boundary logic constrains gauge and mass sectors, suggesting discrete coupling relations and a geometric hierarchy for charged leptons. The construction yields correlated, falsifiable targets tied to a single scale.

Abstract: Climate change presents a challenge for global viticulture due to rising temperatures and water stress, which accelerate grape ripening, increase sugar levels, and reduce acidity. This compromises wine quality and microbial stability, resulting in higher re-liance on sulfur dioxide (SO₂). However, SO₂ can inhibit desirable fermentations, in-cluding those carried out by non-Saccharomyces yeasts, which are key biotechnological tools for climate adaptation due to their ability to modulate acidity, aroma, and etha-nol. Therefore, alternative disinfection methods are needed to control wild microbiota without hindering inoculated yeasts. This review critically analyzes ozone (O₃) as a non-thermal disinfection technology for winemaking. It examines the antimicrobial mechanism of ozone, its efficacy against wine-related microorganisms, its impact on the physicochemical and aromatic parameters of grapes, and its practical viability. Ozone effectively reduces spoilage-causing microbiota while preserving crucial grape compounds and providing a favorable environment for novel fermentation biotech-nologies. Compared to other emerging technologies and SO₂, ozone offers a balanced profile: effective disinfection, minimal residues, cost-effectiveness, and compatibility with sustainable winemaking. Ozone is emerging as a promising alternative to facili-tate controlled fermentations and improve wine quality among the current climatic and oenological challenges.

Abstract: What mechanisms drive and shape the stepwise evolution from simple carbon-based materials (CBMs) to complex organisms and societies? This fundamental question remains unresolved because chemical, biological, and social evolution have often been studied in isolation. Here we propose the Carbon-Based Evolutionary Theory (CBET), which is grounded in rigorous integrative reasoning and supported by extensive empirical evidence, mathematical modeling, resilience to falsification, and cross-hierarchical explanatory power. CBET extends the natural selection mechanism from Darwinian theory and introduces the spirodynamic feedback mechanism. These dual mechanisms respectively drive and shape CBM evolution, resolving the aforementioned fundamental question for the first time and explicitly explaining the increasing orderliness in biological and social systems. Furthermore, CBET reveals the natural balances of competition versus collaboration, elimination versus inclusiveness, selfishness versus altruism, and individual versus collective interests. It thus establishes an evolutionary foundation for the social sciences and fosters the core ethics for harmonious societal development.

Abstract: Background/Objectives: Low-density cancellous bone can amplify crestal cortical strain around implants because trabecular support is reduced. Osseodensification (OD) compacts trabecular bone and may create a peri-osteotomy densified zone, but its strain-level effects in osteoporotic-like bone are unclear. Given that osteoporosis/osteopenia in aging populations reduce trabecular support and can increase crestal cortical loading, this study tested whether an OD-inspired peri-implant densified trabecular zone lowers high-tail crestal cortical strains versus conventional drilling in an osteoporotic-like cancellous model. Materials and Methods: A 3D finite element mandibular posterior segment (2.0-mm cortical shell and D4 cancellous core) was modeled with a 4.3×11.4-mm titanium implant and a cemented monolithic zirconia crown. CD used a 4.0-mm osteotomy in D4 bone. OD used the same osteotomy plus an axially varying concentric densified shell (D1→D3 radially) with minor buccolingual cortical expansion. The implant–bone interface was bonded. Static 100 N loads were applied axially and obliquely (45°). Outcomes were εeq, εmax, and εmin, summarized as mean top-10 nodal values. Results: OD reduced crestal cortical strains under both loads. Axial loading: εeq 1470→1210 µε (−17.7%), εmax 1420→1150 µε (−19.0%), |εmin| 900→683 µε (−24.1%). Oblique loading: εeq 3370→3040 µε (−9.8%), εmax 2510→2310 µε (−8.0%), |εmin| 3040→2770 µε (−8.9%). Oblique loading produced higher cortical strains than axial loading in both models. Conclusions: OD-inspired peri-implant densification attenuated high-tail crestal cortical strain demand in this osteoporotic-like model, whereas off-axis loading remained the dominant driver of elevated strain. These findings support occlusal/prosthetic strategies that minimize oblique forces and warrant experimental and clinical validation.

Abstract: Patient manual handling during positioning is widely recognised to have low evidence-based practices, which exposes healthcare practitioners (HCPs) to a high risk of work-related musculoskeletal disorders (WRMSDs). This study assessed experts’ opinions regarding challenges and best practices during manual handling for patient positioning in long-term care settings. A semi-structured interview was conducted with purposively recruited subject experts in the UK (n=9; aged 30-62 years). Interviews focused on challenges in patient manual handling, experts’ ideas about best practices, and suggested solutions to persistent challenges, and data were analysed thematically. Major gaps in training and in key aspects of positioning were evident, including patient bed mobility, postural management, and turning patients into side-lying. Experts asserted that realistic and comprehensive training structured on optimised use of low-tech equipment such as wedges, breathable pillows, sliding systems, and sleep systems may be more effectively implemented for safer patient handling, even for single-handed care settings. This study provided a novel model and recommendations to optimise practices in patient bed mobility, posture care, repositioning and turning into side-lying, aimed at improving patient outcomes and mitigating occupational risks.