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Background:. Following the repair of a mixed peripheral nerve, functional recovery requires successful nerve regeneration across the repair site and, eventually, reinnervation of distal targets. Reliably determining a failing nerve repair so that revision may be performed before irreversible muscle atrophy remains a challenge in peripheral nerve surgery. This study aimed to ascertain whether any commonly used clinical examination tests during surveillance after nerve repair can detect a failing repair and prompt earlier salvage intervention. Methods:. A prospective observational cohort study was performed to evaluate commonly used clinical determinants of neuron regeneration that may provide early surrogate recovery measures. Sequential cutaneous thermography was used to identify temperature differences between denervated and normal skin in the hand operated on, with the contralateral hand as a control. Results:. Six out of nine patients completed between 6 and 18 months of follow-up. Tinel sign progression was observed in all subjects. Tinel progression rate was associated with motor and sensory Medical Research Council grade. The delta temperature was calculated to document the size and direction of any temperature differentials in the hand detected by thermography, but we did not have sufficient data to calculate any correlations with motor and sensory Medical Research Council grade. Conclusions:. Specifically, the progression of Tinel sign is associated with recovery measured by progression of the British Medical Research Council motor and sensory grades. The use of thermographic imaging demonstrates that there is a difference in temperature between an injured and noninjured nerve. Future studies could investigate to what extent thermographic imaging predicts final nerve repair outcomes.

Abstract Personalized medicine has revolutionized approaches to treatment in the field of lung cancer by enabling therapies to be specific to each patient. However, physicians encounter an immense number of challenges in providing the optimal treatment regimen for the individual given the sheer complexity of clinical aspects such as tumor molecular profile, tumor microenvironment, expected adverse events, acquired or inherent resistance mechanisms, the development of brain metastases, the limited availability of biomarkers and the choice of combination therapy. The integration of innovative next-generation technologies such as deep learning—a subset of machine learning—and radiomics has the potential to transform the field by supporting clinical decision making in cancer treatment and the delivery of precision therapies while integrating numerous clinical considerations. In this review, we present a brief explanation of the available technologies, the benefits of using these technologies in predicting immunotherapy response in lung cancer, and the expected future challenges in the context of precision medicine.

Abstract Purpose Previous research has demonstrated increased stiffness in the multifidus muscle compared to other paraspinal muscles at the fiber bundle level. We aimed to compare single fiber and fiber bundle passive mechanical properties of multifidus muscle: (1) in 40 patients undergoing primary versus revision surgery and (2) in muscle with mild versus severe fatty infiltration. Methods The degree of muscle fatty infiltration was graded using the patients' spine magnetic resonance images. Average single fiber and fiber bundle passive mechanical properties across three tests were compared between primary (N = 30) and revision (N = 10) surgery status, between mild and severe fatty infiltration levels, between sexes, and with age from passive stress–strain tests of excised multifidus muscle intraoperative biopsies. Results At the single fiber level, elastic modulus was unaffected by degree of fatty infiltration or surgery status. Female sex (p = 0.001) and younger age (p = 0.04) were associated with lower multifidus fiber elastic modulus. At the fiber bundle level, which includes connective tissue around fibers, severe fatty infiltration (p = 0.01) and younger age (p = 0.06) were associated with lower elastic modulus. Primary surgery also demonstrated a moderate, but non‐significant effect for lower elastic modulus (p = 0.10). Conclusions Our results demonstrate that female sex is the primary driver for reduced single fiber elastic modulus of the multifidus, while severity of fatty infiltration is the primary driver for reduced elastic modulus at the level of the fiber bundle in individuals with lumbar spine pathology.

In recent years, growing use of information technology (IT) and the big data revolution in agriculture have led many farms to adopt precision agriculture methods and to accumulate large amounts of data. Exploiting these data for effective decision support requires the ability to integrate data from various sources, to conveniently analyze the data, and to infer valuable insights. This paper presents a framework for integrating and analyzing agricultural data from various sources, which leverages cloud-computing, thereby contributing to the scalability, flexibility, affordability, and maintainability of the solution compared to existing solutions. The framework defines a functional infrastructure of cloud-based services that facilitate integration, analysis, and data visualization. These services can be either end-user applications or services intended as a platform for creating new services. To design the framework’s architecture, we applied a top-down and bottom-up approach. Based on the top-down analysis of information collected through interviews, questionnaires, and literature review, we defined an initial architecture of the framework. We then used this initial architecture to develop different applications, and based on the experience and insights gained and new requirements that were faced, the architecture was revised in an iterative process. We demonstrate the application of the framework through several use cases. Each use case represents different data integration requirements and is based on different services of the proposed framework.

BackgroundPatients use social media as an alternative information source, where they share information and provide social support. Although large amounts of health-related data are posted on Twitter and other social networking platforms each day, research using social media data to understand chronic conditions and patients’ lifestyles is limited. ObjectiveIn this study, we contributed to closing this gap by providing a framework for identifying patients with inflammatory bowel disease (IBD) on Twitter and learning from their personal experiences. We enabled the analysis of patients’ tweets by building a classifier of Twitter users that distinguishes patients from other entities. This study aimed to uncover the potential of using Twitter data to promote the well-being of patients with IBD by relying on the wisdom of the crowd to identify healthy lifestyles. We sought to leverage posts describing patients’ daily activities and their influence on their well-being to characterize lifestyle-related treatments. MethodsIn the first stage of the study, a machine learning method combining social network analysis and natural language processing was used to automatically classify users as patients or not. We considered 3 types of features: the user’s behavior on Twitter, the content of the user’s tweets, and the social structure of the user’s network. We compared the performances of several classification algorithms within 2 classification approaches. One classified each tweet and deduced the user’s class from their tweet-level classification. The other aggregated tweet-level features to user-level features and classified the users themselves. Different classification algorithms were examined and compared using 4 measures: precision, recall, F1 score, and the area under the receiver operating characteristic curve. In the second stage, a classifier from the first stage was used to collect patients' tweets describing the different lifestyles patients adopt to deal with their disease. Using IBM Watson Service for entity sentiment analysis, we calculated the average sentiment of 420 lifestyle-related words that patients with IBD use when describing their daily routine. ResultsBoth classification approaches showed promising results. Although the precision rates were slightly higher for the tweet-level approach, the recall and area under the receiver operating characteristic curve of the user-level approach were significantly better. Sentiment analysis of tweets written by patients with IBD identified frequently mentioned lifestyles and their influence on patients’ well-being. The findings reinforced what is known about suitable nutrition for IBD as several foods known to cause inflammation were pointed out in negative sentiment, whereas relaxing activities and anti-inflammatory foods surfaced in a positive context. ConclusionsThis study suggests a pipeline for identifying patients with IBD on Twitter and collecting their tweets to analyze the experimental knowledge they share. These methods can be adapted to other diseases and enhance medical research on chronic conditions.

AIM: To evaluate intraocular pressure (IOP) measurements and fluctuations using the iCare ONE rebound tonometer (RT-ONE), during home monitoring, in diagnosed and suspected glaucoma patients. METHODS: A retrospective case series of consecutive patients with known glaucoma or glaucoma suspects who were followed-up and treated between January 2016 and January 2017. The study included 80 eyes of 40 patients with a mean age of 59.1±14.6y (range, 24-78). All patients have undergone 4-5d of IOP home monitoring with RT-ONE at morning, noon, afternoon, and night time. RESULTS: Baseline mean IOP, as measured in the clinic (8 a.m.-12 p.m.), was 17.4±5.1 mm Hg, compared to RT-ONE home monitoring mean IOP of 15.6±4.1 mm Hg (P=0.002). Mean IOP was significantly lower at noon, afternoon and night times compared to clinic measured IOP and morning measurements (P=0.005). IOP peak measured during home monitoring was significantly higher compared to the clinic measured IOP (21.3±5.6 mm Hg and 17.4±5.1 mm Hg, P

We describe a case of Behçet’s disease (BD) in a young child that presented with recurrent neuroretinitis and developed retinal lesions during follow-up. A 4.5-year-old girl presented with fever of 39.5°C, erythema nodosum in her legs, bilateral knee arthritis, and perineum aphthae. On ocular examination, visual acuity was 20/25 in both eyes. Right eye examination was normal and the left eye (LE) showed mild anterior and intermediate uveitis, normal optic disc, and a macular star appearance. Laboratory workup demonstrated elevated C-reactive protein levels, a normal abdominal ultrasound, and a normal colonoscopy. The patient was diagnosed with BD. One month post initial presentation, the patient presented with visual acuity of finger counting in the LE with significant anterior uveitis, mild intermediate uveitis, and recurrent neuroretinitis. Under treatment of IV methylprednisolone, oral betamethasone, infliximab, and colchicine, a complete systemic remission was noticed, and uveitis became quiescent. On last examination, 4.5 years post first presentation, visual acuity was 20/25 in both eyes and the LE demonstrated a remnant of a juxtafoveal retinal scar. To the best of our knowledge, this is the first case of neuroretinitis presenting as a manifestation of pediatric BD. Ophthalmologists should be aware of these unique manifestations of ocular BD.

Abstract Background To describe the presence of epiretinal proliferation in eyes with various retinal and vitreoretinal interface conditions. Methods Consecutive patients seen at the Stein Eye Institute, by one retina specialist, from December 2018 to March 2019, and demonstrating epiretinal proliferation on optical coherence tomography (OCT) were enrolled in this cross-sectional study. Included patients were divided into two groups: vitreoretinal interface pathologies group or retinal diseases group. Presence of epiretinal proliferation and its localization within the 9 macular sectors, as defined by the Early Treatment Diabetic Retinopathy Study (ETDRS), were assessed on OCT. Results 77 eyes from 69 patients demonstrated epiretinal proliferation on OCT. The most frequently involved ETDRS sector was the 1-mm central subfield, followed by inner temporal and inner nasal sectors. Localization of epiretinal proliferation correlated with the presence of any retinal abnormalities in the same quadrant (r = 0.962; P

This article examines in a preliminary fashion the potential connections between the usage of Gjerdingen's (1988, 2007) skeletal galant schemata, the heyday of the major mode during the period 1750-1799 (Albrecht & Huron, 2014; Horn & Huron, 2015), and the rare intervals of the diatonic set (Browne, 1981). I discuss the relations between the rarity of the tritone and semitone in the diatonic template and in musical usage (Huron 2006, 2008; David Temperley, personal communication, 2017). I hypothesize that the skeletal usage of schemata emphasizes rare intervals (tritone and semitone) respective to their common counterparts. Though this is predominantly an armchair, speculative inquiry, a preliminary pilot analysis of a small expert-annotated corpus from Gjerdingen (2007) provides tentative support for the hypothesis that the skeletal usage of schemata overemphasizes vertical tritones, but not melodic semitones. The prevalence of skeletal tritones in the schemata abstracted by Gjerdingen suggests that the process of abstraction is associated with finding unambiguous cues for a local tonal context. While the present article relies on Gjerdingen's expert analytical annotations of a small corpus and extraction of a contrapuntal skeleton, I conclude by offering hypotheses for future testing regarding the increased prevalence and salience of tritones on the musical surface in the period 1750-1799, a subset of common-practice tonality.

AIM: To evaluate the mechanism of which brimonidine tartrate 0.15% causes clinical hypersensitivity. METHODS: A prospective case-control study comparing 8 glaucoma patients with clinical hypersensitivity to brimonidine to a control group consisting 13 healthy volunteers. Blood samples were stimulated with brimonidine 0.15%, timolol 0.5% or brimonidine tartrate/timolol maleate 0.2%/0.5%. Premixed antibodies (CD63/FITC and aIgE/PE) were added for direct staining and whole-blood samples were lysed, fixed and analyzed by a flow cytometer. The basophil population was defined by high IgE cell expression. Degranulation was identified by the expression of the activation molecule CD63. RESULTS: Basophil activation was not significant when comparing percent of activated basophils of patients and healthy controls after exposure to brimonidine (2.58%, 2.45%, respectively, P=0.72). There was a significant suppression of basophil activation when a combination of brimonidine-timolol (0.87%) was compared to timolol (2.27%; P=0.012) and to brimonidine alone (2.58%; P=0.017). CONCLUSION: The results of our study do not support the hypothesis that brimonidine induces an immediate allergic reaction. Basophil activation was suppressed by the presence of β-blockers in patients hypersensitive to brimonidine and in healthy individuals. This finding indicates that timolol suppress brimonidine drug reaction by a different mechanism.

Detecting malicious activities in cyber systems is a major challenge of cybersecurity service providers. Due to the large amount of network traffic, it is often likened to finding a needle in a haystack. Domain name system (DNS) is one of the fundamental protocols of the internet, and therefore it can give a broad view of those malicious activities, which abuse it and leave fingerprints as part of their attack vector. In this collaborative research between Ben-Gurion University, and IBM, a significant performance improvement was achieved in detecting malicious domains as compared to the state-of-the-art software solutions. Specifically, we establish a novel algorithm to detect malicious domains in large-scale DNS traffic, named Resource-Efficient Malicious Domain Detector (REMaDD), with the following desired properties. First, the algorithm does not require prior knowledge on historical malicious activities in its real-time operations. Second, the development used real live streaming data from The Inter-University Computation Center (IUCC), and operated on real-time IBM system. The algorithm is highly computational efficient and satisfies real-time requirements in terms of running time and computational complexity. REMaDD demonstrated strong performance in terms of both detection accuracy and computational efficiency as compared to existing algorithms. Specifically, experimental results on IBM production environment demonstrated that REMaDD achieved 89.4% Precision score, and 82.9% Recall score. By contrast, the DomainObserver, and LSTM.MI algorithms achieved only 76.7%, 67.2% Precision score, and 81.7%, 75.3% Recall score, respectively.

Today, cyber attacks are constantly evolving and changing, which makes them harder to detect. In particular, detecting attacks in large-scale networks is very challenging because they require high detection rates under real-time resource constraints. In this paper, we focus on detecting infected Internet of Things (IoT) hosts from domain name system (DNS) traffic data. IoT hosts, such as streaming cameras, printers, air conditioners, are hard to protect, unlike PCs and servers. Enterprises are often unaware of the devices which are connected to the network, their types, makes, and vulnerabilities. Since IoT hosts make use of the DNS protocol, analyzing DNS data can give a broad view of malicious activities, because they abuse the DNS protocol and leave fingerprints as part of their attack vector. In this collaborative research between Ben-Gurion University, and IBM, we establish a novel algorithm to detect infected IoT hosts in large-scale DNS traffic, named Anomaly and Reputation Based Algorithm (ARBA). Its novelty resides in developing a framework that combines host classification and domain reputation in a real-time production environment. ARBA is highly computational efficient and meets real-time requirements in terms of run time and computational complexity. By contrast to existing algorithms, it does not require a massive traffic volume for training, which is of significant interest in detecting infected hosts in real-time. The research was conducted on real live streaming data from IBM internal network traffic, and confirm the algorithm's strong performance in a real-time production environment.

This article examines the social acceptability and governance of emotional artificial intelligence (emotional AI) in children’s toys and other child-oriented devices. To explore this, it conducts interviews with stakeholders with a professional interest in emotional AI, toys, children and policy to consider implications of the usage of emotional AI in children’s toys and services. It also conducts a demographically representative UK national survey to ascertain parental perspectives on networked toys that utilise data about emotions. The article highlights disquiet about the evolution of generational unfairness , that encompasses injustices regarding the datafication of childhood, manipulation, parental vulnerability, synthetic personalities, child and parental media literacy, and need for improved governance. It concludes with practical recommendations for regulators and the toy industry.

Purpose. The purpose of this study is to find prognostic factors associated with low visual acuity in patients experiencing vitreous loss during cataract surgery. Methods. A retrospective, noncomparative, interventional, case study of patients experiencing vitreous loss during cataract surgery. Data collected included demographics, best corrected visual acuity (BCVA), axial length (AL), presence of ocular comorbidity affecting central vision, timing of intraocular lens (IOL) implantation, position of the implanted lens, and the presence of corneal sutures. Low visual outcome was defined as BCVA 70 years, gender, axial length, degree of surgeon, corneal suturing, and anterior chamber lens implantation were not found to have significant associations with low visual outcomes (P>0.05). Conclusions. Low visual outcome after vitreous loss during cataract surgery was associated with ocular comorbidities, secondary IOL implantation, development of cystoid macular edema, and additional surgical complications.

The molecular regulation of induction and development of reproductive organs is well established in angiosperms, while it is slowly accumulating in gymnosperms. Here, we conducted comparative transcriptomic profiles at different stages of male and female cone development in Pinus halepensis. Our aim was to reveal transcription factor encoding genes involved in reproductive induction and development. For accurate developmental stage identification, histological analysis preceded the molecular analysis. The flowering induction genes FT/TFL were expressed mainly at the late developmental stages of the male cone, suggesting involvement in vegetative bud dormancy instead of flowering induction. The male cone development was associated with the expression of the C-class PhMADS2, and the B-class genes PhDAL11 and PhDAL13, while the female cone development was associated with the expression of the C-class MADS1 and DAL14 genes. This study adds valuable knowledge to the profile of transcription factors and MADS-box genes regulating cone development in gymnosperms.

Introduction Hydroxychloroquine (HCQ) emerged early in the course of the coronavirus disease 2019 (COVID-19) pandemic as a possible drug with potential therapeutic and prophylactic benefits. It was quickly adopted in China, Europe, and the USA. We systematically reviewed the existing clinical evidence of HCQ use for the prevention and treatment of COVID-19. Methods We screened for clinical studies describing HCQ administration to treat or prevent COVID-19 in PubMed. We included randomized controlled trials (RCTs), non-randomized comparative cohorts, and case series studies that had all undergone peer review. Results A total of 623 studies were screened; 17 studies evaluating HCQ treatment were included. A total of 13 were observational studies, and 4 were RCTs. In terms of effect on mortality rates, observational studies provided conflicting results. As a whole, RCTs, including one large British RCT that has not yet been published, showed no significant effect of HCQ on mortality rates, clinical cure, and virologic response. The use of HCQ as a post-exposure prophylactic agent was found to be ineffective in one RCT. Conclusion There is no evidence supporting HCQ for prophylaxis or treatment of COVID-19. Many observational trials were methodologically flawed. Scientific efforts have been disappointingly fragmented, and well-conducted trials have only recently been completed, more than 7 months and 600,000 deaths into the pandemic.