Abstract: Understanding human disease requires frameworks that can connect molecular and cellular perturbations to systems-level dysfunction and clinical phenotype across time. Recent advances in single-cell and spatial profiling have revealed that cellular identity is dynamic and distributed across continuous state landscapes, while developments in electrophysiology, neuroimaging, and circuit analysis have underscored the importance of distributed neural dynamics in health and disease. In parallel, artificial intelligence (AI) has emerged as a powerful approach for analyzing high-dimensional, multimodal biomedical data and reconstructing biological relationships that are difficult to resolve using conventional methods alone. In this narrative review, we examine how AI-based methods can be used to map cellular and neural circuit state transitions in human disease and how these approaches may be integrated to support multiscale models of disease progression. We discuss current strategies for characterizing cellular state landscapes, including single-cell, spatial, trajectory-based, graph-based, and multimodal approaches, and we review AI-driven methods for decoding neural circuit dynamics from electrophysiological, imaging, and large-scale functional datasets. We further highlight bidirectional interactions linking cellular states, synaptic and microcircuit remodeling, circuit-level dysfunction, and behavioral or clinical outcomes, emphasizing disease progression as a sequence of coupled transitions across molecular, cellular, synaptic, and network scales. Finally, we discuss the implications of AI-integrated multiscale medicine for biomarker discovery, disease trajectory modeling, therapeutic window identification, and adaptive precision intervention, while addressing challenges related to causality, interpretability, validation, ethics, and clinical translation. Together, these developments support a shift from static classifications of disease toward dynamic, multiscale, and clinically relevant models that better reflect the evolving behavior of biological systems.

Abstract: The present study evaluated the effects of three β‑adrenergic agonists, salbutamol, clenbuterol, and terbutaline on growth performance and the kinetics of residue depletion in broiler chickens. A total of 100 Ross 308 chicks were randomly allocated to six treatment groups and one untreated control group. Each β‑agonist was administered via drinking water at two concentration levels (2.5 mg/L and 5 mg/L) starting on Day 19 of age. Body weight was monitored from Day 20 to Day 40 to assess growth performance. Additionally, residue depletion was investigated in breast muscle, liver, kidney, and feathers at predefined time points after treatment cessation. All β‑agonist‑treated groups exhibited significantly reduced body‑weight gain compared with the control group, regardless of compound or dose, indicating that none of the tested β‑agonists conferred growth‑promoting effects in broiler chickens under the conditions of this study. Residue analysis revealed rapid absorption and widespread tissue distribution of all three compounds, with the highest residue concentrations detected during the early post‑exposure period, particularly in kidney and liver tissues. Residue levels declined progressively during withdrawal and fell below the corresponding decision limits (CCα) in all edible tissues at later sampling points. Quantitative residue determination was performed using a validated liquid chromatography–tandem mass spectrometry (LC–MS/MS) method compliant with Commission Decision 2002/657/EC. The findings confirm that salbutamol, clenbuterol, and terbutaline do not improve growth performance in broiler chickens and are efficiently eliminated from edible tissues when appropriate withdrawal periods are observed. These results support existing regulatory restrictions on the use of β‑agonists in poultry production and provide additional evidence relevant to food‑safety risk management.

Abstract: Emodin is a naturally occurring anthraquinone and has been of great interest as a multi-target anticancer agent with potential anti-metastatic effects. There is a growing body of evidence that emodin inhibits the progression of cancer by regulating essential events of epithelial–mesenchymal transition (EMT) and extracellular matrix remodeling. It suppresses matrix metalloproteinases and other associated proteolytic enzymes, thus hindering tumor invasion and metastatic spread. Emodin also suppresses key EMT-related transcription factors, such as Snail, Slug and Twist resulting in lower expression of mesenchymal markers, recovery of epithelial phenotype and lack of cellular motility. These effects are mechanistically mediated by disrupting central oncogenic pathways including transforming growth factor-β (TGF-β)/Smad, Akt/mTOR, MAPK and other signaling pathways that promote EMT plasticity. Recent research also indicates that emodin has a role in regulating cytoskeletal organization, ROS signal, and interactions with the tumor microenvironment that promote metastatic behavior. Although there is strong preclinical evidence, there are still a number of translational gaps. This limits its possible therapeutic use due to low bioavailability, low stability, and inconsistent tumor responsiveness. Possible resistance mechanisms, such as the compensatory activation of other pathways such as Wnt/ β-catenin and survival signaling cascades, are not sufficiently characterized. There is also lack of clinical validation with few controlled trials assessing safety and anti-metastatic efficacy across different types of cancer. The future directions are to focus on optimization of formulation and delivery, improvement of the pharmacokinetics, patient stratification, biomarker-based guided, and rigorous comparisons of combination regimens with chemotherapy, radiotherapy, and targeted agents. These approaches can be used to achieve the full potential of emodin as a therapeutic candidate, which is a metastasis-modulating agent.

Abstract: Microplastics (MPs) are emerging contaminants that have been detected in human blood and tissues, raising concerns regarding systemic exposure and potential health effects. Internal MP burden mitigation techniques, nevertheless, are yet largely unexplored. We evaluated whether oral administration of chitosan derived from Procambarus clarkii (PCC) could reduce circulating MPs in humans via gastrointestinal sequestration in this pilot-controlled study. 11 healthy adults received PCC supplementation (0.8 g/day) for 15 days, while 10 matched controls received a placebo. Using stereomicroscopy, scanning electron microscopy (SEM), and micro-Fourier transform infrared spectroscopy (µFTIR), blood MP concentrations were quantified and characterised according to size, shape, and polymer type. At baseline, MPs were found in every subject. Following PCC supplementation, mean MP concentrations decreased from 1.84 ± 0.28 µg/mL to 1.34 ± 0.20 µg/mL (−26.3%, p < 0.01, paired analysis). The control group observed no significant differences. While polymer-resolved analysis consistently indicated reductions across major polymer classes, whereas size-resolved analysis indicated preferential reductions in intermediate particle fractions (11–50 µm). The circulating MPs' estimated mean residence time (MRT) was 58 ± 28 days. These findings provide preliminary evidence that chitosan-based gastrointestinal sequestration could potentially reduce the systemic MP burden in humans.

Abstract: Background: Therapeutic resistance following cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) plus endocrine therapy (ET) remains a key unmet need in hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2−) metastatic breast cancer (mBC). Treatment paradigms have advanced from non-targeted options, such as fulvestrant monotherapy or everolimus-based combinations, to precision medicine strategies, including inhibitors of the PI3K/AKT pathway, oral selective estrogen receptor degraders (SERDs), and novel ER-modulating agents, often guided by biomarkers and molecular surveillance. Methods: This narrative review synthesizes evidence from randomized clinical trials, real-world studies, and biomarker-driven analyses published from 2010 to 2026, with emphasis on next-generation sequencing (NGS)-guided genomic profiling, targeted pathway therapies, and circulating tumor DNA (ctDNA)-based proactive interventions in the post-CDK4/6i setting. This review was conducted and reported in accordance with SANRA recommendations for narrative reviews. Results: Early second-line standards, including fulvestrant and alpelisib (for PIK3CA-mutated tumors), established the basis for biomarker-guided treatment in hormone receptor–positive, HER2-negative metastatic breast cancer. With the widespread use of CDK4/6 inhibitors in the first-line setting, the optimal post-progression strategy has shifted toward combination approaches rather than single-agent endocrine therapy, as endocrine monotherapy has shown limited efficacy in the setting of acquired resistance. Multiple randomized studies have demonstrated that the addition of targeted agents to endocrine therapy results in significantly improved progression-free survival compared with hormonal therapy alone, supporting combination regimens as the preferred strategy after CDK4/6 inhibitor progression. Current evidence strongly supports that in hormone receptor–positive metastatic breast cancer progressing after CDK4/6 inhibitors, combination therapy with endocrine agents and targeted treatments should be favored over single-agent hormonal therapy, except in carefully selected patients with low disease burden, indolent biology, or frailty where treatment tolerability is a major concern. Precision-based trials have further refined this approach. Elacestrant improved progression-free survival in ESR1-mutated disease in the EMERALD trial, capivasertib demonstrated significant benefit when combined with fulvestrant in tumors harboring AKT/PIK3CA/PTEN pathway alterations in CAPItello-291, and inavolisib achieved both progression-free and overall survival improvement in PIK3CA-mutated patients with early relapse in INAVO120. These findings consistently reinforce that endocrine therapy combined with pathway-targeted agents provides superior clinical outcomes compared with endocrine therapy alone, particularly in patients previously treated with CDK4/6 inhibitors. Real-world analyses further confirm the effectiveness of these combination strategies across diverse clinical subgroups. Comprehensive genomic profiling has identified multiple resistance mechanisms including ESR1 mutations, PI3K/AKT/mTOR pathway activation, RB1 loss, and FGFR alterations, which frequently co occur in up to one third of tumors and contribute to reduced sensitivity to endocrine monotherapy, further emphasizing the importance of combination treatment strategies. Notably, while ESR1 and PI3K pathway alterations guide approved therapies, FGFR alterations remain early-phase targets without integrated standard-of-care options, though ongoing trials are evaluating selective FGFR inhibitors. Proactive switching approaches evaluated in SERENA-6 and PADA-1 demonstrate that serial circulating tumor DNA (ctDNA) monitoring can guide early therapeutic modification, extending endocrine-based disease control by approximately 5 to 7 months when ESR1 mutations are detected prior to radiographic progression. Conclusions: Post-CDK4/6i management increasingly relies on NGS-guided precision approaches, integrating pathway-specific therapies and ctDNA surveillance to tailor sequencing based on resistance profiles, prior ET response, and tumor heterogeneity. Future investigations into novel ER degraders and multi-targeted combinations hold potential to further optimize algorithms, extend non-chemotherapy options, and enhance survival in HR+/HER2− mBC.

Abstract: Bacteriophages are viruses that attack bacterial cells, resulting in their lysis. Since the emergence of antibiotic resistance, phages have gained attention from the scientific community and are being explored for their potential use as anti-microbial agents. Since their discovery, naturally occurring wild-type phages have been used as anti-microbial agents. Though usage of antibiotics is confronted with problems, antibiotic resistance being the most pronounced, phages also have limitations, such as harboring toxin genes, not always lytic in nature, being involved in transduction, not having a broad host range, having a short life in the body due to mammalian immune response, and being attacked by bacterial anti-phage defense mechanisms. Modern approaches to phage therapy can address these problems associated with conventional phage therapy. These modern approaches include genetic phage engineering and using phage-derived enzymes, such as depolymerases and endolysins, in their wild-type form as well as in genetically engineered form. Genetic engineering has been performed on lytic, lysogenic, and filamentous phages for desired targeted results. In this review, we discuss the previous studies that have investigated these modern approaches for phage therapy against bacterial infections. Advantages and disadvantages of phage therapy are being discussed, and it is discussed how the use of modern approaches can affect different aspects of phage therapy.

Abstract: The photoreduction of CO2 is a growingly interesting research topic due to the intriguing possibility of producing solar fuels through a concerning pollutant. TiO2 photocatalysts were the first materials used for this application, but since then, various strategies have been developed to optimise the catalytic performance and operating conditions to obtain competitive yield. This review presents the findings of the last decade of research on dif-ferent semiconductors, TiO2 and g-C3N4 and their composites. The main features of the re-action and its key issues are first overviewed, focusing on the effect of different reaction conditions on the performance and recalling the mechanism of the reaction. The strategies developed to overcome the challenges of this demanding reaction are described in the fol-lowing paragraphs, including the use of dopants or co-catalysts, of heterojunctions be-tween different semiconductors and the use of electron transfer mediators. Finally, some unifying concepts are summarised, suggesting the calculation of the stored energy amount and the relative efficiency to allow a safer comparison between literature data collected under widely variable conditions and leading to different products.

Abstract: Fresh-cut vegetables are perishable products, which means they are prone to rapid physiological and microbiological degradation, leading to a quick deterioration in appearance, a decline in the organoleptic and nutritional properties, and increased losses. Therefore, new solutions are being sought to ensure safety and extend their shelf life. This review focuses on the quality and shelf-life stability of fresh-cut vegetables that have undergone heat shock treatment before or after minimal processing. The aim was to collect and present studies showing the beneficial effects of thermal shock on fresh-cut vegetables. Most studies have been conducted using hot water as a heat carrier, but hot air and steam have also been tested. Experimental data showing the combined effects of thermal shock and other physical or chemical methods are also presented. The collected data serve as guidelines for future research aiming to optimize methods and for use in the minimal processing of vegetables on an industrial scale.

Abstract: This introduction to Overreach: The Deadly Price of Regulatory Surveillance explores the complex interplay between pharmaceutical knowledge, government regulation, and individual autonomy in the United States. The text argues that Americans’ unprecedented consumption of pharmaceuticals is the product of a century-long alliance between medical professionals seeking to eliminate competition and a federal government expanding its regulatory domain. This alliance forged the concepts of “pharmaceutical fact,” the regulatory structures defining drug legitimacy, and “pharmaceuticalization,” the process by which increasing aspects of human life are framed as pharmaceutical problems. These frameworks, the author contends, are not neutral but constitute a sociopolitical system that determines who has authority over medical decisions and the limits of personal autonomy. Drawing on the work of Thomas Szasz, the critique highlights the evolution of the “Therapeutic State,” where state power and medical authority become inseparably linked, resulting in surveillance, behavioral control, and exclusion from necessary medicines for those outside the system. The book traces how professional organizations, in partnership with federal agencies, used regulation to enforce their definitions of scientific fact, transforming both the nature of medicines and the roles of those who dispense them. Through the lens of Nico Stehr’s “knowledge capitalism,” the text demonstrates that pharmaceutical knowledge has been turned into monopoly property, enforced through legal and regulatory mechanisms like the FDA and international agreements such as TRIPS. This transformation, the author asserts, underlies the economic and social power of the pharmaceutical industry, shaping access to medicines and the governance of individual bodies. The introduction frames the book’s central inquiry: whether the current system serves patients or entrenches a regime of knowledge monopolism and state authority.

Abstract: Purpose: To describe a slit-modified 23-gauge infusion trocar designed to enable early postoperative hypotony-free sclerotomy closure by allowing scleral suturing prior to complete trocar removal, and to report initial clinical outcomes in eyes with proliferative diabetic retinopathy with or without vitreous hemorrhage (PDR+H and PDR). Methods: A standard 23-gauge metallic (titanium) trocar was modified by creating a longitudinal slit that permits passage of a suture needle while the trocar remains partially engaged within the scleral tunnel. At the end of pars plana vitrectomy, a transscleral suture was placed through the slit with the knot prepared prior to trocar removal, followed by simultaneous trocar extraction and suture tightening. Eighteen consecutive patients undergoing vitrectomy for PDR (14 with vitreous hemorrhage [PDR+H], 4 without) were included. Intraocular pressure (IOP) was recorded preoperatively, immediately after sclerotomy closure (postoperative baseline), and at 8 and 24 hours postoperatively. Primary outcomes were postoperative IOP stability and wound leakage. Secondary outcomes included early hypotony, postoperative hemorrhage, choroidal effusion, and the need for additional suturing. Results: All procedures were completed without intraoperative complications. Mean IOP was 14.83 ± 2.50 mmHg preoperatively, 13.33 ± 1.53 mmHg immediately after closure, 14.17 ± 3.01 mmHg at 8 hours, and 15.17 ± 1.79 mmHg at 24 hours. No cases of wound leakage or early postoperative hypotony were observed in either subgroup. One eye exhibited a transient IOP increase at 8 hours; no choroidal effusion, postoperative hemorrhage, or need for secondary suturing occurred. Endotamponade consisted of balanced salt solution (BSS) in 8 eyes, SF6 in 7 eyes, silicone oil in 2 eyes, and air in 1 eye. Conclusions: The slit-modified infusion trocar enables secure, hypotony-free closure of the infusion sclerotomy by eliminating the open-wound interval during trocar removal. This simple biomedical device modification provides stable early postoperative IOP across different tamponade agents and appears safe and feasible in high-risk eyes with PDR.

Abstract: Background: COVID-19 not only primarily affects the respiratory system, but renal involvement is increasingly recognized. Prerenal acute kidney injury (AKI) is a common and potentially reversible complication driven by hypovolemia, hypoxia, systemic inflammation, and hemodynamic instability.Case Presentation: A 60-year-old male presented with fever, dry cough, dyspnea, oliguria, and generalized weakness. Laboratory findings revealed elevated blood urea nitrogen and serum creatinine, a high BUN/creatinine ratio, low urine sodium (18 mmol/L), high urine osmolality (650 mOsm/kg), and a low fractional excretion of sodium (0.67%), consistent with prerenal AKI. Chest imaging suggested viral pneumonia, and RT-PCR confirmed COVID-19 infection. Renal ultrasonography showed normal kidney structure with reduced renal perfusion. The patient was diagnosed with stage II prerenal AKI secondary to COVID-19. Management included oxygen therapy, prompt fluid resuscitation with lactated Ringer’s solution, anticoagulation, and supportive care. Renal function and urine output improved within 48 hours without the need for renal replacement therapy.Conclusion: COVID-19 can precipitate prerenal AKI through hypovolemia, hypoxia, and inflammation-mediated hemodynamic disturbances. Early diagnosis using urinary biomarkers and prompt fluid resuscitation can lead to complete renal recovery.

Abstract: We investigate the problem of stable signal estimation under irregular observation conditions characterized by missing samples, heteroscedastic noise, and reportability constraints. In such environments, the primary engineering challenge arises from the severe curvature distortion of the objective landscape, which renders traditional Euclidean gradient methods numerically unstable. To address this, we propose a layered information-geometric framework for stable estimation on a distorted statistical manifold.The architecture consists of three integrated components: (i) a deterministic basin-safe front-end that resolves global navigation on the non-convex information landscape; (ii) a diagonal-Fisher local refiner that performs local metric normalization to correct for geometric scaling under irregular weighting; and (iii) a PT-even gatekeeper that acts as an engineering feasibility constraint by restricting the optimization trajectory to the reportable subspace. As a concrete structured path within this layered estimator, the QFRT branch—a Quaternionic Fourier–Ramanujan representation used here as an arithmetic-periodicity anchor under shared whitening and weighting—serves as a structured source of robustness under gappy observations without altering the bounded scope of the present technical claim.Across a locked stress matrix, the resulting hybrid estimator exhibits a two-layer gain structure. First, a general refinement gain in RMSE_ω is achieved via curvature-aware updates in the classical-tangent regime. Second, a specific PT-sensitive gain emerges when nuisance-coupled sectors become observable, effectively suppressing non-reportable "ghost-mode" leakage (|z| ≈ 0) where unprojected baselines suffer from substantial parameter drift. Mechanism diagnostics support a seed-path shielding interpretation: the classical front-end resolves the ω-dominant basin selection problem, shielding the downstream PT-aware refinement from unfavorable seed geometry. The resulting contribution is a technical methods framework for auditable stable estimation under missing and heteroscedastic observations.

Abstract: Post-compression based on self-phase modulation (SPM) is widely used for femtosecond pulse shortening. However, the influence of the driving beam wavefront on different compression schemes remains unexplored. Using a Yb-doped fiber laser (230 fs, 200 kHz), we experimentally compare pulse compression in a hollow-core fiber (HCF) and a multi-pass cell (MPC). The HCF compresses pulses to 27 fs with an efficiency of approximately 55% and improves beam quality via modal filtering. The MPC achieves 34 fs pulses with an efficiency of approximately 90% and exhibits a quasi-waveguide mode-filtering effect, substantially enhancing output wavefront quality even when the input wavefront is poor. High-harmonic generation (HHG) experiments show that the HCF-driven source yields a higher photon flux (1.25 × 10¹¹ photons/s) compared to the MPC-driven source (4.95 × 10¹⁰ photons/s). Using a second Yb-doped fiber laser (223 fs, 100 kHz), a cascaded MPC–HCF scheme generates 7.5 fs pulses with an overall efficiency of approximately 70%, enabled by employing a larger-core HCF in the second compression stage. HHG experiments performed with the compressed pulses demonstrate that spatial phase evolution is a critical parameter in post-compression design for such applications.

Abstract: Rapid identification of maize waterlogging is essential for post-disaster agricultural assessment, but most existing methods rely on multi-temporal imagery that is often unavailable immediately after extreme rainfall events. This study proposes SAB-DeepLabV3+, a semantic segmentation model for mapping waterlogged maize from single-date multispectral imagery within pre-extracted maize planting areas. Built on DeepLabV3+, the model integrates three task-specific modules: a Spectral-Spatial Information Enhancement Module to improve feature discrimination under spectral mixing, an Adaptive Multi-Scale Pooling Module to capture heterogeneous patch sizes, and a Boundary Enhancement Module to refine transition zones. A pixel-level dataset containing 12,198 image patches was constructed from 62 multispectral scenes collected across five major maize-producing cities in Heilongjiang Province, China, during 2022–2024. On the test set, SAB-DeepLabV3+ achieved a waterlogged-class IoU of 68.30%, mIoU of 80.37%, mF1 of 88.62%, and OA of 93.49%, outperforming DeepLabV3+. Leave-one-city-out evaluation further produced an average mIoU of 76.56% and a waterlogged-class IoU of 63.45%. These results indicate that single-date high-resolution multispectral imagery can support rapid and reliable maize waterlogging mapping.

Abstract: Pathogenic variants in the CLCN4 gene are associated with a rare X-linked neurodevelopmental disorder, Raynaud–Claes syndrome, characterized by intellectual disability, epilepsy, language impairment, motor deficits, stereotypies, and structural brain abnormalities. Although heterozygous females are often considered to be only mildly affected, severe phenotypes have also been reported, and the clinical presentation shows considerable heterogeneity. The present study aims to summarize the current knowledge on CLCN4-related neurodevelopmental disorders through a review of the available literature and to describe two additional patients carrying pathogenic CLCN4 variants, one male and one female. The female patient was found to carry a de novo heterozygous variant (c.2152C>T), while the male patient harbored a de novo hemizygous variant (c.949G>A). Clinical data were compared with those reported in the literature in order to identify phenotypic similarities and differences among patients previously described with the same mutations. Furthermore, in light of the literature review and the clinical data collected from our patients, we propose considering Raynaud–Claes syndrome as a Rett-like condition. This perspective expands the scope of differential diagnosis and underscores the importance of multidisciplinary and longitudinal diagnostic evaluation to improve clinical characterization, therapeutic management, and genetic counseling.

Abstract: Apathy is an increasingly recognized neuropsychiatric syndrome and predictor of cognitive decline, distinct from depression. Although type 2 diabetes mellitus is a well-established risk factor for cognitive impairment, longitudinal evidence examining whether apathy links diabetes risk to adverse cognitive outcomes remains limited. We used data from 4,571 U.S. adults aged ≥60 years without baseline memory problems enrolled in the U.S.Health and Retirement Study. Diabetes risk was measured using glycosylated hemoglobin (HbA1c), treated continuously. Apathy was derived from four CES-D items reflecting diminished positive affect and motivation. Outcomes included incident self-reported Alzheimer’s disease and related dementias (ADRD) and incident cognitive impairment. Accelerated time-to-failure Weibull models were used to estimate associations between HbA1c and time to each outcome. Mediation was tested using a product-of-coefficients approach incorporating survey weights. Higher HbA1c was associated with shorter time to ADRD (coefficient −0.09; 95% CI −0.16, −0.02) and cognitive impairment (−0.16; 95% CI −0.23, −0.09), as well as greater apathy (β = 0.01; 95% CI 0.007, 0.03). After including apathy in Weibull models, associations with ADRD (−0.07; 95% CI −0.14, −0.006; p = 0.032) and cognitive impairment (−0.14; 95% CI −0.21, −0.07; p < 0.001) were changed but remained significant. Indirect effects through apathy were statistically significant for both outcomes, indicating partial mediation. Overall, elevated diabetes risk was associated with accelerated onset of ADRD and cognitive impairment, with apathy partially mediating these relationships, highlighting apathy as a potential target for behavioral interventions in individuals with diabetes.

Abstract: Stepped spillways are engineered structures designed to mitigate the erosive effects of floodwaters on downstream riverbeds. Despite extensive research on spillways with slopes exceeding 26.6°, there is a notable gap in understanding energy loss mechanisms for slopes between 3.4° and 26.6°. This study aims to develop predictive models for energy dissipation in stepped spillways within this slope range, eliminating the need for complex friction factor calculations. Experimental data from air-water flow experiments on a large-scale stepped spillway facility inform the development of these models. The proposed models demonstrate strong correlation with experimental data (R = 0.79 - 0.99), offering a simplified and accurate approach to estimating energy losses.

Abstract: Predictive maintenance has become an essential component of smart manufacturing systems because it enables early detection of machine failures and reduces unexpected pro-duction downtime. However, conventional predictive maintenance approaches typically rely on centralized data collection and model training which may raise concerns regarding data privacy, communication overhead and data ownership in manufacturing environments. To address these challenges, this research proposes a privacy-preserving collaborative federated learning framework for predictive maintenance that can be deployed in distributed smart manufacturing systems. The proposed approach allows multiple factories to jointly train a machine failure prediction model without sharing raw data. In the framework, each factory trains a local multilayer perceptron (MLP) model using its own machine operational data, while a central server aggregates local model parameters using the Federated Averaging (FedAvg) algorithm to construct a global predictive model. The proposed framework was evaluated using the publicly available AI4I 2020 predictive maintenance dataset where multiple factories are simulated by partitioning the dataset into distributed clients. Experimental results show that the federated learning model achieves performance comparable to centralized machine learning baselines, reaching an accuracy of 99.93%, precision of 1.000, recall of 0.980 and F1-score of 0.990 while still preserving data privacy and IP protection across distributed participants.

Abstract: This position paper argues for a rebuttable presumption against AI-attributed layoffs, challenging the hardening managerial default that equates model-addressable task exposure with inevitable worker redundancy. We demonstrate that while generative AI compresses routine workflow substrate, it simultaneously expands a role's elevation space---the critical human layer of judgment, exception handling, orchestration, and institutional accountability. We formalize this dynamic to show that apparent automation ceilings are frequently local artifacts of frozen job designs rather than immutable technological frontiers. Driven by an emerging strategic pattern where firms explicitly use labor cuts to self-fund AI investments, we advance an elevate-first rule: organizations must systematically attempt workflow redesign, paid upskilling, internal mobility, and apprenticeship preservation before declaring headcount redundant. To operationalize this standard within the AI research and deployment community, we propose the Workplace AI Transition Card for transparent transition reporting and introduce an Elevation Impact Factor (EIF). Ultimately, we argue that beneficial AI must be evaluated not merely by throughput or substitution rates, but by its capacity to move the human value frontier outward and sustain long-term epistemic resilience.

Abstract: Background and Purpose: Tumor progression is sustained by a tightly coupled biochemical network linking aerobic glycolysis, extracellular acidification, and glycocalyx-dependent membrane signaling. This study evaluates glucosodiene, a non-enzymatically generated glucose-derived glycosidic system, as a multi-axis perturbant capable of simultaneously modulating metabolic flux, pH homeostasis, and glycan architecture. Methods: A translational framework was constructed integrating chemical synthesis modeling, spectroscopic validation (¹H NMR, ¹³C NMR, FTIR), nanostructured formulation analysis (glucosodiene-loaded nanoferrites, GLONF), in vitro cytotoxicity assessment, preclinical murine data, and early human case-based observations. Results: Structural analysis supports glucosodiene as a 1→2 glycosidic glucose derivative with preserved hydroxyl-rich architecture and altered stereochemical properties. In vitro, no detectable cytotoxicity was observed in BJ1 fibroblasts up to 100 µg/mL (LC₅₀ not reached). In vivo, GLONF administration (50.4 mg/kg/day) in Ehrlich solid tumor-bearing mice resulted in a significant reduction in tumor weight and size compared to untreated controls (p < 0.01), with the most pronounced effect observed in the post-treatment group. This was accompanied by normalization of hepatic biomarkers, as ALT decreased from 47.0 to 34.8 U/L and AST from 306.4 to 199.0 U/L. Antioxidant systems were restored, with GSH increasing from 0.67 to 2.07 mmol/g and SOD from 58.7 to 97.7 U/g, alongside a marked reduction in lipid peroxidation, reflected by a decrease in MDA from 166.8 to 79.1 nmol/g. Molecular analysis demonstrated attenuation of proliferative signaling (PCNA) and modulation of p53-associated stress response pathways. Early clinical observations (n = 3) showed rapid symptomatic improvement by day 5 and metabolically favorable imaging responses within 15–20 days, including PET-documented regression and biomarker reduction, where ALP declined from 700 to 280 U/L and CA15-3 from 146.6 to 78.1 KU/L. Mechanistic Interpretation: Glucosodiene is proposed to reduce effective glycolytic throughput, attenuate lactate-driven extracellular acidosis, and disrupt glycocalyx integrity via altered glycosylation dynamics, thereby reconditioning tumor metabolic and signaling states. Conclusion: Glucosodiene represents a glucose-derived systems-level perturbant targeting the integrated metabolism–microenvironment–glycocalyx network, warranting further mechanistic and translational validation.