Nevin Manimala

Heart Rhythm O2. 2024 Sep 26;5(12):942-950. doi: 10.1016/j.hroo.2024.09.011. eCollection 2024 Dec.

ABSTRACT

BACKGROUND: There is consensus on the safety of standard dose direct oral anticoagulants (DOACs) for stroke prevention in patients undergoing cardioversion of atrial fibrillation (AF), but outcomes of reduced dose DOACs in this setting remain unclear.

OBJECTIVE: This systematic review and meta-analysis aimed to compare the rate of cardioversion-associated thromboembolic events between patients taking reduced dose DOACs and those receiving standard dose anticoagulation.

METHODS: A systematic search was conducted for studies published between January 1, 2009, and February 16, 2024 in PubMed, Embase, and Cochrane Central Register of Controlled Trials. The included studies compared the rate of thromboembolic events in patients with AF undergoing cardioversion on reduced dose DOACs with the rate in those on standard dose anticoagulation. Odds ratios were pooled with a random effects model.

RESULTS: We identified 2 randomized controlled trials and 8 cohort studies, which included 5212 patients with AF who underwent cardioversion on anticoagulation (1010 patients on reduced dose DOACs and 4202 patients on standard dose anticoagulation). Follow-up ranged from 3 hours to 90 days after cardioversion. There was a numerically higher rate of thromboembolic events in patients undergoing cardioversion on reduced dose DOACs than in those on standard dose anticoagulation (0.69% vs 0.29%; odds ratio 1.98; 95% confidence interval 0.72-5.45; P = .19; I² = 0%); however, the difference was not statistically significant.

CONCLUSION: Our systematic review and meta-analysis suggests that there is a numerically higher risk of thromboembolic events in patients with AF undergoing cardioversion on reduced dose DOACs than in those on standard dose anticoagulation. However, the difference was not statistically significant. These findings raise concern about the safety of reduced dose DOACs in patients undergoing cardioversion.

PMID:39803618 | PMC:PMC11721732 | DOI:10.1016/j.hroo.2024.09.011

Heart Rhythm O2. 2024 Sep 26;5(12):925-935. doi: 10.1016/j.hroo.2024.09.010. eCollection 2024 Dec.

ABSTRACT

BACKGROUND: Prediction models for atrial fibrillation (AF) may enable earlier detection and guideline-directed treatment decisions. However, model bias may lead to inaccurate predictions and unintended consequences.

OBJECTIVE: The purpose of this study was to validate, assess bias, and improve generalizability of “UNAFIED-10,” a 2-year, 10-variable predictive model of undiagnosed AF in a national data set (originally developed using the Indiana Network for Patient Care regional data).

METHODS: UNAFIED-10 was validated and optimized using Optum de-identified electronic health record data set. AF diagnoses were recorded in the January 2018-December 2019 period (outcome period), with January 2016-December 2017 as the baseline period. Validation cohorts (patients with AF and non-AF controls, aged ≥40 years) comprised the full imbalanced and randomly sampled balanced data sets. Model performance and bias in patient subpopulations based on sex, insurance, race, and region were evaluated.

RESULTS: Of the 6,058,657 eligible patients (mean age 60 ± 12 years), 4.1% (n = 246,975) had their first AF diagnosis within the outcome period. The validated UNAFIED-10 model achieved a higher C-statistic (0.85 [95% confidence interval 0.85-0.86] vs 0.81 [0.80-0.81]) and sensitivity (86% vs 74%) but lower specificity (66% vs 74%) than the original UNAFIED-10 model. During retraining and optimization, the variables insurance, shock, and albumin were excluded to address bias and improve generalizability. This generated an 8-variable model (UNAFIED-8) with consistent performance.

CONCLUSION: UNAFIED-10, developed using regional patient data, displayed consistent performance in a large national data set. UNAFIED-8 is more parsimonious and generalizable for using advanced analytics for AF detection. Future directions include validation on additional data sets.

PMID:39803613 | PMC:PMC11721729 | DOI:10.1016/j.hroo.2024.09.010

Curr Epidemiol Rep. 2024 Jun;11(2):120-130. doi: 10.1007/s40471-024-00342-6. Epub 2024 Mar 20.

ABSTRACT

PURPOSE OF REVIEW: Our review critically examines research on trends in mental health among US adults following the COVID-19 pandemic’s onset and makes recommendations for research on the topic.

RECENT FINDINGS: Studies comparing pre-pandemic nationally representative government surveys (“benchmark surveys”) with pandemic-era non-benchmark surveys generally estimated 3-4-fold increases in the prevalence of adverse mental-health outcomes following the pandemic’s onset. However, studies analyzing trends in repeated waves of a single survey, which may carry a lower risk of bias, generally estimated much smaller increases in adverse outcomes. Likewise in our analysis of benchmark surveys, we estimated <1% increases in the prevalence of adverse outcomes from 2018/2019-2021. Finally, studies analyzing vital-statistics data estimated spiking fatal-overdose rates, but stable suicide rates.

SUMMARY: Although fatal-overdose rates increased substantially following the pandemic’s onset, evidence suggests the population prevalence of other adverse mental-health outcomes may have departed minimally from prior years’ trends, at least through 2021. Future research on trends through the pandemic’s later stages should prioritize leveraging repeated waves of benchmark surveys to minimize risk of bias.

PMID:39803610 | PMC:PMC11720142 | DOI:10.1007/s40471-024-00342-6

Drug Des Devel Ther. 2025 Jan 8;19:97-110. doi: 10.2147/DDDT.S500253. eCollection 2025.

ABSTRACT

BACKGROUND: YYD601 is a new dual delayed-release formulation of esomeprazole, developed to enhance plasma exposure and prolong the duration of acid suppression.

PURPOSE: This study aimed to evaluate the safety, pharmacokinetic (PK), and pharmacodynamic (PD) profiles of YYD601 20 mg following single and multiple oral administrations in healthy, fasting adult Koreans, and to compare these outcomes to those of the conventional esomeprazole 20 mg capsule.

METHODS: A randomized, open-label, two-period crossover study was conducted in 28 participants, who were divided into two treatment groups: one group received YYD601 20 mg, and the other received conventional esomeprazole 20 mg, once daily for five consecutive days. Blood samples for PK analysis were collected pre-dose and up to 24 hours post-dose. The primary PK parameters (AUC_last and AUC_τ) were evaluated. PD endpoints included integrated gastric acidity, percentage of time with intragastric pH > 4 over 24-hour and nighttime intervals, and percent change in serum gastrin levels after multiple dosing.

RESULTS: A total of 22 participants completed the study. YYD601 displayed more prolonged plasma concentration-time profiles than the conventional formulation, although the extent of the systemic exposure (AUC values) showed no statistically significant difference between the two formulations. With regard to the 24-hour gastric acid inhibition, YYD601 was comparable to the conventional formulation. The YYD601 showed a greater tendency for acid inhibition at night, as indicated by the percentage change of time with nocturnal acid breakthrough and other PD parameters. Both treatments were well tolerated, with no serious adverse events reported.

CONCLUSION: Through extended systemic exposure of esomeprazole, YYD601 produces gastric acid suppression that is comparable to that of the conventional esomeprazole formulation, with a greater tendency to suppress acid at night. YYD601 20 mg was safe and well tolerated following single and multiple oral administrations, supporting its use as an effective alternative to conventional esomeprazole therapy.

CLINICAL TRIAL REGISTRY: http://clinicaltrials.gov, NCT03985319 (Date of registration: May 29, 2019; Study period: between July 2019 and March 2020).

PMID:39803609 | PMC:PMC11725257 | DOI:10.2147/DDDT.S500253

Drug Des Devel Ther. 2025 Jan 6;19:65-66. doi: 10.2147/DDDT.S512114. eCollection 2025.

NO ABSTRACT

PMID:39803608 | PMC:PMC11721147 | DOI:10.2147/DDDT.S512114

Stat Probab Lett. 2025 Mar;218:110295. doi: 10.1016/j.spl.2024.110295. Epub 2024 Nov 22.

ABSTRACT

We introduce a generalized Bayesian credible set that can achieve any preassigned credible level, addressing a limitation of the current credible sets. This is achieved by exploiting a connection between the highest posterior density set and the Neyman-Pearson lemma.

PMID:39803594 | PMC:PMC11722005 | DOI:10.1016/j.spl.2024.110295

bioRxiv [Preprint]. 2024 Dec 30:2024.12.30.630778. doi: 10.1101/2024.12.30.630778.

ABSTRACT

A significant advancement in synthetic biology is the development of synthetic gene circuits with predictive Boolean logic. However, there is no universally accepted or applied statistical test to analyze the performance of these circuits. Many basic statistical tests fail to capture the predicted logic (OR, AND, etc.) and most studies neglect statistical analysis entirely. As synthetic gene circuits shift toward advanced applications, primarily in computing, biosensing, and human health, it is critical to standardize the statistical methods used to evaluate gate success. Here, we propose the application of a linear mixed effects model to analyze and quantify genetic Boolean logic gate performance. First, we analyzed 144 currently published Boolean logic gates for trends and used unsupervised machine learning (k-means clustering) to validate the statistical model. Next, we utilized the model to generate estimates for the fixed effect of the ON state, β, as a general descriptor of the Boolean nature of a circuit and used Monte Carlo simulations to recommend sample sizes for evaluating gate performance. Finally, we examined β as a holistic metric for circuit performance using a series of nested repressor OR gates with intentionally degraded performance. We observed a linear correlation between β and the predicted translation rate, highlighting the use of β for the forward design of new Boolean gates. In summary, we utilized a linear mixed effects model to describe synthetic gene circuits and determined that the fixed effect, β, is an appropriate descriptor of gate behavior that can be used to statistically evaluate performance.

PMID:39803539 | PMC:PMC11722350 | DOI:10.1101/2024.12.30.630778

bioRxiv [Preprint]. 2025 Jan 2:2023.03.02.530774. doi: 10.1101/2023.03.02.530774.

ABSTRACT

Neural cell types have classically been characterized by their anatomy and electrophysiology. More recently, single-cell transcriptomics has enabled an increasingly fine genetically defined taxonomy of cortical cell types, but the link between the gene expression of individual cell types and their physiological and anatomical properties remains poorly understood. Here, we develop a hybrid modeling approach to bridge this gap. Our approach combines statistical and mechanistic models to predict cells’ electrophysiological activity from their gene expression pattern. To this end, we fit biophysical Hodgkin-Huxley-based models for a wide variety of cortical cell types using simulation-based inference, while overcoming the challenge posed by the mismatch between the mathematical model and the data. Using multimodal Patch-seq data, we link the estimated model parameters to gene expression using an interpretable sparse linear regression model. Our approach recovers specific ion channel gene expressions as predictive of biophysical model parameters including ion channel densities, directly implicating their mechanistic role in determining neural firing.

PMID:39803528 | PMC:PMC11722265 | DOI:10.1101/2023.03.02.530774

bioRxiv [Preprint]. 2025 Jan 4:2025.01.03.631258. doi: 10.1101/2025.01.03.631258.

ABSTRACT

Sensory stimuli vary across a variety of dimensions, like contrast, orientation, or texture. The brain must rely on population representations to disentangle changes in one dimension from changes in another. To understand how the visual system might extract separable stimulus representations, we recorded multiunit neuronal responses to texture images varying along two dimensions: contrast, a property represented as early as the retina, and naturalistic statistical structure, a property that modulates neuronal responses in V2 and V4, but not in V1. We measured how sites in these 3 cortical areas responded to variation in both dimensions. Contrast modulated responses in all areas. In V2 and V4, the presence of naturalistic structure both modulated responses and increased contrast sensitivity. Tuning for naturalistic structure was strongest in V4; tuning in both dimensions was most heterogeneous in V4. We measured how well populations in each area could support the linear readout of both dimensions. Populations in V2 and V4 could support the linear readout of naturalistic structure, but only in V4 did we find evidence for a robust representation that was contrast-invariant.

SIGNIFICANCE STATEMENT: Single neurons in visual cortex respond selectively to multiple stimulus dimensions, so signals from single neurons cannot distinguish changes in one dimension from changes in another. We measured responses from simultaneously recorded neural populations in three hierarchically linked visual areas – V1, V2, and V4 – using texture stimuli that varied in two dimensions, contrast and naturalistic image structure. We used linear decoding methods to extract information about each dimension. In all three areas, contrast could be decoded independently of image structure. Only in V4, however, could image structure be decoded independently of contrast. The reason is that selectivity for texture and contrast in V4 was much more diverse than in V1 or V2. This heterogeneity allows V4 to faithfully represent naturalistic image structure independent of contrast.

PMID:39803474 | PMC:PMC11722230 | DOI:10.1101/2025.01.03.631258

J Adv Prosthodont. 2024 Dec;16(6):348-357. doi: 10.4047/jap.2024.16.6.348. Epub 2024 Dec 19.

ABSTRACT

PURPOSE: This pilot study investigated the effect of surface roughness on osseointegration by comparing two types of commercial SLA-treated dental implants with different surface roughness levels: moderately rough (S_a = 1 – 2 µm) and rough surfaces (S_a > 2 µm).

MATERIALS AND METHODS: Two implant groups were studied: TS (rough surface) and ADD (moderately rough surface) groups. Surface characteristics were analyzed using optical profilometry and SEM. In vitro studies using BRITER cells assessed cell adhesion, proliferation, and osteogenic differentiation through CCK-8 assay and qRT-PCR for osteopontin (OPN), osteocalcin (OCN), and alkaline phosphatase (ALP) expression. The in vivo study involved 12 implants (six per group) placed in mandibular defects of two beagle dogs. After 8 weeks, histomorphometric analysis evaluated bone to implant contact (BIC) and inter-thread bone density (ITBD). Statistical analysis used Student’s t-test and two-way ANOVA for in vitro data, and Mann-Whitney U test for in vivo data.

RESULTS: Surface analysis revealed S_a values of 2.50 ± 0.27 µm for the TS group and 1.80 ± 0.06 µm for the ADD group. In vitro studies showed no significant differences in cell adhesion and proliferation between the groups (P > .05). However, gene expression patterns differed, with ADD group showing higher OPN expression (P < .001) and TS group showing higher ALP expression (P < .01). The in vivo study revealed no statistically significant differences in BIC and ITBD between the two groups (P > .05).

CONCLUSION: Surface roughness influenced osteoblast differentiation in vitro, but did not significantly affect osseointegration outcomes in vivo. Both moderately rough and rough surfaces appeared to support comparable levels of osseointegration. Larger studies are needed to confirm these findings and determine optimal implant surface characteristics.

PMID:39803382 | PMC:PMC11711448 | DOI:10.4047/jap.2024.16.6.348