Tag: nevin manimala

Ophthalmol Ther. 2026 Feb 21. doi: 10.1007/s40123-026-01330-3. Online ahead of print.

ABSTRACT

INTRODUCTION: To determine the incidence, clinical characteristics, and spatial associations of retinal arterial vasospasm in retinal vein occlusion (RVO), and to explore its relationship with aqueous humor endothelin-1 (ET-1) concentration.

METHODS: This retrospective cohort study included 58 eyes with RVO that underwent wide-field fluorescein angiography (FA) within 1 month of presentation. In addition, aqueous humor samples were prospectively collected from a subset of 18 treatment-naïve RVO eyes. Arterial vasospasm was defined as a focal narrowing of the arterial lumen on early-phase FA. Cotton wool spots (CWS) and retinal hemorrhage were evaluated using color fundus photography and electronic medical records. Topographic concordance was assessed using quadrant-based, horizontal, and vertical hemifield classifications. Aqueous humor samples were analyzed for ET-1 concentration using enzyme-linked immunosorbent assay (ELISA).

RESULTS: Arterial vasospasm was identified in 21 eyes (36.2%), including six eyes with central RVO and 15 eyes with branch RVO. Vasospasm was most commonly observed in the superotemporal quadrant and predominantly on second-order arteriolar branches (78.6%). CWS were more frequent in eyes with vasospasm compared with those without (81.0% vs. 54.1%; p = 0.050). Significant spatial concordance between vasospasm and CWS was observed in the vertical hemifield (p = 0.049), with no concordance observed with retinal hemorrhage location or severity. Exploratory aqueous humor analysis showed higher ET-1 concentrations in eyes with vasospasm (8.37 ± 4.59 vs. 5.74 ± 1.88 pg/mL), although statistical interpretation was limited by the sample size.

CONCLUSION: Retinal arterial vasospasm is a relatively common but under-recognized feature of RVO. Its association with CWS and higher ET-1 levels suggests localized arterial endothelial dysfunction. Vasospasm may represent an arterial component of RVO pathophysiology and warrants further investigation.

PMID:41722008 | DOI:10.1007/s40123-026-01330-3

Eur J Epidemiol. 2026 Feb 21. doi: 10.1007/s10654-025-01342-6. Online ahead of print.

ABSTRACT

Ease of access to big data and automated analysis tools can facilitate the rapid generation of poorly designed epidemiological studies, which collectively pose a risk to the quality of medical literature. Member organizations of the TriNetX network have the ability to mass-produce retrospective cohort studies at speed using the federated data network’s statistical power and streamlined analytics pipeline. This exploratory meta-research study collated 13 published TriNetX-based retrospective cohort studies that claim to have used a design that is, in fact, impossible on the platform (the setting of a pseudo-index event on the TriNetX platform). Of these, 8 studies described their analysis as being conducted on the platform alone, making their description of the index event impossible. When we queried seven different generative artificial intelligence (AI) tools for advice on how to set an index event on TriNetX, six tools suggested at least one strategy that cannot be implemented on the platform. Unlike previously documented errors in TriNetX-based studies, we argue that the reporting of impossible index event designs in the identified publications likely constitute either distortion of the reported methods or the uncritical adoption of false AI-generated methodological advice. In an age of accelerating and increasingly automated medical research, editors and peer-reviewers must be informed of limitations with emerging epidemiological datasets and analytic tools.

PMID:41721987 | DOI:10.1007/s10654-025-01342-6

J Mol Neurosci. 2026 Feb 21;76(1):36. doi: 10.1007/s12031-026-02494-0.

NO ABSTRACT

PMID:41721963 | DOI:10.1007/s12031-026-02494-0

Adm Policy Ment Health. 2026 Feb 21. doi: 10.1007/s10488-026-01492-z. Online ahead of print.

NO ABSTRACT

PMID:41721949 | DOI:10.1007/s10488-026-01492-z

Bull Math Biol. 2026 Feb 21;88(3):42. doi: 10.1007/s11538-026-01593-8.

ABSTRACT

This study explores the role of mass testing in controlling the COVID-19 pandemic using an age-stratified compartmental model. The model evaluates the impact of different testing strategies on the pandemic’s reproduction number, $R_0$ , while also considering social distancing measures and demographic characteristics. The analysis highlights the importance of combining mass testing with isolation strategies to reduce the spread of the virus. The simulations demonstrate that in countries characterized by high levels of elderly cohabitation with younger individuals, vertical isolation is insufficient; horizontal isolation with work restrictions, alongside testing and susceptibility reduction measures, is crucial. For aged developed countries, where cohabitation of the elderly with younger individuals is less prevalent, and for least developed countries, where the population has a predominantly youthful age structure, pandemic control is more feasible with fewer tests. The study also emphasizes the critical role of identifying asymptomatic cases to achieve optimal epidemic control. Lastly, the cost-effectiveness of various testing strategies is examined, providing insights for public health policy decision-making.

PMID:41721946 | DOI:10.1007/s11538-026-01593-8

Bull Math Biol. 2026 Feb 21;88(3):44. doi: 10.1007/s11538-026-01608-4.

ABSTRACT

The effects of external perturbations (or disorder) in the Hopf bifurcations of a central pattern generator (CPG) network of neurons that serves as a model for the circuit realization of ANIBOT-a biologically-inspired animal robot with four legs-are studied, analytically and computationally, from the standpoint of homeostasis. In particular, we employ recent developments in the mathematical description of homeostasis, e.g., input-output functions, to explore the CPG response to perturbations of the network connectivity, the internal dynamics of the neurons, and electronic noise as it arises in the circuit realization of ANIBOT. The patterns of locomotion (Walk, Jump, Trot, Bound, Pace, and Pronk) are controlled, mainly, by the phase dynamics of a CPG network. The results show that with the exception of the Walk and Jump gaits, the phase dynamics of all other gaits exhibit perfect homeostatic responses. In addition, a distinctive feature of the network dynamics is that, under certain conditions, the external perturbations can lead to the appearance of certain patterns, which are absent in the unperturbed system, i.e., disorder-induced pattern formation.

PMID:41721944 | DOI:10.1007/s11538-026-01608-4

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