Miracle-dz/UniFAR-FTUs huggingface dataset:
Weight Gain and Metabolic Changes in Patients With First-Episode Psychosis or Early-Phase Schizophrenia Treated With Olanzapine: A Meta-Analysis

Abstract Background Patients with first-episode psychosis or early-phase schizophrenia are susceptible to olanzapine-associated weight gain and cardiometabolic dysregulation. This meta-analysis characterized weight and metabolic effects observed during olanzapine treatment in randomized clinical trials in this vulnerable patient population. Methods PubMed, EMBASE, and Dialog were searched for randomized controlled trials (RCTs) reporting weight or cardiometabolic outcomes associated with olanzapine treatment in first-episode psychosis or early-phase schizophrenia. Random-effects meta-analysis and meta-regression were conducted using R v4.0. 5. Results Of 1203 records identified, 26 RCTs informed the analyses. The meta-analytic mean (95% CI) weight gain was 7.53 (6.42–8.63) kg in studies (n = 19) that reported weight gain with olanzapine treatment. Stratified by duration, the mean (95% CI) weight gain was significantly higher in studies >13 weeks in duration than in those lasting ≤13 weeks: 11.35 (10.05–12.65) vs 5.51 (4.73–6.28) kg, respectively. Despite between-study variability, increases from baseline in most glycemic and lipid parameters were generally small in studies of both ≤13 and >13 weeks. There were no correlations, however, between weight gain and metabolic parameter changes when stratified by study duration. Conclusions In RCTs enrolling patients with first-episode psychosis or early-phase schizophrenia, olanzapine was consistently associated with weight gain that was greater in studies lasting >13 weeks compared with those of ≤13 weeks. Metabolic changes observed across studies suggest that RCTs may underestimate metabolic sequelae vs real-world treatment observations. Patients with first-episode psychosis or early-phase schizophrenia are vulnerable to olanzapine-associated weight gain; strategies minimizing olanzapine-associated weight gain should be carefully considered.
Association of stage 1 hypertension defined by the 2017 ACC/AHA guideline with cardiovascular events and mortality in Chinese adults

Abstract Background: The 2017 American College of Cardiology/American Heart Association (ACC/AHA) blood pressure (BP) guideline lowered the threshold defining hypertension to 130/80 mmHg. However, how stage 1 hypertension defined using this guideline is associated with cardiovascular events in Chinese adults remains unclear. This study assessed the association between stage 1 hypertension defined by the 2017 ACC/AHA guideline and clinical outcomes in the Chinese population. Methods: Participants with stage 1 hypertension (n = 69,509) or normal BP (n = 34,142) were followed in this study from 2006/2007 to 2020. Stage 1 hypertension was defined as a systolic blood pressure of 130–139 mmHg or a diastolic blood pressure of 80–89 mmHg. None were taking antihypertensive medication or had a history of myocardial infarction (MI), stroke, or cancer at baseline. The primary outcome was a composite of MI, stroke, and all-cause mortality. The secondary outcomes were individual components of the primary outcome. Cox proportional hazards models were used for the analysis. Results: During a median follow-up of 11.09 years, we observed 10,479 events (MI, n = 995; stroke, n = 3408; all-cause mortality, n = 7094). After multivariable adjustment, the hazard ratios for stage 1 hypertension vs. normal BP were 1.20 (95% confidence interval [CI], 1.13–1.25) for primary outcome, 1.24 (95% CI, 1.05–1.46) for MI, 1.45 (95% CI, 1.33–1.59) for stroke, and 1.11 (95% CI, 1.04–1.17) for all-cause mortality. The hazard ratios for participants with stage 1 hypertension who were prescribed antihypertensive medications compared with those without antihypertensive treatment during the follow-up was 0.90 (95% CI, 0.85–0.96). Conclusions: Using the new definition, Chinese adults with untreated stage 1 hypertension are at higher risk for MI, stroke, and all-cause mortality. This finding may help to validate the new BP classification system in China.
Remote vision testing of central retinal acuity and comparison with clinic-based Snellen acuity testing in patients followed for retinal conditions

Introduction The unmet need for remote monitoring of visual function with home-based, patient-centric technologies became increasingly palpable during the COVID-19 pandemic. Many patients with chronic eye conditions lack access to office-based examinations. Here, we evaluate the efficacy of the Accustat® test, a virtual application for measuring near visual acuity on any portable electronic device via telehealth. Materials and methods Thirty-three adult subjects from the telehealth remote monitoring service of a retina practice performed the Accustat® acuity testing at home. All patients underwent in-office general eye examination with additional fundoscopic examination and optical coherence tomography retina imaging. Best corrected visual acuity assessment using a Snellen chart was compared with remote visual acuity assessment with the Accustat® test. Visual acuity was analyzed and compared between the best-corrected near visual acuity potential achieved on the Accustat® and in-office distance best-corrected Snellen visual acuity. Results The mean logarithm of the minimum angle of resolution (logMAR) visual acuities of all eyes tested using the Accustat test was 0.19 ± 024 and for the office Snellen test 0.21 ± 0.21. A linear regression model with 95% confidence intervals reveals that there is a strong linear relationship between Accustat logMAR and office Snellen logMAR. Bland–Altman analysis demonstrated 95.2% significant agreement between Accustat and Office Snellen’s best corrected visual acuity. Intraclass correlation coefficient (ICC = 0.94) demonstrated a strong positive correlation between at home versus office visual acuity. Conclusion There was a high correlation between the visual acuity measured with the Accustat near vision digital self-test and the office Snellen acuity test, suggesting the potential utility of scalable remote monitoring of central retinal function via telehealth.
Nonparametric Bayesian Q-learning for optimization of dynamic treatment regimes in the presence of partial compliance

Existing methods for estimation of dynamic treatment regimes are mostly limited to intention-to-treat analyses—which estimate the effect of randomization to a particular treatment regime without considering the compliance behavior of patients. In this article, we propose a novel nonparametric Bayesian Q-learning approach to construct optimal sequential treatment regimes that adjust for partial compliance. We consider the popular potential compliance framework, where some potential compliances are latent and need to be imputed. The key challenge is learning the joint distribution of the potential compliances, which we accomplish using a Dirichlet process mixture model. Our approach provides two kinds of treatment regimes: (1) conditional regimes that depend on the potential compliance values; and (2) marginal regimes where the potential compliances are marginalized. Extensive simulation studies highlight the usefulness of our method compared to intention-to-treat analyses. We apply our method to the Adaptive Treatment for Alcohol and Cocaine Dependence (ENGAGE) study , where the goal is to construct optimal treatment regimes to engage patients in therapy.
ASYMPTOTIC DISTRIBUTIONS OF QUASI-MAXIMUM LIKELIHOOD

This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi-maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of those estimators may depend on some general features of the spatial weights matrix of the model. It is important to make the distinction with different spatial scenarios. Under the scenario that each unit will be influenced by only a few neighboring units, the estimators may have >/n-rate of convergence and be asymptotically normal. When each unit can be influenced by many neighbors, irregularity of the information matrix may occur and various components of the estimators may have different rates of convergence.
Using cortico‐cerebellar structural patterns to classify early‐ and late‐trained musicians

A body of current evidence suggests that there is a sensitive period for musical training: people who begin training before the age of seven show better performance on tests of musical skill, and also show differences in brain structure—especially in motor cortical and cerebellar regions—compared with those who start later. We used support vector machine models—a subtype of supervised machine learning—to investigate distributed patterns of structural differences between early‐trained (ET) and late‐trained (LT) musicians and to better understand the age boundaries of the sensitive period for early musicianship. After selecting regions of interest from the cerebellum and cortical sensorimotor regions, we applied recursive feature elimination with cross‐validation to produce a model which optimally and accurately classified ET and LT musicians. This model identified a combination of 17 regions, including 9 cerebellar and 8 sensorimotor regions, and maintained a high accuracy and sensitivity (true positives, i.e., ET musicians) without sacrificing specificity (true negatives, i.e., LT musicians). Critically, this model—which defined ET musicians as those who began their training before the age of 7—outperformed all other models in which age of start was earlier or later (between ages 5–10). Our model's ability to accurately classify ET and LT musicians provides additional evidence that musical training before age 7 affects cortico‐cerebellar structure in adulthood, and is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.
Mixing by barotropic instability in a nonlinear model

Abstract A global, nonlinear, equivalent barotropic model is used to study the isentropic mixing of passive tracers by barotropic instability. Basic states are analytical zonal-mean jets representative of the zonal-mean flow in the upper stratosphere, where the observed 4-day wave is thought to be a result of barotropic, and possibly baroclinic, instability. As is known from previous studies, the phase speed and growth rate of the unstable waves is fairly sensitive to the shape of the zonal-mean jet; and the dominant wave mode at saturation is not necessarily the fastest growing mode; but the unstable modes share many features of the observed 4-day wave. Lagrangian trajectories computed from model winds are used to characterize the mixing by the flow. For profiles with both midlatitude and polar modes, mixing is stronger in midlatitudes than inside the vortex; but there is little exchange of air across the vortex boundary. There is a minimum in the Lyapunov exponents of the flow and the particle dispersio.
Acetaminophen causes neurodevelopmental injury in susceptible babies and children: no valid rationale for controversy

Despite the worldwide acceptance of acetaminophen (APAP) as a necessary medicine in pediatrics, evidence that early exposure to APAP causes neurodevelopmental injury in susceptible babies and children has been mounting for over a decade. The evidence is diverse and includes extensive work with laboratory animals, otherwise unexplained associations, factors associated with APAP metabolism, and limited studies in humans. Although the evidence has reached an overwhelming level and was recently reviewed in detail, controversy persists. This narrative review evaluates some of that controversy. Evidence from the pre- and postpartum periods was considered to avoid controversy raised by consideration of only limited evidence of risks during the prepartum period. Among other issues, the association between APAP use and the prevalence of neurodevelopmental disorders was considered. A systematic review revealed that the use of APAP in the pediatric population was never tracked carefully; however, historical events that affected its use were documented and are sufficient to establish apparent correlations with changes in the prevalence of neurodevelopmental disorders. Moreover, problems with the exclusive reliance on results of meta-analyses of large datasets with limited time frames of drug exposure were reviewed. Furthermore, the evidence of why some children are susceptible to APAPinduced neurodevelopmental injuries was examined. We concluded that available evidence demonstrates that early exposure to APAP causes neurodevelopmental injury in susceptible babies and small children.
Ring Closures and the Hammond Postulate

This work reports an investigation of ring closure processes in relation to the Hammond postulate. Calculations favor the importance of thermodynamics, not kinetics, as the basis for the Hammond postulate. A kinetically rapid, but thermodynamically unfavorable reaction is shown to resemble product. The ease of ring closure to three-membered rings, compared to four-membered rings, is thought to be associated with conformational mobility and perhaps vibrations coupled to the reaction coordinate motion in the case of four-membered rings.
Study on the optimal shape parameter of parametric curves based on PSO algorithm

Abstract Although the curves with shape parameters has become one of the most popular topics in Computer Aided Geometric Design, but the values of shape parameters are always given as intervals, while in practice, we often need the optimal shape parameter values to ensure that the curves have good fairness and smoothness. This paper is motivated to solve the optimal shape parameters. Firstly, an automatic mathematical model is established to obtain the optimal parameters which is based on the fairing criterion, and then the particle swarm optimization (PSO) algorithm is introduced to solve the optimal model. At the end, Three classes of curves are used as examples to illustrate the effectiveness of our methods.
Bronchiolitis Simulation Module in the Pediatric Preclerkship Educational Exercises (PRECEDE) Curriculum

Introduction Acute bronchiolitis is a viral infection infecting 90% of children under the age of 2 years, with approximately 200,000 deaths per year. The current standard of care remains largely respiratory support and prevention. Therefore, understanding how to assess and escalate respiratory supportive care is paramount for health care providers taking care of children. Methods We used a high-fidelity simulator to simulate an infant with progressing respiratory distress in the setting of acute bronchiolitis. The participants were pediatric clerkship medical students during their preclerkship educational exercises (PRECEDE). The students were asked to evaluate and treat the simulated patient. After debriefing, the students repeated the simulation. We assessed both performances via a weighted checklist specifically developed for this case to measure team performance. Students also completed an overall course evaluation. Results Ninety out of 121 pediatric clerkship students were enrolled. Performance improved from 57% to 86% ( p < .05). Donning appropriate personal protection equipment was the most missed item both pre- and postdebriefing. Overall, the course was well liked and received. Participants requested more simulation opportunities within PRECEDE as well as a summary document to reinforce learning. Discussion Pediatric clerkship students improved their performance managing progressing respiratory distress due to acute bronchiolitis via a performance-based assessment tool with sound validity evidence. Improvements going forward include improving faculty diversity and offering more simulation opportunities.
Parameter-Efficient Densely Connected Dual Attention Network for Phonocardiogram Classification

Cardiac auscultation, exhibited by phonocardiogram (PCG), is a non-invasive and low-cost diagnostic method for cardiovascular diseases (CVDs). However, deploying it in practice is quite challenging, due to the inherent murmurs and a limited number of supervised samples in heart sound data. To solve these problems, not only heart sound analysis based on handcrafted features, but also computer-aided heart sound analysis based on deep learning have been extensively studied in recent years. Though with elaborate design, most of these methods still use additional pre-processing to improve classification performance, which heavily relies on time-consuming experienced engineering. In this article, we propose a parameter-efficient densely connected dual attention network (DDA) for heart sound classification. It combines two advantages simultaneously of the purely end-to-end architecture and enriched contextual representations of the self-attention mechanism. Specifically, the densely connected structure can automatically extract the information flow of heart sound features hierarchically. Alongside, improving contextual modeling capabilities, the dual attention mechanism adaptively aggregates local features with global dependencies via a self-attention mechanism, which captures the semantic interdependencies across position and channel axes respectively. Extensive experiments across stratified 10-fold cross-validation strongly evidence that our proposed DDA model surpasses current 1D deep models on the challenging Cinc2016 benchmark with significant computational efficiency.
The use of digital health in heart rhythm care

ABSTRACT Introduction Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligence, machine learning, and other novel technologies, digital health is particularly relevant to the field of cardiac arrhythmias, with roles pertinent to education, prevention, diagnosis, management, prognosis, and surveillance. Areas covered This review summarizes information on the clinical use of digital health technology in arrhythmia care and discusses its opportunities and challenges. Expert opinion Digital health has begun to play an essential role in arrhythmia care regarding diagnostics, long-term monitoring, patient education and shared decision making, management, medication adherence, and research. Despite remarkable advances, integrating digital health technologies into healthcare faces challenges, including patient usability, privacy, system interoperability, physician liability, analysis and incorporation of the huge amount of real-time information from wearables, and reimbursement. Successful implementation of digital health technologies requires clear objectives and deep changes to existing workflows and responsibilities.
Maxillomandibular Advancement for Obstructive Sleep Apnea Syndrome: Long-Term Results of Respiratory Function and Reverse Face-Lift

Purpose: Scientific literature considers maxillomandibular advancement (MMA) as the most effective surgical treatment for the management of adult obstructive sleep apnea syndrome (OSAS). Maxillomandibular advancement enlarges the pharyngeal space by expanding the skeletal framework. Moreover, it projects the soft tissue of the cheeks, the mouth, and the nose in the aging face, which is characterized by multiple signs affecting the middle third and the lower third. The potential of orthognathic surgery (double jaw surgical advancement) of expanding the skeletal foundation to increase the facial drape support and to rejuvenate the face by a “reverse face-lift” is now recognized. The aim of this study was to review the surgical outcomes after MMA in terms of respiratory function and assessment of facial esthetics. Methods: We retrospectively reviewed the charts of all patients affected by OSAS who underwent maxillomandibular advancement between January 2010 and December 2015 in 2 tertiary hospitals (IRCCS Policlinico San Martino of Genoa and IRCCS Policlinico Ca’ Granda of Milan). During the postoperative follow-up examination, all patients underwent polysomnographic examination and esthetic assessment to evaluate the respiratory function and facial rejuvenation after double jaw surgical advancement. Results: The final study sample included 25 patients (5 females, 20 males). The overall success rate of the surgical treatment (apnea/hypopnea index, AHI <20) was 79%; the overall rate of surgical cure (AHI <5) was 47%. Twenty-three patients (92%) showed a degree of rejuvenation after MMA. Conclusions: Maxillomandibular advancement is currently the most effective surgical treatment for the management of OSAS in adult patients who are not responders to medical treatment. “Reverse face-lift” is the consequence of the double jaw surgical advancement.
Long-tailed distribution of synaptic strength reveals origin and functional roles of ongoing fluctuation in cortical circuit

Neurons in the cortical circuit continuous to generate irregular spike firing with extremely low firing rate (about 1-2 Hz) even when animals neither receive any external stimuli nor they do not show any significant motor movement. The ongoing activity is often called neuronal noise because measured spike trains are often highly irregular and also spike timings are highly asynchronous among neurons. Many experiments imply that neural networks themselves must generate the noisy activity as an intrinsic property of cortical circuit. However, how a network of neurons sustains the irregular spike firings with low firing rate remains unclear. Recently, by focusing on long-tailed distribution of amplitude of synaptic connections or EPSP (Excitatory Post-Synaptic Potential), we successfully revealed that due to coexistence of a few extremely strong synaptic connections and majority of weak synapses, nonlinear dynamics of population of spiking neurons can have a nontrivial stable state that corresponding to the i.
Profiling compliers and noncompliers for instrumental variable analysis with covariates: A weighting approach

Instrumental variable (IV) estimation is an essential tool to estimate the causal effect of a treatment in randomized experiments when noncompliance exists. In such studies, standard statistical approaches can be biased because compliers and noncompliers can differ in unmeasured ways that affect both the compliance behavior and outcome. Based on a few assumptions such as monotonicity, the IV estimand represents the causal effect of compliers. Profiling compliers and noncompliers has important implications because the IV estimand applies only to compliers. A method for estimating the covariate means for compliers and noncompliers has recently been proposed in political sciences literature. However, this approach requires an assumption that the instrument is randomly assigned, which confines the application of this approach to randomized experiments. In this study, we present two weighting methods for profiling compliers and noncompliers when the instrument and compliance behavior are confounded by several covariates. The proposed approach can be used for both experimental and nonexperimental studies, and hence is more broadly applicable. For the development, an instrumental propensity score is adopted to account for confounded instruments. We demonstrate the utility of the proposed methods based on simulation and real data experiments.