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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.

ObjectiveThe 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.BackgroundCurrently, 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.MethodsNineteen 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.ResultsThe 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).ConclusionsThis 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.

Abstract Cladribine tablets (CladT), like alemtuzumab, acts as an immune reconstitution therapy. However, CladT is administered orally (alemtuzumab is given by infusion) and without the potential for serious side effects that limit the therapeutic use of alemtuzumab in multiple sclerosis (MS). Treatment with CladT, given initially as short courses of treatment 1 year apart, provides years of freedom from MS disease activity in responders to treatment. The appearance of mild or moderate MS disease activity after the initial 2 years of treatment may prompt careful follow-up or a further course of CladT, depending on the nature of the activity and individual circumstances. The appearance of severe MS disease activity requires a switch to an alternative high-efficacy disease-modifying treatment (DMT). The accumulating data from CladT-treated people with MS in real-world studies, including those with follow-up durations extending for years beyond the initial treatment, have demonstrated long-term freedom from MS disease activity in a good proportion of patients. This clinical experience has also confirmed that treatment with CladT is generally safe and well tolerated. The best time to prescribe a high-efficacy DMT is the subject of debate, with evidence that earlier versus later use of such agents may provide more effective long-term protection from disability progression. High-efficacy DMTs have traditionally been reserved for use in people with MS and high disease activity on presentation or breakthrough disease on one or more DMTs, as per the current product labels. The latest evidence from real-world studies suggests that CladT is effective and safe in DMT-naïve patients, including those with shorter disease duration.

Abstract Maintenance of autonomic homeostasis is continuously calibrated by sensory fibers of the vagus nerve and sympathetic chain that convey compound action potentials (CAPs) to the central nervous system. Lipopolysaccharide (LPS) intravenous challenge reliably elicits a robust inflammatory response that can resemble systemic inflammation and acute endotoxemia. Here, we administered LPS intravenously in nine healthy subjects while recording ventral cervical magnetoneurography (vcMNG)-derived CAPs at the rostral Right Nodose Ganglion (RNG) and the caudal Right Carotid Artery (RCA) with optically pumped magnetometers (OPM). We observed vcMNG RNG and RCA neural firing rates that tracked changes in TNF-α levels in the systemic circulation. Further, endotype subgroups based on high and low IL-6 responders segregate RNG CAP frequency (at 30-120 min) and based on high and low IL-10 response discriminate RCA CAP frequency (at 0-30 min). These vcMNG tools may enhance understanding and management of the neuroimmune axis that can guide personalized treatment based on an individual’s distinct endophenotype.

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the greatest pandemic in the world. This virus involves the respiratory system, causes pulmonary dysfunction, and causes coronavirus disease (COVID-19). Pulmonary dysfunction due to COVID-19 may be asymptomatic, mild, moderate, and severe/critical. COVID-19 may involve other organs, and its sequelae may be persistent for a long time. The pulmonary function test is a method for evaluating the lungs in people. In this study, we reviewed the results of pulmonary function test (PFT) in patients with a history of COVID-19 involvement based on previous studies. Materials and Methods: The present review was conducted in 2024 using the keywords COVID-19, pulmonary function test, recovery, and pulmonary involvement in English. Eligible articles (articles containing the mentioned keywords) published during the years 2019 to 2023 were searched in Scopus, Pubmed, Wiley, and Google Scholar international databases. Relevant articles were identified, and after review, the most important and valuable points were presented. Results: PTF should not be done during COVID-19 involvement because it increases the rate of disease transmission. Small airway dysfunction, restrictive ventilatory dysfunction, and pulmonary diffusion impairment patterns are the most common findings in the PFTs of patients with a history of COVID-19. PFT improves gradually after the recovery of pulmonary involvement of COVID-19 for two years, even in patients with severe or critical forms of COVID-19. Conclusion: In this review, we summarized the results of studies about pulmonary function tests after COVID-19 involvement in survivors. Small airway dysfunction, restrictive ventilatory dysfunction, and pulmonary diffusion impairment are the most common findings in the PFT of survivors of COVID-19. These patterns are more prevalent among patients with severe or critical forms of COVID-19, and they are associated with the risk factors of COVID-19 severity, such as age, underlying disease, and pulmonary disorders. Forced vital capacity and diffusion capacity of lungs for carbon monoxide decreased in patients with COVID-19, and forced expiratory volume in 1 second (FEV1)/FVC and residual volume (RV) increased in these patients and they were associated with COVID-19 severity. The pulmonary involvement of COVID-19 recovers over time, and after two years, patients return to their baseline PFTs.

Abstract Studies on the association between coffee consumption and risk of lung cancer have been conflicting. The aim of this study was to systematically review the current evidence on the association between coffee consumption and risk of lung cancer and to quantify this association by performing a meta-analysis. A comprehensive systematic search was performed on online databases up to July 2023 investigating the association between coffee consumption and risk of lung cancer. All prospective cohort studies reporting odds ratios (ORs), rate or risk ratios (RRs), or hazard ratios (HRs) and 95% confidence intervals (CIs) in this context were included. The overall effect size was calculated using the random-effects model and statistical between-studies heterogeneity was examined using Cochrane’s Q test and I2. A total of 14 prospective cohort studies were included in this systematic review and meta-analysis. We found a significant positive association between coffee consumption and risk of lung cancer (RR: 1.28; 95% CI: 1.12, 1.47). This association remained significant when we included a pooled analysis paper and excluded 5 cohort studies (RR: 1.37; 95% CI: 1.12, 1.66). We observed no proof of significant publication bias using Egger’s test (P = 0.58). Moreover, dose–response analysis showed that each one cup/day increase in coffee consumption was related with a 6% higher lung cancer risk (RR: 1.06; 95% CI: 1.03, 1.09). In conclusion, we found a significant positive association between coffee consumption and risk of lung cancer.

Alzheimer's disease (AD) is an increasingly important public health concern due to the increasing proportion of older individuals within the general population. The impairment of processes responsible for adequate brain energy supply primarily determines the early features of the aging process. Restricting brain energy supply results in brain hypometabolism prior to clinical symptoms and is anatomically and functionally associated with cognitive impairment. The present study investigated changes in metabolic profiles induced by intracerebroventricular‐streptozotocin (ICV‐STZ) in an AD‐like animal model. To this end, male Wistar rats received a single injection of STZ (3 mg·kg−1) by ICV (2.5 μL into each ventricle for 5 min on each side). In the second week after receiving ICV‐STZ, rats were tested for cognitive performance using the Morris Water Maze test and subsequently prepared for positron emission tomography (PET) to confirm AD‐like symptoms. Tandem Mass Spectrometry (MS/MS) analysis was used to detect amino acid changes in cerebrospinal fluid (CFS) samples. Our metabolomics study revealed a reduction in the concentrations of various amino acids (alanine, arginine, aspartic acid, glutamic acid, glycine, isoleucine, methionine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine, and valine) in CSF of ICV‐STZ‐treated animals as compared to controls rats. The results of the current study indicate amino acid levels could potentially be considered targets of nutritional and/or pharmacological interventions to interfere with AD progression.

Abstract High efficiency and unity power factor (PF) are the most important requirements of a wireless charger system simultaneous with the output voltage regulation. Achieving all above‐mentioned criteria in a wide range of the load is challenging in the system. This paper presents a novel control approach applied to series‐series wireless power transmission converter by using a dual‐function compensator to achieve unity PF and maximum efficiency during the constant power‐constant voltage (CP‐CV) charging scenarios. A semi‐active rectifier with impedance matching capability along with a switch‐controlled capacitor constitutes the dual‐function compensator on the secondary side. Meanwhile, the primary side inverter executes the CP‐CV charging scenario for the battery with various charging characteristics at a fixed‐switching frequency. Besides that, all secondary side switches experience soft switching condition throughout the battery charging. Finally, a prototype with a power of 200 W and roughly regulated efficiency of 90% is presented in order to verify the proposed control method.

Abstract In many cancers, a stem-like cell subpopulation mediates tumor initiation, dissemination and drug resistance. Here, we report that cancer stem cell (CSC) abundance is transcriptionally regulated by C-terminally phosphorylated p27 (p27pT157pT198). Mechanistically, this arises through p27 co-recruitment with STAT3/CBP to gene regulators of CSC self-renewal including MYC, the Notch ligand JAG1, and ANGPTL4. p27pTpT/STAT3 also recruits a SIN3A/HDAC1 complex to co-repress the Pyk2 inhibitor, PTPN12. Pyk2, in turn, activates STAT3, creating a feed-forward loop increasing stem-like properties in vitro and tumor-initiating stem cells in vivo. The p27-activated gene profile is over-represented in STAT3 activated human breast cancers. Furthermore, mammary transgenic expression of phosphomimetic, cyclin-CDK-binding defective p27 (p27CK-DD) increases mammary duct branching morphogenesis, yielding hyperplasia and microinvasive cancers that can metastasize to liver, further supporting a role for p27pTpT in CSC expansion. Thus, p27pTpT interacts with STAT3, driving transcriptional programs governing stem cell expansion or maintenance in normal and cancer tissues.

The main aim of this research is to study the influence of traditional, online, and hybrid teaching modes on student academic performance. For this purpose, three determinants of perceived satisfaction and academic performance are used to compare student learning outcomes across the different teaching mediums. This is the first study to examine different teaching modes and their influence on students enrolled in higher education institutions. The study context is a set of China’s higher education sector after the COVID-19 outbreak. Data were collected on the model variables through an online questionnaire and distributed amongst a sample of undergraduate students who were enrolled at Overseas Education College at Jiangsu University. Data collection was divided into three categories: pre-pandemic, pandemic, and endemic situations in China. Structural equation modelling technique was adopted to inspect the collected data and confirm the hypothesis. Results show that student learning and student expectations have a significant positive impact on student perceived satisfaction in all contexts. Moreover, online mode of teaching yielded higher level of student satisfaction and hence, their academic performance. Findings of this study have generated implications for stakeholders of the education sector. Teachers must consistently improve themselves in terms of knowledge and skills, while the ministry of education should set required standards and monitor compliance. They should make some courses related to technology and innovation as a part of the undergraduate syllabus. These will help to stay relevant in today’s competitive academic sector.

In pre-adolescence, repeated anesthesia may be required for therapeutic interventions. Adult cognitive and neurobehavioral problems may result from preadolescent exposure to anesthetics. This study examined the long-term morphological and functional effects of repeated sub-anesthetic doses of ketamine exposure on male and female rat adults during pre-adolescence. Weaned 48 pre-adolescent rats from eight mothers and were randomly divided into four equal groups: control group and the ketamine group of males and females (20 mg/kg daily for 14 days); then animals received care for 20–30 days. Repeated exposure to sub-anesthetic doses of ketamine on cognitive functions was assayed using Social discrimination and novel object tests. Besides, an elevated plus maze and fear conditioning apparatus were utilized to determine exploratory and anxiety-like behavior in adults. Toluidine blue stain was used to evaluate the number of dead neurons in the hippocampus, and the effects of ketamine on synaptic plasticity were compared in the perforant pathway of the CA1 of the hippocampus. Our study indicates that repeated exposure to sub-anesthetic doses of ketamine during pre-adolescence can result in neurobehavioral impairment in male and female rat adulthood but does not affect anxiety-like behavior. We found a significant quantifiable increase in dark neurons. Recorded electrophysiologically, repeat sub-anesthetic doses of ketamine resulted in hampering long-term potentiation and pair pulse in male adult animals. Our results showed that repeated exposure to sub-anesthetic doses of ketamine during pre-adolescence can induce hippocampus and neuroplasticity changes later in adulthood. This study opens up a new line of inquiry into potential adverse outcomes of repeated anesthesia exposure in pre-adolescent rats.

Introduction Astaxanthin is a widely used carotenoid pigment in the food industry which is extracted from various natural and synthetic sources. Nowadays, due to the adverse effects of organic solvents green solvents which are non-toxic, non-volatile and environmentally friendly have been proposed. Therefore, this study focuses on comparison of the extraction of astaxanthin from shrimp (Fenneropenaeus merguiensis) and Gammarus (Pontogammarus maeoticus) under soaking conditions for 24 hours with organic solvent (combination of ethanol with ethyl acetate), green solvent (microemulsion of ionic liquid in water) and vegetable oil (sunflower oil). Ionic liquid microemulsion in water is considered a newnovel solvent for astaxanthin extraction. Determination of density, conductivity and diameter were the characteristics of microemulsion test. In extraction,Solvent to sample ratios of 5x, 12.5x and 20x were used for the extraction and compared with the control sample. Materials and Methods merguiensis and P. maeoticus With species approval were procured from Persian Gulf Ecology Research Institute (Iran). Commercial astaxanthin (>98 % purity), α-diphenyl-β-picrylhydrazyl (DPPH), and butylated hydroxytoluene (BHT) were procured from Sigma-Aldrich (USA). The HPLC grade ethanol, propanol, ethyl acetate,, tributyl octyl phosphonium bromide, Triton X-100, and n-butanol were obtained from Merck Chemicals Co. (Germany). Refined sunflower oil which was antioxidant-free, was also purchased from Hayat Company (Iran). The shell of F. merguiensis and P. maeoticus were carefully washed with distilled water, then freeze-dried (Christ-Alpha 1–4, LD freeze dryer, Germany) for 48 h at -50 °C. After sieving the powders with a laboratory sieve with a mesh smaller than 15 µm. The obtained powders were kept at Refrigerator. All experiments were done in the Food and Drug Administration Department of Hormozgan University of Medical Sciences. Results and Discussion According to the results, the density of the microemulsion was determined in the range of 0.97151 g/cm3, its diameter was 15.8 nanometers and the conductivity was 312 microsiemens at 27.1°C. The results of astaxanthin extraction with different solvents in the comparison with control solvent were statistically significant (p< 0.05). According to the results obtained from the extraction of astaxanthin from two sources of shrimp and gammarus, shrimp was selected as the source with the highest amount of extracted astaxanthin. The use of green solvent (ionic liquid microemulsion in water) in a ratio of 12.5 times solvent to sample was also chosen as the optimal method. The amount of astaxanthin extracted under optimal conditions was 77.44 ± 1.09 mg/ml. The results of DPPH radical inhibition by extracted astaxanthin using ionic, oily and organic solvents compared to synthetic antioxidant BHT showed that the antioxidant activity increased with increasing the concentration of astaxanthin, but this increase was always lower than BHT. ConclusionIn general, the results of this research show that the use of microemulsion based on ionic liquids is a suitable alternative to conventional methods in extracting and recovering astaxanthin from natural biological sources. AcknowledgementWe are grateful to the Honorable Vice-Chancellor of Hormozgan Food and Drug Administration for the help in using the Hormozgan Food and Drug Laboratory to conduct the experiments of this doctoral thesis.

Abstract Ricin, an extremely potent toxin produced from the seeds of castor plant, Ricinus communis, is ribosome-inactivating protein that blocks cell-protein synthesis. It is considered a biological threat due to worldwide availability of castor beans, massive quantities as a by-product of castor oil production, high stability and ease of production. The consequence of exposure to lethal dose of ricin was extensively described in various animal models. However, it is assumed that in case of aerosolized ricin bioterror attack, the majority of individuals would be exposed to sublethal doses rather than to lethal ones. Therefore, the purpose of current study was to assess short- and long-term effects on physiological parameters and function following sublethal pulmonary exposure. We show that in the short-term, sublethal exposure of mice to ricin resulted in acute lung injury, including interstitial pneumonia, cytokine storm, neutrophil influx, edema and cellular death. This damage was manifested in reduced lung performance and physiological function. Interestingly, although in the long-term, mice recovered from acute lung damage and restored pulmonary and physiological functionality, the reparative process was associated with lasting fibrotic lesions. Therefore, restriction of short-term acute phase of the disease and management of long-term pulmonary fibrosis by medical countermeasures is expected to facilitate the quality of life of exposed survivors.

We propose a masked pretraining method for Graph Neural Networks (GNNs) to improve their performance on fitting potential energy surfaces, particularly in water and small organic molecule systems. GNNs are pretrained by recovering the spatial information of masked-out atoms from molecules selected with certain ratios and then transferred and fine-tuned on atomic force fields. Through such pretraining, GNNs learn meaningful prior about the structural and underlying physical information of molecule systems that are useful for downstream tasks. With comprehensive experiments and ablation studies, we show that the proposed method improves both the accuracy and convergence speed of GNNs compared to their counterparts trained from scratch or with other pretraining techniques. This approach showcases its potential to enhance the performance and data efficiency of GNNs in fitting molecular force fields.

This paper aims to incorporate Greimassian semiotics of passions in current cognitive science. Concepts such as passional codes, the canonical passional schema, and other central Greimassian notions in the domain of passions are mapped against ideas such as frames and layers of meaning within cognitive science. By integrating the two fields artificially kept apart, the authors endeavour to show how the resulting synergy could shed new light on the study of passions.

Abstract Background Israeli‐Arab adolescents are reported to consume higher amounts of fast food, sweets, and candies. This study examined possible associations among energy drink consumption, anxiety, and well‐being in Israeli‐Arab adolescents. We also investigated these associations concerning fast food consumption, physical activity, and hours of sleep per night. Methods A cross‐sectional exploratory study assessed adolescents’ energy drink consumption, nutritional and lifestyle habits, well‐being, and anxiety using self‐reported questionnaires. Adolescents aged 12–18 from several cities and villages in northern Israel were considered for the study. Anthropometric measurements—weight, height, and waist circumference—were also assessed. Results One hundred and fourteen adolescents (59 females) participated in the study. Gender and energy drink consumption were associated with psychological status. Energy drink consumers reported a lower well‐being index and a higher anxiety index than nonconsumers (73.02 ± 2.64 and 23 ± 1.56 vs. 79.37 ± 1.67 and 18.86 ± 1.41, respectively). Energy drink consumers ate significantly more fast food per week than nonconsumers (1.25 ± 0.07 vs. 1.03 ± 0.09). Additionally, hours of sleep per night were correlated with anxiety levels among energy drink consumers [rs = 0.352, p = 0.018]. These results differed between genders. Conclusions Our study shows complex associations between energy drink consumption and mental health indices. These associations can serve as a basis for further research into this topic.

IntroductionThe zygomatic bone has a great impact on the anterior and lateral projection of the midface as well as the proper position of the globe. Primary alignment of zygomatic fractures is very important as secondary reconstruction is far more challenging. Treatment of misaligned zygoma requires refracturing of the bone to allow for repositioning. Due to the great impact of the zygoma on the projection of the midface, a precise 3D realignment is of great importance. Technology nowadays develops rapidly and allows for superior results in many surgical fields. The use of patient specific surgical guides and fixation plates is becoming more abundant.MethodsUsing 3D segmentation and design software, we developed a sequence for using 3D planning and printing both for the refracturing stage, avoiding a coronal approach, and for precise repositioning and fixation of the zygoma in the new position.ResultsThe method is described as well as a unique advanced 3D analysis, allowing for objectively assessing the results. Two cases are presented, including the design and post operative changes.DiscussionPre-op, planned and final positions were compared and showed exceptional accuracy allowing for the elimination of human errors which are common in a 3D sensitive procedure such as refracturing of the zygoma. This method can easily be applied to other secondary reconstruction procedures requiring realignment.

Introduction: Tumor-induced osteomalacia (TIO) is a rare paraneoplastic syndrome defined by severe hypophosphatemia, bone loss, fractures, and muscle weakness. Identifying of the tumor site is often difficult. The primary treatment for Tumor-induced osteomalacia (TIO) is currently surgical resection. Removing the primary tumor is the most definitive treatment for this disease. Methods: Here we describe the case of a 32-year-old man who exhibited sever muscle weakness and pain that had continued for three years. The patient has three sisters and one brother, all of whom are completely healthy and free of bone and muscle problems.Laboratory data indicate low serum phosphorus, normal serum and urine calcium level, besides raised alkaline phosphatase level. Due to elevated phosphorus levels in the urine and the lack of an alternative source for phosphorus excretion, along with the absence of short stature, bone deformities, and a negative family history that might suggest the potential for Tumor-induced osteomalacia (TIO), an octreotide scan was performed to the localized the tumor site. The scan, corroborated by CT and MRI scans, displayed absorption in the right maxillary sinus. Surgical excision of the lesion confirmed it to be a central giant cell granuloma. Results: Following surgery and without receiving any other treatment, the patient's phosphorus levels and clinical condition improved compared to before the surgical treatment. Subsequently, the symptoms of muscle weakness and skeletal pain significantly diminished, and the patient regained the ability to move. Conclusion: Tumor enucleation was conducted, and the pathological examination of the maxillary sinus lesion unveiled a central Giant cell granuloma. The patient had clinical and laboratory improvement after surgery. This finding confirmed our diagnosis of a paraneoplastic hypophosphatemia associated with a giant cell granuloma.

Anticancer immunotherapies with a dendritic Cell (DC) basis are becoming more popular. However, it has been suggested that the tumor's immunosuppressive mechanisms, such as inhibitory immunological checkpoint molecules, reduce the effectiveness of anticancer immunogenicity mediated by DC. Thus, overcoming immune checkpoints and inducing effective antigen-specific T-cell responses uniquely produced with malignant cells represent the key challenges. Among the inhibitory immune checkpoints, DCs' ability to mature and present antigens is decreased by CTLA-4 expression. Consequently, we hypothesized that by expressing CTLA-4 cells on DCs, the T cells' activation against tumor antigens would be suppressed when confronted with these antigens presented by DCs. In this research, by loading cell lysate of breast cancer (BC) on DCs and the other hand by inhibiting the induction of CTLA-4 using small interfering RNA (siRNA), we assessed the functional activities and phenotypes of DCs, and also the responses associated with T-cells following co-culture DC/T cell. Our research has shown that the suppression of CTLA-4 enhanced the stimulating capabilities of DCs. Additionally, CTLA-4-suppressed BC cell lysate-loaded DCs produced more IL-4 and IFN-ϒ and increased T cell induction in contrast to DCs without CTLA-4 suppression. Together, our data point to CTLA-4-suppressed DCs loaded with BC cell lysate as a potentially effective treatment method. However, further research is required before employing this method in therapeutic contexts.

Defects in Laser Powder Bed Fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. Experimental in-situ monitoring of the three-dimensional melt pool physical fields is challenging, due to the short length and time scales involved in the process. Multi-physics simulation methods can describe the three-dimensional dynamics of the melt pool, but are computationally expensive at the mesh refinement required for accurate predictions of complex effects. Therefore, we develop a generative deep learning model based on the probabilistic diffusion framework to map low-fidelity simulation information to the high-fidelity counterpart. By doing so, we bypass the computational expense of conducting multiple high-fidelity simulations for analysis by upscaling lightweight coarse mesh simulations. We demonstrate the preservation of key metrics of the melting process between the ground truth simulation data and the diffusion model output, such as the temperature field, the melt pool dimensions and the variability of the keyhole vapor cavity. We predict the melt pool depth within 3 μm based on low-fidelity input data 4× coarser than the high-fidelity simulations, reducing analysis time by two orders of magnitude.