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ObjectiveThe aim of this study was to characterize the phenotype and genotype of patients with Yao syndrome (YAOS), with focus on comparing to prior cohorts, identifying novel features, and describing treatment observations.MethodsA retrospective medical records review of patients with YAOS seen at Mayo Clinic was conducted to characterize clinical features, NOD2 genotypes, and therapeutic trials and responses.ResultsTwenty-two patients diagnosed with YAOS were included. Eighteen patients (81.8%) were female and twenty (90.9%) were White. Mean age at symptom onset was 24.0 ± 14.8 years. Common clinical manifestations included fever (81.8% of patients), rash (95.5%), chronic gastrointestinal symptoms (100%), arthralgia/arthritis (95.5%), and sicca symptoms (68.2%). NOD2 genotypes as single variants included IVS8 + 158 in 14 patients (63.6%), R702W in 8 patients (36.4%), 1007fs in 4 (18.2%), and one patient had only a previously unreported rare variant. Eight patients (36.4%) had compound (two or more) NOD2 variants. Potential comorbidities of YAOS observed in this cohort included gastrointestinal dysmotility, autonomic dysfunction, and mast cell activation-like symptoms. Glucocorticoid responsiveness was observed in 15 of 20 patients exposed (75%). Eleven patients (50.0%) received IL-1 inhibitor therapy, and one patient (4.5%) received IL-6 inhibitor therapy with adequate disease control.ConclusionOur findings substantiate the occurrence of fevers, arthralgia/arthritis, rash, chronic gastrointestinal symptoms, and sicca-like symptoms described previously in patients with YAOS. Novel clinical features and one NOD2 variant not previously described were identified. Glucocorticoids, biologic IL-1 inhibitors, and IL-6 receptor inhibitors appeared to be effective for treatment of patients with YAOS.

Active learning is a field of machine learning that seeks to find the most efficient labels to annotate with a given budget, particularly in cases where obtaining labeled data is expensive or infeasible. This is becoming increasingly important with the growing success of learning-based methods, which often require large amounts of labeled data. Computer vision is one area where active learning has shown promise in tasks such as image classification, semantic segmentation, and object detection. In this research, we propose a pool-based semi-supervised active learning method for image classification that takes advantage of both labeled and unlabeled data. Many active learning approaches do not utilize unlabeled data, but we believe that incorporating these data can improve performance. To address this issue, our method involves several steps. First, we cluster the latent space of a pre-trained convolutional autoencoder. Then, we use a proposed clustering contrastive loss to strengthen the latent space's clustering while using a small amount of labeled data. Finally, we query the samples with the highest uncertainty to annotate with an oracle. We repeat this process until the end of the given budget. Our method is effective when the number of annotated samples is small, and we have validated its effectiveness through experiments on benchmark datasets. Our empirical results demonstrate the power of our method for image classification tasks in accuracy terms.

Background: Identifying neurological biomarkers to aid with diagnoses and treatment effect evaluation of mood and cognitive symptoms in major depressive disorder (MDD) is an unmet need. This study explores the Brain Network Analytics (BNA) tool, which provides information on cortical patterns compared to a healthy normative group, for improving MDD management. Methods: BNA was used to extract event-related potentials (ERPs) from high-density EEG, and its clinical utility to assess the effects of vortioxetine on depression and cognition was evaluated. Twenty-five MDD subjects (20–65 years old) with cognitive dysfunction underwent an 8-week open-label treatment using vortioxetine. ERP data, generated during cognitive tasks, were collected at pre-treatment, two weeks and eight weeks into treatment. Correlations with MDD symptoms and cognitive functioning were investigated. Exploratory analyses assessed the differences in baseline and endpoint ERP characteristics between MDD subjects and matched controls (N = 41). Results: Compared to controls, MDD subjects exhibited increased baseline latencies of P200 and P3b ERP components, which normalized at treatment endpoint. P200 and P300 in the MDD group were correlated with clinical assessments, and indicated a pro-cognitive effect of vortioxetine independent of its antidepressant effect. Limitations: This study was limited by a small sample size and lack of a placebo condition. Conclusions: Our results suggest that the application of BNA can potentially support MDD diagnosis and monitor treatment efficacy across various symptom and functional domains. Further studies are warranted to explore the role of BNA in clinical research and practice.

Abstract Background In the United States, rare disease (RD) is defined as a condition that affects fewer than 200,000 individuals. Collectively, RD affects an estimated 30 million Americans. A significant portion of RD has an underlying genetic cause; however, this may go undiagnosed. To better serve these patients, the Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD) was created under the auspices of the Center for Individualized Medicine (CIM) aiming to integrate genomics into subspecialty practice including targeted genetic testing, research, and education. Methods Patients were identified by subspecialty healthcare providers from 11 clinical divisions/departments. Targeted multi-gene panels or custom exome/genome-based panels were utilized. To support the goals of PRaUD, a new clinical service model, the Genetic Testing and Counseling (GTAC) unit, was established to improve access and increase efficiency for genetic test facilitation. The GTAC unit includes genetic counselors, genetic counseling assistants, genetic nurses, and a medical geneticist. Patients receive abbreviated point-of-care genetic counseling and testing through a partnership with subspecialty providers. Results Implementation of PRaUD began in 2018 and GTAC unit launched in 2020 to support program expansion. Currently, 29 RD clinical indications are included in 11 specialty divisions/departments with over 142 referring providers. To date, 1152 patients have been evaluated with an overall solved or likely solved rate of 17.5% and as high as 66.7% depending on the phenotype. Noteworthy, 42.7% of the solved or likely solved patients underwent changes in medical management and outcome based on genetic test results. Conclusion Implementation of PRaUD and GTAC have enabled subspecialty practices advance expertise in RD where genetic counselors have not historically been embedded in practice. Democratizing access to genetic testing and counseling can broaden the reach of patients with RD and increase the diagnostic yield of such indications leading to better medical management as well as expanding research opportunities.

Arabic students of IAIN Kendari are unique in terms of their living environment which still had internet network issues lead to different experiences in using Zoom. Research on the sustainability of Zoom-based Arabic learning during the Covid-19 pandemic aimed to analyze creative and innovative learning models and observe through the perception of Arabic students of IAIN Kendari towards the use of Zoom as a learning medium during COVID-19. A qualitative and phenomenological approaches were used. The data were collected by interviews and documentation. The respondents in this study were 20 Arabic course students from the 2019 batch who attended lectures using Zoom. Data analysis, data reduction, data display and conclusion were discussed. The results showed varied responses from students to Arabic learning based on Zoom. Most of the students stated that Zoom was well applied in learning compared to other media. It was also proved efficacious with a few palpable advantages, such as students’ visibility during classes and room capacity to accommodate larger numbers of students. The results illustrated that Arabic learning on Zoom, both during and post Covid-19, may continue by considering the condition of the student learning environment. After participating in distance learning through its application, the changes occurring at the level of students pertain to increased levels of involvement in the use of ICT, leading to the learners who initially did not use the platforms and switching to Zoom as a learning medium and benefiting from discussions and other existing features.

BackgroundWhile surgical simulation is regularly used in surgical training in high-income country settings, it is uncommon in low- and middle-income countries, particularly for surgical training that primarily occurs in rural areas. We designed and evaluated a novel surgical simulator for improving trachomatous trichiasis (TT) surgery training, given that trichiasis is mostly found among the poorest individuals in rural areas.Methodology/principal findingsTT surgery programs were invited to incorporate surgical simulation with a new, high fidelity, low-cost simulator into their training. Trainees completed standard TT-surgery training following World Health Organization guidelines. A subset of trainees received three hours of supplemental training with the simulator between classroom and live-surgery training. We recorded the time required to complete each surgery and the number of times the trainer intervened to correct surgical steps. Participants completed questionnaires regarding their perceptions. We also assessed trainer and trainee perceptions of surgical simulation training as part of trichiasis surgery training. 22 surgeons completed standard training and 26 completed standard training plus simulation. We observed 1,394 live-training surgeries. Average time to first live-training surgery completion was nearly 20% shorter the simulation versus the standard group (28.3 vs 34.4 minutes; p = 0.02). Trainers intervened significantly fewer times during initial live-training surgeries in the simulation group (2.7 vs. 4.8; p = 0.005). All trainers indicated the simulator significantly improved training by allowing trainees to practice safely and to identify problem areas before performing live-training surgeries. Trainees reported that simulation practice improved their confidence and skills prior to performing live-training surgeries.ConclusionsA single high-fidelity surgical simulation session can significantly improve critical aspects of initial TT surgeries.

Abstract Background High-intensity glucocorticoid regimens are commonly used to induce and maintain remission in Juvenile Dermatomyositis but are associated with several adverse side-effects. Evidence-based treatment guidelines from North American and European pediatric rheumatology research societies both advocate induction with intravenous pulse steroids followed by high dose oral steroids (2 mg/kg/day), which are then tapered. This study reports the time to disease control with reduced glucocorticoid dosing. Methods We retrospectively reviewed the records at a single tertiary-care children’s hospital of patients diagnosed with Juvenile Dermatomyositis between 2000 and 2014 who had a minimum of 2 years of follow-up. The primary outcome measure was time to control of muscle and skin disease. Additional outcome measures included glucocorticoid dosing, effect of treatment on height, frequency of calcinosis, and complications from treatment. Results Of the 69 patients followed during the study period, 31 fulfilled inclusion criteria. Median length of follow-up was 4.58 years, (IQR 3–7.5). Myositis control was achieved in a median of 7.1 months (IQR 0.9–63.4). Cutaneous disease control was achieved in a median of 16.7 months (IQR 4.3–89.5). The median starting dose of glucocorticoids was 0.85 mg/kg/day, (IQR 0.5–1.74). The median duration of steroid treatment was 9.1 months, (IQR 4.7–17.4), while the median duration of any pharmacotherapy was 29.2 months (IQR 10.4 to 121.3). Sustained disease control off medications was achieved in 21/31 (68%) patients by the end of review. Persistent calcinosis was identified in only one patient (3%). Conclusion Current accepted treatment paradigms for Juvenile Dermatomyositis include oral glucocorticoids beginning at 2 mg/kg/day and reduced over a prolonged time period. However, our results suggest that treatment using reduced doses and duration with early use of steroid-sparing agents is comparably effective in achieving favorable outcomes in Juvenile Dermatomyositis.

Abstract Background and Aims Hyperbaric oxygen therapy (HBOT), utilizes 100% oxygen at pressures greater than sea‐level atmospheric pressure, for the treatment of conditions in which the tissues starve for oxygen. The Undersea and Hyperbaric Medical Society (UHMS) has granted HBOT approval for the treatment of various conditions. On the other hand, applying informatics registry systems can improve care delivery, ameliorate outcomes, and reduce the costs and medical errors for the patients receiving HBOT treatment. Therefore, we aimed to design, develop, and evaluate a registry system for patients undergoing HBOT. Methods In the first phase, the conceptual and logical models were designed after conducting symposiums with experts and having other experts review the models. In the second phase, the system was developed on the web using ASP.NET and C# programming languages frameworks. The last phase involved Nielsen's heuristic evaluation method for the system's usability. Five experts evaluated the system, including three health information management specialists and two medical informatics specialists. Results The hyperbaric patient information registry system (HPIRS) interacts with three types of users—a specialist physician, a nurse, and a system administrator. A scenario for each predefined activity was designed, and all the information was stored in the SQL servers. The five experts independently found 152 issues, of which 84 were duplicates. The 68 distinct issues of the system were then resolved. Conclusions The design and development of such registry systems can make data available and stored carefully to improve clinical care and medical research and decrease costs and errors. These registries can provide the healthcare systems with E‐health applications, improved data management, more secure data transfer, and support for statistical reporting. The implemented heuristic evaluation method can also provide a low‐cost and readily available system to fix the issues of the designed systems.

Saffron authenticity is important for the saffron industry, consumers, food industry, and regulatory agencies. Herein we describe a combo of two novel methods to distinguish genuine saffron from fake in a user-friendly manner and without sophisticated instruments. A smartphone coupled with Foldscope was used to visualize characteristic features and distinguish “genuine” saffron from “fake.” Furthermore, destaining and staining agents were used to study the staining patterns. Toluidine blue staining pattern was distinct and easier to use as it stained the papillae and the margins deep purple, while its stain is lighter yellowish green toward the central axis. Further to automate the process, we tested and compared different machine learning-based classification approaches for performing the automated saffron classification into genuine or fake. We demonstrated that the deep learning-based models are efficient in learning the morphological features and classifying samples as either fake or genuine, making it much easier for end-users. This approach performed much better than conventional machine learning approaches (random forest and SVM), and the model achieved an accuracy of 99.5% and a precision of 99.3% on the test dataset. The process has increased the robustness and reliability of authenticating saffron samples. This is the first study that describes a customer-centric frugal science-based approach to creating an automated app to detect adulteration. Furthermore, a survey was conducted to assess saffron adulteration and quality. It revealed that only 40% of samples belonged to ISO Category I, while the average adulteration percentage in the remaining samples was 36.25%. After discarding the adulterants from crude samples, their quality parameters improved significantly, elevating these from ISO category III to Category II. Conversely, it also means that Categories II and III saffron are more prone to and favored for adulteration by fraudsters.

One of the most challenging problems associated with the development of accurate and reliable application of computer vision and artificial intelligence in agriculture is that, not only are massive amounts of training data usually required, but also, in most cases, the images have to be properly labeled before models can be trained. Such a labeling process tends to be time consuming, tiresome, and expensive, often making the creation of large labeled datasets impractical. This problem is largely associated with the many steps involved in the labeling process, requiring the human expert rater to perform different cognitive and motor tasks in order to correctly label each image, thus diverting brain resources that should be focused on pattern recognition itself. One possible way to tackle this challenge is by exploring the phenomena in which highly trained experts can almost reflexively recognize and accurately classify objects of interest in a fraction of a second. As techniques for recording and decoding brain activity have evolved, it has become possible to directly tap into this ability and to accurately assess the expert’s level of confidence and attention during the process. As a result, the labeling time can be reduced dramatically while effectively incorporating the expert’s knowledge into artificial intelligence models. This study investigates how the use of electroencephalograms from plant pathology experts can improve the accuracy and robustness of image-based artificial intelligence models dedicated to plant disease recognition. Experiments have demonstrated the viability of the approach, with accuracies improving from 96% with the baseline model to 99% using brain generated labels and active learning approach.

Abstract Malignant gliomas are the most common and deadly type of central nervous system tumors. Despite some advances in treatment, the mean survival time remains only about 1.25 years. Even after surgery, radiotherapy and chemotherapy, gliomas still have a poor prognosis. Exosomes are the most common type of extracellular vesicles with a size range of 30 to 100 nm, and can act as carriers of proteins, RNAs, and other bioactive molecules. Exosomes play a key role in tumorigenesis and resistance to chemotherapy or radiation. Recent evidence has shown that exosomal microRNAs (miRNAs) can be detected in the extracellular microenvironment, and can also be transferred from cell to cell via exosome secretion and uptake. Therefore, many recent studies have focused on exosomal miRNAs as important cellular regulators in various physiological and pathological conditions. A variety of exosomal miRNAs have been implicated in the initiation and progression of gliomas, by activating and/or inhibiting different signaling pathways. Exosomal miRNAs could be used as therapeutic agents to modulate different biological processes in gliomas. Exosomal miRNAs derived from mesenchymal stem cells could also be used for glioma treatment. The present review summarizes the exosomal miRNAs that have been implicated in the pathogenesis, diagnosis and treatment of gliomas. Moreover, exosomal proteins could also be involved in glioma pathogenesis. Exosomal miRNAs and proteins could also serve as non-invasive biomarkers for prognosis and disease monitoring. Video Abstract

Objective The purpose of this study is to explore the possibility of developing a biomarker that can discriminate early-stage Parkinson’s disease from healthy brain function using electroencephalography (EEG) event-related potentials (ERPs) in combination with Brain Network Analytics (BNA) technology and machine learning (ML) algorithms. Background Currently, diagnosis of PD depends mainly on motor signs and symptoms. However, there is need for biomarkers that detect PD at an earlier stage to allow intervention and monitoring of potential disease-modifying therapies. Cognitive impairment may appear before motor symptoms, and it tends to worsen with disease progression. While ERPs obtained during cognitive tasks performance represent processing stages of cognitive brain functions, they have not yet been established as sensitive or specific markers for early-stage PD. Methods Nineteen PD patients (disease duration of ≤2 years) and 30 healthy controls (HC) underwent EEG recording while performing visual Go/No-Go and auditory Oddball cognitive tasks. ERPs were analyzed by the BNA technology, and a ML algorithm identified a combination of features that distinguish early PD from HC. We used a logistic regression classifier with a 10-fold cross-validation. Results The ML algorithm identified a neuromarker comprising 15 BNA features that discriminated early PD patients from HC. The area-under-the-curve of the receiver-operating characteristic curve was 0.79. Sensitivity and specificity were 0.74 and 0.73, respectively. The five most important features could be classified into three cognitive functions: early sensory processing (P50 amplitude, N100 latency), filtering of information (P200 amplitude and topographic similarity), and response-locked activity (P-200 topographic similarity preceding the motor response in the visual Go/No-Go task). Conclusions This pilot study found that BNA can identify patients with early PD using an advanced analysis of ERPs. These results need to be validated in a larger PD patient sample and assessed for people with premotor phase of PD.

Abstract Queen discrimination behavior in the fire ant Solenopsis invicta maintains its two types of societies: colonies with one (monogyne) or many (polygyne) queens, yet the underlying genetic mechanism is poorly understood. This behavior is controlled by two supergene alleles, SB and Sb, with ~600 genes. Polygyne workers, having either the SB/SB or SB/Sb genotype, accept additional SB/Sb queens into their colonies but kill SB/SB queens. In contrast, monogyne workers, all SB/SB, reject all additional queens regardless of genotype. Because the SB and Sb alleles have suppressed recombination, determining which genes within the supergene mediate this differential worker behavior is difficult. We hypothesized that the alternate worker genotypes sense queens differently because of the evolution of differential expression of key genes in their main sensory organ, the antennae. To identify such genes, we sequenced RNA from four replicates of pooled antennae from three classes of workers: monogyne SB/SB, polygyne SB/SB, and polygyne SB/Sb. We identified 81 differentially expressed protein‐coding genes with 13 encoding potential chemical metabolism or perception proteins. We focused on the two odorant perception genes: an odorant receptor SiOR463 and an odorant‐binding protein SiOBP12. We found that SiOR463 has been lost in the Sb genome. In contrast, SiOBP12 has an Sb‐specific duplication, SiOBP12b′, which is expressed in the SB/Sb worker antennae, while both paralogs are expressed in the body. Comparisons with another fire ant species revealed that SiOBP12b′ antennal expression is specific to S. invicta and suggests that queen discrimination may have evolved, in part, through expression neofunctionalization.

Introduction: Precise lead localization is crucial for an optimal clinical outcome of subthalamic nucleus (STN) deep brain stimulation (DBS) treatment in patients with Parkinson's disease (PD). Currently, anatomical measures, as well as invasive intraoperative electrophysiological recordings, are used to locate DBS electrodes. The objective of this study was to find an alternative electrophysiology tool for STN DBS lead localization.Methods: Sixty-one postoperative electrophysiology recording sessions were obtained from 17 DBS-treated patients with PD. An intraoperative physiological method automatically detected STN borders and subregions. Postoperative EEG cortical activity was measured, while STN low frequency stimulation (LFS) was applied to different areas inside and outside the STN. Machine learning models were used to differentiate stimulation locations, based on EEG analysis of engineered features.Results: A machine learning algorithm identified the top 25 evoked response potentials (ERPs), engineered features that can differentiate inside and outside STN stimulation locations as well as within STN stimulation locations. Evoked responses in the medial and ipsilateral fronto-central areas were found to be most significant for predicting the location of STN stimulation. Two-class linear support vector machine (SVM) predicted the inside (dorso-lateral region, DLR, and ventro-medial region, VMR) vs. outside [zona incerta, ZI, STN stimulation classification with an accuracy of 0.98 and 0.82 for ZI vs. VMR and ZI vs. DLR, respectively, and an accuracy of 0.77 for the within STN (DLR vs. VMR)]. Multiclass linear SVM predicted all areas with an accuracy of 0.82 for the outside and within STN stimulation locations (ZI vs. DLR vs. VMR).Conclusions: Electroencephalogram biomarkers can use low-frequency STN stimulation to localize STN DBS electrodes to ZI, DLR, and VMR STN subregions. These models can be used for both intraoperative electrode localization and postoperative stimulation programming sessions, and have a potential to improve STN DBS clinical outcomes.

Abstract Background The external oblique myocutaneous flap has been previously described for reconstruction of chest-thoracic wall defects smaller than 400–500 cm2. However, it is utilized less often than workhorse flaps such as the omental, pectoralis, rectus abdominis, and latissimus dorsi myocutaneous flaps as many plastic surgeons are not aware that the flap can cover larger areas than previously documented. Case presentation We report a 57-year-old female tobacco user who underwent a resection of a grade 3 breast angiosarcoma resulting in a high left chest wall soft tissue defect approximating 900 cm2. The patient underwent an external oblique myocutaneous pedicle flap reconstruction of the defect, most notably in anticipation of postoperative adjuvant radiation therapy. No gross flap complications and or patient impairment were noted. Thirteen months status post flap reconstruction, the patient underwent an aortic valve replacement requiring re-elevation of the same flap for exposure. The flap demonstrated excellent viability during the procedure and postoperatively. Conclusion The pedicled external oblique myocutaneous flap should be considered when reconstructing larger high chest wall defects when other more common flaps used in chest reconstruction may not be indicated. The external oblique myocutaneous flap is an excellent tool in the armamentarium of any reconstructive surgeon; it is a straightforward and versatile flap that can be safely and reliably used in durable reconstruction of defects of the chest wall and covers defects larger than previously described in the literature.

The quality of learning Arabic at IAIN Bone still requires perfection. That means there are still many problems found such as from the aspect of teaching, students, method and the media. From the method aspect, lecturers tend to maintain the old method compared to exploring various methods that have been suggested by researchers in learning Arabic, in this case is Idafah. This tendency is one of the problem factors in understanding Arabic (Idafah). Learning Arabic, still desperately needs new innovations, because most of them (students) are khirrij (luaran) from public schools that do not have basic or even some who have never learned Arabic at all. Apart from that, the problems that are obtained are lack of facilities and infrastructure, facilities, language laboratories.

Abstract Background Few risk factors have been identified for the development of calcinosis among patients with Juvenile Dermatomyositis, and currently no clinical phenotype has been associated with its development. We analyzed a large database of patients to further elucidate any relationships among patients with and without calcinosis. Method The CARRA legacy registry recruited pediatric rheumatology patients from 55 centers across North America from 2010 through 2014, including over 650 subjects with Juvenile Dermatomyositis. We compared the demographic characteristics, clinical disease features and treatment histories of those with and without calcinosis using univariate and multivariate logistic regression. Results Of the 631 patients included in the analysis, 84 (13%) had a current or prior history of calcinosis. These patients were statistically more likely to have longer durations of disease prior to diagnosis and treatment, have lipodystrophy and joint contractures, and to have received intravenous immune globulin or rituximab as treatments. Conclusions Calcinosis is found more often in patients with prolonged active disease, severe disease, and certain clinical features such as lipodystrophy and joint contractures. When these factors are combined with other known associations and predictors, groups of at-risk patients can be more effectively identified, treated and studied to improve overall outcomes.

15q13.3 microdeletion syndrome causes a spectrum of cognitive disorders, including intellectual disability and autism. We assessed the ability of the EEG analysis algorithm Brain Network Analysis (BNA) to measure cognitive function in 15q13.3 deletion patients, and to differentiate between patient and control groups. EEG data was collected from 10 individuals with 15q13.3 microdeletion syndrome (14–18 years of age), as well as 30 age-matched healthy controls, as the subjects responded to Auditory Oddball (AOB) and Go/NoGo cognitive tasks. It was determined that BNA can be used to evaluate cognitive function in 15q13.3 microdeletion patients. This analysis also significantly differentiates between patient and control groups using 5 scores, all of which are produced from ERP peaks related to late cortical components that represent higher cognitive functions of attention allocation and response inhibition (P < 0.05).

Studies on clean energy transition amongst low-income urban households in the Global South use an array of qualitative and quantitative methods. However, attempts to combine qualitative and quantitative methods are rare and there are a lack of systematic approaches to this. This paper demonstrates a two stage approach using clustering methods to analyse a mixed dataset containing quantitative household survey data and qualitative interview data. By clustering the quantitative and qualitative data separately, latent groups with common characteristics and narratives arising from each of the two analyses are identified. A second stage of clustering identifies links between these qualitative and quantitative clusters and enables inference of energy transition pathways followed by low-income urban households defined by both quantitative characteristics and qualitative narratives. This approach can support interdisciplinary collaboration in energy research, providing a systematic approach to comparing and identifying links between quantitative and qualitative findings. • A mixed dataset comprising of quantitative survey data and qualitative interview data on low-income household energy use is analysed using hierarchical clustering to detect communities within each dataset. • Interviewees are matched to quantitative survey clusters and a second stage of clustering is performed using cluster membership as variables. • Second stage clusters identify common pairs of survey and interview clusters which define energy transition pathways based on socio-economic characteristics, energy use patterns, and narratives for decision making and practices.

E-Commerce in recent times has exploded many folds due to the invention of new Information and Communication (ICT) technologies and applications. Business models of today are highly depending upon internet based transaction and trading platforms, use of Web portals and mobile applications. Proposition of new business models sans the inclusion of internet and their application has become almost impossible for business. Business data pertaining to E Commerce has become highly valuable in recent times. Social networking websites, sharing of product data and its reviews in blogs paves ways for promoting business in new methods. There is need to develop metrics to assess the strength of E Commerce penetration in Business and also evaluate the various E Commerce platforms. Use of E business tools for data analysis, prediction and decision making has become the latest order of the day. Changing trends in E business has a drastic impact on the organizations depending upon internet based applications for handling its business processes and day to day transactions.

Background The use of negative pressure wound therapy (NPWT) devices has gained wide acceptance in the management of wounds. There have been a few reported cases of its use immediately after free tissue transfer. This is the first systematic review and pooled analysis on the immediate use of NPWT for free flaps with emphasis on the rate of free flap loss. Methods The authors performed a systematic review that focused on the rate of total free flap loss after immediate application of NPWT. EMBASE, Cochrane Library, Ovid Medicine, MEDLINE, Google Scholar, and PubMed databases were searched from 1997 to April of 2019. Peer-reviewed articles published in the English language were included. Results Ten articles were included in the review, yielding 211 free flap procedures. All studies were retrospective cohort studies except for two that were prospective studies and one that was a case series. The overall complete flap failure rate was n = 7 (3.3%). The most commonly reconstructed area was the lower extremity (n = 158 [74.9%]) followed by head and neck (n = 42 [19.9%]) and upper extremity (n = 11 [5.2%]). The vacuum pressure ranged from 75 to 125 mm/Hg. The time of application of the NPWT ranged from 5 to 7 days. The etiologies of wound defects were from trauma (n = 82 [63.6%]), tumor extirpation (n = 43 [33.3%]), and infection and burn (n = 4 [3.1%]). Conclusion The immediate application of NPWT on free flaps does not seem to be associated with an increased risk of flap failure.

West Virginia schools are consistently below the national average on the National Assessment of Educational Progress. Using Data Envelopment Analysis, we estimate the technical efficiency of West Virginia school districts. We find less variation in technical efficiency in West Virginia than in similar studies conducted in other states. This appears to be because of state policy imposing homogeneity of input usage. Due to the limited variation in technical efficiency across districts, we cannot analyze how non-school inputs such as socioeconomic factors affect technical efficiency across districts. Summary statistics organized by county economic status, however, suggest that socioeconomic status plays a role. Our results highlight an important limitation of DEA analysis on schools.

The beta-1 adrenergic receptor (ADRB1) is a promising therapeutic target intrinsically involved in the cognitive deficits and pathological features associated with Alzheimer's disease (AD). Evidence indicates that ADRB1 plays an important role in regulating neuroinflammatory processes, and activation of ADRB1 may produce neuroprotective effects in neuroinflammatory diseases. Novel small molecule modulators of ADRB1, engineered to be highly brain permeable and functionally selective for the G protein with partial agonistic activity, could have tremendous value both as pharmacological tools and potential lead molecules for further preclinical development. The present study describes our ongoing efforts toward the discovery of functionally selective partial agonists of ADRB1 that have potential therapeutic value for AD and neuroinflammatory disorders, which has led to the identification of the molecule STD-101-D1. As a functionally selective agonist of ADRB1, STD-101-D1 produces partial agonistic activity on G protein signaling with an EC50 value in the low nanomolar range, but engages very little beta-arrestin recruitment compared to the unbiased agonist isoproterenol. STD-101-D1 also inhibits the tumor necrosis factor α (TNFα) response induced by lipopolysaccharide (LPS) both in vitro and in vivo, and shows high brain penetration. Other than the therapeutic role, this newly identified, functionally selective, partial agonist of ADRB1 is an invaluable research tool to study mechanisms of G protein-coupled receptor signal transduction.

In gravitational lensing, magnification cross sections characterize the probability that a light source will have magnification greater than some fixed value, which is useful in a variety of applications. The (area) cross section is known to scale as μ − 2 for fold caustics and μ − 2.5 for cusp caustics. We aim to extend the results to higher-order caustic singularities, focusing on the elliptic umbilic, which can be manifested in lensing systems with two or three galaxies. The elliptic umbilic has a caustic surface, and we show that the volume cross section scales as μ − 2.5 in the two-image region and μ − 2 in the four-image region, where μ is the total unsigned magnification. In both cases our results are supported both numerically and analytically.

BackgroundHyper‐ and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood‐free method for tracking potassium would be an important clinical advance. Methods and ResultsTwo groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high‐resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single‐channel ECG. In addition, by analyzing the entire development group's first‐visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). ConclusionsThe signal‐processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost‐effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

MicroRNAs (miRNAs) are short, non-coding RNAs, which post-transcriptionally regulate gene expression and are proposed to play a key role in the regulation of innate and adaptive immunity. Here, we report a next generation sequencing (NGS) approach profiling the expression of miRNAs in primary bovine mammary epithelial cells (BMEs) at 1, 2, 4 and 6 hours post-infection with Streptococcus uberis, a causative agent of bovine mastitis. Analysing over 450 million sequencing reads, we found that 20% of the approximately 1,300 currently known bovine miRNAs are expressed in unchallenged BMEs. We also identified the expression of more than 20 potentially novel bovine miRNAs. There is, however, a significant dynamic range in the expression of known miRNAs. The top 10 highly expressed miRNAs account for >80% of all aligned reads, with the remaining miRNAs showing much lower expression. Twenty-one miRNAs were identified as significantly differentially expressed post-infection with S. uberis. Several of these miRNAs have characterised roles in the immune systems of other species. This miRNA response to the Gram-positive S. uberis is markedly different, however, to lipopolysaccharide (LPS) induced miRNA expression. Of 145 miRNAs identified in the literature as being LPS responsive, only 9 were also differentially expressed in response to S. uberis. Computational analysis has also revealed that the predicted target genes of miRNAs, which are down-regulated in BMEs following S. uberis infection, are statistically enriched for roles in innate immunity. This suggests that miRNAs, which potentially act as central regulators of gene expression responses to a Gram-positive bacterial infection, may significantly regulate the sentinel capacity of mammary epithelial cells to mobilise the innate immune system.

Over 1.2 million people are blind from trachomatous trichiasis (TT). Lid rotation surgery is the mainstay of treatment, but recurrence rates can be high. We investigated the outcomes (recurrence rates and other complications) of posterior lamellar tarsal rotation (PLTR) surgery, one of the two most widely practised TT procedures in endemic settings.We conducted a two-year follow-up study of 1300 participants who had PLTR surgery, conducted by one of five TT nurse surgeons. None had previously undergone TT surgery. All participants received a detailed trachoma eye examination at baseline and 6, 12, 18 and 24 months post-operatively. The study investigated the recurrence rates, other complications and factors associated with recurrence. Recurrence occurred in 207/635 (32.6%) and 108/641 (16.9%) of participants with pre-operative major (>5 trichiatic lashes) and minor (5 lashes (major recurrence). Recurrence was greatest in the first six months after surgery: 172 cases (55%) occurring in this period. Recurrence was associated with major TT pre-operatively (OR 2.39, 95% CI 1.83-3.11), pre-operative entropic lashes compared to misdirected/metaplastic lashes (OR 1.99, 95% CI 1.23-3.20), age over 40 years (OR 1.59, 95% CI 1.14-2.20) and specific surgeons (surgeon recurrence risk range: 18%-53%). Granuloma occurred in 69 (5.7%) and notching in 156 (13.0%).Risk of recurrence is high despite high volume, highly trained surgeons. However, the vast majority are minor recurrences, which may not have significant corneal or visual consequences. Inter-surgeon variation in recurrence is concerning; surgical technique, training and immediate post-operative lid position require further investigation.

With increasing use of prosthetic valves to treat degenerative valvular heart disease (VHD) in an aging population, the incidence and adverse consequences of paravalvular leaks (PVL) are better recognized. The present work aims to provide a cohesive review of the available literature in order to better guide the evaluation and management of PVL.Despite gains in operator experience and design innovation, significant PVL remains a significant complication that may present with congestive heart failure and/or hemolytic anemia. To date, clear consensus or guidelines on the evaluation and management of PVL remain lacking. Although the evolution of transcatheter valve therapies has had a tremendous impact on the management of patients with VHD, the limitations and complications of such techniques, including PVL, present further challenges. Incidence of PVL, graded as moderate or greater, ranges from 4 to 7.4% in surgical and transcatheter valve replacements, respectively. Improved imaging modalities and the advent of novel surgical and percutaneous therapies have undoubtedly yielded a better understanding of PVL including its anatomical location, mechanism, severity, and treatment options. Echocardiography, used in conjunction with cardiac computed tomography and cardiac magnetic resonance, provides essential details for diagnosis and management of PVL. Transcatheter intervention has become a favored approach in lieu of surgical intervention in select patients after previous surgical or percutaneous valve replacement. PVL treatment with vascular plugs, balloon post-dilation, and the valve-in-valve methods have shown technical success with promising clinical outcomes in appropriately selected patients.

This paper is based on an ethnographic study of how domesticity is enacted and adapted at homeless shelters for determining which clients are “service worthy .” The study draws on nineteen placement meetings with homeless men and focuses on institutional mechanisms for encouraging homemaking skills or domesticity among clients. Adapting Robert K. Merton's typology of adaptations to social norms, as well as Jaber Gubrium's “task‐designated identity,” we showcase male clients' self‐presentation strategies for adapting to the institutional mandates of domesticity. Specifically, our qualitative analysis reveals four modes of task adaption: (1) task conformity by professing the desired norms in their service encounters, (2) task evasion to avoid conversations and related tasks, (3) task transformation by linking the task at hand with something other than originally intended, particularly by reframing biographies to meet the local goals of domesticity, and (4) task protestation, which involves questioning the rationale and necessity of assigned tasks. [ABSTRACT FROM AUTHOR]