Abstract: Digital Transformation (DT) increasingly relies on project-based organizing to develop and deploy new capabilities, yet corporate innovation projects frequently stall not for lack of ideas but because of recurring governance and resource-commitment bottlenecks. This study presents a micro-longitudinal, AI-enabled, and human-reviewed analysis of 711 episodes drawn from 28 weekly project governance meetings across two corporate startup initiatives participating in the same internal incubation program, conducted between November 2024 and April 2025. Employing a six-stage analytical pipeline that combines episode-level segmentation, linguistic tension markers, and a large language model (LLM) classifier, we identify 28 decision-relevant governance tensions, which are then abductively grouped into 13 project governance dilemmas and mapped onto Teece's dynamic capabilities framework (sensing, seizing, reconfiguring). The key finding is that 62% of dilemmas are structural in nature—reflecting persistent governance design tensions between autonomy and control, compliance and agility, and centralization and decentralization—and that 69% concentrate at the seizing stage, corresponding to resource-commitment and execution decisions. This pattern indicates a governance choke point in corporate DT projects that is structural and decisional rather than ideational. By shifting attention from lagging indicators (overruns) to governance-tension leading indicators, the approach supports earlier interventions to reduce decision latency and protect project delivery performance. We further synthesize two incubation-specific meso-level governance dilemmas—stakeholder engagement and compliance vs. agility—that serve as transmission mechanisms between macro structural constraints and micro-level decision bottlenecks. The AI-enabled pipeline is proposed as a replicable early-warning system for project governance tensions in organizations pursuing digital transformation.

Abstract: This study evaluates the performance of classical machine learning models for one-step-ahead agroclimatic time-series forecasting under degraded sensor-data conditions. The motivation is the operation of IoT-based field monitoring systems, where measurements may be noisy, incomplete, temporally irregular, and constrained by limited local storage and computational resources. Using a real meteorological dataset collected by a field weather station in the Dnipro region of Ukraine, we compared twelve regression models: Ridge Regression, Random Forest, Extra Trees, Gradient Boosting, HistGradientBoosting, Support Vector Regression, Linear SVR, KNN, PLSRegression, ElasticNet, Lasso, and MultiTaskElasticNet. The models were evaluated under five controlled experimental scenarios: baseline data, missing values, additive noise, reduced training history, and combined noise–missingness degradation. The results indicate that Ridge Regression provides the highest accuracy under clean and mildly degraded conditions, whereas HistGradientBoosting is more stable under severe combined degradation. These findings support the use of deployment-oriented model selection for agroclimatic forecasting; however, the proposed edge/fog workflow should be interpreted as a conceptual deployment direction unless validated by direct measurements of latency, memory footprint, and energy consumption on representative hardware. The study therefore provides a benchmark for robustness-oriented model selection rather than a fully validated embedded deployment framework.

Abstract: IoT/LoRa devices emit radiofrequency electromagnetic fields (RF-EMF) ensuring long-range, low-power communication, and their use in precision agriculture continuously expands. Thus the interest in the impact of low intensity but long-term EMF exposure on plants has increased. In this study, maize plants were exposed to 868 MHz EMF for the first 28 days of their development with soil-buried antennas. Plants were divided into three groups: Control, Sham-exposed, and EMF-exposed. Biological effects were followed on morphological, physiological and biochemical levels every week. The plant height values were fitted to Gompertz function to model the growth. The results showed slightly faster early development of EMF-exposed plants in about 21 days. The relative dry leaf biomas from EMF-plants was a bit higher than Control and Sham until 21st day. Chlorophyll fluorescence analysis (JIP-test) indicated photosynthetic stability. Antioxidant enzymes activity, antioxidant capacity, content of malondialdehyde, hydrogen peroxide and reducing sugars were measured, and principal component analysis was done for all parameters. In general, the developmental stage accounted much more than EMF exposure for most of the observed data variation. The results suggest that under the tested conditions, IoT/LoRa-emitted EMF did not provoke adverse effects in maize and acted as a modest modulator of physiological functions.

Abstract: Tumor segmentation in whole-body PET/CT imaging is crucial for precise disease evaluation and treatment planning. However, it remains challenging due to variability in lesion size, contrast, and anatomical distribution. Relying on manual segmentation makes the process time-consuming and prone to intra- and inter-observer variability. This work presents a whole-body tumor segmentation method developed for the AutoPET III challenge, where the goal is to build models that generalize across tracers and multi-center data. We employ the nnU-Net framework with a ResNet-based encoder as our baseline and systematically investigate the impact of training strategies, including intensity normalization, batch dice optimization, and data augmentation using CraveMix. Our experiments show that these strategies significantly influence model performance, particularly in reducing false positives and improving robustness to lesion variability. The best-performing configuration achieves a Dice score of up to 0.80 on the preliminary test phase, and our method ranked third in the AutoPET III challenge. The code is publicly available here: https://github.com/HussainAlasmawi/AutoPet_Final.

Abstract: Background: MASLD has a prevalence of almost one-third in adults worldwide and is not currently treated pharmacologically with a first-line therapy. Lifestyle change is still the foundation of management, however, the relative effectiveness of various behavioral and dietary intervention approaches is poorly defined in both metabolic and psychobehavioral outcome areas. Objective: We compared four classes of interventions, behavioral motivation support (BMS), biomarker-guided personalized diet management (BPDM), general diet education (GDE), and prescribed diet models (PDM) against usual care (UC) in patients with MASLD using network meta-analysis (NMA). Methods: Six electronic databases and two trial registerswere searched through 31 March 2026. Eligible studies were randomized controlled trials (RCTs) in adults with MASLD/NAFLD; risk of bias was assessed with the Cochrane ROB 2 tool, and evidence certainty was graded using the CINeMA-informed GRADE framework. A frequentist random-effects NMA was conducted using the R package netmeta; interventions were ranked by P-scores. Results: Fourteen RCTs (n = 1,805; published 2016–2026) were included. BMS showed the largest ALT reduction (MD −15.63 U/L, 95% CI −27.56 to −3.69; P-score 0.89) and ranked highest for dietary behavior and self-efficacy outcomes. BPDM ranked first for BMI (MD −1.84 kg/m², 95% CI −3.48 to −0.20; P-score 0.82), body weight (MD −5.80 kg; P-score 0.76), and HbA1c improvement (P-score 0.75). All certainty ratings were very low. Conclusions: These findings suggest that BMS and BPDM may target complementary outcome domains in MASLD; however, all estimates carry very low certainty, and adequately powered direct comparative trials are essential before clinical translation.

Abstract: Feline pseudomembranous cystitis (PMC) is an infrequent condition characterized by acute urinary disturbances. This study examines the diagnostic criteria, surgical interventions, and postoperative management strategies to furnish clinical guidance. A retrospective analysis was conducted on the clinical data of a 3-year-old neutered male golden tabby cat (weighing 4 kg) presenting with acute urinary retention. The diagnosis of PMC was established through clinical manifestations, abdominal ultrasonography, and laboratory tests, followed by cystotomy and targeted postoperative management. The surgical procedure lasted one hour with a blood loss of 5 mL, and spontaneous urination resumed by the fourth postoperative day. Ultrasound examination on the twelfth day revealed normal bladder mucosa, and the infection had resolved without recurrence during the follow-up period. Cystotomy with complete pseudomembrane removal effectively treats severe feline pseudomembranous cystitis. Careful preoperative assessment, precise surgery, and postoperative treatment guided by drug sensitivity greatly reduce risks and enhance outcomes. Key to recovery are thorough pseudomembrane removal and proper bladder irrigation.

Abstract: Climate change represents the defining global health challenge of the 21st century, with far-reaching implications for population health, health systems, and health equity. The acceleration of environmental change, evidenced by record-breaking global temperatures, extreme weather events, and ecological degradation, poses a direct threat to achieving Sustainable Development Goal 3 (SDG 3), which aims to ensure healthy lives and promote well-being for all. This manuscript examines the intersection of climate change and global public health in light of the outcomes of the 2025 United Nations Climate Change Conference (COP30) in Belém, Brazil. Drawing on recent global reports and emerging evidence, we explore how climate change exacerbates communicable and non-communicable diseases, undermines health system resilience, and disproportionately affects vulnerable populations worldwide. Particular attention is given to heat-related morbidity, infectious disease expansion, air pollution, food and water insecurity, displacement, gender inequities, antimicrobial resistance, and mental health impacts. The paper highlights the significance of the Belém Health Action Plan (BHAP), which places health more centrally within climate policy. However, major challenges remain, including voluntary implementation, financing gaps, and insufficient accountability mechanisms. We argue that achieving SDG 3 is no longer feasible without integrating climate adaptation and mitigation into health systems and policies.

Abstract: This study proposes a reproducible exploratory framework to link long-term territorial development with electricity demand in data-scarce contexts, and applies it to Ecuador’s Costa region. The pipeline combines three commonly available input streams: periodic census microdata, an official demand series, and macroeconomic aggregates. Socioeconomic heterogeneity across five non-uniform census rounds (1974, 1982, 1990, 2001, 2010) is summarized through Principal Component Analysis (PCA), and territorial indicators are projected to the demand horizon using low-order polynomial functions. Eleven regression specifications are compared on a log-transformed demand variable, and a rollingorigin backtesting scheme plus a 2020–2024 holdout are used for validation. The selected Trend OLS log model attains R2 = 0.551 and MAPE = 6.08%, and projects a regional demand of approximately 6,940 MW by 2050, equivalent to a compound annual growth rate of 3.45%. Beyond the Ecuadorian case, the results show that transparent, low-data pipelines based on harmonized census information, macroeconomic drivers and simple regression models can provide defensible medium- and long-term demand signals for planners in other emerging economies with limited high-frequency data.

Abstract: Congenital pericardial agenesis (CPA) is a rare anomaly that is often considered a benign incidental finding but may present with nonspecific symptoms and mimic structural heart disease. Its clinical relevance remains incompletely defined, particularly regarding the distinction between harmless anatomical variant and clinically significant condition. We present a retrospective two-center case series of four patients with imaging-confirmed CPA, combined with a narrative review of the literature aiming to evaluate the clinical spectrum, diagnostic challenges, and management implications of CPA. The clinical presentation of our patients was heterogeneous, ranging from incidental findings to chest discomfort and dyspnea. In all cases, initial echocardiography suggested alternative diagnoses, including right ventricular cardiomyopathy, atrial septal defect, or pericardial disease, leading to diagnostic uncertainty. Definitive diagnosis was established using multimodality imaging, particularly cardiac magnetic resonance and computed tomog-raphy, which demonstrated characteristic features such as cardiac levoposition and in-terposition of lung parenchyma. Three patients had complete left pericardial agenesis and one had a partial defect. All patients were managed conservatively, with no complications observed during follow-up.

Abstract: Background: Non-small cell lung cancer (NSCLC) is driven by distinct oncogenic al-terations with important therapeutic and prognostic implications. Noninvasive bi-omarkers that predict molecular status in surgically resectable disease may aid in their management. We investigated the association of preoperative primary-tumor SUVmax on PET/CT, smoking history, and corrected serum calcium levels with driver oncogenic alterations and PD-L1 expression in surgically resected NSCLC. Methods: We retrospectively studied 170 patients with surgically resected NSCLC at a single tertiary center. Resected tumors were assessed for EGFR, KRAS, and BRAF mu-tations, ALK and ROS1 rearrangements, and PD-L1 expression. Associations between molecular status, PD-L1 expression, and clinicometabolic parameters were evaluated using univariate analyses and multivariable regression models. Results: A driver alteration was detected in 51.2% of tumors, and 30% of evaluable cases showed high PD-L1 expression (≥50%). Corrected serum calcium was positively correlated with SUVmax and emerged as the strongest independent predictor retained in the final linear regression model, with pack-years also contributing independently. Most molecular subgroups did not show significant differences in SUVmax. EGFR-mutated tumors showed a trend toward lower SUVmax compared with EGFR wild-type tumors, although this did not reach statistical significance. Smoking history was not significantly associated with PD-L1 expression, and pack-years did not differ significantly across the molecular groups examined. Conclusions: In this cohort of surgically resected NSCLC, preoperative corrected se-rum calcium and smoking exposure were more closely associated with tumor meta-bolic activity than with specific molecular alterations. These findings suggest that simple clinical and biochemical parameters may provide complementary information, although their utility for discriminating individual molecular subgroups appears limited.

Abstract: This article develops a coherent set of outcome indicators for assessing progress in rural development in South Africa by directly linking policy objectives to measurable de-velopment outcomes. Drawing on a multidimensional conceptual framework encom-passing economic, social and environmental dimensions of rural development, the ar-ticle employs a document‑based research design analysing strategic plans of the De-partment of Rural Development and Land Reform, now known as the Department of Agriculture, Land Reform and Rural Development, for the period 2009–2025. Rural development objectives are first translated into ideal output indicators and subse-quently screened using internationally recognised indicator‑selection criteria to iden-tify outcome‑focused indicators aligned with policy intent. The analysis yields ten core indicators that capture key rural development outcomes, including employment, household income, housing quality, education, health, waste management, and sus-tainable natural resource use. These indicators strengthen the alignment between rural development policy objectives and measurable outcomes and provide a practical and replicable framework for monitoring rural development progress at both national and municipal levels. The proposed indicator set contributes to evidence‑based planning, monitoring, and accountability in efforts to promote a more inclusive and sustainable rural economy.

Abstract: Background: Autism spectrum disorder (ASD) affects approximately 1-2% of children worldwide, yet its etiology remains incompletely understood. Emerging evidence suggests that offspring of parents with autoimmune diseases show elevated autism prevalence. Notably, children of parents with psoriasis (OR 1.59), type 1 diabetes (OR 1.49-2.36), and rheumatoid arthritis (OR 1.51) demonstrate particularly strong associations.Hypothesis: I propose that autism may be conceptualized as an immune-metabolic disorder in which multiple pro-inflammatory cytokines—including TNF-α, IL-6, IL-1β, and IFN-γ—act through distinct molecular pathways yet converge on a common endpoint of mitochondrial dysfunction and cerebral energy deficiency. This convergence implies that it is the cumulative prenatal inflammatory burden, rather than any single cytokine, that drives the energy deficit. The resulting energy shortage may impair three critical processes: (1) synaptic pruning during neurodevelopment, (2) real-time social cognition including gaze processing and emotion recognition, and (3) protein synthesis of critical synaptic scaffolding molecules.The proposed mechanism is a chronic low-grade pro-inflammatory cytokine state—clinically silent, yet biologically consequential—arising from inherited inflammatory susceptibility and/or direct fetal exposure to elevated maternal inflammatory signaling during pregnancy. Unlike high-grade inflammatory states in which maternal and fetal survival are acutely threatened, low-grade cytokine elevations may proceed without conspicuous symptoms or detectable clinical signs, particularly when chronic. Although seemingly quiet, such a state may be insufficient to endanger maternal or fetal survival, yet sufficient to disrupt fetal brain bioenergetics during sensitive gestational windows—producing neonates who appear outwardly healthy at term while their neurodevelopmental trajectories have already been altered.I further propose that the well-documented "firstborn effect" in autism reflects maternal immune maladaptation during primigravid pregnancies. Additionally, for cases without parental autoimmune history, a speculative secondary mechanism is proposed: mitonuclear immune conflict, where paternal immune genes may partially recognize maternal mitochondria as non-self, generating endogenous pro-inflammatory signaling.Implications: This framework may provide an integrative account of disparate observations about autism pathophysiology and suggests that pro-inflammatory immune pathways and mitochondrial protection strategies merit further investigation for potential risk modification, particularly in pregnancies identified as high-risk through parental autoimmune or inflammatory disease. If supported by sufficient subsequent evidence, prenatal cytokine monitoring and corresponding clinical management—currently not part of routine obstetric care—may merit consideration by the medical community as a candidate strategy for autism risk reduction.

Abstract: Autoimmune diseases comprise a broad group of conditions that affect virtually any organ or tissue and share mechanisms of chronic, autoimmune-based inflammation. Once rare or unknown, they have become increasingly common in recent years, affecting individuals of all ages, including the elderly, due to the growing the number of older people. According to evolutionary medicine, if the frequency of a disease, or group of diseases, increases sharply over a few decades, the primary cause cannot be the effect of genetic alterations but rather the consequence of one or more alterations in the living conditions of the species. For autoimmune diseases, there is no environmental, dietary, or infectious factor that appears to correlate with their increased frequency. On the contrary, the epidemic of autoimmune diseases is likely correlated with serious alterations of our holobiont (i.e., our organism, the host species, plus the myriad of species coexisting with us). In particular, the critical factor appears to be the decreasing incidence of macroparasite infestations, without, however, excluding the effects of profound alterations in the bacterial ecosystems that are also part of our holobiont. The macroparasites modulate and curb the intensity of immune responses in order to survive in our bodies. In the coevolution of host organism and other species of the holobiont, a delicate balance has developed that is severely altered by the eradication of macroparasites. Therefore, it is necessary to move beyond the concept of macroparasites as harmful species by definition and therefore to be eliminated without hesitation. Alternatively, it is essential to study our holobiont as a whole and consider the balances of its ecosystems before modern alterations. Furthermore, it is essential to evaluate the effects of reintroducing macroparasite species with which we have coevolved into our holobiont.

Abstract: Explainable Artificial Intelligence (XAI) has emerged as a critical enabler for the adoption of machine learning models in high-stakes domains such as healthcare. While significant progress has been made in XAI for computer vision and natural language processing, tabular data—the predominant format of electronic health records—presents unique challenges and opportunities. This systematic review provides a comprehensive analysis of XAI methods specifically applied to tabular healthcare data for classification tasks. We examine 15 representative studies published between 2025 and 2026, covering three complementary perspectives: (1) intrinsically interpretable models such as Concept and Argumentation Models (CAM), (2) post-hoc methods including LIME, SHAP, and their variants like TransLIME, and (3) evaluation frameworks that assess both model-centered fidelity and human-centered clinical alignment. Our analysis reveals that SHAP remains the dominant post-hoc method for tabular healthcare data, achieving strong model fidelity but showing inconsistent alignment with clinical expert reasoning. Intrinsically interpretable models, such as CAM, offer transparency by design but require semantic feature descriptions. Emerging trends include integrating XAI with federated learning to preserve privacy, applying transfer learning to improve explanations in data-scarce settings, and deploying real-time XAI systems in occupational health. We identify critical gaps, including limited adoption of XAI in automated machine learning pipelines (in only 30.7% of studies), a lack of standardized evaluation metrics that combine technical fidelity with clinical utility, and the predominance of single-institution validation studies. This review provides researchers and practitioners with a structured roadmap for selecting, evaluating, and deploying XAI methods for trustworthy tabular healthcare classification.

Abstract: Background: Type 1 diabetes mellitus (T1D) is associated with chronic inflammation, platelet activation, and increased cardiovascular risk (CVR). The relationships between adipokines and platelet indices in long-standing T1D remain incompletely defined. Objective: To explore the relationships between adipokines (adiponectin and leptin), platelet indices, and inflammatory status in adults with long-standing T1D. Methods: This cross-sectional study included 124 adults with long-standing T1D and 59 non-diabetic controls. Platelet indices were obtained from automated blood count, and serum leptin (LEP), adiponectin (ADNC), and C-reactive protein (CRP) were measured using standardized assays. Associations were evaluated using correlation and multivariable regression analyses with adjustment for body mass index (BMI). Results: Platelet count (PLT) and plateletcrit (PCT) were higher in T1D compared with non-diabetic individuals (p=0.003 for both), while mean platelet volume (MPV) and platelet distribution width (PDW) showed non-significant upward trends. ADNC levels were higher in T1D (p< 0.001), whereas LEP and the leptin–adiponectin ratio (LAR) did not differ between groups. In T1D, LEP correlated with PLT (rho=0.235), PCT (rho=0.263), and CRP (rho=0.474), all p< 0.05. Similar associations were observed for LAR. No significant associations were found in non-diabetic controls. In multivariable analyses, PCT remained associated with LEP in T1D after adjustment for BMI, whereas in the control group LEP was associated with BMI only. Conclusion: LEP and platelet-related indices were associated in individuals with long-standing T1D, whereas ADNC showed no such relationships. These findings suggest a distinct pattern of adipokine–platelet associations in long-standing T1D.

Abstract: The Developmental Origins of Health and Disease framework proposes that environmental exposures during critical periods of development can shape physiological systems and influence the risk of chronic diseases later in life, including diabetes and metabolic syndrome. Most research on metabolic programming has focused on classical metabolic organs such as the liver, pancreas, and adipose tissue. However, skeletal muscle plays a central role in systemic glucose homeostasis and metabolic flexibility, accounting for the majority of insulin-stimulated glucose uptake in the body. Because muscle metabolism is closely regulated by neural activity through the organization of motor units, the development of the motor neuromuscular axis may represent an underexplored dimension of metabolic programming. This review examines evidence linking early-life metabolic environments to neuromuscular development and discusses how alterations in the maturation of motor neurons, neuromuscular junctions, and muscle fiber phenotype may influence long-term metabolic outcomes. Evidence from epidemiological studies, experimental models, and mechanistic research suggests that maternal metabolic disturbances, including hyperglycemia, obesity, and systemic inflammation, can influence fetal development through metabolic and inflammatory pathways affecting both neural and muscular components of the motor system. These findings support the hypothesis that the motor neuromuscular axis may represent a structural interface linking early developmental exposures to long-term metabolic regulation and risk of metabolic syndrome.

Abstract: Congenital Cytomegalovirus (cCMV) infection is the leading non-genetic cause of sensorineural hearing loss in newborns. Systematic nationwide screening programs are lacking. Antiviral valganciclovir therapy could improve auditory outcomes if initiated within the first 30 days of life, making timely diagnosis crucial. To address this, we investigated whether a hearing screening-based protocol is suitable. Between 2015 and 2019, newborns ≤21 days of age with repeated abnormal Newborn Hearing Screening (NHS) were prospectively enrolled at University Hospital Frankfurt. Oral mucosal swabs were tested for CMV DNA by real-time PCR, with confirmatory urine and blood-diagnostics in positive cases. Of 2,741 infants presenting for repeat NHS, 2,059 (75.1%) showed normal bilateral findings. Of the 682 (24.9%) with abnormal results, 575 (84.3%) were >21 days and thus ineligible. 107 infants (3.9%) met both criteria — abnormal NHS and age ≤21 days — of whom 100 entered per-protocol analysis. Two (2%) were confirmed cCMV-positive and received valganciclovir. Among the 48 infants who additionally underwent DBS testing, diagnostic sensitivity and specificity were 100%. The presented NHS–driven cCMV protocol reliably identified cCMV-infected newborns timely to offer antiviral therapy. In the absence of universal cCMV screening, this targeted approach offers a challenging, but WHO-screening-criteria-compliant strategy to enable timely antiviral intervention.

Abstract: Background: Good Pharmacy Practice (GPP) provides a globally recognized framework to promote the safe, effective, and rational use of medicines while strengthening the role of pharmacists in patient-centered health care. To enhance awareness and practical understanding of GPP principles in the local context, a one-day workshop titled “GPP: Strengthening the Role of Pharmacists in Health Care Delivery” was conducted. Methods: The workshop was facilitated by subject experts and faculty members and included focused presentations and interactive discussions addressing key components of GPP, such as rational use of medicines, medication counseling, professional ethics, and the evolving responsibilities of pharmacists. Particular emphasis was placed on the current status, challenges, and opportunities for GPP implementation in Nepal in comparison with international standards. Participant feedback was collected at the end of the program. Results: Participants reported a high level of satisfaction with the workshop, highlighting the relevance and clarity of the content as well as its perceived professional and career-related benefits. Interactive discussions enabled participants to identify context-specific challenges and opportunities in pharmacy practice in Nepal. Minor logistical limitations, including sound system and internet connectivity issues, were noted but did not significantly affect overall engagement. Conclusion: The workshop underscored the importance of continuous professional development initiatives to strengthen the implementation of GPP and enhance pharmacists’ contributions to health care delivery. Conducting similar capacity-building programs, particularly in remote and underserved regions, may support the promotion of standardized pharmacy practice and contribute to improved health care outcomes in Nepal.

Abstract: Numerous adverse effects caused by oxidative stress are commonly observed in preterm infants. This stress is caused by the oxidative burden resulting mainly from supplemental oxygen and parenteral nutrition (PN), and by their precarious antioxidant defense system. The natural antioxidant defense against these oxidant molecules relies on glutathione, levels of which are low in preterm infants. Given that several short- and long-term biological complications, including lung damage, are associated with this oxidative stress, the aim of this review was to discuss possible methods for reducing it. Consequently, after briefly discussing the effectiveness of reducing oxidative stress-related effects achieved through adequate photoprotection of PN, it is proposed to correct glutathione deficiency by adding glutathione to PN intended for premature infants. This article addresses the 1) importance and efficacy of parenteral glutathione in preventing oxidative stress, 2) causes of glutathione deficiency and ways to prevent it, 3) reasons why the disulfide form (GSSG) is recommended over the reduced form (GSH) for enriching PN, and 4) safety profile of glutathione infusion. In conclusion, we believe that the time has come to improve the health of premature infants by providing them with GSSG supplemented PN that is adequately photoprotected.

Abstract: We develop a unified first-order framework for relativistic fields of different spin, in which the dynamics are governed by a common operator-based equation. This formulation provides a coherent description of scalar, spinor, vector, and tensor fields within a single structure and reproduces the corresponding second-order wave equations in appropriate limits. A central result is the emergence of a consistent spin-2 sector from the same underlying dynamics. By constructing the tensor field as a bilinear combination of internal spacetime degrees of freedom, we obtain a symmetric rank-2 field with the correct number of independent components. In the massless limit, the resulting equation matches the structure of linearized gravity, while source-like terms arise naturally from quadratic combinations of field derivatives, providing an intrinsic origin for an effective energy–momentum tensor. The Lagrangian formulation yields conserved quantities via Noether’s theorem and reproduces derivative structures consistent with the weak-field Einstein–Hilbert action. These results suggest that gravitational dynamics may emerge from a more fundamental first-order field theory.