A Case of Extreme Dipping with a Nocturnal Blood Pressure Drop Exceeding 50%

Tuberculosis-associated paradoxical immune reconstitution inflammatory syndrome in an HIV-negative patient presenting with a recurrent pleural effusion successfully treated with prednisolone:

A document by Toktam Zamani. Click on the document to view its contents.

Penicillin allergy delabelling (PADL) is increasingly recognised as a key antimicrobial stewardship strategy and important public health priority. Over the past decade, multiple PADL guidelines (PADLGs) have been published, yet the consistency of their recommendations and overall quality have not been systematically reviewed. This review compared the scope, purpose, and recommendations of internationally published PADLGs, and assessed their quality using the Appraisal of Guidelines for Research and Evaluation II instrument. Eighteen guidelines published between 2014 and 2024 were identified, representing twelve countries across four regions. Most guidelines provided recommendations for risk stratification, testing, and delabelling methods, with many supporting direct delabelling/direct challenge in low-risk patients. However, substantial variation was observed in risk assessment tools, eligibility criteria, and post-test delabelling strategies, highlighting opportunities for greater standardisation. Overall, the quality of PADLGs was low, with only two meeting predefined high-quality criteria. Critical gaps included limited methodological rigour, poor stakeholder involvement, and lack of guidance for real-world implementation. PADLGs also demonstrated variation in scope, target users, and clinical recommendations, both within and across clinical settings. To support safe and scalable PADL approaches, clearer, more consistent, and methodologically robust guidelines are needed to address the global burden of inappropriate penicillin allergy labels.

Understanding rainfall partitioning and streamflow generation processes have become indispensable due to the increasing frequency of hydrological extremes globally. River catchments in the tropics are particularly vulnerable to changing characteristics of rainfall and decoding the rainfall partitioning into pre-event and event water becomes more critical in tropical catchments where runoff generation processes, are often poorly understood. In this context, the present study is aimed at understanding the runoff generation processes in Vamanapuram river – a humid tropical forested experimental catchment in the Southern Western Ghats, India utilizing high-resolution (30 min) hydrological measurements. Data from 78 and 76 storm events (during 2022 and 2023) were used for storm hydrograph separation using the conductivity mass balance method at Kallar River Gauging Station (KRGS) and Chettachal River Gauging Station (CRGS), respectively. Both KRGS and CRGS are found to be sub-surface dominated catchments irrespective of season. In 98% and 96% of the storm events respectively at KRGS and CRGS, pre-event water dominated the hydrograph.. The seasonality in the PEWF(avg) and Pre-Event Water Fraction at peak (PEWF(at peak)) has higher values in the dry period and lower values in the wet period. PEWF(avg) decreases from 0.82 to 0.80, and PEWF(at peak) from 0.76 to 0.73 from upstream to downstream reaches respectively. The beta distribution fits well the temporal variability in the PEWF(avg) and PEWF(at peak) at both river gauging stations. The effect of differential precipitation forcing in the subsequent year’s storm PEWFs has been studied, and it was observed that higher precipitation forcing results in higher PEWF at CRGS. However, the effect of precipitation forcing is not seen at KGRS, possibly due to significantly different geomorphic characteristics and higher forest cover. A more extended period of hydrological data in catchments with diverse climatic and geological settings will provide a better understanding on the effect of precipitation forcing on catchment rainfall partitioning and thus improve conceptualization of rainfall-runoff models.

Trait-based approaches provide robust tools to understand how spatial and temporal environmental variability shapes community assembly and functional diversity. Here, we investigated the thermal tolerance of three cereal aphid species (Sitobion avenae, Rhopalosiphum padi, and Metopolophium dirhodum) across a 1200 km longitudinal gradient from western to eastern Europe, comparing autumn and spring populations. We tested whether: 1) eastern populations (experiencing larger seasonality and harsher winters) exhibited broader thermal tolerance ranges than western ones; 2) autumn aphids were more tolerant to cold and less tolerant to heat comparing with spring aphids; and (3) larger seasonality drove trait convergence within the aphid guild. Our results revealed that thermal tolerance varied across the longitudinal gradient, with autumn populations in eastern Europe with larger temperature variability displaying broader thermal ranges, supporting the Climatic Variability Hypothesis. However, spring populations exhibited a counter-gradient pattern, where aphids from regions with milder winter (western Europe) had higher cold tolerance than those from regions with harsher winter (eastern Europe), likely explained by different overwintering strategies between western (as active adults) and eastern Europe population (as diapausing eggs). Seasonal differences were pronounced: autumn aphids were less heat-tolerant than spring individuals. At the guild level, eastern populations exhibited trait convergence driven by large intraspecific variation, while western populations showed interspecific divergence, suggesting environmental filtering shaped thermal traits differently across climates. These findings highlighted the importance of seasonal and geographic context in thermal adaptation. Increasing climate variability may drive functional homogenization in ectotherm communities, potentially stabilizing populations but reducing long-term resilience. Our study underscored the need to integrate seasonal dynamics and intraspecific variation when predicting species responses to climate change, emphasizing how temperature variability - not just warming - reshaped insect communities.

The upscaling of wind turbines has shifted rotor design from a purely aerodynamic challenge to a multidisciplinary design optimization (MDO) problem, requiring simultaneous consideration of aerodynamic performance, structural integrity, and cost. One promising approach within this framework is the Low Induction Rotor (LIR) concept, which trades reduced aerodynamic efficiency for decreased structural loading and increased rotor size. However, integration of LIR design into high-fidelity MDO environments has been limited, particularly with respect to structural modeling. This work presents a novel MDO framework that applies the LIR concept to the IEA 15 MW reference turbine using a parameterized axial induction distribution and incorporates two structural constraints: root bending moment and blade tip deflection. High-fidelity structural modeling is achieved through NuMAD and BeamDyn, enabling the generation of Pareto-optimal blade families that offer meaningful gains in power capture while satisfying structural constraints. This approach demonstrates the viability of LIRs in realistic engineering applications and establishes a pathway for high-fidelity rotor design optimization.

Alpay Algebra is introduced as a self-contained axiomatic framework with the ambition of serving as a universal foundation for mathematics. Developed in the spirit of Bourbaki's structural paradigm and Mac Lane's emphasis on form and function, Alpay Algebra posits a single abstract system from which diverse mathematical domains emerge. We present the precise axioms defining Alpay Algebra and develop its core constructs-including a recursive transformation operator ϕ, its transfinite iteration ϕ ∞ , an iterative state hierarchy χ λ , a limit object Ξ ∞ , and an evaluation functional ψ λ. From these primitives, we rigorously rebuild key fields: we derive fixed-point theorems and internal stability results, realize category theory within the algebra by interpreting compositional morphisms as iterative state transitions, recast homological algebra through cycles and invariants of the recursion, and outline an internal logic akin to topos theory grounded in stable truth values emerging from ψ λ. All definitions, theorems, and proofs are given entirely within the Alpay Algebra system without appeal to external frameworks. The development showcases how Alpay Algebra can subsume algebraic geometry, category theory, homological algebra, logic (including topos theory), and general structural mathematics under one unifying language. We conclude by highlighting new conjectures and problems that naturally arise from this universal algebraic perspective, underscoring the foundational depth and future potential of Alpay Algebra.

Country Innovative Integrated Strategy for Preventing Climate Change and Drought Phenomena in Industrial Regions: Analysis of Causes, Intervention Modeling and Implementation Mechanisms on the Example of Central and Eastern EuropeAuthorsAnatoliy Zhukov¹ - Independent Researcher, Technical Expert, Kryvyi Rih, UkraineWalery Zukow² - Nicolaus Copernicus University, Toruń, PolandAbstractIntroduction : The study aims to analyze the relationship between climate change, renewable energy development, and the intensification of drought phenomena in industrial regions of Central and Eastern Europe, in order to develop an integrated strategy to prevent negative climate impacts.Methods : Meteorological data for the period 1990-2024 were analyzed using ERA5 and MERRA-2 reanalysis. Statistical methods were applied to detect trends in climate indicators and their correlation with energy infrastructure development. Numerical modeling of atmospheric circulation was performed using the WRF model.Results : A tendency toward decreasing precipitation in continental regions of Central and Eastern Europe was detected. Analysis of literature sources shows that large-scale wind farms can influence local meteorological conditions, however, their impact on regional climate remains the subject of scientific discussion. Modeling shows that optimizing the spatial distribution of energy infrastructure can reduce potential negative impacts on atmospheric circulation.Conclusions : Based on the research results, an integrated strategy for preventing climate change and drought phenomena was developed, which includes optimizing the spatial distribution of energy infrastructure, diversifying renewable energy sources, and developing water resource protection systems.Keywords : climate change, drought, renewable energy, atmospheric circulation, moisture transport, industrial regions, Central and Eastern Europe, integrated strategy, adaptation, climate modeling.

Background: Mastoiditis, a common complication of acute otitis media (OM), is a significant concern for pediatric otolaryngologists, with an incidence of 1-6 cases per 100,000 children annually. While most cases are caused by common pathogens such as Streptococcus pneumoniae and Staphylococcus aureus, Mycobacterium abscessus (M. abscessus), a rapidly growing nontuberculous mycobacterium,

The photorespiratory CO 2 compensation point (Γ*) and the rate of CO 2 release in the light (D L) are critical parameters for understanding the carbon dynamics of C 3 plants. These two parameters can be derived from the widely-used Laisk method as the intercept of linear regression lines fitted to net assimilation rates (A net) versus chloroplast CO 2 partial pressures (C c) obtained at different low-irradiance levels. However, photosynthetic theory indicates curvature in the A net-C c relationship which conflicts with the use of linear relationships for analysis. We, therefore, systematically evaluated the limitations of the use of linear relationships across temperatures from 5 to 40 °C and quantified the sensitivity of errors in Γ* and D L estimates to the selected C c range. We found that wide CO 2 ranges, especially when they exclude the actual Γ*, can introduce substantial biases in parameter estimation with linear regressions, particularly at lower temperatures. It can lead to marked underestimates of Γ*, and biologically unrealistic D L. We propose refining the Laisk method by using a photosynthesis model to analyse data. The model better represents the non-linear A net-C c relationship and yields consistent Γ* and D L estimates, regardless of the CO 2 range used.

MicroRNA-122 (miR-122) is a sensitive biomarker for paracetamol-induced liver injury. This study evaluated Dynamic Chemical Labelling (DCL) combined with a clinical laboratory assay to quantify miR-122 in human serum, as a proof-of-concept for hospital use. Serum was collected from 19 healthy individuals and 19 patients with paracetamol drug-induced liver injury (DILI). miR-122 was labelled with a biotinylated SMART-Base and quantified using a multiplex, bead-based, fluorescence detection system. Median miR-122 concentration was 233.4pg/ml in DILI patients vs. 15.2pg/ml in controls. Concentrations ranged from 17.5–1376.9pg/ml (DILI) and 2.2–67.2pg/ml (controls). The Mann-Whitney U test showed significant group differences (p < 0.0001). ROC analysis yielded an AUC of 0.96, with a 29.7pg/ml cut-off providing 92.6% sensitivity and 89.4% specificity. miR-122 moderately correlated with ALT (r=0.56, p=0.03). DCL with fluorescence detection is a promising clinical tool for miR-122 quantification.

Affinity-purified antibody to S100 calcium binding protein B that has undergone gradual technological processing and was additionally modified with an electromagnetic signal is an active pharmaceutical substance of a novel drug Prospekta. Earlier studies have shown that the drug possesses a wide range of pharmacological properties, not limited to pro-cognitive and anxiolytic activity. Here, we aimed to determine the effect of Prospekta on the baseline electrical activity of the mouse brain. Extradural electrodes were surgically implanted into the skull of adult male socially submissive mice. Mice were orally administered Prospekta or purified water as a control via gavage for 5 days starting from the end of the recovery period. Brain baseline activity was recorded during 5 min after placing animals into arena. Quantitative measures of EEG delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–100 Hz) power were assessed. It was shown that the drug led to a decrease in theta and alpha band power in the left prefrontal cortex. Furthermore, the drug exhibited a tendency to influence the coherence of electrical activity between the left prefrontal cortex and the right hippocampus, resulting in a moderate phase shift across all examined brain regions. At the same time, no prominent changes in EEG activity were observed in the right hippocampal region. We show that Prospekta modifies EEG parameters of animals and thereby confirm that the drug mechanism of action is based on its ability to affect functional (electrophysiological) brain activity.

Background/Aim PARP inhibitors (PARPi) proved effective in Ewing’s sarcoma cells in preclinical studies. In clinical evaluation, however, the PARPi olaparib failed to elicit substantial responses, suggesting an unknown mechanism of resistance to PARPi in Ewing’s sarcoma. Since autophagy has been identified as a PARPi resistance mechanism in other tumours, this study aimed at exploring the impact of autophagy on PARPi effectiveness in Ewing’s sarcoma cells. Methods Effects of the PARPi olaparib and veliparib were assessed by flow cytometry in the Ewing’s sarcoma cell lines WE-68 and SK-ES-1. Autophagy levels were determined using the autophagosome tracer dye Cyto-ID, and cytotoxic effects were determined by the analysis of cell death and loss of mitochondrial membrane potential. Cyto-ID was used to separate cell populations into subpopulations with low, medium and high autophagy by flow cytometric cell sorting. Results Olaparib and veliparib induced autophagy and cell death in parallel in WE-68 and SK-ES-1 cells. Induction of autophagy and cell death occurred at the same concentrations of both PARPi in both cell lines. Analysis of cells sorted according to autophagy levels revealed a clear association between PARPi effectiveness and autophagy level. The subpopulation of Ewing’s sarcoma cells with high autophagy responded significantly less to PARPi with cell death than the subpopulation with low autophagy. Conclusion This study demonstrates that autophagy affects the anticancer activity of PARPi in Ewing’s sarcoma cells.

Gastrointestinal symptoms have emerged as a common, but underappreciated, cause of morbidity in relation to SARS-CoV-2 infection and the COVID-19 pandemic. This manifests as a range of indications including diarrhea, anorexia, nausea, vomiting and abdominal pain. In addition, the gastrointestinal tract may represent a route of viral entry via the epithelial cell layer lining the gut wall. This route of entry could be a significant component of disease pathogenesis, including effects on the nervous system via the gut-brain axis. In this review we provide an assessment of the effects of COVID-19 on the gastrointestinal system, its involvement in disease severity and potential pathways for viral entry and infection in the gastrointestinal tract. We also examine evidence that gut-derived serotonin is affected by SARS-CoV-2 infection, how this may link to symptoms and disease pathogenesis, and the potential link to the efficacy of selective serotonin reuptake inhibitors in reducing COVID-19 severity.

As catastrophic wildfires increasingly devastate the interior landscapes of British Columbia, Canada, conventional approaches to post-wildfire recovery often overlook Indigenous values, knowledge systems, and food sovereignty. In collaboration with six Northern St’át’imc communities and guided by the “walking on two legs” framework, which brings together Indigenous and Western knowledge systems led by Indigenous worldview, we reanalyzed post-wildfire vegetation trajectory data from the McKay Creek wildfire. We replaced colonial-era “native/non-native” plant classifications with culturally grounded categories to better reflect Indigenous wildfire recovery priorities. Vegetation trajectories were based on percent cover data collected across 80 plots, stratified by burn severity and pre-wildfire invasive plant presence. Our results show that conventional plant classifications may obscure critical vulnerabilities in traditional plant food systems and protein sources. While ”native” plant cover exceeded 25% across all treatments, our cultural plant classifications ranged from just 7% to 18%. While elevation emerged as a key factor in post-fire vegetation dynamics, government-defined “Mule deer forage” plant classification indicated increased forage at higher elevations, while the Indigenous-informed classification, “Mule deer preferred forage” showed the opposite trend. These findings demonstrate that classifying plants by cultural knowledges reveals a more accurate picture of post-wildfire recovery. Conventional plant classifications may overestimate ecosystem resilience and thus overlook areas requiring urgent intervention. Indigenizing Western scientific approaches can strengthen ecological restoration by aligning data interpretation with Indigenous sovereignty and community-led priorities. This study offers a concrete model for advancing culturally appropriate wildfire recovery while supporting the implementation of legal obligations to protect Indigenous food sovereignty under Section 35 of the Constitution Act, 1982, and British Columbia’s Declaration on the Rights of Indigenous Peoples Act (DRIPA). Our study suggests that reframing plant classification by Indigenous values not only deepens understanding of post-wildfire recovery but also supports more effective, place-based decision-making for long-term ecosystem stewardship.

Quantifying phenotypic plasticity, the capacity of organisms to adjust phenotypes in response to environmental changes is essential for understanding ecological and physiological resilience under climate stress. However, existing methods often lack flexibility and precision, especially under multi-dimensional environmental conditions. Here, we introduce a novel statistical approach, the Environmentally Standardised Plasticity Index (*ESPI), which integrates Hedges’ g for effect size quantification and Euclidean distance for characterizing environmental variability. We validated this method using both simulated datasets and empirical data from the marine diatom Thalassiosira weissflogii, investigating five key phenotypic traits over seven days under varying temperature, irradiance, and nutrient conditions. Our findings indicate distinct temporal patterns of plasticity: certain traits, such as photosynthetic efficiency (alpha) and saturation irradiance (Ek), demonstrated high initial plasticity followed by gradual acclimation, whereas others, like pigment composition, exhibited delayed phenotypic responses. This temporal dimension highlights the critical role of the growth phase in shaping plasticity responses. The proposed *ESPI method provides a robust, intuitive, and versatile framework for quantifying phenotypic plasticity, offering significant advances in predicting organismal adaptation to environmental change.

Title: Noncaseating Parotid Tuberculosis Mimicking Neoplasm and Sarcoidosis

Vaginal cytology is a diagnostic tool for evaluating estrous cycle stages and reproductive health in female dogs and cats. It involves microscopic examination of vaginal epithelial cells, but subjective interpretation can lead to inconsistencies. This study explores artificial intelligence (AI), specifically deep learning, to enhance accuracy. A total of 1,096 vaginal smear samples were collected, stained, digitized, and analyzed using AI. Several pre-trained convolutional neural networks (CNNs), including MobileNetV2, ResNet152V2, EfficientNetV2L, Xception, VGG-16, InceptionV3, NasNetLarge, InceptionResNetV2, DenseNet201, and ConvNeXtSmall, were evaluated. The Xception model achieved the highest accuracy at 97.65%. These findings demonstrate AI’s potential to reduce subjectivity, improve diagnostic consistency, and advance reproductive health assessments in veterinary medicine.

Objective: The mode of birth for twin pregnancies has been a topic of debate, but vaginal birth in twin pregnancies appears both possible and safe, despite the upward trend of cesarean section. Design: This retrospective multicenter study compares outcomes before and after the implementation of a vaginal twin intervention in two Italian hospitals. Setting: In January 2021 in Pescara and in July 2022 in Florence, physicians with expertise in twin and breech vaginal birth started working in each center, and clinicians and midwives started quarterly training in these skills. Setting: The study period, divided into two equal time intervals, lasted 8 years in Pescara and 5 years in Florence. Providers were also surveyed about how the intervention affected their confidence, skill, and knowledge levels. Population: Diamniotic pregnancies with two viable twins; ≥34 weeks of gestation; cephalic presentation of the first twin were included. 278 women were evaluated, split into pre-intervention (n=131) and post-intervention (n=147). Results: Vaginal birth rates increased from 9.2% to 40.8% overall with no negative effect on maternal or neonatal outcomes. Participating providers felt more skilled, knowledgeable, and confident and agreed that the training improved vaginal birth rates as well as their vaginal breech skills. Conclusion: A rapid increase in the vaginal birth rate of twins is possible via either staff-wide training or specialist teams without adversely affecting maternal or neonatal outcomes. Simulation and skills training can improve provider confidence, knowledge, and skill levels as well as impact clinical practice in the labor ward.

This paper introduces a coherent light metric derived from topological constraints in the Knot of Light framework. We present a formal structure for light propagation under coherent dimensional conditions, emphasizing phase-synchronized flow and resonanceinformed speed modulation. The equation defines a modified light speed that integrates structural resonance coefficients.

The increasing Internet of Things (IoT) integration of consumer healthcare devices raises serious cybersecurity and data privacy issues. The current research uses Artificial Intelligence of Things (AIoT) technology to present an anomaly detection system that addresses these issues. Using machine learning techniques, the framework offers a proactive security solution for consumer healthcare devices by identifying and reducing cyber threats in real time. The SCADA and BoT-IoT datasets, which concentrate on cybersecurity vulnerabilities in healthcare-related networks, are used for experimental validation even though the framework is intended for protecting consumer healthcare IoT devices. Using the SCADA and BoT-IoT datasets, the framework achieves an anomaly detection accuracy of 99%, outperforming existing techniques in terms of false alarm rate (0.1%), scalability (95%), and real-time threat detection (98%).

Background: Cervical cancer, as one of the malignant tumors threatening women’s health and survival, has demonstrated a marked increase in incidence in China. In recent years, the HPV vaccine has become an effective preventive measure against cervical cancer, with college students representing an important target group for HPV vaccination. Therefore, comprehensive and professional conclusions are needed to guide the improvement of the cervical cancer prevention and treatment service system regarding the willingness to receive the HPV vaccine and the actual vaccination rate among college students in China. Methods: Relevant studies were retrieved from PubMed, Embase, Web of Science, The Cochrane Library, CINAHL, PsycINFO, SinoMed, CNKI, Wanfang, and VIP Database from the time the databases were established to March 12, 2025. Meta-analysis was conducted using Stata 17.0 and RevMan 5.4 to assess college students’ willingness to receive HPV vaccination, actual vaccination status, and influencing factors. Results: A total of 35 studies involving 62,958 samples were included. The meta-analysis results showed that the willingness rate of college students to receive HPV vaccination in China was 67.0% (95%CI: 0.61-0.74, P<0.001), and the actual vaccination rate was 9.0% (95%CI: 0.07-0.11, P<0.001). Fifteen influencing factors were extracted. Female (OR=3.47, 95%CI: 2.49-4.85, P<0.001), having a history of sexual behavior (OR=1.91, 95%CI: 1.09-3.35, P=0.020), accepting premarital sex (OR=1.36, 95%CI: 1.04-1.78, P=0.020), having a family history of tumors (OR=1.69, 95%CI: 1.28-2.23, P<0.001), monthly consumption level ≥ 2000 yuan (OR=1.50, 95%CI: 1.22-1.84, P<0.001), knowing about HPV vaccine (OR=1.75, 95%CI: 1.11-2.77, P=0.020), knowing that HPV vaccine is on the market (OR=1.71, 95%CI: 1.44-2.03, P<0.001), knowing that HPV infection is related to cervical cancer (OR=1.44, 95%CI: 1.15-1.81, P=0.002), having someone around who has been vaccinated with HPV vaccine (OR=2.23, 95%CI: 1.66-3.01, P<0.001), and having a high cognitive score of HPV and its vaccine (OR=1.86, 95%CI: 1.32-2.62, P<0.001) were identified as influencing factors. Conclusion: Current evidence indicates that while the willingness rate of college students in China to receive HPV vaccination is relatively high, the actual vaccination rate is low. Public health authorities and healthcare institutions should face the problem of ”high vaccination willingness rate and low actual vaccination rate” among college students by strengthening the professional popularization of HPV vaccine-related knowledge and optimizing the HPV vaccination service system to enhance cervical cancer prevention efforts.

Purpose: The aim of this study was to examine the relationship between childhood trauma and premenstrual syndrome in female university students. Methods: This descriptive and relational study was conducted with 603 female university students between October 2024 and December 2024. Data collection tools included a Sociodemographic Characteristics Form, the Premenstrual Syndrome Scale, and the Childhood Trauma Questionnaire. Results: When students with and without premenstrual syndrome were compared in terms of Childhood Psychological Trauma Scale sub-dimensions and total mean scores, those with premenstrual syndrome symptoms scored significantly higher in the physical neglect, sexual abuse, and denial sub-dimensions. Additionally, an increase in childhood psychological trauma was associated with earlier menarche, longer menstrual bleeding, and more severe premenstrual syndrome. Conclusions: The findings of this study suggest that premenstrual syndrome in young women is influenced not only hormonal factors but also by psychosocial factors such as childhood trauma. This highlights the importance of a holistic approach to assessment and intervention for women presenting with premenstrual syndrome symptoms.