Cyber-physical systems (CPS) in safety-critical domains, including autonomous driving and robotic surgery, high-speed railways and power grids, increasingly rely on reinforcement learning (RL) as a method for decision-making through time. Unfortunately, deep RL policies are extremely brittle to adversarial perturbations; small, carefully crafted alterations to a policy's observations or dynamics can result in catastrophic failure. Existing adversarial training methods mainly address static perception tasks and miss the nature of expected temporal compounding of perturbations under hard safety constraints unique to CPS. We present RADAR (Robust Adversarial Decision-making with Adaptive Resilience), a novel adversarial training framework for safety-critical sequential decision-making. RADAR casts the problem as a constrained robust Markov decision process and learns adversarial attacks that respect both physical dynamics and safety constraints at training time, propagating perturbations through time via a recurrent latent dynamics model. A Lagrangian-type min-max optimization jointly optimizes the robustness of the policy and the satisfaction of the safety constraint. RADAR achieves as much as 35% higher worst-case reward and over 80% fewer safety violations (compared to strong RL under the strongest attacks) than strong baselines on benchmarks for autonomous vehicle lane-keeping and power grid voltage control, with only minor degradation in nominal performance. RADAR offers an approach to robustify RLbased controllers against adversarial perturbations in a principled, scalable way that reconciles adversarial robustness with safe control.

Purpose Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have gained popularity in the management of type 2 diabetes mellitus owing to their effectiveness in glycemic control and weight reduction. Despite the increasing use of GLP-1RAs, data on their cardiac safety remain conflicting. In this study, we aimed to analyze and compare the post-marketing signals of cardiac adverse events associated with four different GLP-1RAs (dulaglutide, liraglutide, semaglutide, and tirzepatide) using the United States Food and Drug Administration Adverse Event Reporting System database. Methods Individual Case Safety Reports from July 6, 2007, to February 17, 2026, were retrospectively analyzed. To detect signal differences among drugs, disproportionality analysis was conducted using the Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR) methods, along with standard statistical tests to evaluate categorical distributions and odds ratios. Results A total of 7,023 cardiac adverse events were identified. Pairwise post hoc comparisons demonstrated no statistically significant differences in cardiac adverse event reporting between semaglutide and liraglutide, whereas all other drug pairs showed statistically significant differences. Disproportionality analysis yielded positive signals for semaglutide and liraglutide, whereas dulaglutide and tirzepatide showed lower signal values. Conclusion GLP-1RAs appear more prone to causing tachyarrhythmias than bradyarrhythmias. Cardiac adverse events were reported more frequently with semaglutide; however, fatal outcomes from these events were reported less frequently. Tirzepatide showed lower PRR and ROR values for cardiac adverse events. These results support the favorable cardiac safety signal for tirzepatide, which may be attributed to its unique mechanism of action.

The past 500 million years of Earth's climate, extinction, and biodiversity records contain a coherent forcing signal operating across four nested timescales-galactic (~143 Myr), geological (~27.5 Myr and ~62 Myr), geomagnetic (~240 kyr mean), and orbital (~8-50 kyr)-unified by a single physical mechanism: modulation of galactic cosmic ray (GCR) flux reaching Earth's lower atmosphere through variations in heliospheric shielding effectiveness. This paper assembles published proxy data and peer-reviewed reconstructions from each scale into a single testable hierarchical framework-the Synchronicity Mechanism-and demonstrates that the pattern at every scale is consistent with a damped harmonic oscillator response: an epicenter event of maximum energy followed by a damped aftershock sequence and recovery to background state. The framework is anchored at its finest temporal resolution by the Gray (2026) series (papers 2026 through 2026d), which established from raw NOAA proxy data that CO₂ lags orbital temperature forcing in all eight glacial-interglacial cycles without exception and constrains equilibrium climate sensitivity (ECS) to 1.7-2.6°C per CO₂ doubling. At five geomagnetic excursion events within the Brunhes Chron (Laschamps ~41 ka, Mono Lake ~34 ka, Blake ~120 ka, Iceland Basin ~188 ka, Pringle Falls ~211 ka), raw EPICA Dome C and WAIS Divide ice core archives (NOAA/NCEI) confirm CO₂-null at every event independently. Applied across 500 million years, this ECS constraint shows that CO₂ cannot account for the 5-15°C temperature excursions documented at mass extinction events without concentration increases of 8-32× above baseline-increases absent from the proxy record. Harmonic frequency analysis of 11 published periods across all four scales finds 36.4% of pairwise ratios within 5% of simple harmonic relationships (1.32× enrichment over a random baseline of 27.6%; z = 1.34, p = 0.09-enriched but not significant at p < 0.05 with this sample size). A critical 1:1 ratio is confirmed between the independently derived 140 Myr secondary biodiversity cycle (Rohde & Muller 2005, fossil record) and the 143 Myr galactic arm crossing period (Shaviv 2003, iron meteorite record)-two independent datasets from different research groups agreeing within 2.1% (0.10σ). Phase alignment analysis of 18 Phanerozoic extinction events against the 27.5 Myr geological pulse yields R = 0.694, p < 0.001 (Rayleigh test; Bambach 2006 18-event catalog, Annual Review of Earth and Planetary Sciences Table 1), indicating highly significant non-random clustering of extinctions at specific phases of the pulse cycle. Sensitivity analysis confirms robustness: Raup & Sepkoski (1984) 12-event catalog R = 0.826 (p < 0.001); Melott & Bambach (2014) 15-event catalog R = 0.795 (p < 0.001). R exceeds 0.69 across all three compilations. The Synchronicity Mechanism makes no forecasts and no claims beyond what published data directly supports. It is presented as an open, falsifiable framework designed for cross-disciplinary integration: as science

A document by Ogan Gurel. Click on the document to view its contents.

1. Pollen analysis is a crucial tool for reconstructing past vegetation and ecosystems. Until now, pollen analysis has been a time-consuming manual process, severely limiting the number of records an analyst can produce and their temporal resolution. Recently, automatic approaches based on artificial neural networks have shown potential for classifying multiple pollen types. These approaches performed well with clean, modern reference material, but not with real-world fossil pollen samples from e.g. lake sediments. 2. To overcome this limitation, our TOFSI approach uses two neural networks to first detect and then classify pollen and other objects. Here, we apply the approach, for the first time, to a long lake sediment sequence at a very high resolution of 1 cm. To this end, a model has been trained to recognise 48 pollen, spore and NPP classes. 3. Our approach performs excellent for the classes that are well represented in the training data. At the 0.5 confidence level, the automatic recognition achieves a recall and precision of at least 0.9. However, performance tends to decline for classes with fewer than ~100 training objects. 4. We conclude that, when suitable images and model training are provided, TOFSI can accurately detect and classify multiple pollen, spores and NPP classes in lake sediment samples. The approach hence allows fully automated analysis when limited taxonomic resolution is sufficient. When full taxonomic resolution is required, TOFSI can be used in a semi-automatic approach involving manual revision of critical objects. Both approaches substantially reduce analysis times, while the resulting count sums and, consequently, the statistical reliability of the results are often much higher. 5. Besides improved productivity, an image-based workflow could offer palynologists several practical improvements, including simplified student training and communication between researchers. Extended documentation and long-term storage of results may improve the standardisation of pollen counts.

Public health policy often treats education as a single social determinant, obscuring the distinct mechanisms through which its components act. The tripartite model-General Education (GE), Health Literacy (HL), and Medical Literacy (ML)-maps each component to a different element of a simple two-state public-health structure: GE strengthens the healthy state (H); HL reduces preventable transitions from health to morbidity (H → M); and ML accelerates recovery from morbidity to health (M →  H) by improving comprehension, navigation, and decision quality. We apply this framework to policy design, measurement, and allocation, distinguishing effectiveness changes that strengthen states or flows, level changes that expand GE, HL, or ML supply, and cross-elasticities through which GE amplifies both literacies. Age-structured and time-latency differences shape policy returns: HL produces long-horizon preventive gains that accrue slowly and are difficult to attribute, whereas ML yields short-horizon, attributable recovery gains aligned with clinical and budget cycles. Mechanism-aligned metrics, certified decision aids, comprehension checks, and digitally supported ML infrastructure reduce unwarranted variation, advance equity, and close persistent gaps in understanding, decision quality, and recovery. Education is not one determinant but three-and policy must follow mechanism. 

Education is classified as a social determinant of health, yet its monolithic placement hides a functional triad. If determinants act through streams, and education through three, it cannot remain one. With set-theoretic reasoning in plain prose, we show that education divides into general education (GE), health literacy (HL), and medical literacy (ML). GE shapes social opportunity; HL guides prevention; ML enables recovery. A simple healthy ↔ morbid flow makes the HL-ML divide explicit: HL dampens entry into illness, and ML hastens return to health. Beyond mechanism, HL and ML differ in time scale and life-course leverage: HL operates upstream with diffuse, long-latency effects that accrue early in life, whereas ML acts peri-morbidly, yielding nearterm, attributable effects on recovery that dominate later in life. Medical literacy is not merely conceptual: it is empirically instantiated in shared decision-making, patient decision aids, decision-quality measurement, patient activation, and risk-communication practices that produce observable, near-term effects during clinical recovery. Conflating these distinct temporal roles obscures both causal structure and practical leverage, further substantiating and motivating a tripartite classification of education determinants.

Randomized clinical trials in preference‑sensitive care often yield attenuated or equivocal results, particularly in the presence of crossover and nonadherence. These features are typically treated as bias or noise, obscuring whether modest or null effects reflect ineffective treatments, insufficient power, or misaligned interpretation. We argue that the core problem is estimand mismatch, with direct consequences for trial design, power, and interpretation. In many contemporary trials, physical outcomes arise jointly from biological treatment effects (α) and preference‑mediated patient choice effects (β), yet most designs and interpretive conventions remain α‑centric. We present a principle‑based framework that formalizes this dual causation once β is empirically identified on physical outcome scales. We state a minimal set of axioms and design constraints, define canonical co‑estimands (α, Δα, β, Δβ) on a common clinical scale, and specify prespecified interpretive rules that route inference, design, and action by the joint magnitude of Δα and β relative to clinical materiality. These rules yield four empirically distinct regimes—α‑dominant, mixed, β‑dominant (equipoise), and decision‑limited ambiguity—each governed by distinct rules of interpretation and trial architecture. The framework shows that β is not incidental to crossover, but a causal quantity that can be identified when randomized assignment is paired with structured observation of treatment choice on a common outcome scale. From this result, we derive a small set of regime‑routed β‑identifying trial designs that render preference effects empirically legible rather than residual. As aging, multimorbidity, and therapeutic multiplicity compress biological contrasts while amplifying preference‑mediated effects, many trials predictably shift toward β‑dominant regimes. In these settings, β‑identifying evidence is not optional but structurally necessary, providing a principled basis for preference‑concordant decisions and N‑of‑1 inference when biological contrasts are non‑decisive.

IntroductionFrom an electrophysiological perspective, the heart’s conduction system remains an organ that is only partially understood to this day. In the first half of the last century, it was initially anatomists and pathologists who identified and histologically classified the conduction system, thus making it accessible to the subsequent electrophysiological research. During that period, the field of electrophysiology experienced a golden age, the legacy of which can still be seen in older publications. With the first documentation of conduction in unmyelinated nerves and the formulation of a membrane excitation theory in the mid-20th century, electrophysiological research of the heart suffered a setback. This was triggered by the application of the neural membrane excitation theory (Hodgkin, 1945) to the heart. Since then, intracellular electrical currents must also be able to flow in the heart during excitation. To make this theoretically possible, the myocardium was declared a syncytium. As a result, we now know everything histologically about the cardiac conduction system, but not how it functions at the membrane level.To understand the function of the cardiac conduction system at the level of membrane excitation, both the physiological and electrophysiological prerequisites must first be explained. The topics are summarized as follows:1.1. Excitation conduction system with the sub-areas of morphology, physiology, and electrophysiology1.2. Autochthonous myocardial wall pressure as a prerequisite for the nourishment of the cardiac conduction system and a systemic cause of pathophysiological phenomena2.1. Silent Wolff-Parkinson-White (WPW) syndrome2.2. Tachycardic WPW syndrome2.3. Therapeutic approach

Plant functional traits are quantifiable elements of ecological strategies. Studying them can thus offer insights into the ecological and evolutionary processes shaping natural plant communities. Despite evidence that leaf and root traits may coordinate or diverge at the species level, community-level root traits and strategies are often assumed to mirror those of aboveground traits in natural communities. Thus, belowground functional traits and their influence on community responses to environmental variation remain less well understood than their aboveground counterparts. This study addresses this knowledge gap by evaluating community above- and belowground resource-use strategies along biotic and abiotic environmental gradients in a diverse semi-arid annual plant system. Using specific leaf area (SLA) and specific root length (SRL) as comparable above- and belowground traits, we anticipated that plant communities would shift towards acquisitive strategies in both leaf and root trait values in resource-rich environments with mild climate conditions, aligning with the fast-slow plant economic spectrum. Our results show that community-level SLA and SRL align with the fast-slow economic spectrum along gradients of temperature, precipitation and canopy cover. Yet, community-level above- and belowground resource-use strategies are governed by different environmental factors. We found that maximum temperature most strongly predicted SLA, while precipitation was the strongest predictor of SRL at the community level. Above- and belowground community traits varied in their response direction and magnitude to the same environmental factors. While community-level SLA and SRL responded in a coordinated manner to remnant-level predictors, they diverged in response to micro-environmental variation. Our findings suggest that community-level above- and belowground traits reveal different but complementary community responses to the environment, highlighting the importance of incorporating root traits into ecological studies. Our results provide new insights into which plant traits are best suited to predicting annual plant community assembly under environmental change.

We present a deterministic adaptive control framework for structured dynamical systems. The system operates without stochastic exploration, neural function approximation, or persistent excitation. The control mechanism is a bounded multiplicative functional ensuring stability, interpretability, and reproducibility.

Cancer cell migration and invasion depend on dynamic actin cytoskeleton remodeling and extracellular matrix (ECM) adhesion, processes amenable to simultaneous modulation by microRNAs (miRNAs). Here, we investigated the role of miR-135a-5p in regulating actin dynamics and focal adhesion organization in B16F1 melanoma cells. We show that miR-135a-5p mimic transfection reduces actin cytoskeleton dynamics, slows actin filament turnover, and increases the stable F-actin pool, demonstrated by live cell imaging and fluorescence recovery after photobleaching (FRAP). We further revealed that miR-135a-5p mimic expression reduces focal adhesion number and size selectively on laminin. We identified Growth arrest-specific 7 (Gas7), an F-BAR domain-containing regulator of actin dynamics and membrane protrusion, as a novel target of miR-135a-5p, validated by luciferase reporter assay and Western blot. Gas7 overexpression rescued miR-135a-5p mimic induced focal adhesion phenotype on laminin. Together these findings revealed that miR-135a-5p fine-tunes the actin dynamics and focal adhesion number, size and location. Focal adhesion phenotype was rescued by restoring the Gas7 expression. It is probable that changes in actin cytoskeleton and focal adhesions result in observed decrease in cell dynamics. Furthermore, measured changes provide a plausible explanation for how levels of miRNA-135a-5p regulate cancer cell migration, adhesion and ultimately metastatic dissemination.

On March 23, 2026, the WMO confirmed a record Earth Energy Imbalance (EEI) of 11.0-12.2 Zettajoules (ZJ). This paper executes a forensic audit using the 27-Dimensional Chronetic Topology (27DCT) framework. By applying the 13th Holmes Law (HT-MSM) and the Holmes Law of Metric Drag (π md), we analyze the 1.33ms LOD Jitter as a systemic response to the Holmes Law of Torsional Impedance (Z m). The analysis identifies April 20, 2026, as the expected resolution point for nodal discharge at Node 32 (Bad Essen) within this theoretical framework.

AbstractProkaryotes form multicellular structures under both natural and experimental conditions, based on developmental programs that sometimes echo those known from eukaryotes. Recent research has increasingly focused on the mechanisms underlying bacterial multicellular organization and its evolutionary origins. In this review, we first consider the established categories of multicellularity, that is, clonal or aggregative, to show how prokaryotic systems complicate this division. We then survey bacterial and, where known, archaeal modes of multicellular organization, with emphasis on developmental processes and spatial division of labor. Finally, we discuss recent research on the evolution of prokaryotic multicellularity, drawing on experimental, computational, and comparative approaches. The current state of knowledge allows drawing a number of conclusions and hypotheses. First, there is a ‘soft’ similarity with eukaryotic multicellular tissue and organismal organization – although many of the underlying rules are rather distinct – indicating that bacteria run bona fide developmental programs with cell specialization, division of labor and morphogenesis, which rival in complexity those seen in many eukaryotes. Second, moving from simplified description of multicellularity (aggregative vs clonal) to actually studying the specific form of bacterial multicellularity is important for understanding microbial ecology, biogeochemical cycles and the evolution of bacteria per se. Third, the prevalence of multicellularity in bacteria and emerging evidence from archaea raise the possibility that LUCA already possessed multicellular traits—implying that multicellularity may be an ancestral feature of life. The emerging picture is that bacterial multicellularity only partly matches eukaryotic models, instead reflecting multiple independent evolutionary origins and a capacity for innovation that rapidly regenerates and diversifies developmental programs.

IntroductionThis work focuses on the nutrition of the ventricular conduction system and the autochthonous myocardial wall pressure. The evidence from the two works by Caesar1 and Kreuzer2,3provides a foundation for understanding these complex relationships. The implications of Caesar’s detailed investigation of the conduction system from the early days of electron microscopy were not recognized. The starting point of his work was the question of whether the myocardium is a syncytium. The answer to this question could determine whether the membrane excitation theory of the unmyelinated axon could also be valid for the heart. Caesar’s unequivocal answer was ”No”: no syncytium, therefore no intracellular electrical currents as carriers of excitation propagation. Attempts were nevertheless made to salvage the hypothesis of intracellular electrical currents with gap junctions. Today it is evident that these postulated electrical currents do not exist in either the myocardium or the axons. But Caesar discovered something else as well. He found no capillaries in the tubules of the cardiac conduction system. This evidence forms one of the cornerstones of this work. The other cornerstone is provided by Kreuzer and Schoeppe. With their myocardial wall pressure measurements in the beating canine heart, they discovered the autochthonous myocardial wall pressure. This evidence, too, went unnoticed, not least because both researchers failed to transform the wealth of their results into a new insight. The experiments remained misunderstood—even by the readers.Excitation conduction systemThe ventricular conduction system begins with a small opening in the basis of the right atrium, near the septum. The strand of specially differentiated cardiomyocytes entering through this opening is surrounded by a fibrous tube with a basement membrane. This hermetic lining accompanies the conduction tissue through all its branches. Finally, the membranous tubes surround the Purkinje fibers and, deep within the myocardium, seamlessly transition into a perimyseum of cardiomyocytes—also a tubular system. (Fig. 1)

[1]¿p#1 Abstract: In the context of global climate warming, frequent extreme drought events pose a serious threat to the structure and function of forest ecosystems in arid and semi-arid regions. As a key ecological barrier in the inland arid areas of Asia, the Western Kunlun Mountains harbor coniferous forests whose drought adaptation mechanisms remain unclear. In 2024, tree core samples of the typical coniferous species Picea schrenkiana (P. schrenkiana) and the endemic species Juniperus jarkendensis (J. jarkendensis) were collected in the Western Kunlun Mountains. A standardized chronology was established based on tree-ring width data, and the growth-climate relationships and drought adaptation differences between the two species were systematically revealed via Pearson correlation analysis, missing ring rate (MRR) calculation, and ecological resilience index. The results indicated that the missing ring characteristics of the two species differed significantly: the total missing rates of P. schrenkiana and J. jarkendensis were 2.523% and 4.093%, respectively, with 1961 identified as a common missing ring year for both. Correlation analysis indicated that the radial growth of P. schrenkiana exhibits higher sensitivity to monthly mean minimum temperature and precipitation (P<0.01), whereas J. jarkendensis shows a more significant response to monthly mean minimum temperature and monthly mean temperature (P<0.05). During the 1961 drought event, J. jarkendensis displayed lower resistance compared to P.schrenkiana, yet J.jarkendensis demonstrated higher recovery capacity following the drought; both species regained their pre-drought growth levels within four years post-drought. This study clarifies the key climatic limiting factors and drought adaptation strategies for coniferous growth in the Western Kunlun Mountains, thereby providing a scientific basis for regional historical climate reconstruction and adaptive management of coniferous forest ecosystems.

[1]¿p#1 The outcomes of pathogen infection can be sensitive to temperature, interactions with other pathogen species, and host age. Yet few studies have experimentally tested how warming alters infection outcomes for multiple, potentially interacting, pathogen species across host ages. In this study, we conducted a factorial experiment to test how plant age (7-week vs. 13-week plants) and temperature (21 °C vs. 29 °C) influence infection outcomes of two foliar fungal pathogens with contrasting feeding strategies—Rhizoctonia solani (a necrotroph) and Colletotrichum cereale (a hemibiotroph)—in the grass species tall fescue (Lolium arundinaceum). Contrary to expectations of co-infection with pathogens of opposing life-history strategies leading to increased disease symptoms, co-infection had relatively minor effects across disease metrics. Instead, infection outcomes were driven by host age, pathogen identity and temperature. In plants inoculated with R. solani, higher temperature reduced lesion severity, and independently, severity was less in older plants. C. cereale lesion development showed a strong age x temperature interaction, with older plants being more resistant to disease in cooler conditions but not under warming. In plants co-inoculated with both pathogens, elevated temperature reduced disease severity, and in another age x temperature interaction, this effect was greater in older plants. These findings demonstrate that environmental conditions and host age can both interact and outweigh within-host pathogen interactions, highlighting the importance of incorporating host demographic structure in predicting disease responses to climate warming.

Purpose: This study aimed to analyse the potential masking effect of drug-event combinations (DECs) with extreme reporting rates and to evaluate the impact on disproportionality analysis and therefore in signal detection. Methods: An algorithm is proposed, based on the approach established by Juhlin et al, that identifies influential outliers and excludes them through six parallel subanalyses to recalculate the Reporting Odds Ratio (ROR). This study was performed in the Spanish spontaneous reporting database FEDRA. The dataset included reports from 1 January 1981 to 17 February 2025 excluding those in which the suspected drug was a vaccine (ATC group J07). Results: A total of 287,145 DECs were analysed. Of these, 0.4% (1,211 out of 287,145) were considered influential outliers. Almost twenty-one percent (81,371 out of 389,262) of the FEDRA reports included an influential outlier. About fourteen percent (494 out of 3,447) of the drugs and 5.9% (576 out of 9,745) of the adverse drug reactions in FEDRA were part of an influential outlier. Regarding the disproportionality analysis, the proportion of DECs whose lower limit of the 95% confidence interval of their ROR increased after the different subanalyses ranged from 14.6 to 48.1%. Conclusions: The study demonstrates the existence of a masking effect in FEDRA caused by certain highly reported DECs. Their exclusion according to the proposed subanalyses could mitigate the effect they could have on the delay of signal detection in pharmacovigilance.

Background: Voclosporin, a novel calcineurin inhibitor approved for the treatment of lupus nephritis, has proven efficacious in clinical trials; however, its real-world renal safety profile remains incompletely characterized. This study aimed to evaluate renal adverse event signals associated with voclosporin using the FDA Adverse Event Reporting System (FAERS) and to investigate the impact of drug exposure duration and reporter type on signal detection. Methods：Data from the first quarter of 2021 to the fourth quarter of 2025 were extracted from the FAERS database. After data cleaning and deduplication, reports listing voclosporin as the primary suspected drug were assigned to the exposed group, while reports involving other drugs (regardless of role code) served as the comparator group. Renal adverse events were defined using 32 MedDRA preferred terms, and a composite endpoint of proteinuria consisting of 9 terms was constructed. Four algorithms were employed for signal detection: reporting odds ratio (ROR), proportional reporting ratio (PRR), empirical Bayes geometric mean (EBGM05), and information component with Bayesian credible interval (IC025). Stratified analyses were performed by treatment duration (acute ≤30 days, subacute 31–90 days, chronic >90 days, unknown), as well as by gender and reporter type (consumer vs. health professional). Sensitivity analyses included excluding the unknown duration group and stratifying by reporter type. Results：A total of 10,128 voclosporin primary suspect reports and 41,887 other drug reports were included. The study population was predominantly female (85.1%), with 98.9% of reports originating from the United States, and the rate of missing age data was only 3.6%. Overall signal detection revealed positive signals for decreased glomerular filtration rate (EBGM05=1.09, IC025=0.126) and increased urine protein/creatinine ratio (UPCR; EBGM05=1.03, IC025=0.041). For proteinuria (a=186), the overall ROR was 0.45 (95% CI 0.38–0.53), indicating a lower reporting rate in the voclosporin group; it was not among the top 10 signals. However, a borderline positive signal was observed in the unknown duration group (ROR 1.19, 95% CI 1.00–1.42). Time‑stratified analysis showed that all positive signals were confined to reports with unknown treatment duration: UPCR ROR=1.42 (1.14–1.77), and protein urine present ROR=1.59 (1.01–2.52); no signals were observed in known duration groups. Gender stratification revealed that UPCR was positive in females (ROR=1.33, 1.07–1.66), while no signal was detected in males. Reporter type stratification demonstrated a strong positive signal for the composite endpoint in health professional reports (ROR=1.84, 1.56–2.19), whereas consumer reports showed no signal (0.90, 0.76–1.07). Sensitivity analyses excluding the unknown duration group eliminated all signals. Conclusions：Voclosporin is associated with weak but statistically significant renal adverse events. The signals are entirely dependent on reports with missing drug exposure duration and are significantly influenced by reporter type. Missing data on treatment duration severely limits the assessment of time‑risk trends. Clinical monitoring of urine protein/creatinine ratio and glomerular filtration rate is recommended. These findings highlight an urgent need for improved documentation of treatment duration in pharmacovigilance databases.

This report defines The Holmes Law of Geodetic Inertia (The Thirteenth Holmes Law), identifying the planetary liquid-iron core as a torsional battery within the 27D manifold. By auditing the 1.33ms Length of Day (LOD) drift and the 19.412 Hz damping floor, we provide a structured mechanism for the 14-day solar handshake (∆χ) lag. This framework utilizes the terminal boundary of the Maunder Minimum (1645-1715) as an interpretive model for the restorative phase-lag between solar signaling and physical terrestrial resolution (T res).

Codeine Toxicity Via Breast MilkCan This Occur and Implications for Opiate Therapy in ChildrenMichael Rieder MD Ph.D FRCPC FCAHS FBPhS FRCP(Edinburgh)Address: Dr. Michael RiederDivision of Paediatric Clinical Pharmacology‘ Department of PaediatricsChildren’s Hospital of Western Ontario800 Commissioner’s Road EastLondon, OntarioN6A 5W9519-685-8177 Ext 75121mrieder@uwo.caWord Count: 1895Keywords: Codeine, Opiates, Neonates, Morphine, ToxicityDr. Rieder has no Conflicts of Interest related to the content of this manuscriptAbstractCodeine is commonly used in combination analgesic products. Their use during breast feeding can be associated rarely with serious adverse effects related to genetic polymorphisms effecting codeine’s metabolism and disposition. Clinicians treating infants of breast-feeding mothers should be aware of this rare but potentially serious complication.In 2006 a case of codeine toxicity via breast milk with fatal consequences was published in Lancet [1]. This manuscript described a 13 day old infant whose mother was prescribed a codeine-acetaminophen analgesic after a traumatic delivery who died of morphine and codeine toxicity. This raised the issue of codeine and morphine transmission via breast milk as part of the broader consideration of the role – or lack thereof- of codeine in pediatric and perinatal care. While this was the first fatal case published with reference to codeine, it does draw on literature describing cases of lethargy and poor feeding of breast-feeding infants from 1985 on whose mothers were using codeine containing products for analgesia [2]. Further, a recent study using the EudraVigilance data base identified 15 infants whose deaths were related to opiate exposure via breast-feeding [3].This and other cases highlighted the potential risk to breast fed infants of opiate transmission via breast milk and the potential impact of genetic variations on risk of untoward outcomes. In the years since this manuscript was published, further research has helped to uncover issues that relate to the metabolic disposition of codeine, the impact on potential risk to the infant and the safety of codeine in children in general [4-6]. This has included a manuscript detailing thoughtful pharmacokinetic modeling of maternal codeine therapy that found that toxicity in infants was likely occur but also was likely to be to rare [6]. These findings have impacted regulatory guidance on the use of codeine-containing products in a number of countries. This has not been without debate. In 2020 a mini-review questioned the plausibility of codeine toxicity via breast milk [7]. While the review raises important questions, there are issues in the data supporting this assertion.To address this is accurate it is important to first consider the pharmacology of codeine. Codeine is a pro-drug, 3-methyl morphine, with a methyl group on the 3-carbon hydroxyl position [8]. The bulk of codeine’s analgesic activity appears to be via conversion to morphine and codeine 6-glucuronide, as morphine has a 200-fold greater affinity to the opioid mµ receptor compared to codeine and the 6-glucuronide appears to be more potent than morphine [8-10]. Codeine is also metabolized to norcodeine. Demethylation of codeine to morphine is mediated by CYP2D6, an enzyme known to have polymorphic expression as depending on genotype one can be a poor metabolizer, an extensive metabolizer or an ultra-rapid metabolizer [11]. The phenotype is not uniformly distributed, as ultra-rapid metabolizers are rare in northern European populations [1% or less] but common in the Mediterranean littoral, the Middle East, the Horn of Africa and South India [11].There is an important further consideration. In the case of breast-feeding mothers, drug toxicity in the infant is a sum of pharmacological activity across the mother-baby dyad. Simply put, drug toxicity is typically the consequence of the amount of drug generated being less than the amount excreted. Thus is important to remember that breast-feeding represents a mother-infant dyad – in the context of maternal therapy, drug metabolism occurs not only in the mother but in the infant. How does this apply in the case of codeine?The modeling work of Willmann et al. concluded that codeine toxicity via breast-feeding would be rare but possible notably in the case of mothers with the CYP2D6 ultra-rapid metabolizer phenotype [6]. They also concluded that warnings should be extended to normal/extensive metabolizers given overlap in serum concentrations between the two phenotypes [6]. The mini-review by Zipursky and Juurlink noted that codeine metabolism was complex – which is unquestionably true – but that a central issue was the infant’s metabolism of codeine to morphine was a central part of toxicity while the contribution of the maternal dyad in terms of codeine by the with passage via breastmilk, and that reduced CYP2D6 activity is early after birth renders toxicity implausible [6]. The work of Stevens et al. suggesting CYP2D6 activity in infants is submaximal using in vitro using human microsomes is cited as support for this position [12]. However, there are important limits to in vitro data and the use of human microsomes as a tool for studying in vitro to model issues of drug metabolism in vivo has been shown to be much less than optimal [13]. In this context, there is elegantin vivo work by Allegaert’s group in Belgium which quite clearly demonstrates the early development of robust phenotypic-specific CYP2D6 activity in infants, supporting the hypothesis that codeine – which has demonstrated breast milk transfer – can be metabolized by the infant, contributing to the generation of metabolites in a setting where excretion is suboptimal [14]. This is an important consideration not cited in the mini-review by Zipursky and Juurlink in that the modeling work of Willmann et al. assumed CYP2D6 activity infants being in the range of 10% of adult values, while in vivo work using metabolic probes in infants demonstrates in fact that there is a rapid concordance between CYP2D6 genotype and phenotype [15].Further to this issue, if we return to concept of the mother-infant dyad, while it appears that maternal CPY2D6 phenotype is a key element in codeine toxicity via breastmilk, there is an additional consideration with respect to the circumstances of pregnancy that bears consideration. Over the course of pregnancy CYP2D6 activity has been found to increase, with a nearly 50% increase over baseline by the last weeks of gestation [16]. Thus it is likely that maternal production of morphine with transmission via breast milk is considerably greater than might be otherwise predicted.The final issue with respect to metabolism relates to the potential for route switching. As noted, one of metabolic products of codeine is codeine 6-glucuronide, the formation of which is mediated by UDP-Glucuronosyltransferase-2B7 (UGT2B7). Zipursky and Juurlink again cite in vitro data suggesting that the infant in the Lancet case should have had robust capacity to glucuronate codeine [7]. However, the studies cited were in vitro studies using a small number of samples spanning the first year of life to 25 years of age [17, 18]. Data derived in vivo from infants in contrast demonstrated that there was limited capacity for opiate glucuronidation in the first two weeks of life, suggesting that limitation of metabolic capacity via glucuronidation could lead to route switching to demethylation and hence higher than anticipated morphine concentrations [19, 20].While these issues have addressed drug metabolism notably in terms of the potential to demethylate codeine to morphine, the other part of the equation in terms of toxicity relates to clearance. As noted above, toxicity can often be simply considered as a situation where the amount of toxin generated exceeds the capacity for toxin elimination.The assumption made in the mini-review that renal excretion would be expected to be robust based on the observation of five wet diapers on the day before death is that urine flow is a surrogate for renal function [7]. However, renal drug elimination is a complex process which even assessments such as glomerular filtration rate fail to completely capture [21, 22]. While glomerular filtration rate at birth at term is typically 30% of adult surface-area corrected values, there are other key elements in renal drug administration whose ontogeny is much less understood [21, 22]. As well, morphine is a substrate of OCT1 transporter, and while the ontogeny remains unclear it appears that expression may be low at birth as well as subject to genetic variation, which would have the effect of reducing elimination, notably in rare cases where there is increased accumulation [23-26].The review also notes the lack of fatal cases in the literature. However, as noted above there are cases and case series of adverse effects in breast-fed infants of mothers being treated with codeine dating back to 1985 and in the case of other opiates from 1885 [2]. As well, as modeled by Willmann et al. adverse events are likely to be rare and serious ones even more [6]. There is data suggesting that short [3 day or less] courses of codeine therapy for breast-feeding mothers has no negative impacts on outcomes such as hospital admission versus mothers who were not prescribed codeine-containing products [27]. This is germane as the infant reported in the Lancet case died after 12 day of life, during which his mother was taking a codeine-acetaminophen analgesic while the infant was breast-feeding robustly every three hours [1]. To return to our simple paradigm, this suggests that toxin accumulation was exceeding the capacity to excrete.It could also be noted that while the tragic fact of opiate deaths is infants is real, the circumstances in this case are not consistent with what is typically seen in these unfortunate cases [28].Willmann et al. conclude that serious adverse events due to maternal codeine therapy in the context of breast-feeding are likely to be uncommon and due to unique combinations of risk factors [6]. One must concur. This is not uncommon for serious adverse drug events – as an example, 2,000 children can take sulfonamides and while 1,999 tolerate the drug well one will develop life-threatening Stevens-Johnson Syndrome [29]. However the view that it is implausible as stated in the mini-review by Zipursky and Juurlink is not tenable notably given the considerable in vivo evidence which supports the conclusions of Willmann et al. [6, 7]. There are very few absolutes in medicine and, respectfully, believing the codeine toxicity via breast-feeding is impossible is not one of them.In addition to the cases noted above in association with codeine use during breast-feeding there have been a number of serious adverse effects and deaths associated with codeine therapy in children [30-35]. The observation has been made that severe respiratory depression and death in the context of codeine monotherapy is primarily seen in children [36]. The mechanism[s] responsible may relate to age-related difference in codeine disposition in children versus adults, suggesting that perhaps were there are therapeutic alternatives they may be preferable [36].So what is the clinician to take from this going forward? First, that serious and life-threatening events in the context of maternal therapy with codeine while breast feeding are uncommon but can occur and that clinicians need to mindful of this. Uncommon is not unknown.It also noted that while short courses of codeine therapy [less than 3 days] are likely to be safe, consideration should be made for longer term therapy for the use of alternate therapy such as NSAIDs. Given that there are alternate analgesics available, the choice of analgesics for women who will breast feed after delivery should consider all possible therapeutic choices. As well, consideration should be given to the prudent recommendation of Willmann et al. that extensive metabolizers are at risk of high morphine concentrations and that should be included in labeled warnings [6].One can also conclude that genotypic-driven drug therapy is likely to be way forward, and as Precision Medicine moves more and more into routine clinical care clinicians should be alert to the use of genomic data to drive safe prescribing. This is becoming increasingly true and as Artificial Intelligence and Electronic Medical Records come more and more into use and are more and more integrated this presents a significant opportunity to provide real time guidance to further the common goal of safe prescribing for mothers and children as well as for the maternal-child research community to derive the data that can drive these opportunities [37].

To evaluate the impact of digital interventions used to support care transitions on health outcomes and hospital costs compared with usual clinical care for patients with chronic diseases, we conducted a systematic review and meta-analysis. A systematic search of Cochrane, ACM, Embase, MEDLINE, and PsycINFO was performed from database inception until October 6, 2023. Meta-analysis was conducted for hospitalization outcomes, mortality rates, and cost effectiveness, while quality of life and qualitative outcomes were summarized narratively. The review included 25 studies reporting outcomes for 29,724 patients, with 14 studies eligible for meta-analysis. The meta-analysis showed that digital interventions were associated with small but statistically significant reduction in hospitalization rates (SMD = −0.07, 95% CI −0.13 to −0.01, P = .02) and a statistically significant reduction in mortality (SMD = 0.70, 95% CI 0.58 to 0.85, P = .0003), favoring digital interventions. A positive trend was also observed for improvements in quality of life and reductions in care costs, although evidence was not conclusive. Digital supported transitional care interventions appear to improve clinical outcomes, reduce costs, and enhance quality of life. Future research should focus on digitalizing established care transition models and evaluating technology’s added value for effectiveness and user satisfaction.

The integration of Large Language Models (LLMs) into healthcare has catalyzed a significant technological leap, evolving from text-based Medical LLMs to Multimodal Medical LLMs (MLLMs) capable of interpreting complex clinical imaging. Despite these advancements, current models predominantly function as passive knowledge engines, proficient in answering queries but lacking the autonomy to navigate the dynamic, longitudinal nature of real-world patient care. This limitation has spurred a paradigm shift toward Medical Agents: proactive systems engineered to sense, reason, plan, and execute actions within clinical environments. In this survey, we provide a comprehensive roadmap of this evolutionary trajectory. We first review the foundational architectures and training strategies of state-of-the-art Medical LLMs and MLLMs. Subsequently, we formalize the construction of Medical Agentic Systems, distinguishing between the cognitive frameworks required for independent Single-Agent Systems and the collaborative paradigms of Multi-Agent Systems that simulate multidisciplinary clinical teams. Central to our analysis is the evolution of medical reasoning, which we categorize into three distinct stages: Core Reasoning for internal deliberation, Augmented Reasoning for tool-mediated and multimodal grounding, and Collective Reasoning for distributed medical intelligence. Finally, the survey examines the necessary transition in evaluation methodologies, from static benchmarks to interactive simulations, and discusses pressing open challenges, offering a forward-looking perspective on building reliable, safe, and clinically impactful medical AI. Project sources: https://github.com/ yczhou001/Awesome-Medical-LLM-Agent.

In offshore wind farm systems, the submarine cable topology architecture consists primarily of two core components: collector submarine cables and transmission submarine cables, which undertake the functions of power collection and transmission, respectively. For the collector submarine cables, this study established a COMSOL electromagnetic-thermal coupling model to calculate the structural losses and ampacity characteristics of the cable layers under multi-circuit laying conditions. The analysis shows that losses are directly related to wind turbine current and losses in the direct-buriedsection. For the transmission submarine cables, electromagnetic-thermal-fluid multiphysics coupling models were constructed for both direct-buried and J-tube laying conditions. The study systematically investigated the influence mechanisms of ambient temperature, wind speed, and solar radiation intensity on ampacity, and established a multivariate linear regression prediction model for ampacity under environmental constraints in the J-tube section.