Tag: pubmed

J Mol Neurosci. 2026 Feb 21;76(1):37. doi: 10.1007/s12031-026-02486-0.

ABSTRACT

There is an urgent need for early and accurate biomarkers of neurodegenerative disorders. Due to the high innervation and accessibility of the skin, a skin biopsy is a minimally invasive method of detecting phosphorylated α-synuclein (p-α-syn) and assessing intraepidermal nerve fiber density (IENFD). We analyzed biopsies taken from the back and the leg of patients with parkinsonian syndromes (Park.sy.), α-synucleinopathies, multiple system atrophies (MSA), tauopathies, and other neurological disorders, as well as from healthy controls. Double immunofluorescence was performed for p-α-syn (Ser129) and protein gene product 9.5 (PGP 9.5), alongside quantitative IENFD assessment. p-α-syn was significantly more prevalent in the patient groups than in the control group. The highest prevalence was observed in patients with parkinsonian syndromes, α-synucleinopathies and MSA. Tauopathies showed preferential paravertebral positivity. Reduction or absence of IENFD was most pronounced in tauopathies (75%), while IENFD was most commonly preserved in MSA (83.3%), indicating that disease-specific patterns of peripheral nerve involvement are exhibited. p-α-syn positivity was found to correlate with shorter disease duration, suggesting its potential as an early biomarker. Combined with olfactory testing, cutaneous markers improved diagnostic discrimination. Our findings support the use of skin biopsies as a promising clinical tool in diagnosing biomarker-based neurodegenerative diseases.

PMID:41721941 | DOI:10.1007/s12031-026-02486-0

Bull Math Biol. 2026 Feb 21;88(3):43. doi: 10.1007/s11538-026-01606-6.

ABSTRACT

Rooted phylogenetic networks allow biologists to represent evolutionary relationships between present-day species by revealing ancestral speciation and hybridization events. A convenient and well-studied class of such networks are ‘tree-child networks’ and a ‘ranking’ of such a network is a temporal ordering of the ancestral speciation and hybridization events. In this short note, we investigate the question of counting such rankings on any given binary (or semi-binary) tree-child network. We also investigate the relationship between rankable tree-child networks and the class of ‘normal’ networks. Finally, we provide an explicit asymptotic expression for the expected number of rankings of a tree-child network chosen uniformly at random.

PMID:41721936 | DOI:10.1007/s11538-026-01606-6

Neurochem Res. 2026 Feb 21;51(2):83. doi: 10.1007/s11064-026-04681-2.

ABSTRACT

Major depressive disorder (MDD) is a prevalent and complex condition with limited treatment success in many patients. Photobiomodulation (PBM), particularly transcranial PBM (tPBM) using red to near-infrared light, has emerged as a promising non-invasive intervention. However, optimal parameters and precise mechanisms remain unclear. This research aimed to analyze the effects of transcranial photobiomodulation (red and infrared) on behavioral and biological parameters related to MDD in a chronic mild stress (CMS) model. Male Wistar rats were exposed to CMS for five weeks and subsequently categorized into two groups-resilient (CMS-R) and susceptible (CMS-S)-based on their performance in the sucrose consumption test (SCT). The CMS-S group was further divided into three subgroups: (1) sham treatment, (2) tPBM red (600 nm), and (3) tPBM infrared (840 nm). A control group of non-stressed animals was included for baseline comparisons. Biological measures included lipid damage (TBARS), antioxidant defense (TEAC), mitochondrial complex IV activity (CCO), and nitric oxide (NO) concentration in the prefrontal cortex and blood were measured. As expected, post-tPBM treatment (both red and infrared groups) exhibited increased sucrose consumption compared to the sham (p < 0.001). The red and infrared presented higher serum TEAC levels than the sham and control groups, but these effects did not reach statistical significance (p = 0.306). In contrast, the red group showed lower peripheral TBARS levels than the sham group (p = 0.0048); such effect was similar to the control non-stress group. The infrared group showed higher NO levels within the hippocampus than the sham group p = 0.0134) and higher prefrontal CCO activity levels than the red group (p = 0.012), which was similar to the control non-stress group. Our study demonstrated that animals treated with tPBM using red (600 nm) or infrared (840 nm) wavelengths exhibited significant improvements in both behavioral and biological parameters in the CMS model. In particular, tPBM may offer therapeutic benefits by ameliorating oxidative stress and enhancing mitochondrial function, thereby presenting a promising alternative for the management of MDD.

PMID:41721935 | DOI:10.1007/s11064-026-04681-2

Health Care Manag Sci. 2026 Feb 21;29(1):8. doi: 10.1007/s10729-025-09750-6.

ABSTRACT

In response to the growing number of hospital bankruptcies across the United States, this study sought to develop a predictive and interpretable model tailored specifically to the healthcare industry. Utilizing a longitudinal dataset of 3,091 short-term acute care hospitals from 2008 to 2021, we evaluated and compared traditional bankruptcy prediction models-Altman’s Z”, Ohlson’s O-score, and Zmijewski’s model-against a newly developed hospital-specific logistic regression model (BRKFSST). We incorporated over 30 financial and hospital-level variables, including quality indicators, ownership type, and market characteristics. Unlike prior models, ours lagged all unknowable variables to ensure true out-of-sample prediction. The BRKFSST model achieved strong performance, with an Area Under the Curve (AUC) of 81.8%, balanced accuracy of 72.2%, and a mean recall of 60.6% across multiple test/train splits, outperforming all benchmark models. Importantly, the model retained interpretability, allowing for the identification of key predictors such as labor compensation ratio, adjusted patient days, and quality ratings. These findings provide actionable insights for hospital leaders and policymakers to identify at-risk institutions and implement early interventions to prevent financial collapse and preserve access to care.

PMID:41721925 | DOI:10.1007/s10729-025-09750-6

Int Ophthalmol. 2026 Feb 21;46(1):125. doi: 10.1007/s10792-026-03980-5.

ABSTRACT

OBJECTIVES: To investigate the incidence of endophthalmitis following penetrating keratoplasty (PKP) and compare the effectiveness of different antibiotic regimens during the perioperative period.

METHODS: A retrospective cohort study was conducted involving 3706 patients who underwent PKP at Zhongshan Ophthalmic Center between 2012 and 2021. The preventive effects of intraoperative intraoperative local antibiotic injection, preoperative intravenous antibiotic administration, and the combination of both were evaluated. Logistic regression and survival analyses were performed to compare differences in endophthalmitis incidence among the different antibiotic prophylaxis groups.

RESULTS: Postoperative endophthalmitis occurred in 15 of 3706 patients (0.40% incidence). Among 419 patients with underlying infectious corneal disease, 12 developed postoperative endophthalmitis (2.86% incidence). Among 3287 patients with non-infectious corneal diseases, 3 developed postoperative endophthalmitis (0.09% incidence; OR: 32.28, 95% CI 9.07-114.85). For patients with primary non-infectious corneal disease, no statistically significant difference was observed between the intraoperative intraoperative local antibiotic injection, group and the combined antibiotic administration group (P = 0.079).

CONCLUSION: The primary corneal disease is a key risk factor for endophthalmitis after PKP. For non-infectious keratopathy, intraoperative local antibiotic injection, alone is appears adequate for preventing postoperative endophthalmitis.

PMID:41721919 | DOI:10.1007/s10792-026-03980-5

Mol Biol Rep. 2026 Feb 21;53(1):409. doi: 10.1007/s11033-026-11565-9.

ABSTRACT

BACKGROUND: Breast cancer (BC) and Thyroid cancer (TC) are prevalent malignancies in women that share epidemiological and molecular features. Emerging evidence indicates that non-coding RNAs are key regulators of cancer associated gene expression. Long non-coding RNA (lncRNA) drive tumor progression by acting as competing endogenous RNAs (ceRNAs), sponging microRNA (miRNA) to deregulate oncogenic messenger RNA (mRNA). The influence of functional genetic polymorphisms of lncRNAs on their expression, as well as the expression of their ceRNA components RNA in a direct comparative context of BC and TC, remains unexplored.

METHODS: 60 breast cancer and 60 thyroid cancer tissue samples, alongside matched adjacent healthy controls from a Pakistani female patient, were used. Genotyping of lncRNA H19 SNPs (rs3741219 and rs2839698) was performed using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) followed by quantitative real-time PCR (qRT-PCR) to assess the expression of lncRNA H19, miR-152, and DNMT1. Expression and genotype associations, association with clinical parameters, and diagnostic and prognostic utility of the studied RNA were statistically evaluated.

RESULT: Genotyping revealed that rs3741219 showed significant tumor-control differences in breast cancer (p < 0.05). Expression analysis revealed upregulation of lncRNA H19 and DNMT1, and downregulation of miR-152, in tumor samples compared with adjacent healthy controls in both cancers. In genotype-expression analysis, rs3741219 influenced lncRNA H19 expression in both cancer types. Receiver Operating Characteristic (ROC) analysis confirmed the strong diagnostic potential of H19 and DNMT1 (AUC 0.98-1.00). Correlation and regression analyses validated the proposed ceRNA interactions and their significant association with advanced cancer stage. A high-risk score from the H19/miR-152/DNMT1 axis was prognostic only in thyroid cancer (HR = 2.97).

PMID:41721915 | DOI:10.1007/s11033-026-11565-9

Environ Monit Assess. 2026 Feb 21;198(3):239. doi: 10.1007/s10661-026-15060-3.

ABSTRACT

The influence of invasive plant species (IPS) on forest ecosystems has been of sufficient concern to warrant data acquisition on their presence and abundance. These data are needed at various spatial scales for both land management and policy purposes. One potential source of data are national forest inventories (NFIs) that often record IPS observations on sample plots that span relatively large spatial and temporal extents, thus providing data users with a wide range of analytical opportunities to meet desired information needs. In the NFI of the USA, which is conducted by the USA Forest Service’s Forest Inventory and Analysis (FIA) program, IPS presence and foliar cover area are visually observed and recorded nationally on a spatially balanced subset of inventory plots measured each year. As with any sample-based assessment, the implementation of statistically appropriate methods is imperative for credibility of the final estimates. In this paper, statistical methods for calculating population estimates and associated measures of uncertainty for current status and change in IPS attributes are presented. The estimators address both presence and cover area estimation, as well as estimation of area proportions relative to total area domains. Also included are data and various numeric examples that assist in understanding the estimation steps and provide for verification of accuracy in results. The methods should be applicable to most IPS data collected in other forest inventories with little or no modification.

PMID:41721903 | DOI:10.1007/s10661-026-15060-3

Biodegradation. 2026 Feb 21;37(2):39. doi: 10.1007/s10532-026-10267-0.

ABSTRACT

This study investigated the biotransformation of three different plastic surfaces, polypropylene (PP), polyvinyl chloride (PVC) and polyethylene (PE), by anaerobic digestion (AD) system microorganisms under mesophilic conditions. For that, a laboratory-scale AD system was established and plastics were immersed in the sludge for a 50-day incubation period, measured for any significant mass loss. Statistical analysis showed a significant mass loss (p < 0.05) in PVC pieces with a 1.1 ± 0.16 mg average reduction, while PP and PE didn’t show any significant mass loss. Raman spectroscopy analysis revealed temporally increasing novel peaks in PVC at 1729 cm^-1 corresponding to C = O stretching vibrations. This was considered significant and compared against an unchanged marker of PVC, revealing a newly identified peak that has not been documented in prior studies of this material. PP also indicated a temporal increase of novel peaks in the spectral range of C = C stretching vibrations in the region of 1512 cm^-1. Atomic force microscopy (AFM) analysis of PVC showed a reduction in average roughness amplitude from 100 to 90 nm in 30 days and 65 nm to 50 days revealing surface biotransformation. Phase-contrast microscopy further confirmed surface embrittlement across all plastics. Several bacterial species that were associated with plastic biotransformation were isolated and characterized using 16 s rRNA molecular marker gene-based identifications. In conclusion, this study suggests that, the changes to overall surface of the plastics and newly observed surface transformation of PVC leading to biodeterioration, by AD system microorganisms.

PMID:41721890 | DOI:10.1007/s10532-026-10267-0

Abdom Radiol (NY). 2026 Feb 21. doi: 10.1007/s00261-026-05406-3. Online ahead of print.

ABSTRACT

OBJECTIVE: Traditional MRI often requires breath-holding, which is challenging for some patients. This study investigates the Liver Acceleration Volume Acquisition-Flexible (LAVA-Flex) sequence using Cartesian sampling. We aim to assess how various combinations of compressed sensing (CS) and number of excitations (NEX) parameters affect image quality and scanning time for liver MRI under free-breathing conditions. Our goal is to identify the optimal parameter combination and offer a liver imaging protocol that is easily applicable for patients who cannot hold their breath.

METHOD: In this preliminary study, six CS-NEX parameter combinations were tested on healthy volunteers using a 3.0 T MRI: Group A (CS1.2/NEX2), Group B (CS2/NEX5), Group C (CS2/NEX6), Group D (CS2/NEX7), Group E (CS2.5/NEX5), and Group F (CS2.5/NEX6). Objective evaluation indicators included the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective assessment employed a 5-point scoring system to evaluate liver margin sharpness, vascular clarity, respiratory motion artifacts, and overall diagnostic value. Statistical analysis was performed using one-way analysis of variance (ANOVA), the Kruskal-Wallis test, and the weighted kappa test, with P < 0.05 considered statistically significant.

RESULT: We included a total of 30 volunteers in the study. The scanning times varied significantly across the six groups. Objective assessment indicated that the SNR increased progressively with the optimization of the CS-NEX combination, whereas the CNR did not differ significantly between groups. Subjectively, Group A scored the lowest for image quality, while Groups D to F scored the highest. Group E, with the shortest scanning time, achieved the best balance of image quality and efficiency.

CONCLUSION: The combined effect of CS and NEX successfully addressed the challenge of liver imaging during free breathing using traditional MRI equipment. The optimal parameter combination, Group E, achieved the best balance between image quality and time efficiency in 98 s, offering a viable solution for breath-hold-impaired patients.

PMID:41721868 | DOI:10.1007/s00261-026-05406-3

Eur Radiol. 2026 Feb 21. doi: 10.1007/s00330-026-12385-y. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the performance of a commercial artificial intelligence (AI) software in detecting intracranial hemorrhage (ICH) in emergency settings, compared to on-call radiology residents.

MATERIALS AND METHODS: All consecutive unenhanced cerebral CT-scans performed in a single center over a 3-month period in the emergency department in patients with suspected ICH, initially interpreted by radiology residents on-call and subsequently verified and approved by a board-certified radiologist, were concomitantly analyzed by an AI software for the presence of ICH. Results from the AI software were stored in a separate PACS partition and were unavailable to the radiologists for the case reading. We assessed the diagnostic performance of the AI software and of the radiology residents in detecting ICH. The reference standard was the final report of the board-certified radiologist.

RESULTS: Radiology reports of 2153 CT-scans were analyzed, and ICH prevalence was 15.4% (331/2153). The AI software achieved an overall sensitivity of 84% and a specificity of 94.4%, and radiology residents achieved a sensitivity of 96.4% and a specificity of 99.6%, respectively (p-values < 0.001). The sensitivity was 97.7% for AI and 98.5% for residents when CT examinations displayed an association of multiple hemorrhagic types (p = 1). The sensitivity was 95.2% for AI and 98.4% for radiology residents in the presence of multiple ICH sites (p = 0.11).

CONCLUSION: Radiology residents demonstrated a significantly higher performance in detecting ICH compared to the AI software. AI exhibited very good diagnostic performance only in the presence of multiple hemorrhagic sites or multiple hemorrhage types.

KEY POINTS: QuestionHow does the performance of the AI software compare to that of radiology residents in detecting ICH on unenhanced CT in real-life emergency workflow conditions? FindingsIn the emergency setting, the AI software demonstrated lower overall sensitivity and specificity than radiology residents for detecting ICH. Clinical relevanceIn real-life emergency conditions at a university hospital, the AI software did not offer a superior performance compared to radiology residents in detecting ICH. The integration of AI in this specific setting remains to be defined.

PMID:41721849 | DOI:10.1007/s00330-026-12385-y