University of Fairfax

With high-stakes industries such as healthcare, finance, and autonomous systems, an increasing number of cognitive artificial intelligence are being utilized, which presents new challenges for developing calibrated trust. The complexity of trust involves balancing reliance and skepticism. Mistrust and misalignment cause complacency towards automation, premature skepticism, and outright rejection of the automation systems. Previous literature describes trust via isolated theoretical perspectives (cognitive load theory, expectancy-disconfirmation theory, algorithmic fairness). But these analyses examine trust in fragments and overlook important multidimensional dynamics, as well as failing to sufficiently quantify the principles of human-centered design and advanced ensemble architecture to an underdeveloped extent for capturing nonlinear sociotechnical phenomena. This research presents the first synthesized and integrated model to examine trust using a psychological, organizational, and computationally grounded approach. The integrated model uses engineered human-centered metrics such as Trust Stability Index (TSI), Bias Penalty Factor (BPF), and Cognitive Stress Aggregate (CSA), combined with rigorous mathematical formulations and advanced Sobolev-space functional analysis. Of 16 models analyzed with varying architecture and ensemble methods, the Stacking Ensemble achieved the best performance ( R^2 = 0.9489, RMSE = 2.06, MAE = 1.54). Overall analysis of the model yielded excellent generalization, a high level of noise tolerance (96.98

O parto é um acontecimento natural, sendo uma das experiências mais complexas e subjetivas da vida de uma mulher, motivo pelo qual observa-se a importância de ações de cuidado individualizadas, humanizadas e voltadas à promoção de maior nível de conforto, segurança, humanização e alívio de dores para tais mulheres, papel em que se destaca a atuação do fisioterapeuta. Adotou-se como objetivo geral do presente artigo compreender como a fisioterapia obstétrica promove o alívio da dor durante o trabalho de parto. Utilizou-se a metodologia de pesquisa bibliográfica e qualitativa, realizada através de uma revisão bibliográfica de literatura, com base na busca, análise de conteúdo e escolha de publicações nas bases de dados dos portais da Biblioteca Virtual em Saúde, LILACS e SciELO. Após leitura e análise dos estudos selecionados, destacou-se que a fisioterapia obstétrica tem papel indispensável no alívio da dor de gestantes durante o trabalho de parto, ofertando benefícios significativos à sua saúde, bem-estar, conforto e segurança. Além disto, constatou-se que a atuação do fisioterapeuta através do uso de abordagens não farmacológicas e implementação de práticas como exercícios físicos e respiratórios, deambulação, mobilidade pélvica, massagens, utilização de bola suíça, terapia de calor e estimulação elétrica transcutânea impacta diretamente na diminuição de dores, assim como de quadros de ansiedade e outros desconfortos físicos, permitindo uma evolução fisiológica do trabalho de parto mais natural e a oferta de uma experiência mais humanizada e positiva para a gestante.

Background: Sepsis, a life-threatening organ dysfunction driven by a dysregulated host response to infection, causes profound muscle atrophy, weakness, and long-term morbidity in most survivors. Several chemokines (e.g., CXCL1, CXCL2, CXCL10, and CCL2) are elevated in septic mice and signal through CXCR2, CXCR3, and CCR2 receptors expressed on immune and skeletal muscle cells. We hypothesized that these chemokine pathways contribute to the sepsis-induced inflammation and muscle dysfunction, and that pharmacological inhibition of their receptors would attenuate skeletal muscle atrophy, weakness, and systemic inflammation during sepsis. Methods: Male C57BL/6 mice (n = 6/group) underwent cecal ligation and puncture (CLP) and received daily intraperitoneal injections of chemokine receptor antagonists (SB225002 for CXCR2, AMG487 for CXCR3, or BMSCCR2 for CCR2) or matched vehicles for 11 days. Body mass loss, and spleen weight were quantified as indices of disease severity and systemic inflammation. Tibialis anterior (TA) and soleus cross-sectional area (CSA) were assessed from OCT-embedded frozen sections. Soleus contractility was tested ex vivo. Group differences for morphological outcomes were analyzed using unpaired two-tailed Student’s t-tests (p < 0.05). Results: CXCR3 and CCR2 inhibition did not improve systemic outcomes or prevent muscle atrophy. In contrast, CXCR2 inhibition with SB225002 attenuated disease severity, reducing body mass loss (Vehicle: -7.3 ± 7.6%, SB225002: -1.2 ± 5.5%), preserving spleen weight (Vehicle: 325.8 ± 56.6 mg vs SB225002: 221.1 ± 53.7 mg), and increasing TA CSA (Vehicle: 1656.6 ± 144.8 μm 2 vs SB225002: 2004.8 ± 189.8 μm 2 ). Soleus muscle mass and contractile force were unchanged across groups. Conclusions: CXCR2 inhibition preserved skeletal muscle morphology and mitigates systemic inflammatory indicators in septic mice, identifying CXCR2 mediated signaling as a key contributor to sepsis-induced myopathy. These findings support CXCR2 inhibition as a promising therapeutic strategy to protect skeletal muscle during sepsis. Funding: This work was supported by the National Institutes of Health (NIH) under grant number R21AG072011 and R01AR085126 to OL. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Artificial Intelligence (AI) is gradually changing the landscape of product management by improving how PMs gather, process, and evaluate data and options to manage products across their lifecycle. This review explores the new paradigm of Human-AI collaboration in the product management domain and looks at how AI functions effectively on the side of the product manager. It merges a variety of machine learning, predictive analytics, NLP, recommender systems, generative AI, and emerging agentic AI applications in customer and market discovery, product ideation, strategy and prioritization, road mapping, product development, product launch, and post-launch optimization. Specific focus is placed on task distribution, responsibilities and decision-making power between product manager and AI system. The study suggests that AI can offer many benefits in areas such as data analysis, pattern recognition, prediction, information synthesis, content creation, recommendations, and automation, while human involvement is still crucial for aspects of context interpretation, strategic decision-making, creativity, empathy, ethical considerations, and accountability. Yet, collaboration is hindered by issues such as algorithmic bias, hallucination, opacity, automation bias, over-reliance, privacy issues, deskilling and unclear accountability. The review thus suggests a framework of integration between product lifecycle activities, AI capabilities, human expertise, collaboration mechanisms, governance and organizational outcomes. The framework also emphasizes how product managers will be moving away from AI-enabled product management and toward agentic systems where product managers will take on more supervisory, orchestrating, evaluating and governing roles. Lastly, the review pinpoints research priorities related to human-AI task allocation, trust calibration, autonomous agents, measurement of collaboration, responsible AI, and end-to-end empirical evaluation.

Nigeria’s agrifood system supports employment, income generation, and food security, but post-harvest losses of perishable crops, especially leafy vegetables, threaten these benefits. This study examined the magnitude, profitability implications, and determinants of post-harvest losses in leafy vegetable production in Southwest Nigeria. Primary data were collected from 240 leafy vegetable producers selected through a multistage sampling procedure. Data were analysed using descriptive statistics, budgetary analysis, post-harvest loss estimation, and a two-stage least squares regression model. Respondents had a mean age of 41.8 years, average household size of 5.6 persons, and mean farming experience of 8.9 years; 68.3% were male, 66.7% married, 41.7% had secondary education, 28.3% accessed credit, and 25.0% had extension contact. Average post-harvest loss was 33.49%, with Telfairia occidentalis recording the highest loss at 37.78%, followed by Amaranthus spp. and Corchorus olitorius. Despite these losses, leafy vegetable production remained profitable, with return on investment ranging from 2.8 to 4.4. The 2SLS results showed that household size and storage costs significantly increased post-harvest losses, while education, farming experience, farm size, and access to credit significantly reduced them. Major constraints were price volatility, inadequate capital, poor road networks, and weak extension services. The study concludes that reducing post-harvest losses through improved preservation methods, cold chain infrastructure, access to agrifinance, and digital market linkages can enhance food availability and rural livelihoods.