Miracle-dz/UniFAR-FTUs huggingface dataset:
Medicare Spending on Drugs With Accelerated Approval

BACKGROUND The U.S. Food and Drug Administration provides accelerated approval to drugs on the basis of surrogate end points deemed to be "reasonably likely" to predict clinical benefit. To receive full approval, drugs must complete a confirmatory trial. Although most accelerated approved drugs ultimately receive full approval, others remain on the market without full approval for many years, and some are withdrawn before full approval is granted. Until confirmatory trials are completed and full approval is granted, there is uncertainty surrounding each drug's clinical benefits. OBJECTIVE To estimate fee-for-service Medicare payments on accelerated approved drugs without full approvals. DESIGN Cross-sectional analysis. SETTING Fee-for-service Medicare Part B and Part D drug claims in 2019. PARTICIPANTS Beneficiaries enrolled in Medicare Part B and Part D plans. MEASUREMENTS Medicare spending for drugs treating accelerated approved indications without full approval, beneficiary spending, and drug characteristics. RESULTS In 2019, 45 drugs associated with 69 accelerated approved indications lacked full approval. Of those, the fee-for-service Medicare program spent $1.2 billion on 36 drugs across 55 indications. Medicare beneficiaries had $209 million in out-of-pocket spending on these drugs. Oncology drugs represented 82% of these indications and 72% of the Medicare spending. Extrapolating to Medicare Advantage, total Medicare spending on these drugs in 2019 was $1.8 billion. LIMITATIONS The study drugs may have clinical benefit and may come to receive full approval after this analysis. The algorithm used to identify accelerated approved indications is novel. Generalizability to other years is unclear. CONCLUSION In 2019, fee-for-service Medicare spent $1.2 billion on accelerated approved drugs without full approval. Medicare should adjust incentives to encourage sponsors to complete confirmatory trials as soon as possible. PRIMARY FUNDING SOURCE Laura and John Arnold Foundation.
A Scalable and Low-Cost Interactive Shape-Changing Display

Research in new display technologies has garnered great interest in the recent years. Curved screens and foldable displays have already been commercialized. However a relatively new field of research is in dynamic shape-changing or shape-shifting displays. These displays utilize the ability to change their shape dynamically as another dimension of representing visual data. These displays potentially augmented with colors, can help visualize three dimensional data such as terrains, city and building plans, and medical data. They can also be used in new ways of Human-Computer Interaction by developing user interfaces that transform physically based on the scenario. While there is research being done on new ways of using shape displays for interaction and manipulation, not much focus has been given to the issue of cost and scalability. The general shape displays which are currently being developed have individual pixels which need to be actuated. The commercial linear actuators which are used in these displays are extremely expensive and are not meant for such purposes. This thesis presents a design for a dynamic pixel-based shape changing display which focuses on cost and scalability by using custom designed modular actuators and sensor
Evaluation of collision/reaction gases in single-particle ICP-MS for sizing selenium nanoparticles and assessment of their antibacterial activity

Selenium nanoparticles (SeNPs) have recently attracted attention because they combine the benefits of Se and lower toxicity compared to other chemical forms of this element. In this study, SeNPs were synthesized by a green method using ascorbic acid as the reducing agent and polyvinyl alcohol as stabilizer. The nanoparticles were widely characterized. To determine the total concentration of Se by ICP-MS, several isotopes and the use of He as collision gas were evaluated, which was effective in minimizing interferences. A method for sizing SeNPs by single particle ICP-MS (SP-ICP-MS) was developed. For this purpose, He and H2 were evaluated as collision/reaction gases, and the second one showed promising results, providing an average diameter of 48 nm for the SeNPs. These results agree with those obtained by TEM (50.1 nm). Therefore, the SP-ICP-MS can be implemented for characterizing SeNPs in terms of size and size distribution, being an important analytical tool for Se and other widely studied nanoparticles (e.g. Ag, Au, Ce, Cu, Fe, Zn). Finally, the antibacterial activity of SeNPs was assessed. The SeNPs showed bacteriostatic activity against three strains of Gram-positive bacteria and were particularly efficient in inhibiting the growth E. faecalis even at very low concentrations (MIC < 1.4 mg l−1). In addition, a bactericidal activity of SeNPs against S. aureus was observed. These nanoparticles may have potential application in pharmaceutical industry, biomedicine and agriculture.
Design principles of PI(4,5)P2 clustering under protein-free conditions: Specific cation effects and calcium-potassium synergy

Significance Clustering of phosphatidylinositol 4,5-bisphosphate (PIP2) with proteins into what are known as “PIP2 rafts” is a critical component of intracellular signaling, yet little is known about PIP2 clusters at the atomic level. Using molecular dynamics simulations and network theory, this paper shows that Ca2+ generates large clusters by linking PIP2 dimers already formed by doubly charged P4/P5 phosphates, while monovalent cations form smaller and less-stable clusters by adding PIP2 monomers preferentially via weaker interactions with P4/P5 (for Na+) or with glycerol P1 (for K+). Synergy arises between K+ and Ca2+ because each ion forms linkages with different phosphates, thereby giving clusters more ways to grow. This explains why Ca2+ is pumped into cells by ion channels to form PIP2 rafts.
Fostering emotional intelligence in preadolescence: Effects of a pilot training on emotions, coping and psychological well-being

The purpose of the present study was to examine the efficacy of a short training programme (eight 1-hour sessions) aimed to promote Emotional Intelligence (EI) abilities in primary school on a set of outcomes related to affect, coping and psychological well-being. Sixty-eight preadolescents (10.68±.58 years) were randomly assigned to either the experimental condition (EI training) or the active control condition (pro-environmental training). ANOVAs and Bayesian analyses were performed on pre/post-training measures of ability and trait EI, positive/negative affect, regulatory emotional self-efficacy, coping styles, and psychological well-being. Results showed that only in the EI training condition emotional abilities significantly improved, whereas negative affect and the preference for distraction coping significantly diminished. Although the effects of the present EI training did not extend to the other measures, the findings suggest its effectiveness in improving preadolescents’ EI basic skills and some important adjustment variables. This study confirms the efficacy of short school-based programmes in enhancing EI abilities and highlights the importance of further investigating the training features required to extend its benefits also to psychological well-being. Implications for research and educational practices are discussed.
Comparison of ANP and BNP Granular Density in Atria of Rats After Physiological and Pathological Hypertrophy

Atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) are cardiac hormones located in atria granules. Both peptides respond to cardiac pressure and volume dynamics and accordingly serve as translation biomarkers for the clinical treatment of heart failure. Serum ANP and BNP play central secretary roles in blood pressure and cardiac output regulation and have proven utility as differential biomarkers of cardiovascular proficiency and drug-induced maladaptation, yet both peptides are impervious to exercise-induced hypertrophy. We employed immunoelectron microscopy to examine the effects of 28 days of chronic swim exercise or administration of a PPARγ agonist on atrial granules and their stored natriuretic peptides in Sprague Dawley rats. Chronic swimming and drug treatment both resulted in a 15% increase in heart weight compared with controls, with no treatment effects on perinuclear granule area in the left atria (LAs). Drug treatment resulted in larger size granules with greater BNP density in the right atria. Comparing swimming and PPARγ agonist treatment effects on ANP:BNP granule density ratios between atrial chambers revealed a shift toward a greater proportion of ANP than BNP in LAs of swim-trained rats. These data suggest a distinction in the population of ANP and BNP after chronic swim or PPARγ that makes it a novel metric for the differentiation of pathological and physiological hypertrophy.
Prevalence and Distribution of Human Papillomavirus Genotypes (1997–2019) and Their Association With Cervical Cancer and Precursor Lesions in Women From Southern Mexico

Background Cervical cancer (CC) is the fourth most common malignancy of the female genital tract. Human Papillomavirus (HPV) is the main cause of precancerous lesions and CC cases worldwide Objective We assessed the prevalence and distribution of HPV types and their association with precancerous lesions and CC. Methods HPV genotypes were detected by 3 methods depending on the year of in which the sample was analyzed: MY09/11 RFLPs (1997 to 2010), GP5+/6+ primer systems (2005 to 2010) and INNO-LiPA HPV Genotyping Extra (2010 to 2019) in cervical samples (No-IL: 4445; LSIL: 2464; HSILs: 151 and CC: 253) from women from southern Mexico. Results The overall HPV prevalence was 54.17%, and hpv-16 was the most common genotype. In single infection, the high-risk HPV genotypes (group 1) were associated with squamous intraepitelial lesions (LSIL: HPV–39 (OR = 10.58, 95% CI 4.09–27.36, P < .001); HSIL: HPV-31 (OR = 14.76, 95% CI 6.56–33.20, P < .001); and CC: HPV-16 (OR = 25.01, 95% CI 18.83–33.21, P < .001). In multiple infections, the HPV genotypes (HPV-16 and HPV-18) were also associated with a high risk of lesions [LSIL: HPV-18 (OR = 3.45; 95% CI 1.36–8.91; P = .009); HSIL: HPV-18 (OR = 5.12; 95% CI 1.21–21.68; P = .026); and CC: HPV-16 (OR = 3.03; 95% CI 1.72–5.32; P < .001)] compared to single infection. In the analysis adjusted for age, giving birth, and cigarette smoking, a significant increase in the risk of LSIL, HSIL, and CC was maintained. Conclusions This study provides current data on the prevalence and distribution of HPV genotypes in women from southern Mexico, which could serve as a valuable reference to guide nationwide CC screening programs and provide scientific evidence that could be useful for vaccine development efforts. Likewise, it was identified that infection with carcinogenic HPV genotypes is an independent risk factor for LSIL, HSIL, and CC.
Children's socio-moral judgments and behaviors toward peers with and without incarcerated parents.

Adults often respond negatively toward children with incarcerated parents. Yet, the developmental foundations for such negativity remain unclear. Two studies (N = 331 U.S. residents; plurality White; plurality male; data collected between Winter 2019 and Spring 2021) addressed this topic. Study 1 probed 5- to 6-year-olds' and 7- to 8-year-olds' inferences about peers with and without incarcerated parents. Children reported less certainty that peers with, versus without, incarcerated parents possess moral beliefs. Study 2 showed that among older children, inferences about parental absence did not fully account for this pattern of results. Across studies, children behaved less generously toward peers with, versus without, incarcerated parents. These studies illuminate how early socio-moral judgment may contribute to negativity toward children with incarcerated parents.
Diverse human and bat-like rotavirus G3 strains circulating in suburban Bangkok

Although rotavirus vaccines are available in many parts of the world and are effective in reducing the overall incidence of rotavirus infection, it remains a major cause of diarrhea in less-developed countries. Among various rotavirus group A (RVA) strains, the increasingly common genotype G3 (defined by the VP7 gene) has been identified in both humans and animals. Our previous epidemiological surveillance in Bangkok found several unusual non-vaccine-like G3 strains in patients with diarrhea. In this study, we sequenced and characterized the genomes of seven of these G3 strains, which formed combinations with genotypes P[4], P[6], P[9], and P[10] (defined by the VP4 gene). Interestingly, we identified a bat-like RVA strain with the genome constellation G3-P[10]-I3-R3-C3-M3-A9-N3-T3-E3-H6, which has not been previously reported in the literature. The amino acid residues deduced from the nucleotide sequences of our G3 strains differed at the antigenic epitopes to those of the VP7 capsid protein of the G3 strain in RotaTeq vaccine. Although it is not unusual for the segmented genomes of RVA to reassort and give rise to emerging novel strains, the atypical G3 strains identified in this study suggest possible animal-to-human RVA zoonotic spillover even in urban areas.
How drivers of seasonality in respiratory infections may impact vaccine strategy: a case study in how COVID-19 may help us solve one of influenza's biggest challenges

Abstract Vaccines against seasonal infections like influenza offer a recurring testbed, encompassing challenges in design, implementation, and uptake to combat a both familiar and ever-shifting threat. One of the pervading mysteries of influenza epidemiology is what causes the distinctive seasonal outbreak pattern. Proposed theories each suggesting different paths forwards in being able to tailor precision vaccines and/or deploy them most effectively. One of the greatest challenges in contrasting and supporting these theories is, of course, that there is no means by which to actually test them. In this communication we revisit theories and explore how the ongoing COVID-19 pandemic might provide a unique opportunity to better understand the global circulation of respiratory infections. We discuss how vaccine strategies may be targeted and improved by both isolating drivers and understanding the immunological consequences of seasonality, and how these insights about influenza vaccines may generalize to vaccines for other seasonal respiratory infections.
Association of APOE-Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults

Background and Objectives Brain amyloid deposition, a major risk factor for Alzheimer disease (AD), is currently estimated by measuring CSF or plasma amyloid peptide levels or by PET imaging. Assessing genetic risks relating to amyloid deposition before any accumulation has occurred would allow for earlier intervention in persons at increased risk for developing AD. Previous work linking amyloid burden and genetic risk relied almost exclusively on APOE, a major AD genetic risk factor. Here, we ask whether a polygenic risk score (PRS) that incorporates an optimized list of common variants linked to AD and excludes APOE is associated with brain amyloid load in cognitively unimpaired older adults. Methods We included 291 asymptomatic older participants from the INveStIGation of AlzHeimer's PredicTors (INSIGHT pre-AD) cohort who underwent amyloid imaging, including 83 amyloid-positive (+) participants. We used an Alzheimer's (A) PRS composed of 33 AD risk variants excluding APOE and selected the 17 variants that showed the strongest association with amyloid positivity to define an optimized (oA) PRS. Participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (228 participants, 90 amyloid [+]) were tested as a validation cohort. Finally, 2,300 patients with AD and 6,994 controls from the European Alzheimer's Disease Initiative (EADI) were evaluated. Results A-PRS was not significantly associated with amyloid burden in the INSIGHT or ADNI cohorts with or without correction for the APOE genotype. However, oA-PRS was significantly associated with amyloid status independently of APOE adjustment (INSIGHT odds ratio [OR]: 5.26 [1.71–16.88]; ADNI OR: 3.38 [1.02–11.63]). Of interest, oA-PRS accurately discriminated amyloid (+) and (−) APOE ε4 carriers (INSIGHT OR: 181.6 [7.53–10,674.6]; ADNI OR: 44.94 [3.03–1,277]). A-PRS and oA-PRS showed a significant association with disease status in the EADI cohort (OR: 1.68 [1.53–1.85] and 2.06 [1.73–2.45], respectively). Genes assigned to oA-PRS variants were enriched in ontologies related to β-amyloid metabolism and deposition. Discussion PRSs relying on AD genetic risk factors excluding APOE may improve risk prediction for brain amyloid, allowing stratification of cognitively unimpaired individuals at risk of AD independent of their APOE status.
Subjects with bipolar disorder showed different reward system activation than subjects with major depressive disorder in the monetary incentive delay task

Differentiating between bipolar disorder (BD) and major depressive disorder (MDD) during the depressive episode is an important clinical challenge. Reward system abnormalities have received much attention as one of the biological underpinnings of BD and MDD, but few studies have directly compared these abnormalities in remitted and depressed states.
Knowledge Transfer-Based Sparse Deep Belief Network

Deep learning has made remarkable achievements in various applications in recent years. With the increasing computing power and the “black box” problem of neural networks, however, the development of deep neural networks (DNNs) has entered a bottleneck period. This article proposes a novel deep belief network (DBN) based on knowledge transfer and optimization of the network structure. First, a neural-symbolic model is proposed to extract rules to describe the dynamic operation mechanism of the deep network. Second, knowledge fusion is proposed based on the merge and deletion of the extracted rules from the DBN model. Finally, a new DNN, knowledge transfer-based sparse DBN (KT-SDBN) is constructed to generate a sparse network without excessive information loss. In comparison with DBN, KT-SDBN has a more sparse network structure and better learning performance on the existing knowledge and data. The experimental results in the benchmark data indicate that KT-SDBN not only has effective feature learning performance with 30% of the original network parameters but also shows a large compression rate that is far larger than other structure optimization algorithms.
Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies

Fear conditioning paradigms are critical to understanding anxiety-related disorders, but studies use an inconsistent array of methods to quantify the same underlying learning process. We previously demonstrated that selection of trials from different stages of experimental phases and inconsistent use of average compared to trial-by-trial analysis can deliver significantly divergent outcomes, regardless of whether the data is analysed with extinction as a single effect, as a learning process over the course of the experiment, or in relation to acquisition learning. Since small sample sizes are attributed as sources of poor replicability in psychological science, in this study we aimed to investigate if changes in sample size influences the divergences that occur when different kinds of fear conditioning analyses are used. We analysed a large data set of fear acquisition and extinction learning (N = 379), measured via skin conductance responses (SCRs), which was resampled with replacement to create a wide range of bootstrapped databases (N = 30, N = 60, N = 120, N = 180, N = 240, N = 360, N = 480, N = 600, N = 720, N = 840, N = 960, N = 1080, N = 1200, N = 1500, N = 1750, N = 2000) and tested whether use of different analyses continued to produce deviating outcomes. We found that sample size did not significantly influence the effects of inconsistent analytic strategy when no group-level effect was included but found strategy-dependent effects when group-level effects were simulated. These findings suggest that confounds incurred by inconsistent analyses remain stable in the face of sample size variation, but only under specific circumstances with overall robustness strongly hinging on the relationship between experimental design and choice of analyses. This supports the view that such variations reflect a more fundamental confound in psychological science—the measurement of a single process by multiple methods.
Robust-adaptive sliding mode control for actuator system

In a practical actuator system consisting of a motor and gear transmission, nonlinearities such as mechanical friction, backlash, and kinematic error can increase the complexity of system dynamics. To reduce the system complexity, a simplified model of the system is developed by linearizing its nonlinearities and minimizing the effect of perturbation/disturbance. The controller is designed using a simplified model and accounts for the system complexities and unknown parameters as unmodeled dynamics. Perturbation estimation can then be added to the controller to account for the unmodeled dynamics improving system performance and stability. In this study, robust-adaptive sliding mode control and proportional-integral-derivative (PID) control methods are applied to a practical actuator system and the effectiveness, performance and stability characteristics are studied. Based on the practical actuator system, composed of a 3-phase brushless motor, gear bearing drive, and hysteresis brake, this study aims to: 1) model single-degree-of-freedom first-order system to simplify the actuator system; 2) estimate numerical parameter values to design the simulation model of the actuator system; 3) design robust-adaptive sliding mode and PID speed controllers under both the simulation and real-time environment; and 4) analyze the effectiveness of each controller according to reference signals, step and sinusoidal inputs. In the simulation, the effectiveness of each controller was examined for the case of the undisturbed system. In the realtime environment, the effectiveness was tested under two conditions, first on the system with no disturbance and later with the addition of an unknown disturbance. In the simulation, the system performance and stability from each controller were guaranteed. On the other hand, in the real-time environment, robust-adaptive sliding mode control of the system with unknown disturbance ensured better performance and stability than PID controller in the same condition. This study suggests that robust-adaptive sliding mode control proves its effectiveness in a nonlinear system with parameter uncertainty and unknown perturbation/disturbance. The control scheme guarantees a nonlinear system performance and stability through on-line parameter and perturbation/disturbance estimations.