Nevin Manimala

Curr Neuropharmacol. 2026 Jul 10. doi: 10.2174/011570159X468669260626223524. Online ahead of print.

ABSTRACT

BACKGROUND: Genetic evidence implicates the contribution of the gut-brain axis to neurodegenerative diseases (NDDs). Alterations in gut microbiota and inflammation are key pathophysiological contributors. Elucidating the genetic basis and the role of cytokines can provide insights into mechanisms linking gut microbial composition to neurodegeneration.

METHODS: Using aggregated statistics from five large-scale Genome-Wide Association Studies (GWAS) on Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, multiple sclerosis, and amyotrophic lateral sclerosis, bidirectional two-sample Mendelian Randomization (MR) was used to examine the associations. A two-step multivariable Mendelian randomization approach incorporates data from 91 cytokines to explore potential mediators.

RESULTS: The study reveals 18 positive and 17 negative effects between gut microbiota and NDDs, as well as 10 positive and 10 negative effects between cytokines and NDDs. Remarkably, mediation analysis identified a causal pathway, with evidence that plasma neurturin levels partially mediate the association from genus Ruminococcus2 to multiple sclerosis, with a mediation proportion of 19.19% (OR = 1.038, 95% CI = 1.001-1.086, P = 0.044). No pleiotropy or heterogeneity was detected.

DISCUSSION: These MR findings provide compelling evidence for a genetically anchored gutimmune-brain network in NDDs, with cytokines as intermediates. Bidirectional effects highlight disease-specific microbial signatures and inflammatory contexts. The Ruminococcus2-neurturin pathway in multiple sclerosis may offer mechanistic specificity, aligning with neurotrophic and anti-inflammatory signaling pathways.

CONCLUSION: This study emphasizes the importance of gut microbiota alterations in NDDs and explores inflammation’s partial intermediary role. The findings suggest potential targets for personalized neurodegeneration prevention strategies.

PMID:42460525 | DOI:10.2174/011570159X468669260626223524

J Surg Oncol. 2026 Jul 16. doi: 10.1002/jso.70337. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the survival impact of radical hysterectomy versus simple hysterectomy on non-endometrioid endometrial cancer with cervical involvement.

METHODS: We conducted a multicenter retrospective cohort study of 422 women with uterine serous carcinoma or uterine clear cell cancer treated between 2013 and 2020 at four tertiary teaching hospitals. We classified the patients by the type of hysterectomy. Overall survival and disease-free survival were analyzed and compared using the Kaplan-Meier method and the log-rank test. To adjust for the potential confounders, the Cox proportional hazards regression model was employed.

RESULTS: Our cohort included 275 women who underwent radical hysterectomy and 147 women who underwent simple hysterectomy. The baseline characteristics of the two groups did not differ significantly. There was no statistical difference in recurrence between the two groups (23.8% vs. 20.4%, p = 0.456). Compared with a simple hysterectomy, a radical hysterectomy was not associated with improved overall survival (hazard ratio 0.93, 95% confidence interval 0.69-1.26, p = 0.652), and improved disease-free survival (hazard ratio 0.96, 95% confidence interval 0.72-1.26, p = 0.745). After adjusting for potential confounders, the analysis showed that the type of hysterectomy did not affect overall survival (hazard ratio 0.99, p = 0.968) and disease-free survival (hazard ratio 1.01, p = 0.985) in non-endometrioid endometrial cancer with cervical involvement.

CONCLUSION: Radical hysterectomy was not associated with a survival benefit in non-endometrioid endometrial cancer with cervical involvement.

PMID:42460510 | DOI:10.1002/jso.70337

Bioanalysis. 2026 Jul 16:1-8. doi: 10.1080/17576180.2026.2698605. Online ahead of print.

ABSTRACT

BACKGROUND: Cumene is a high-production volume aromatic hydrocarbon recently reclassified as a Category 1B carcinogen, and 2-Phenyl-2-Propanol (2P2P) is its primary urinary metabolite. Highly sensitive analytical methods, required to detect the low-level exposures typical of the non- occupationally exposed general population, are not available for this compound in literature to this day.

RESEARCH DESIGN AND METHODS: This research details the development and validation of a fully automated Gas Chromatography-Mass Spectrometry (GC-MS) method using SPME extraction to quantify 2P2P at ng/L levels.

RESULTS: The study established reference values by analyzing 242 non-exposed workers, yielding a background range of 31.6-652.7 ng/L (5th-95th percentiles). The literature review encompassed global production trends, environmental ubiquity, and human metabolism. Furthermore, the study utilized biomarkers like cotinine and S-Phenyl Mercapturic Acid (SPMA) to statistically evaluate smoking as a potential confounder.

CONCLUSION: This method fills a significant technical gap by providing a noninvasive, highly sensitive tool for health surveillance. Establishing empirical background reference values is essential for accurately distinguishing between environmental and occupational exposure. Critically, statistical analysis confirms that cigarette smoking is not a significant confounding factor for urinary 2P2P levels, reinforcing its reliability as a specific biomarker for cumene.

PMID:42460492 | DOI:10.1080/17576180.2026.2698605

J Biopharm Stat. 2026 Jul 16:1-17. doi: 10.1080/10543406.2026.2685280. Online ahead of print.

ABSTRACT

By early 2023, there were over 100 gene, cell and RNA products approved globally (Chancellor et al. 2023). The way in which autologous cell and cell-based gene therapy products are administered can include multiple treatment stages, at times including leukapheresis, optional bridging therapy during manufacturing, conditioning regimen, and one or more doses of product. This brings important considerations in the development of the statistical analysis plan for clinical trials of autologous cell and cell-based gene therapies, including application of the estimand framework for key facets. In this article, we review all of the FDA currently approved autologous cell and cell-based gene therapy products as examples as they apply to general considerations for the statistical analysis plan as well as more in-depth discussion of treatment exposure, safety and efficacy analyses, and other aspects.

PMID:42460470 | DOI:10.1080/10543406.2026.2685280

Acta Odontol Scand. 2026 Jul 16;85:416-424. doi: 10.2340/aos.v85.46468.

ABSTRACT

OBJECTIVE: To analyze the effects of cervical headgear (CHG) timing on costs and orthodontic outcome.

MATERIAL AND METHODS: Sixty-seven participants with Class II malocclusion were randomized into two groups. In the early group (EG, n = 33), CHG treatment began after the eruption of first upper molars. In the later-timed group (LG, n = 34), CHG treatment began nearly 2 years later. Orthodontic outcome was evaluated when CHG ended and at the end of follow-up using the Peer Assessment Rating (PAR) index and Little’s Irregularity Index (LII). Costs were calculated using medical records, estimated chairside times and average personnel and material costs.

RESULTS: The mean total costs including personnel and material costs during the follow-up were higher in the EG (€416) compared with the LG (€364) (p = 0.043). No statistically significant differences between the groups were found in the PAR and in the LII scores at the end of follow-up. The number of visits during CHG treatment was higher in the EG (13.3) compared with the LG (10.4) (p = 0.01).

CONCLUSIONS: Earlier initiation of CHG treatment increased the personnel and material costs, number of appointments, and chairside time. Based on the PAR and in the LII scores, the orthodontic outcome of CHG treatment was equal regardless of the timing of the treatment. If orthodontic treatment during mixed-dentition stage is considered, it would be justified from an economic perspective to favor treatment during late mixed-dentition.

PMID:42460461 | DOI:10.2340/aos.v85.46468

Pain Res Manag. 2026;2026(1):e3699422. doi: 10.1155/prm/3699422.

ABSTRACT

BACKGROUND: Medication-overuse headache (MOH) is a disabling secondary headache arising from frequent acute medication intake in individuals with preexisting primary headache. Behavioral and psychosocial factors may perpetuate medication overuse. As a reduction of acute medication intake is essential for remission, educational and behavioral interventions are commonly used; however, their effectiveness remains uncertain.

OBJECTIVES: To systematically evaluate the effectiveness of educational and behavioral interventions on acute medication use, headache frequency, and headache-related disability in patients with MOH, and to assess short- and longer-term outcomes compared to usual care.

METHODS: PubMed, Embase, and the Cochrane Central Register of Controlled Trials were searched from inception to January 2026 for randomized controlled trials evaluating educational or behavioral interventions in adults with MOH. Outcomes included reduction of acute medication use, headache frequency, and headache-related disability. Random-effects meta-analyses were performed where appropriate.

RESULTS: Six trials (610 participants) were included. Brief educational interventions were associated with clinically meaningful reductions in acute medication use and headache frequency. Multiple-session interventions, compared to minimal intervention, were associated with additional mean reductions in acute medication use of approximately 3 days per month and in headache frequency of 2.6 days per month at 3 months and 0.8 days per month at 12 months; however, between-group differences were not statistically significant. Substantial heterogeneity was observed.

CONCLUSIONS: Brief educational interventions may be considered as a potentially useful component of MOH care. Multisession interventions may offer additional benefit but remain inconclusive because of heterogeneity and limited evidence. Further high-quality trials are needed to define optimal strategies.

PMID:42460454 | DOI:10.1155/prm/3699422

Comput Brain Behav. 2023 Nov 6;7(2):255-267. doi: 10.1007/s42113-023-00184-3. eCollection 2024 Jun.

ABSTRACT

The race model for stop signal processing is based on the assumption of context independence between the go and stop process. Recent empirical evidence inconsistent with predictions of the independent race model has been interpreted as a failure of context independence. Here we demonstrate that, keeping context independence while assuming stochastic dependency between go and stop processing, one can also account for the observed violations. Several examples demonstrate how stochastically dependent race models can be derived from copulas, a rapidly developing area of statistics. The non-observability of stop signal processing time is shown to be equivalent to a well known issue in random dependent censoring.

PMID:42460438 | PMC:PMC13298679 | DOI:10.1007/s42113-023-00184-3

Comput Brain Behav. 2024 Apr 8;7(2):242-254. doi: 10.1007/s42113-024-00200-0. eCollection 2024 Jun.

ABSTRACT

We apply cognitive modeling to improve the wisdom of the crowd in a spatial knowledge task. Participants provided point estimates for where 48 US cities are located and then, using the point estimate as a center point, chose a radius large enough that they believed the resulting circle was certain to contain the city’s location. Simple and radius-weighted arithmetic averages of the individuals’ point estimates produced more accurate group answers than the majority of individuals. These statistical aggregates, however, assume there are no differences in individual expertise nor in the difficulty of locating different cities. Accordingly, we develop a set of cognitive models to infer group estimates that make various assumptions about individual expertise and differences in city difficulty. The model-based estimates generally outperform the statistical averages. The models are especially accurate if they allow for individual differences in expertise that can vary city by city. We replicate this finding by applying the same cognitive models to data reported by Mayer and Heck (2023) in which participants provided point estimates for the locations of European cities.

PMID:42460437 | PMC:PMC13298622 | DOI:10.1007/s42113-024-00200-0

Comput Brain Behav. 2023 Oct 26;7(2):207-224. doi: 10.1007/s42113-023-00183-4. eCollection 2024 Jun.

ABSTRACT

The timing of intervals in both humans and nonhuman animals is susceptible to imprecision, leading to trial-to-trial variations in timed behaviors. A notable statistical characteristic of this timing behavior is the linear increase in the standard deviation of timed responses as the intervals become longer, known as time-scale invariance. Although the exact mechanism responsible for this property is not yet fully understood, “time cells” have emerged as a potential mechanism, particularly in relation to interval timing within the episodic memory system. These specialized networks of neurons exhibit sequential firing, with each neuron becoming active during a specific phase of the timed experiment. Notably, the resulting “ramping wave” decelerates during later phases of the timed event, and the duration of cell activity increases over time. In this paper, we propose a new model of a biological neural network composed of time cells, utilizing integrate-and-fire neurons with slow after-hyperpolarization currents and varying resting membrane potentials. This proposed network does not rely on any specific network architecture apart from self-excitation. Remarkably, the network successfully reproduces the experimentally observed ramping activity, with the standard deviation of spike times among the participating neurons increasing linearly with the average spike time. Furthermore, the results of the model are consistent with the experimental findings, providing additional evidence for its accuracy and validity.

PMID:42460436 | PMC:PMC13298657 | DOI:10.1007/s42113-023-00183-4

Comput Brain Behav. 2023 Nov 21;7(2):225-241. doi: 10.1007/s42113-023-00190-5. eCollection 2024 Jun.

ABSTRACT

Human observers are known to frequently act like Bayes-optimal decision-makers. Growing evidence indicates that the deployment of the visual system may similarly be driven by probabilistic mental models of the environment. We tested whether eye movements during a dynamic interception task were indeed optimised according to Bayesian inference principles. Forty-one participants intercepted oncoming balls in a virtual reality racquetball task across five counterbalanced conditions in which the relative probability of the ball’s onset location was manipulated. Analysis of pre-onset gaze positions indicated that eye position tracked the true distribution of onset location, suggesting that the gaze system spontaneously adhered to environmental statistics. Eye movements did not, however, seek to minimise the distance between the target and foveal vision according to an optimal probabilistic model of the world and instead often reflected a ‘best guess’ about onset location. Trial-to-trial changes in gaze position were, however, found to be better explained by Bayesian learning models (hierarchical Gaussian filter) than associative learning models. Additionally, parameters relating to the precision of beliefs and prediction errors extracted from the participant-wise models were related to both task-evoked pupil dilations and variability in gaze positions, providing further evidence that probabilistic context was reflected in spontaneous gaze dynamics.

PMID:42460434 | PMC:PMC13298623 | DOI:10.1007/s42113-023-00190-5