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Visual classification of allergenic pollen in iteratively reconstructed lens-less DIHM images

Abstract Lens-less digital in-line holographic microscopy (DIHM) is a low-cost, wide-field imaging technique that relies on computational reconstruction to form focused images that should ideally be free of twin-image artifacts. While current DIHM-based pollen classification systems are typically automated and rely on large datasets and deep learning, our study explored whether iteratively reconstructed DIHM images using the Gerchberg–Saxton (GS) algorithm are suitable for visual classification by human experts. Two veterinary cytopathologists evaluated images of six clinically relevant pollen types, namely timothy grass, common ragweed, silver birch, common alder, olive tree, and hazel, using both lens-less DIHM and conventional optical microscopy. Classification accuracy was comparable across modalities, with DIHM achieving 95.8% and optical microscopy 96.9%. Inter-observer agreement was high (Cohen’s κ = 0.91), indicating near-perfect consistency between evaluators. Most misclassifications involved silver birch pollen, likely due to its morphological variability and overlap with common alder and hazel. These findings demonstrate that lens-less DIHM combined with iterative reconstruction enables accurate visual identification of allergenic pollen, offering a promising alternative to conventional microscopy in veterinary and other resource-limited settings.

A pilot multimodal study of cervical cancer: Raman spectroscopy as a molecular fingerprint tool

Cervical cancer remains a significant global health burden, highlighting the need for more effective tools for early detection and tissue characterization. In this study, we propose a multimodal strategy that combines Raman spectroscopy, Atomic Force Microscopy (AFM), and Scanning Electron Microscopy (SEM) to investigate the molecular and morphological features of cervical squamous cell carcinoma (SCC). Raman spectroscopy was used to analyze biochemical signatures across different tissue regions tumor, necrotic, stromal, and glandular within the 813–1668 cm -1 range, identifying distinct molecular profiles between malignant and healthy areas. Specific vibrational peaks associated with DNA, proteins, and lipids were examined to track molecular changes related to tumor progression. AFM enabled nanoscale mapping of surface morphology, revealing structural irregularities associated with malignancy, while SEM provided detailed imaging of cellular and extracellular architecture, enhancing the visualization of cancer-induced morphological alterations. Although Raman spectroscopy has been studied for decades in cancer research, it has not yet replaced Pap smears and biopsies in clinical practice due to challenges in standardization, reproducibility, and clinical validation. This pilot study aims to serve as a stepping stone toward that goal, providing proof-of-concept data that may support the gradual translation of Raman spectroscopy into clinically relevant diagnostic workflows and underscores the potential of the technique, supported by complementary high-resolution imaging techniques, in the characterization of cervical cancer tissues. The integration of Raman, AFM, and SEM was used here as a pilot approach on paraffin-embedded samples, with AFM and SEM providing supportive morphological information while the long-term aim is to transfer Raman spectroscopy to fresh, untreated tissues, where its non-destructive and label-free nature could enable minimally invasive diagnostic applications.

Pleading Poverty — Related-Party Payments and Health Care Entities’ Financial Health

Accretion bursts crystallize silicates in a planet-forming disk

The role of goal orientation, collaboration, and stress in shaping scientific creativity

Assessing in-hospital mortality risk in ICU lung cancer patients using machine learning: An analysis based on the MIMIC-IV database

Background Patients with advanced lung cancer admitted to the intensive care unit (ICU) face a substantially elevated risk of in-hospital mortality. Early identification of high-risk individuals is essential to support timely clinical decision-making. This study aimed to develop and validate a predictive model using machine learning (ML) techniques to estimate in-hospital mortality in this patient population. Methods Clinical data were obtained from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. Feature selection was performed using least absolute shrinkage and selection operator (LASSO) regression, enabling the construction of eight ML models: logistic regression (LR), support vector machine (SVM), gradient boosting machine (GBM), artificial neural network (ANN), extreme gradient boosting (XGBoost), k-nearest neighbors (k-NN), adaptive boosting (AdaBoost), and random forest (RF). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), as well as accuracy, sensitivity, specificity, and F1 score. Discrimination, calibration, and clinical utility were also evaluated. The final model incorporated 27 clinically interpretable variables, including not only established severity scores (e.g., SAPS II) but also dynamic treatment factors (e.g., vasopressin, mechanical ventilation duration) that reflect real-world ICU practice. SHAP analysis was employed to enhance interpretability, allowing clinicians to understand both the magnitude and directionality of key predictors—an improvement over black-box ML applications in prior studies. Results Among the 1,755 patients included, 368 (21%) died during hospitalization in the training cohort.Notably, older individuals, particularly those of Caucasian descent, demonstrated a higher susceptibility to mortality during their hospital stay. Lasso regression revealed that 27 variables demonstrated a significant correlation with lung cancer, such as gender, hospital stay duration The XGBoost model achieved the highest predictive performance, achieving an accuracy of 0.783, an F1 score of 0.595, and an AUC of 0.865 (95% CI: 0.840–0.891)within the training cohort. The performance metrics for the test cohort reflected similar trends, with an accuracy of 0.719, an F1 score of 0.543, and an AUC of 0.790(95% CI: 0.741–0.840). Key predictors identified consistently across models (LR, SVM, ANN, and XGBoost) included hospital stay duration, Simplified Acute Physiology Score II (SAPS II), use of norepinephrine and vasopressin, prothrombin time (PT), mechanical ventilation duration, white blood cell count (WBC), and blood urea nitrogen (BUN). The SHAP summary plot further illustrated the direction and magnitude of influence for the top 15 predictors. Conclusion The XGBoost-based model showed the best performance in predicting in-hospital mortality among critically ill lung cancer patients. Hospital stay duration and SAPS II score emerged as the most influential predictors,which can serve as the basis for a simplified clinical risk score. These findings may support early risk stratification and guide clinical decision-making in the ICU. The analysis, relying exclusively on internal divisions from MIMIC-IV, restricts the model’s generalizability and, consequently, its applicability in broader clinical contexts.

Idiopathic Intracranial Hypertension

Construction and application of knowledge graph for seed quality standard documents

Spontaneous cervical artery dissection is associated with a distinct peripheral immune cell signature

Objectives Despite being a major cause of ischemic stroke in young adults, the biological underpinnings of cervical artery dissection (CeAD) remain poorly defined. Recent data implicate immune activation as a potential contributor. We aimed to determine whether patients with CeAD display a distinct peripheral immune signature, which may provide insights into pathogenic inflammatory processes. Methods Peripheral blood mononuclear cells (PBMCs) from patients with spontaneous CeAD (n = 7 without and n = 11 with ischemic stroke) and ten age-matched healthy controls were analyzed via multi-color flow cytometry. Immune cell composition and activation markers were assessed, and sparse partial least squares discriminant analysis (sPLS-DA) was employed to identify CeAD-associated immune features. A secondary comparison with ischemic stroke controls was included to assess the specificity of identified immune alterations. Results Compared to healthy controls, CeAD patients displayed increased frequencies of CD4 ⁺ T cells and decreased natural killer T (NKT) cells. sPLS-DA demonstrated clear separation of CeAD and control immune profiles, driven by increased CD28 expression on naïve CD8 ⁺ T cells, NKp46 on NK cells, and IL-2Rα (CD25) on myeloid dendritic cells (mDC2). Elevated granzyme K in naïve CD8 ⁺ T cells indicated enhanced cytotoxic potential, while regulatory T cells were diminished. These alterations were largely preserved when compared to ischemic stroke controls, suggesting CeAD-specific immune activation. No microbial pathogens were detected by untargeted metagenomic sequencing. Discussion CeAD is associated with a distinct peripheral immune signature characterized by enhanced cytotoxic activity and reduced regulatory features. These alterations may reflect a post-infectious autoimmune mechanism triggering CeAD or a secondary immune-inflammatory response to vascular injury. Larger, longitudinal studies are needed to clarify causality and assess whether immune modulation could serve as a therapeutic target in CeAD.

Changing Role of Adjuvant Therapy in Stage III Melanoma

Correction: AOH induces oxidative stress and DNA damage in ovarian cancer cells via modulation of GPER1 and HIF1α/PI3K/CLDNs signaling pathway

Latent TB infection in solid organ transplant recipients in Serbia: A single center experience from a low TB burden country

Background Solid organ transplant (SOT) recipients face a heightened risk of latent tuberculosis infection (LTBI) reactivation and progression to active tuberculosis (TB) because of their immunosuppressed state . In low TB burden countries like Serbia, data on LTBI and TB incidence in transplant recipients are limited. Objectives To determine the prevalence of latent tuberculosis infection and the incidence of active tuberculosis among kidney and liver transplant recipients, and to identify factors associated with LTBI in this high-risk group. Methods A retrospective cohort study was conducted among 275 adult SOT recipients (203 kidney, 72 liver) who underwent transplantation at a tertiary care center in Serbia between 2007 and 2017. LTBI was assessed using Interferon-Gamma Release Assay. Patients were followed for five years post-transplantation to monitor for LTBI and active TB. Multivariable logistic regression was used to identify independent predictors of LTBI. Results The post-transplant LTBI prevalence among kidney transplant recipients was 23.4 (95% CI = 14.7%–35.1%), while 5.6 (95% CI = 2.2%–13.4%) among liver transplant recipients (p = 0.003). The crude incidence of post-transplant TB was 151.4 per 100,000 person-years, over seven times higher than the general population in Serbia. Median time to TB diagnosis was 6 months (IQR: 3.0–12.0). Independent predictor of LTBI was previous contact with a TB case (OR =26.08; 95% CI = 5.63–120.90). Conclusions The substantially elevated burden of LTBI and TB among SOT recipients underscores the need for systematic LTBI screening and targeted preventive treatment. Strengthened collaboration among transplant physicians, pulmonologists, and public health teams is essential to improve TB prevention strategies in this vulnerable population, particularly in countries aiming for TB elimination.

A Phase 2 Trial of Tobevibart plus Elebsiran in Hepatitis D

Computational analysis of blood flowing through an artery with post stenotic dilatation by implying Sisko model parametric approach

Evaluating community pharmacists’ involvement in patient counselling and health education in Nairobi, Kenya: A cross-sectional study

Background Community pharmacists serve as the most accessible healthcare providers, playing a pivotal role in patient counselling, health education, and disease prevention. Despite their critical function in the healthcare system, limited research has examined their actual involvement in these areas within Nairobi, Kenya. This study aimed to assess community pharmacists’ engagement in patient counselling and health education, comparing self-reported practices with observed behaviours using a simulated patient approach. Methods This study employed a cross-sectional descriptive design incorporating both structured questionnaires and a simulated patient (SP) methodology to compare self-reported and observed counselling practices among registered community pharmacies in Nairobi. Sixty pharmacies were randomly selected, and forty-eight pharmacists completed the study. Data were collected using structured questionnaires that assessed pharmacists’ self-reported counselling and health education practices, alongside simulated patient visits that evaluated actual pharmacist–patient interactions. The case scenarios included a request for diabetes medication without a prescription, an over-the-counter acne treatment request, and a consultation for severe acne. These encounters were used to assess counselling competence, regulatory adherence, and patient education. Data were analysed using descriptive statistics to compare self-reported practices with observed behaviours. Results While 66.7% of pharmacists reported providing detailed counselling, only 26.7% of simulated visits reflected this practice. Additionally, 75% of pharmacists provided minimal verbal counselling beyond stating the drug name and dosage. Patient satisfaction levels were low, with most simulated patients rating their encounters poorly on a 20-point scale. Conclusion The study underscores critical gaps in patient counselling, health education, and adherence to prescription regulations among community pharmacists in Nairobi. The disconnect between self-reported and observed counselling practices suggests the need for targeted training programs to enhance pharmacists’ communication skills, regulatory compliance, and disease prevention counselling. Strengthening enforcement mechanisms and integrating patient-centred education strategies in pharmacy curricula are essential to optimizing pharmacists’ roles in healthcare. These findings highlight the need for targeted training and regulatory enforcement to strengthen pharmacists’ roles in patient counselling and health education in Nairobi.

Medical Imaging and Hematologic Cancer Risk among Children and Teens

Author Correction: Rolling back human pluripotent stem cells to an eight-cell embryo-like stage

Impact of autumn–winter wind speed and low temperatures on acute coronary syndrome: a 5-year single-center study in Beijing

Evidence for motor imagery in the management of vestibular disorders does not support recent guidelines: A systematic search and review

Context Vestibular disorders significantly impact people’s quality of life, affecting functions such as balance and walking. Current treatments involve pharmacological and non-pharmacological approaches, with vestibular rehabilitation proving effective in helping to compensate for deficits. Although traditional techniques address various aspects of the vestibular system, many fundamental studies suggest motor imagery could reduce vestibular impairment. Despite the paucity of research on motor imagery for vestibular disorder rehabilitation, recent expert recommendations suggest it could enhance functional recovery. This review questions the evidence in the literature on the clinical value benefits of motor imagery as part of vestibular rehabilitation. The aims of this study were 1. to identify motor imagery interventions used in the literature, 2. to critically appraise them, and 3. to report their impact on clinical outcomes. Methods We conducted a systematic search using the PubMed, Cochrane Library, Web Of Science, CINAHL and Scopus databases. The review was registered on PROSPERO and is reported according to the PRISMA guidelines. PICO criteria were adults undergoing a motor imagery intervention as part of vestibular rehabilitation, studies with or without comparators, and the use of clinical outcome measures. A critical grid was completed, and a risk of bias assessment was performed. Results Despite identifying 2404 (after duplicate removal) concerning motor imagery and vestibular rehabilitation, only two articles met our inclusion criteria. Our findings suggest a clinical benefit of integrating motor imagery into vestibular rehabilitation. However, the limited evidence and methodological shortcomings warrant caution, including small sample size, absence of imagery quality assessment, and poor generalizability. Conclusion Future research should address the identified limitations, including the need to study a broader range of vestibular pathologies, use comprehensive assessments, and evaluate long-term effects. This would contribute to a more thorough understanding of motor imagery as part of vestibular rehabilitation. Trial registration PROSPERO CRD42023444673

The 25th Anniversary of a Nearly Unknown Health Policy Turning Point