Amyloid deposition in the central nervous system is increasingly recognized in transthyretin (ATTR) amyloidosis, particularly in patients with prolonged survival following liver transplantation or disease-modifying therapies. However, the structural basis of transthyretin aggregation in the brain remains unknown. Here we determine cryo-electron microscopy (cryo-EM) structures of ex vivo brain-derived ATTR fibrils from patients carrying the ATTRv-V30M and ATTRv-V30G variants. Both fibrils adopt folds distinct from those previously reported in peripheral tissues and the vitreous humor. V30M fibrils exhibit a continuous ordered core spanning residues Pro11-Asn124, whereas V30G fibrils consist of a substantially reduced ordered core, revealing pronounced structural divergence even within the same tissue environment. Despite this diversity, comparative analyses identify conserved regions across ATTR fibrils, including a segment implicated in transthyretin aggregation and targeted for diagnostic and therapeutic development. These results provide direct evidence that local tissue context can shape amyloid fibril architecture in human disease.

The design of azo-imine derivatives with tunable photochromic and nonlinear optical (NLO) properties is crucial for developing advanced optoelectronic materials. In this study, three new azo-imine derivatives (C1-C3) incorporating methyl (-CH3), methoxy (-OCH3), and chloro (Cl) substituents, along with an octyloxy chain, were synthesized and characterized through a combination of experimental and theoretical approaches. FT-IR and [1]H NMR spectra confirmed the successful formation of the azo-imine framework. DFT calculations at the B3LYP/6-311++G(d,p) level were used to examine optimized geometries and electronic structures. UV-Vis spectra showed weak absorption bands at 272-274 nm and intense π-π* transitions at 354-360 nm, with substituent-dependent spectral shifts reflecting modulation of conjugation and electron density. Photochromic studies demonstrated that C1 undergoes the fastest E → Z isomerization, whereas the chloro-substituted derivative C3 exhibits the highest photoisomerization efficiency and the most rapid Z → E thermal recovery. The electron-donating methoxy group in C2 enhances conjugation but reduces photoisomerization efficiency. Thermogravimetric analyses confirmed high thermal stability for all derivatives. Frontier molecular orbital and DOS analyses revealed a reduced HOMO-LUMO gap for C2, indicating facilitated electronic transitions. NBO results showed dominant σ → σ* interactions with Lewis-type contributions of 97.545%, 97.564%, and 97.606% for C1, C2, and C3, respectively. Transition density matrix and excitation binding energy analyses indicated strong charge-transfer character and effective electron delocalization in C2. Nonlinear optical (NLO) responses increased markedly with solvent polarity, and in the aqueous phase, C2 exhibited the highest βtotal (878 × 10[-31] esu), surpassing urea by more than two orders of magnitude. These results underscore the significant role of substituent effects in governing photochromic reversibility and nonlinear optical (NLO) performance, with C3 exhibiting the highest photoswitching efficiency and C2 emerging as the most promising NLO-active candidate. Thus, this study offers valuable insights for the rational design of azo-imine systems with tunable photophysical and optical properties, paving the way for advanced optoelectronic applications.

This study presents a universal method for fabricating size-selective, liquid-gated field-effect transistor (FET) sensors using semiconducting single-walled carbon nanotubes (scSWCNTs) combined with metal-organic frameworks (MOFs) and poly(vinylidene fluoride) (PVDF) polymer barriers. By employing a layer-by-layer architecture, scSWCNTs were coated with a single layer of MOF crystals followed by a PVDF thin film, which restricts the access to scSWCNTs to only through MOF pores. This design enables a gate capacitance modulation mechanism, where only analyte molecules small enough to enter the MOF pores can modulate the scSWCNT conductance. Four MOFs, namely UiO-66, UiO-67, ZIF-8, and MIL-96, were fabricated into the scSWCNT/MOF/PVDF FET sensors and tested for their sensing capabilities toward norfentanyl (NF) and dopamine (DA) in 0.1 M KCl solution. UiO-67 devices showed positive responses to NF due to favorable pore size matching, while devices fabricated with other MOFs exhibited negative responses due to pore size exclusion. Tests with DA also confirmed the size-selective sensing abilities of the sensors. Long-term stability tests revealed that weak interactions between MOFs and PVDF limit the sensor durability in aqueous solution. Despite this limitation, the proposed approach shows considerable potential for constructing diverse size-selective sensors that enhance specificity and selectivity in scSWCNT/MOF/polymer sensing platforms.

Contamination of feed with mycotoxins and the intensive use of therapeutic antibiotics in modern poultry farming have resulted in the accumulation of chemical residues in meat and the environment. These residues may contribute to hepatic, renal, and cardiac dysfunctions, leading to significant public-health concerns. Despite growing awareness and extensive studies on individual poultry contaminants, comprehensive molecular-level assessments of all our selected compounds are still limited. Integrated computational analyses combining density functional theory (DFT), molecular docking, molecular dynamics (MD) simulation, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and prediction of activity spectra for substances (PASS) evaluations to disclose their multi-organ toxic mechanisms also remain scarce. This study was designed to evaluate the hepatic, renal, and cardiac toxicity of selected mycotoxins and therapeutic antibiotics through a computational framework. Molecular geometries and electronic properties were assessed using DFT calculations. As per DFT results, ZER, CIP, ENR, and OTA showed better thermodynamic stability due to higher HOMO-LUMO energy gap; and exhibited higher dipole moments in AB1 (8.26 Debye), CIP (9.70 Debye), ENR (9.80 Debye), and OXY (6.89 Debye). The lower HOMO-LUMO energy gap indicates that these compounds have higher chemical reactivity. Molecular docking result revealed strong binding affinities (ranging from -7.5 kcal mol-1 to -9.4 kcal mol-1) within selected ligands and proteins, while MD simulation confirmed stable protein-ligand interactions. Additionally, ADMET and PASS prediction elucidated the potential nephrotoxicity (ENR +0.37, OXY +0.87, and OTA +0.72); hepatotoxicity (ENR +0.94, OXY +0.61, and OTA +0.49); and myocarditis (ENR +0.28, OXY +0.92, and OTA +0.35). Overall, our findings highlighted the potential health risks posed by mycotoxin residues and therapeutic antibiotics used in poultry farms.

Bangla, one of the most widely spoken languages in the world, presents major challenges in handwritten character recognition because of its complex compound characters with intricate shapes, diverse writing styles, and structural similarities. These features make Bangla a representative example of complex scripts that remain difficult for conventional Optical Character Recognition (OCR) systems. This study focuses on improving the recognition of Bangla handwritten compound characters using a modified DenseNet architecture named CompoundDenseNet. The architecture enhances feature extraction and reuse to better capture the visual variations and fine structural details that existing models often struggle to handle. Its performance was evaluated on three benchmark datasets, BanglaLekha Isolated, Ekush, and CMATERdb, achieving recognition accuracies of 98.5%, 98%, and 96.2% respectively, surpassing previously reported methods. Misclassification analysis using a confusion matrix revealed that the Adam optimizer produced the most stable and accurate results with faster convergence compared to other optimizers tested. While the results demonstrate significant progress, the study also highlights the need for larger and more diverse datasets. Overall, CompoundDenseNet contributes to advancing Bangla handwritten compound character recognition and has the potential to enhance real-world applications such as education, legal documentation, and digital accessibility in Bangla language technologies.

Medical image classification requires models that effectively capture both fine-grained local patterns and global anatomical structures while maintaining computational efficiency for clinical deployment. Although state-of-the-art models such as MedMamba utilize State-Space Models (SSMs) to balance accuracy and efficiency, their sequential operations limit parallelism and increase runtime. To overcome these limitations, we propose MedSpectralNet, a lightweight Convolutional Neural Network (CNN) architecture that approximates self-attention with linear complexity to efficiently extract multi-frequency features. The model introduces a dual-stream feature extractor that processes global and local information in parallel, and a ContextGate block that adaptively fuses multi-scale representations. MedSpectralNet is evaluated across six benchmark datasets from MedMNIST (including BloodMNIST, BreastMNIST, DermaMNIST, PneumoniaMNIST, OrganCMNIST, and OrganSMNIST), MedSpectralNet achieves an average accuracy of 93.7% on OrganCMNIST and 98.0% on BloodMNIST, showing 1-4.3% relative accuracy gains when compared to larger transformer-based models. Importantly, it delivers this performance with only 8.5 million parameters, representing approximately 60% fewer parameters than MedMamba-T, which requires 14.5 million parameters. MedSpectralNet has also achieved high AUC values up to 0.999 across multiple classes, demonstrating state-of-the-art accuracy with substantially reduced computational cost and improved parallelization, which makes MedSpectralNet well-suited for real-time and resource-constrained classification-based medical applications.

Background: The goal of this study was to evaluate whether medical recommendation of Angocin[®]Anti-Infekt N (hereafter referred to as Angocin[®]) on the day of diagnosis of an acute upper respiratory tract infection (aURTI) or acute sinusitis (AS) is negatively associated with a recurrence of these diagnoses, incidence of antibiotic prescriptions, incidence of chronic sinusitis, nasal polyps, or sick leave duration. Methods: This retrospective cohort study utilized the IQVIA[TM] Disease Analyzer database and included patients by general practitioners with at least one diagnosis of aURTI or AS from 2005 to 2024 and a prescription of Angocin[®], nasal medications (xylometazoline, oxymetazoline) and mucolytics (ambroxol or acetylcysteine), other phytopharmaceutical drugs, or antibiotics on the day of diagnosis. Patients who received Angocin[®] were matched separately to each of the three comparison cohorts in a 1:5 ratio using a nearest-neighbor propensity score approach. The relationship between Angocin[®] prescription and the risks of a recurrence, subsequent antibiotic use or progression to chronic disease was then estimated with Cox proportional hazard models. To examine whether Angocin[®] exposure was associated with the length of sick leave, univariable conditional logistic regression was applied. Results: A total of 3501 Angocin[®] patients and 17,505 patients in each further cohort were investigated. Angocin[®] prescription was associated with a significantly lower incidence of a newly diagnosed aURTI/AS as compared to other phytopharmaceuticals (Hazard ratio (HR): 0.78; 95% confidence interval (CI): 0.68-0.86), nasal medications and mucolytics (HR: 0.79; 95% CI: 0.71-0.88), or antibiotics (HR: 0.85; 95% CI: 0.77-0.95). In addition, there was a significantly lower incidence of subsequent further prescriptions of antibiotics when compared to other phytopharmaceuticals (HR: 0.92; 95% CI: 0.82-0.99), nasal medications and mucolytics (HR: 0.87 (95%; CI: 0.80-0.95), or antibiotics (HR: 0.62; 95% CI: 0.57-0.67). Furthermore, Angocin[®] was associated with the most advantageous pattern of work absence across all time periods examined. Conclusions: Considering the limitations of the study, the results cast a positive light on Angocin[®] prescription in the management of aURTI/AS, particularly with regard to recurrence rates, subsequent antibiotic prescriptions, and sick leave duration.

Prolonged use of topical nasal decongestants such as xylometazoline or oxymetazoline can lead to rhinitis medicamentosa (RM). This medication-induced condition is characterized by rebound congestion and compulsive reuse. A debated question is whether RM signifies physiological dependence, addiction, or simply a habit. This commentary aimed to evaluate Lakatos et al.'s (2025) work, which investigated this issue through qualitative interviews with 20 affected individuals. Using directed content analysis based on Griffiths' (2005) components model of addiction, Lakatos et al., identified all six elements (salience, mood modification, tolerance, withdrawal, conflict, and relapse) in patient histories. Lakatos et al. (2025) performed a timely and conceptually sophisticated study that connects addiction theory to a common otorhinolaryngological condition. Their qualitative approach captures the everyday lived experience of patients with RM with robust ecological validity and clinical relevance. However, the theory-driven analysis risks confirmation bias by fitting data to Griffiths' addiction model, and the small, convenience-based sample limits generalizability. Despite these constraints, the paper offers valuable insight into how negative reinforcement and conditioned anxiety sustain compulsive nasal spray use. Overall, it successfully bridges clinical observation and theoretical debate, advancing understanding of iatrogenic dependence within everyday medical practice.

ALECT2 amyloidosis is a rare systemic disease characterized by the pathological deposition of leukocyte cell-derived chemotaxin-2 (LECT2) as amyloid fibrils, primarily affecting the kidneys and liver. The molecular mechanisms underlying LECT2 aggregation remain poorly defined, hindering diagnostic and therapeutic development. Here, we present cryo-electron microscopy structures of ex-vivo ALECT2 fibrils extracted from a patient's kidney. We identified three fibril polymorphs: a predominant single-protofilament morphology and two minor double-protofilament morphologies. The dominant single-protofilament morphology comprises the full-length 133-residue LECT2 protein and retains all three native disulfide bonds. Low-resolution reconstructions of double-protofilament morphologies suggest they adopt a similar fold to the single protofilament morphology, but form paired assemblies with different inter-filament interfaces. Mass spectrometry also reveals acetylation within the fibrils. These findings offer critical insights into the structural basis of ALECT2 amyloid formation and identify molecular features that could inform future diagnostic and therapeutic approaches.