Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Sequencing of HPV16 E6 Region Reveals Unique Mutation Pattern of HPV16 and Predicts Cervical Cancer

The study provides evidence for the first time that HPV16 E6 sequences contain vital mutation features in predicting the high‐grade squamous intraepithelial lesion and can reduce even more unneeded colposcopies without a loss of sensitivity to detect cervical cancer. Moreover, the D32E and H85Y variants of E6 exhibited a significantly higher ability to degrade p53, which may play a vital role in the development of cervical cancer. ABSTRACT The genetic diversity of human papillomavirus (HPV) 16 within cervical cells and tissue is usually associated with persistent virus infection and precancerous lesions. To explore the HPV16 mutation patterns contributing to the cervical cancer (CC) progression, a total of 199 DNA samples from HPV16-positive cervical specimens were collected and divided into high‐grade squamous intraepithelial lesion (HSIL) and the non‐HSIL(NHSIL) groups. The HPV16 E6 region (nt 7125-7566) was sequenced using next-generation sequencing. Based on HPV16 E6 amino acid mutation features selected by Lasso algorithm, four machine learning approaches were used to establish HSIL prediction models. The receiver operating characteristic was used to evaluate the model performance in both training and validation cohorts. Western blot was used to detect the degradation of p53 by the E6 variants. Based on the 13 significant mutation features, the logistic regression (LR) model demonstrated the best predictive performance in the training cohort (AUC = 0.944, 95% CI: 0.913–0.976), and also achieved a high discriminative ability in the independent validation cohort (AUC = 0.802, 95% CI: 0.601–1.000). Among these features, the E6 D32E and H85Y variants have higher ability to degrade p53 compared to the E6 wildtype (P < 0.05). In conclusion, our study provides evidence for the first time that HPV16 E6 sequences contain vital mutation features in predicting HSIL. Moreover, the D32E and H85Y variants of E6 exhibited a significantly higher ability to degrade p53, which may play a vital role in the development of CC. IMPORTANCE The study provides evidence for the first time that HPV16 E6 sequences contain vital mutation features in predicting the high‐grade squamous intraepithelial lesion and can reduce even more unneeded colposcopies without a loss of sensitivity to detect cervical cancer. Moreover, the D32E and H85Y variants of E6 exhibited a significantly higher ability to degrade p53, which may play a vital role in the development of cervical cancer.
Lilliput: speech perception in speech-weighted noise and in quiet in young children

Abstract Objective The aim of this study was to develop an open-set word recognition task in speech-weighted noise and in quiet for young children and examine age effects for open versus closed response formats. Design Dutch monosyllabic words were presented in quiet and in stationary speech-weighted noise to 4- and 5-year-old children as well as to young adults in an open-set response format. Additionally, performance in open and closed context was assessed, as well as in a picture-pointing paradigm Study sample: More than 200 children and 50 adults with normal hearing participated in the various validation phases. Results Average fitted speech reception thresholds (50%) yielded an age effect between 4-year and 5-year olds (and adults), both in speech-weighted noise and in quiet. The closed-set format yielded lower (better) SNRs than the open-set format, and children benefitted to the same extent as adults from phonetically similar words in speech-weighted noise. Additionally, the 4 AFC picture-pointing paradigm can be used to assess word recognition in quiet from 3 years of age. Conclusions The same materials reveal performance differences between 4 and 5 years of age (and adults), both in quiet and speech-weighted noise using an open-set response format. This relatively small yet significant difference in SRT for a gap of only 1 year shows a developmental change for word recognition in speech-weighted noise and in quiet in the first decade of life. The study is part of the protocol registered on ClinicalTrials.gov (ID = NCT04063748).
Gaussian-Based Smoothing of Wind and Solar Power Productions Using Batteries

Intermittent nature of Distributed Energy Resources (DER) such as solar and wind cause significant power fluctuations and integrating them to a power systems requires control mechanisms to reduce fluctuations. One way to control the effect of fluctuation is to use Energy Storage Systems (ESS) for smoothing out their power productions. A typical method to attain this goal is to use ESS with classical moving average approaches. However, these methods are affected by peaks and troughs in power production due to cloud passing and wind gust effects on solar panels and wind turbines, respectively. In this paper, we propose a Gaussian-based smoothing method to alleviate pitfalls of moving average methods to smooth out forecasted values of solar and wind powers. Then, we determine a minimum ESS size required to maintain a smoothed power curve for a day-ahead period. From our experiments, the proposed algorithm requires smaller ESS size than the classical approaches. 
Certolizumab Pegol Efficacy in Patients With Non‐Radiographic Axial Spondyloarthritis Stratified by Baseline MRI and C‐Reactive Protein Status: An Analysis From the C‐axSpAnd Study

Tumor necrosis factor inhibitors (TNFi) are an effective treatment for non‐radiographic axial spondyloarthritis (nr‐axSpA). To be eligible, however, many authorities require patients with nr‐axSpA to show active sacroiliitis on magnetic resonance imaging (MRI) and/or an elevated C‐reactive protein (CRP) level, possibly resulting in a perception that patients with nr‐axSpA without both factors have only low responses to TNFi treatment. We evaluated clinical responses to certolizumab pegol (CZP) in patients with nr‐axSpA stratified by baseline MRI/CRP status.
Biogeographical Patterns of Bacterial Communities and Their Antibiotic Resistomes in the Inland Waters of Southeast China

Antibiotic resistance has been a serious global threat to environmental and human health. The “One Health” concept further emphasizes the importance of monitoring the large-scale dissemination of ARGs. ABSTRACT Freshwater ecosystems are important sources of drinking water and provide natural settings for the proliferation and dissemination of bacteria and antibiotic resistance genes (ARGs). However, the biogeographical patterns of ARGs in natural freshwaters and their relationships with the bacterial community at large scales are largely understudied. This is of specific importance because data on ARGs in environments with low anthropogenic impact is still very limited. We characterized the biogeographical patterns of bacterial communities and their ARG profiles in 24 reservoirs across southeast China using 16S rRNA gene high-throughput sequencing and high-throughput-quantitative PCR, respectively. We found that the composition of both bacterial communities and ARG profiles exhibited a significant distance-decay pattern. However, ARG profiles displayed larger differences among different water bodies than bacterial communities, and the relationship between bacterial communities and ARG profiles was weak. The biogeographical patterns of bacterial communities were simultaneously driven by stochastic and deterministic processes, while ARG profiles were not explained by stochastic processes, indicating a decoupling of bacterial community composition and ARG profiles in inland waters under relatively low-human-impact at a large scale. Overall, this study provides an overview of the biogeographical patterns and driving mechanisms of bacterial community and ARG profiles and could offer guidance and reference for the control of ARGs in drinking water sources. IMPORTANCE Antibiotic resistance has been a serious global threat to environmental and human health. The “One Health” concept further emphasizes the importance of monitoring the large-scale dissemination of ARGs. However, knowledge about the geographical patterns and driving mechanisms of bacterial communities and ARGs in natural freshwater environments is limited. This study uncovered the distinct biogeographical patterns of bacterial communities and ARG profiles in inland waters of southeast China under low-anthropogenic impact at a large scale. This study improved our understanding of ARG distribution in inland waters with emphasis on drinking water supply reservoirs, therefore providing the much-needed baseline information for future monitoring and risk assessment of ARGs in drinking water resources.
More than good seed: Cultivating investigators from underrepresented minority backgrounds in physiatric research

Drs. Skelton and Sholas highlight the importance of diversity in academic medicine, specifically regarding physician-scientists from groups historically excluded from or underrepresented in medicine. They explain how through increasing the diversity of physiatrist-scientists, physiatric research benefits from novel perspectives that use a range of research methodologies to ask and answer questions that will advance physiatric clinical care and knowledge. They explore historical and existing bar-riers to a diverse physiatric research workforce. Drs. Skelton and Sholas outline specific components to be implemented at individual academic institutions and at the academic society level to help physiatrist-scientists from diverse backgrounds flourish.
Diagnostic capabilities of nanopore long‐read sequencing in muscular dystrophy

Many individuals with muscular dystrophies remain genetically undiagnosed despite clinical diagnostic testing, including exome sequencing. Some may harbor previously undetected structural variants (SVs) or cryptic splice sites. We enrolled 10 unrelated families: nine had muscular dystrophy but lacked complete genetic diagnoses and one had an asymptomatic DMD duplication. Nanopore genomic long‐read sequencing identified previously undetected pathogenic variants in four individuals: an SV in DMD, an SV in LAMA2, and two single nucleotide variants in DMD that alter splicing. The DMD duplication in the asymptomatic individual was in tandem. Nanopore sequencing may help streamline genetic diagnostic approaches for muscular dystrophy.
Distribution models calibrated with independent field data predict two million ancient and veteran trees in England

Abstract Large, citizen‐science species databases are powerful resources for predictive species distribution modeling (SDM), yet they are often subject to sampling bias. Many methods have been proposed to correct for this, but there exists little consensus as to which is most effective, not least because the true value of model predictions is hard to evaluate without extensive independent field sampling. We present here a nationwide, independent field validation of distribution models of ancient and veteran trees, a group of organisms of high conservation importance, built using a large and internationally unique citizen‐science database: the Ancient Tree Inventory (ATI). This validation exercise presents an opportunity to test the performance of different methods of correcting for sampling bias, in the search for the best possible prediction of ancient and veteran tree distributions in England. We fitted a variety of distribution models of ancient and veteran tree records in England in relation to environmental predictors and applied different bias correction methods, including spatial filtering, background manipulation, the use of bias files, and, finally, zero‐inflated (ZI) regression models, a new method with great potential to investigate and remove sampling bias in species data. We then collected new independent field data through systematic surveys of 52 randomly selected 1‐km2 grid squares across England to obtain abundance estimates of ancient and veteran trees. Calibration of the distribution models against the field data suggests that there are around eight to 10 times as many ancient and veteran trees present in England than the records currently suggest, with estimates ranging from 1.7 to 2.1 million trees compared to the 200,000 currently recorded in the ATI. The most successful bias correction method was systematic sampling of occurrence records, although the ZI models also performed well, significantly predicting field observations and highlighting both likely causes of undersampling and areas of the country in which many unrecorded trees are likely to be found. Our findings provide the first robust nationwide estimate of ancient and veteran tree abundance and demonstrate the enormous potential for distribution modeling based on citizen‐science data combined with independent field validation to inform conservation planning.
Therapeutic writing in a programme for binge eating disorder—A tool to come closer to clarifying feelings

Abstract Introduction Therapeutic writing involving affect consciousness (AC) can be used to put difficult topics into words. In this study, we investigated how patients with binge eating disorder (BED) experienced therapeutic writing and AC in the context of cognitive behavioural therapy. The elements were included in an existing cognitive behavioural therapy group programme and the participants' experiences investigated qualitatively. Aim To investigate therapeutic writing as experienced by patients in the context of a BED group programme focusing on AC. Method A phenomenological, hermeneutic design with semi‐structured interviews was employed. Eight participants were recruited after completing the BED programme at a Community Mental Health Centre on the West Coast of Norway. Findings Four sub‐themes emerged: Struggling to achieve a flow in the writing process, Deeper understanding of eating patterns through writing, Moving specific feelings towards the surface by writing and Greater insight into oneself as a human being by shared writing. Based on the sub‐themes, one main theme was developed: Therapeutic writing in a binge eating disorder programme means focusing on oneself as a human being by becoming closer to one's feelings. Conclusion Therapeutic writing offered in treatment for BED involves individual movements at different levels, including processes of awareness of feelings, cognitions and oneself as a human being.
Changes in interstitial cells and gastric excitability in a mouse model of sleeve gastrectomy

Obesity is a critical risk factor of several life-threatening diseases and the prevalence in adults has dramatically increased over the past ten years. In the USA the age-adjusted prevalence of obesity in adults was 42.4%, i.e., with a body mass index (BMI, weight (kg)/height (m)2) that exceeds 30 kg/m2. Obese individuals are at the higher risk of obesity-related diseases, co-morbid conditions, lower quality of life, and increased mortality more than those in the normal BMI range i.e., 18.5–24.9 kg/m2. Surgical treatment continues to be the most efficient and scientifically successful treatment for obese patients. Sleeve gastrectomy or vertical sleeve gastrectomy (VSG) is a relatively new gastric procedure to reduce body weight but is now the most popular bariatric operation. To date there have been few studies examining the changes in the cellular components and pacemaker activity that occur in the gastric wall following VSG and whether normal gastric activity recovers following VSG. In the present study we used a murine model to investigate the chronological changes of gastric excitability including electrophysiological, molecular and morphological changes in the gastric musculature following VSG. There is a significant disruption in specialized interstitial cells of Cajal in the gastric antrum following sleeve gastrectomy. This is associated with a loss of gastric pacemaker activity and post-junctional neuroeffector responses. Over a 4-month recovery period there was a gradual return in interstitial cells of Cajal networks, pacemaker activity and neural responses. These data describe for the first time the changes in gastric interstitial cells of Cajal networks, pacemaker activity and neuroeffector responses and the time-dependent recovery of ICC networks and normalization of motor activity and neural responses following VSG.
Efficient nanoparticle focusing utilizing cascade AC electroosmotic flow

This study presents on‐chip continuous accumulation and concentration of nanoscale samples using a cascade alternating current electroosmosis (cACEO) flow. ACEO can generate flow motion caused by ion movement due to interactions between the AC electric field and the induced charge layer on the electrode surface, with the potential to accumulate particles, especially in low‐conductive liquid. However, the intrinsic particle diffusive motion, which is sensitive to particle size, is an essential element influencing accumulation efficiency. In this study, an electrode combining chevron and double‐gap geometry embedded in a microfluidic channel was developed to perform efficient three‐dimensional (3D) nanoparticle focusing using ACEO. The chevron electrode pattern was introduced upstream of the focusing zone to overcome particle accumulation in scattering zones near the channel sidewall. To demonstrate the efficiency of the proposed device for particle accumulation, three nanoparticle types were used: latex, metal, and biomaterial. Continuous 3D concentration of 50‐nm polystyrene particles was confirmed. The concentration factor, determined based on image processing, became quite high when 50‐nm gold nanoparticles were used. Moreover, nanoparticles with a 20‐nm diameter were accumulated using cACEO. Finally, we used the concentrator chip to accumulate 50‐nm liposome particles, confirming that the device could also successfully concentrate biomaterials.
Improved Design for Hardware Implementation of Graph-Based Large Margin Classifiers for Embedded Edge Computing

The number of connected embedded edge computing Internet of Things (IoT) devices has been increasing over the years, contributing to the significant growth of available data in different scenarios. Thereby, machine learning algorithms arise to enable task automation and process optimization based on those data. However, due to some learning methods’ computational complexity implementing geometric classifiers, it is a challenge to map these on embedded systems or devices with limited resources in size, processing, memory, and power, to accomplish the desired requirements. This hampers the applicability of these methods to complex industrial embedded edge applications. This work evaluates strategies to reduce classifiers’ implementation costs based on the CHIP-clas model, independent of hyperparameter tuning and optimization algorithms. The proposal aims to evaluate the tradeoff between numerical precision and model performance and analyze the hardware implementations of a distance-based classifier. Two 16-b floating-point formats were compared to the 32-b floating-point precision implementation. Also, a new hardware architecture was developed and then compared to the state-of-the-art reference. The results indicate that the model is robust to low precision computation, providing statistically equivalent results compared to the baseline model, also pointing out statistically equivalent performance and a global speed-up factor of approx 4.39 in processing time.
Image-based parameter inference for epithelial mechanics

Measuring mechanical parameters in tissues, such as the elastic modulus of cell-cell junctions, is essential to decipher the mechanical control of morphogenesis. However, their in vivo measurement is technically challenging. Here, we formulated an image-based statistical approach to estimate the mechanical parameters of epithelial cells. Candidate mechanical models are constructed based on force-cell shape correlations obtained from image data. Substitution of the model functions into force-balance equations at the cell vertex leads to an equation with respect to the parameters of the model, by which one can estimate the parameter values using a least-squares method. A test using synthetic data confirmed the accuracy of parameter estimation and model selection. By applying this method to Drosophila epithelial tissues, we found that the magnitude and orientation of feedback between the junction tension and shrinkage, which are determined by the spring constant of the junction, were correlated with the elevation of tension and myosin-II on shrinking junctions during cell rearrangement. Further, this method clarified how alterations in tissue polarity and stretching affect the anisotropy in tension parameters. Thus, our method provides a novel approach to uncovering the mechanisms governing epithelial morphogenesis.
Case identification, retention and blood pressure control in Kenya.

BACKGROUND Prevalence of hypertension in Africa is rising but it remains underdiagnosed and poorly controlled. In Kenya, only 22% of individuals known to have hypertension were on treatment, and only 51.7% were controlled. This study will assess screening outcomes, retention and blood pressure (BP) control of a hypertension programme in Kenya. DESIGN This was a retrospective cohort study using data routinely collected between 2015 and 2018. All patients aged >18 years screened and treated in the programme were included. RESULTS Of 663,028 screening encounters, 70.4% were female; the median age was 34 years. Overall, 19% of the study population, mainly males and older persons, had high BP higher rates. Of 66,981 patients started on treatment, the majority were females (71.2%); the median age was 55 years. Only 12% of patients were reported as having been retained after 12 months, and 48.6% of patients on treatment 10.5-13.5 months after enrolment had controlled BP. Older age and treatment at primary care level were associated with better retention and females had better BP control. CONCLUSIONS The programme screened primarily females and younger individuals at lower risk. Retention was poor and close to half of patients retained had controlled BP. Hypertension programmes should target high-risk individuals, decentralise treatment, incorporate retention strategies and improve longitudinal data management.
Overexpression of p-4EBP1 associates with p-eIF4E and predicts poor prognosis for non-small cell lung cancer patients with resection

Eukaryotic initiation factor 4E (eIF4E) and its phosphorylated form (p-eIF4E) play a crucial role in the protein synthesis, both are under regulation of eIF4E-binding protein 1 (4EBP1) and mitogen-activated protein kinase (MAPK)-interacting kinases (MNKs). This study aims to explore the potential prognostic significance of p-4EBP1 and p-eIF4E in NSCLC patients. The expression of p-4EBP1 and p-eIF4E in NSCLC patients was detected by immunohistochemistry (IHC) staining in tissue microarrays (TMAs) containing 354 NSCLC and 53 non-cancerous lung tissues (Non-CLT). The overexpression percentage of p-4EBP1 and p-eIF4E in lung squamous cell carcinoma (SCC) and adenocarcinoma (ADC) was significantly higher than that of Non-CLT. P-4EBP1 expression in patients with advanced clinical stage was higher than that in early stage. Expression of p-4EBP1 had a positive relationship with p-eIF4E expression both in lung SCC and ADC. NSCLC patients with high expression of p-4EBP1 and p-eIF4E alone or in combination had a lower survival rate than that of other phenotypes. For NSCLC patients, p-4EBP1 is an independent poor prognostic factor as well as clinical stage, LNM and pathological grade. Overexpression of p-4EBP1 and p-eIF4E might be novel prognostic marker for NSCLC, who possesses potential application value for NSCLC targeted therapy.