Miracle-dz/UniFAR-FTUs huggingface dataset:
Socioeconomic status impacts blood pressure response to positive airway pressure treatment.

STUDY OBJECTIVES Positive airway pressure (PAP) treatment of obstructive sleep apnea (OSA) reduces blood pressure (BP). Retrospective data suggest that African Americans (AA), a group at high-risk for hypertensive organ dysfunction, may have a greater BP response to PAP therapy than European Americans (EA). We examined the difference in 24-hour BP response to three months of PAP treatment between AA and EA. METHODS Participants (N=259, 161 AA and 98 EA) with apnea-hypopnea index (AHI) ≥15/hour from two prospective cohorts were included. T-tests and multiple linear regression were used to examine BP outcomes in AA vs. EA, adjusting for PAP adherence, socioeconomic status (SES), and baseline characteristics. RESULTS Participants were middle-aged (mean ± standard deviation, 53.8±9.3 years), 86% (227) men, AHI 35.6±19.2/hour, and PAP adherence of 3.36±2.24 hours/day. The reductions in 24-hour systolic and diastolic BP (mm Hg) were not different in AA vs. EA (systolic=-1.13±12.1 vs. -0.61±12.8, p=0.80 and diastolic=-0.74±7.9 vs. -0.80±7.4, p=0.96), and race was not a predictor of 24-hour systolic or diastolic BP reduction (p=0.75 and 0.54). SES and PAP adherence demonstrated a significant interaction; low SES was associated with an increase in 24-hour systolic BP (β=19.3, p=0.03) in the absence of PAP use but a greater reduction in 24-hour systolic BP with higher PAP adherence (β=-3.96, p=0.03). CONCLUSIONS 24-hour BP response to PAP treatment is similar in AA and EA. Adherence to PAP treatment is more effective in improving 24-hour systolic BP in those with low SES. The study was a clinical trial. Clinical Trial Registration: NCT01960465 and NCT01578031.
Barriers to workplace-based learning in the intensive care unit: A qualitative description of internal medicine residents’ and intensivists’ perspectives

Abstract Background Residency programs leverage the acquisition of critical care competencies through off-service rotations in the intensive care unit (ICU). However, recent literature questions the effectiveness of increasing the exposition of residents to critical care units to improve their critical care competencies. We aimed to describe the barriers to learning in the ICU from the perspective of internal medicine (IM) residents and intensivists. Methods A qualitative description methodology was applied to data gathered during an ICU quality improvement initiative in a large tertiary academic hospital. Verbatim transcriptions of 12 focus groups including 22 IM residents and 17 intensivists were assessed through thematic data analysis. Results We identified three key themes and 13 subthemes related to barriers to learning. Aspects of the environment such as the slow socialization process of residents to the ICU environment and stakeholders’ perceptions influenced the quality of learning interactions. Dedicated teaching was further influenced by factors related to the IM residency curricula (e.g. competing co-curricular demands) and contributed to tensions in delivering a standardized ICU curriculum. Conclusion This study provides a description of educational barriers that may be present during ICU rotations. Recognizing these barriers may help clinical teachers improve their trainees’ educational experience.
Evaluating the Influence of COVID-19 Among Dental Practitioners After Lockdown

Clinical activities at dental premises after the COVID-19 lockdown period or post-COVID-19 are likely to be a challenge for all practicing dentists. To assess the impact of the COVID-19 pandemic on dentists and change in dental practice following lockdown, a total of 1150 participants were approached through online survey forms registered on www.surveys. google. A link containing details of the questionnaire and a consent form was sent to dentists through emails and social media forums. The questionnaire included 3 domains comprising of seventeen questions. The first section focused on demographics. The second section inquired about the change in dental practice, that is, clinical hours, use of PPE, type of treatment, and patient flow. The third section investigated the impact of COVID-19 on dentistry. Means, standard deviation, and percentages were calculated using descriptive statistics. Chi-square was used to find an association between different variables. The response rate was 87%. Demographic factors revealed participants aged from 20.45 to 40.55 years. The data showed around 89.6% (896) of dentists have altered their clinical working hours post lockdown and, approximately, 59.7% (597) of dentists provided only emergency treatments. 88.1% (881) of the dentists wore PPE during dental procedures. Overall, a huge negative impact of the COVID-19 pandemic was observed among practicing dentists in terms of the dental supply chain, cost, and availability of dental equipment, treatment cost, and bill payments.COVID-19 pandemic compromised dental care. Though dentists were taking precautionary measures and have changed their practice according to the guidelines provided by the ADA and World Health Organization, they were still experiencing monetary loss due to decrease patient influx post lockdown.
The synthesis of half-band filter using frequency-response masking technique

An important property of a half-band filter is that half of its coefficient values are trivial. This yields significant advantage in terms of its computational complexity. Nevertheless, the complexity of a half-band filter is still very high if its transition-width is very narrow. In this letter, we introduce a novel method for the synthesis of very sharp half-band filter using the frequency response masking technique. >
Exploring the association with disease recurrence of miRNAs predictive of colorectal cancer

Introduction Disease recurrence after surgery is a crucial predictor of poor prognosis in colorectal cancer, where disseminated disease at the time of intervention can also be observed in localized early-stage cases. We evaluated the ability to predict disease recurrence of miRNAs from two signatures that we have found linked to the presence of colorectal cancer (CL signature) or adenoma (HgA signature) in higher-risk subjects. Methods miRNAs from the signatures were studied longitudinally by quantitative real-time polymerase chain reaction in plasma from 24 patients with resectable colorectal cancer collected at the time of surgery and during scheduled follow-up across 36 months. Patients either showed relapse within 36 months (alive with disease (AWD)), or remained disease-free (no evidence of disease (NED)) for the same period. Results Although the signatures did not predict recurrence, expression of the miRNAs from the CL signature decreased 1 year after surgery, and one miRNA of the signature, miR-378a-3p, almost reached significance in the NED subgroup (Wilcoxon signed-rank test: p-value = 0.078). Also, miR-335-5p from the HgA signature was higher in AWD patients before surgery (Kruskal–Wallis test: p-value = 0.019). Conclusions These data, although from a small cohort of patients, support the possible use of miRNAs as non-invasive biomarkers in liquid biopsy-based tests to identify patients at risk of relapse and to monitor them during follow-up.
HFA-PEFF scores: prognostic value in heart failure with preserved left ventricular ejection fraction

Background/Aims The Heart Failure Association (HFA)-PEFF score is recognized as a simple method to diagnose heart failure (HF) with preserved ejection fraction (HFpEF). This study aimed to evaluate the relationship between HFA-PEFF scores and cardiovascular outcomes in HFpEF patients. Methods A total of 502 consecutive HFpEF patients were prospectively observed for up to 1,500 days. Cardiovascular outcomes were compared between two groups of patients, defined by their HFA-PEFF scores: those who scored 2–4 (the intermediate-score group) and those who scored 5–6 group (the high-score group). Overall, 236 cardiovascular events were observed during the follow-up period (median, 1,159 days). Results Kaplan-Meier analysis showed that there were significant differences in composite cardiovascular events and HF-related events between the intermediate-score group and the high-score group (p = 0.003 and p < 0.001, respectively). Multivariate Cox proportional hazards analysis showed that the HFA-PEFF scores significantly predicted future HF-related events (hazard ratio, 1.66; 95% confidence interval [CI], 1.11 to 2.50; p = 0.014); receiver operating characteristic analysis confirmed this relationship (area under the curve, 0.633; 95% CI, 0.574 to 0.692; p < 0.001). The cutoff HFA-PEFF score for the identification of HF-related events was 4.5. Decision curve analysis revealed that combining the HFA-PEFF score with conventional prognostic factors improved the prediction of HF-related events. Conclusions HFA-PEFF scores may be useful for predicting HF-related events in HFpEF patients.
Optimization of Spray-Drying Parameters for Formulation Development at Preclinical Scale

Spray-drying dispersion (SDD) is a well-established manufacturing technique used to prepare amorphous solid dispersions (ASDs), allowing for poorly soluble drugs to have improved bioavailability. However, the process of spray-drying with multiple factors and numerous variables can lead to a lengthy development timeline with intense resource requirements, which becomes the main obstacle limiting spray-drying development at the preclinical stage. The purpose of this work was to identify optimized preset parameters for spray-drying to support the early development of ASDs suitable for most circumstances rather than individual optimization. First, a mini-DoE (Design of Experiment) study was designed to evaluate the critical interplay of two key variables for spray-drying using a BUCHI B-290 mini spray dryer: solid load and atomizing spray gas flow. The critical quality attributes (CQAs) of the ASDs, including yield, particle size, morphology, and in vitro release profile, were taken into account to identify the impact of the key variables. The mini-DoE results indicated that a 5% solid load (w/v %) and 35 mm height atomizing spray gas flow were the most optimized parameters. These predefined values were further verified using different formulation compositions, including various polymers (Eudragit L100-55, HPMCAS-MF, PVAP, and PVP-VA64) and drugs (G-F, GEN-A, Indomethacin, and Griseofulvin), a range of drug loading (10 to 40%), and scale (200 mg to 200 g). Using these predefined parameters, all ASD formulations resulted in good yields as well as consistent particle size distribution. This was despite the differences in the formulations, making this a valuable and rapid approach ideal for early development. This strategy of leveraging the preset spray-drying parameters was able to successfully translate into a reproducible and efficient spray-drying platform while also saving material and reducing developmental timelines in early-stage formulation development.
Concurrent semantic priming and lexical interference for close semantic relations in blocked-cyclic picture naming: Electrophysiological signatures.

In the present study, we employed event-related brain potentials to investigate the effects of semantic similarity on different planning stages during language production. We manipulated semantic similarity by controlling feature overlap within taxonomical hierarchies. In a blocked-cyclic naming task, participants named pictures in repeated cycles, blocked in semantically close, distant, or unrelated conditions. Only closely related items, but not distantly related items, induced semantic blocking effects. In the first presentation cycle, naming was facilitated, and amplitude modulations in the N1 component around 140-180 ms post-stimulus onset predicted this behavioral facilitation. In contrast, in later cycles, naming was delayed, and a negative-going posterior amplitude modulation around 250-350 ms post-stimulus onset predicted this interference. These findings indicate easier object recognition or identification underlying initial facilitation and increased difficulties during lexical selection. The N1 modulation was reduced but persisted in later cycles in which interference dominated, and the posterior negativity was also present in cycle 1 in which facilitation dominated, demonstrating concurrent effects of conceptual priming and lexical interference in all naming cycles. Our assumptions about the functional role these two opposing forces play in producing semantic context effects are further supported by the finding that the joint modulation of these two ERPs on naming latency exclusively emerged when naming closely related, but not unrelated items. The current findings demonstrate that close relations, but not distant taxonomic relations, induce stronger semantic blocking effects, and that temporally overlapping electrophysiological signatures reflect a trade-off between facilitatory priming and interfering lexical competition.
Statistical Forecasting : Third Wave of COVID-19-With an Application to India

The pandemic due to the SARS-CoV-2 virus impacted the entire world in different waves. An important question that arise after witnessing the first and second waves of COVID-19 is - Will the third wave also arrive and if yes, then when. Various types of methodologies are being used to explore the arrival of third wave. A statistical methodology based on the fitting of mixture of Gaussian distributions is explored in this paper and the aim is to forecast the third wave using the data on the first two waves of pandemic. Utilizing the data of different countries that are already facing the third wave, modelling of their daily cases data and predicting the impact and timeline for the third wave in India is attempted in this paper. The Gaussian mixture model based on algorithm for clustering is used to estimate the parameters.
Qualitative and quantitative aspects of maintenance performance measurement: a data fusion approach

The measurement of maintenance performance is often faced with a lack in knowledge about the real function of the maintenance department within organisations, and consequently appropriate targets from the global mission and vision are absence. Measurement metrics are not adapted to real needs, which have a strong human factor; nor is there a roadmap of the amount of data to be collected, their processing or how they are used in decision making. This article proposes a model where qualitative and quantitative methods are combined to complement the advantages of both.
VaxiMap: optimal delivery of vaccinations for housebound patients

Background. Throughout the UK's Covid-19 vaccination campaign, responsibility for vaccinating housebound patients has rested with individual GP surgeries, posing them a difficult logistical challenge (the travelling salesman problem). In response to demand from GPs, and a lack of existing solutions tailored specifically to vaccination, VaxiMap was created. This tool provides optimal routes for vaccine delivery and has been free to all users since its inception in January 2021. Methods. VaxiMap generates optimal routes subject to the constraint that the number of patients per route should be fixed. This ensures that a known quantity of vaccine can be set aside for each route and minimises wastage. The user need only upload an Excel spreadsheet of patient postcodes to be visited. A divide-and-conquer approach of iterative k-means clustering followed by within-cluster route optimisation is used to generate the routes. Findings. We find substantial savings in the time taken to plan vaccinations, as well as savings in the time taken to visit housebound patients. We estimate total savings to date of 4,700 hours of practitioner time, equivalent to 2.5 work-years, or approximately GBP 91k at typical practitioner salaries. Interpretation. The adoption of VaxiMap yielded both time and cost savings for GP surgeries and accelerated the UK's Covid-19 vaccination campaign at a critical moment. Funding. Financial support was provided by Magdalen College, Oxford, Oxford University Innovation, and JHubMed, part of UK Strategic Command. These parties were not involved in the preparation of this manuscript.
Rare coding variation illuminates the allelic architecture, risk genes, cellular expression patterns, and phenotypic context of autism

Individuals with autism spectrum disorder (ASD) or related neurodevelopmental disorders (NDDs) often carry disruptive mutations in genes that are depleted of functional variation in the broader population. We build upon this observation and exome sequencing from 154,842 individuals to explore the allelic diversity of rare protein-coding variation contributing risk for ASD and related NDDs. Using an integrative statistical model, we jointly analyzed rare protein-truncating variants (PTVs), damaging missense variants, and copy number variants (CNVs) derived from exome sequencing of 63,237 individuals from ASD cohorts. We discovered 71 genes associated with ASD at a false discovery rate (FDR) [≤] 0.001, a threshold approximately equivalent to exome-wide significance, and 183 genes at FDR [≤] 0.05. Associations were predominantly driven by de novo PTVs, damaging missense variants, and CNVs: 57.4%, 21.2%, and 8.32% of evidence, respectively. Though fewer in number, CNVs conferred greater relative risk than PTVs, and repeat-mediated de novo CNVs exhibited strong maternal bias in parent-of-origin (e.g., 92.3% of 16p11.2 CNVs), whereas all other CNVs showed a paternal bias. To explore how genes associated with ASD and NDD overlap or differ, we analyzed our ASD cohort alongside a developmental delay (DD) cohort from the deciphering developmental disorders study (DDD; n=91,605 samples). We first reanalyzed the DDD dataset using the same models as the ASD cohorts, then performed joint analyses of both cohorts and identified 373 genes contributing to NDD risk at FDR [≤] 0.001 and 662 NDD risk genes at FDR [≤] 0.05. Of these NDD risk genes, 54 genes (125 genes at FDR [≤] 0.05) were unique to the joint analyses and not significant in either cohort alone. Our results confirm overlap of most ASD and DD risk genes, although many differ significantly in frequency of mutation. Analyses of single-cell transcriptome datasets showed that genes associated predominantly with DD were strongly enriched for earlier neurodevelopmental cell types, whereas genes displaying stronger evidence for association in ASD cohorts were more enriched for maturing neurons. The ASD risk genes were also enriched for genes associated with schizophrenia from a separate rare coding variant analysis of 121,570 individuals, emphasizing that these neuropsychiatric disorders share common pathways to risk.
Variability in Physical Inactivity Responses of University Students during COVID-19 Pandemic: A Monitoring of Daily Step Counts Using a Smartphone Application

This study investigated the changes in physical inactivity of college students during the COVID-19 pandemic, with reference to their academic calendar. We used the daily step counts recorded by a smartphone application (iPhone Health App) from April 2020 to January 2021 (287 days) for 603 students. The data for 287 days were divided into five periods based on their academic calendar. The median value of daily step counts across each period was calculated. A k-means clustering analysis was performed to classify the 603 participants into subgroups to demonstrate the variability in the physical inactivity responses. The median daily step counts, with a 7-day moving average, dramatically decreased from 5,000 to 2,000 steps/day in early April. It remained at a lower level (less than 2,000 steps/day) during the first semester, then increased to more than 5,000 steps/day at the start of summer vacation. The clustering analysis demonstrated the variability in physical inactivity responses. Independent of the academic calendar, many inactive students did not recover their original daily step counts after its dramatic decrement. Consequently, promoting physical activity is recommended for inactive university students over the course of the whole semester.
Comparing system identification techniques for identifying human-like walking controllers

While human walking has been well studied, the exact controller is unknown. This paper used human experimental walking data and system identification techniques to infer a human-like controller for a spring-loaded inverted pendulum (SLIP) model. Because the best system identification technique is unknown, three methods were used and compared. First, a linear system was found using ordinary least squares. A second linear system was found that both encoded the linearized SLIP model and matched the first linear system as closely as possible. A third nonlinear system used sparse identification of nonlinear dynamics (SINDY). When directly mapping states from the start to the end of a step, all three methods were accurate, with errors below 10% of the mean experimental values in most cases. When using the controllers in simulation, the errors were significantly higher but remained below 10% for all but one state. Thus, all three system identification methods generated accurate system models. Somewhat surprisingly, the linearized system was the most accurate, followed closely by SINDY. This suggests that nonlinear system identification techniques are not needed when finding a discrete human gait controller, at least for unperturbed walking. It may also suggest that human control of normal, unperturbed walking is approximately linear.
The wettability of electron spun membranes by synovial fluid

Aseptic loosening due to periprosthetic osteolysis has been accepted as one of the leading causes of revision procedures in patients with previous joint arthroplasty. Recently, several strategies for suppression of osteolysis were proposed, mostly based on biological treatment such as mitigation of chronic inflammatory reactions. However, these biological treatments do not stop the debris migration but only reduce the inflammatory reaction. To address this shortcoming, we propose the concept of ultrahigh molecular weighted polyethylene particles filtration storage by electrospun membranes. Firstly, the surface tension of synovial fluid (SF) is obtained by use of a pendant droplet. Secondly, the contact angle of the electrospun membranes wetted by two different liquids is measured to obtain the free surface energy using of the Owens–Wendt model. Additionally, the wettability of electrospun membranes by SF as a function of technology parameters is studied.
Rapid indicators of deprivation using grocery shopping data

Measuring socio-economic indicators is a crucial task for policy makers who need to develop and implement policies aimed at reducing inequalities and improving the quality of life. However, traditionally this is a time-consuming and expensive task, which therefore cannot be carried out with high temporal frequency. Here, we investigate whether secondary data generated from our grocery shopping habits can be used to generate rapid estimates of deprivation in the city of London in the UK. We show the existence of a relationship between our grocery shopping data and the deprivation of different areas in London, and how we can use grocery shopping data to generate quick estimates of deprivation, albeit with some limitations. Crucially, our estimates can be generated very rapidly with the data used in our analysis, thus opening up the opportunity of having early access to estimates of deprivation. Our findings provide further evidence that new data streams contain accurate information about our collective behaviour and the current state of our society.