# Bar Ilan University

• Ramat Gan, Israel
Recent publications
Abstract Purpose To present the response of the Israel National Transplantation Center (NTC) to the evolving challenge of COVID-19, the impact on deceased organ donation and living organ kidney donation during 2020, and resultant policy and ethical implications. Methods Data collected included (i) for deceased donors, the total number of potential organ donors, if hospitalized in ICU or general ward, cause of death, number of family authorizations and refusals, number of actual donors, number of organs transplanted/donor and total number of transplants performed; (ii) for living-kidney-donors (related or altruistic), the number of procedures performed; and (iii) the number of patients registered on the national organ waiting-list. Results Following the first case (February 2020), deceased organ donation continued uninterrupted. The total number of potential donors was similar to 2019 (181 vs. 189). However, the number of families approached for donation decreased significantly (P = 0.02). This may be attributed to COVID-19-imposed limitations including fewer brain death determinations due to limited possibilities for face-to-face donor coordinator-donor family interactions providing emotional support and visual explanations of the medical situation. Fewer donors were admitted to ICU (P = 0.1) and the number of organs retrieved/donor decreased (3.8/donor to 3.4/donor). The overall result was a decrease of 24.2% in the number of transplant procedures (306 vs. 232). Living kidney donation, initially halted, resumed in May and the total number of procedures increased compared to 2019 due to a significant increase in altruistic donations (P
Introduction Hyperbaric oxygen therapy (HBOT) has been used to increase endurance performance but has yet to be evaluated in placebo-controlled clinical trials. The current study aimed to evaluate the effect of an intermittent HBOT protocol on maximal physical performance and mitochondrial function in middle-aged master athletes. Methods A double-blind, randomized, placebo-controlled study on 37 healthy middle-aged (40–50) master athletes was performed between 2018 and 2020. The subjects were exposed to 40 repeated sessions of either HBOT [two absolute atmospheres (ATA), breathing 100% oxygen for 1 h] or SHAM (1.02ATA, breathing air for 1 h). Results Out of 37 athletes, 16 HBOT and 15 SHAM allocated athletes were included in the final analysis. Following HBOT, there was a significant increase in the maximal oxygen consumption (VO2Max) (p = 0.010, effect size(es) = 0.989) and in the oxygen consumption measured at the anaerobic threshold (VO2AT)(es = 0.837) compared to the SHAM group. Following HBOT, there were significant increases in both maximal oxygen phosphorylation capacity (es = 1.085, p = 0.04), maximal uncoupled capacity (es = 0.956, p = 0.02) and mitochondrial mass marker MTG (p = 0.0002) compared to the SHAM sessions. Conclusion HBOT enhances physical performance in healthy middle-age master athletes, including VO2max, power and VO2AT. The mechanisms may be related to significant improvements in mitochondrial respiration and increased mitochondrial mass. Trial Registration ClinicalTrials.gov Identifier: https://clinicaltrials.gov/ct2/show/NCT03524989 (May 15, 2018).
Neuropeptides act mostly on a class of G-protein coupled receptors, and play a fundamental role in the functions of neural circuits underlying behaviors. However, physiological functions of some neuropeptide receptors are poorly understood. Here, we used the molluscan model system Aplysia and microinjected the exogenous neuropeptide receptor apATRPR ( Aplysia allatotropin-related peptide receptor) with an expression vector (pNEX3) into Aplysia neurons that did not express the receptor endogenously. Physiological experiments demonstrated that apATRPR could mediate the excitability increase induced by its ligand, apATRP ( Aplysia allatotropin-related peptide), in the Aplysia neurons that now express the receptor. This study provides a definitive evidence for a physiological function of a neuropeptide receptor in molluscan animals.
Background Mental health contact centers (also known as Hotlines) offer crisis intervention and counselling by phone calls and online chats. These mental health helplines have shown great success in improving the mental state of the callers, and are increasingly becoming popular in Israel and worldwide. Unfortunately, our knowledge about how to conduct successful routing of callers to counselling agents has been limited due to lack of large-scale data with labeled outcomes of the interactions. To date, many of these contact centers are overwhelmed by chat requests and operate in a simple first-come-first-serve (FCFS) scheduling policy which, combined, may lead to many callers receiving suboptimal counselling or abandoning the service before being treated. In this work our goal is to improve the efficiency of mental health contact centers by using a novel machine-learning based routing policy. Methods We present a large-scale machine learning-based analysis of real-world data from the online contact center of ERAN, the Israeli Association for Emotional First Aid. The data includes over 35,000 conversations over a 2-years period. Based on this analysis, we present a novel call routing method, that integrates advanced AI-techniques including the Monte Carlo tree search algorithm. We conducted an experiment that included various realistic simulations of incoming calls to contact centers, based on data from ERAN. We divided the simulations into two common settings: standard call flow and heavy call flow. In order to establish a baseline, we compared our proposed solution to two baseline methods: (1) The FCFS method; and (2) a greedy solution based on machine learning predictions. Our comparison focuses on two metrics - the number of calls served and the average feedback of the callers (i.e., quality of the chats). Results In the preliminary analysis, we identify indicative features that significantly contribute to the effectiveness of a conversation and demonstrate high accuracy in predicting the expected duration and the callers’ feedback. In the routing methods evaluation, we find that in heavy call flow settings, our proposed method significantly outperforms the other methods in both the quantity of served calls and average feedback. Most notably, we find that in the heavy call flow settings, our method improves the average feedback by 24% compared to FCFS and by 4% compared to the greedy solution. Regarding the standard-flow setting, we find that our proposed method significantly outperforms the FCFS method in the callers’ average feedback with a 12% improvement. However, in this setting, we did not find a significant difference between all methods in the quantity of served-calls and no significant difference was found between our proposed method and the greedy solution. Conclusion The proposed routing policy has the potential to significantly improve the performance of mental health contact centers, especially in peak hours. Leveraging artificial intelligence techniques, such as machine learning algorithms, combined with real-world data can bring about a significant and necessary leap forward in the way mental health hotlines operate and consequently reduce the burden of mental illnesses on health systems. However, implementation and evaluation in an operational contact center is necessary in order to verify that the results replicate in practice.
Distinctiveness theory suggests that numeric rarity is correlated with stronger homophily. In this paper, we examine this theory by studying gender homophily in social networks of older adults. We document subjective social networks in multiple long term care settings for older adults over several time points. Homophily for each gender is estimated using exponential random graph models. We find evidence for positive homophily across all networks, and show that it is correlated to the magnitude of the female majority or male minority. Our findings empirically verify distinctiveness theory and could improve interventions to promote tie formation in social networks.
We study a new type of symmetry for the hydrogen atom involving algebraic families of groups parametrized by the energy value in the time-independent Schrödinger equation. We construct an algebraic family of Harish-Chandra modules from the solutions of the Schrödinger equation, and we characterize this family. We show that the subspaces of physical states may be obtained from our algebraic family using a Jantzen filtration, and we relate our algebraic methods with spectral theory and scattering theory using the limiting absorption principle.
Purpose Non-melanoma skin cancer (NMSC) is the most frequent keratinocyte-origin skin tumor. It is confirmed that dermoscopy of NMSC confers a diagnostic advantage as compared to visual face-to-face assessment. COVID-19 restrictions diagnostics by telemedicine photos, which are analogous to visual inspection, displaced part of in-person visits. This study evaluated by a dual convolutional neural network (CNN) performance metrics in dermoscopic (DI) versus smartphone-captured images (SI) and tested if artificial intelligence narrows the proclaimed gap in diagnostic accuracy. Methods A CNN that receives a raw image and predicts malignancy, overlaid by a second independent CNN which processes a sonification (image-to-sound mapping) of the original image, were combined into a unified malignancy classifier. All images were histopathology-verified in a comparison between NMSC and benign skin lesions excised as suspected NMSCs. Study criteria outcomes were sensitivity and specificity for the unified output. Results Images acquired by DI ( n = 132 NMSC, n = 33 benign) were compared to SI ( n = 170 NMSC, n = 28 benign). DI and SI analysis metrics resulted in an area under the curve (AUC) of the receiver operator characteristic curve of 0.911 and 0.821, respectively. Accuracy was increased by DI (0.88; CI 81.9–92.4) as compared to SI (0.75; CI 68.1–80.6, p < 0.005). Sensitivity of DI was higher than SI (95.3%, CI 90.4–98.3 vs 75.3%, CI 68.1–81.6, p < 0.001), but not specificity ( p = NS). Conclusion Telemedicine use of smartphone images might result in a substantial decrease in diagnostic performance as compared to dermoscopy, which needs to be considered by both healthcare providers and patients.
In this paper, we introduce the Hausdorff operator associated with the Opdam--Cherednik transform and study the boundedness of this operator in various Lebesgue spaces. In particular, we prove the boundedness of the Hausdorff operator in Lebesgue spaces, in grand Lebesgue spaces, and in quasi-Banach spaces that are associated with the Opdam--Cherednik transform. Also, we give necessary and sufficient conditions for the boundedness of the Hausdorff operator in these spaces.
Let f be a normalized Hecke–Maass cusp form of weight zero for the group SL2(Z)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$SL_2({\mathbb {Z}})$$\end{document}. This article presents several quantitative results about the distribution of Hecke eigenvalues of f. Applications to the Ω±\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Omega _{\pm }$$\end{document}-results for the Hecke eigenvalues of f and its symmetric square sym2(f)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2(f)$$\end{document} are also given.
As new variants of SARS-CoV-2 continue to emerge, it is important to assess the cross-neutralizing capabilities of antibodies naturally elicited during wild type SARS-CoV-2 infection. In the present study, we evaluate the activity of nine anti-SARS-CoV-2 monoclonal antibodies (mAbs), previously isolated from convalescent donors infected with the Wuhan-Hu-1 strain, against the SARS-CoV-2 variants of concern (VOC) Alpha, Beta, Gamma, Delta and Omicron. By testing an array of mutated spike receptor binding domain (RBD) proteins, cell-expressed spike proteins from VOCs, and neutralization of SARS-CoV-2 VOCs as pseudoviruses, or as the authentic viruses in culture, we show that mAbs directed against the ACE2 binding site (ACE2bs) are more sensitive to viral evolution compared to anti-RBD non-ACE2bs mAbs, two of which retain their potency against all VOCs tested. At the second part of our study, we reveal the neutralization mechanisms at high molecular resolution of two anti-SARS-CoV-2 neutralizing mAbs by structural characterization. We solve the structures of the Delta-neutralizing ACE2bs mAb TAU-2303 with the SARS-CoV-2 spike trimer and RBD at 4.5 Å and 2.42 Å resolutions, respectively, revealing a similar mode of binding to that between the RBD and ACE2. Furthermore, we provide five additional structures (at resolutions of 4.7 Å, 7.3 Å, 6.4 Å, 3.3 Å, and 6.1 Å) of a second antibody, TAU-2212, complexed with the SARS-CoV-2 spike trimer. TAU-2212 binds an exclusively quaternary epitope, and exhibits a unique, flexible mode of neutralization that involves transitioning between five different conformations, with both arms of the antibody recruited for cross linking intra- and inter-spike RBD subunits. Our study provides additional mechanistic understanding about how antibodies neutralize SARS-CoV-2 and its emerging variants and provides insights on the likelihood of reinfections.
Background While pharmacological treatments for positive symptoms of schizophrenia are widely used, their beneficial effect on negative symptoms, particularly social impairment, is insufficiently studied. Therefore, there is an increasing interest in preclinical research of potentially beneficial treatments, with mixed results. The current review aims to evaluate the efficacy of available treatments for social deficits in different animal models of schizophrenia. Study Design A systematic literature search generated 145 outcomes for the measures “total time” and “number” of social interactions. Standardized mean differences (SMD) and 95% confidence interval (CI) were calculated, and heterogeneity was tested using Q statistics in a random-effect meta-analytic model. Given the vast heterogeneity in effect sizes, the animal model, treatment group, and sample size were all examined as potential moderators. Study Results The results showed that in almost all models, treatment significantly improved social deficit (total time: SMD = 1.24; number: SMD = 1.1). The moderator analyses discovered significant subgroup differences across models and treatment subgroups. Perinatal and adult pharmacological models showed the most substantial influence of treatments on social deficits, reflecting relative pharmacological validity. Furthermore, atypical antipsychotic drugs had the highest SMD within each model subgroup. Conclusions Our findings indicate that the improvement in social interaction behaviors is dependent on the animal model and treatment family used. Implications for the preclinical and clinical fields are discussed.
We show that a Bose-Einstein condensate consisting of dark excitons forms in GaAs coupled quantum wells at low temperatures. We find that the condensate extends over hundreds of micrometers, well beyond the optical excitation region, and is limited only by the boundaries of the mesa. We show that the condensate density is determined by spin-flipping collisions among the excitons, which convert dark excitons into bright ones. The suppression of this process at low-temperature yields a density buildup manifested as a temperature-dependent blueshift of the exciton emission line. Measurements under an in-plane magnetic field allow us to preferentially modify the bright exciton density and determine their role in the system dynamics. We find that their interaction with the condensate leads to its depletion. We present a simple rate-equations model, which well reproduces the observed temperature, power, and magnetic-field dependence of the exciton density.
Financial exploitation of older adults bears detrimental physical and psychological consequences. However, risk factors of financial exploitation vulnerability (FEV) remain elusive. In line with a growing awareness of the importance of subjective perceptions of the aging process for older adults' functioning and well-being, this study examined the connection between subjective age (feeling younger/older than one's chronological age) and FEV, and the moderating effect of social support on this connection. Data were collected from a convenience sample of 137 Israeli older adults (age range 60-89, M = 69.90, SD = 6.85), who completed scales of FEV, subjective age, and social support, as well as relevant socio-demographic information. Older subjective age was associated with increased FEV when social support was low, but not when social support was high. Results are discussed in line with Socio-Emotional Selectivity Theory and provide initial information pertaining to the relevance of subjective age perceptions to FEV in older adults.
Introduction Work overload in hospitals enforced reducing shifts length of physicians in many countries over the last decade. In Israel, the current shift standard is of 26 hours, however, there is a residents’ struggle alongside a governmental intent to short the shifts to 16 hour. We aim to evaluate residents and interns support and preferences regarding shortening shifts and their ramifications to quality of life and residency programs. Methods A structured questionnaire was distributed to all resident and interns in a single center. We evaluated their current quality of residency and life, their support in the shorter shifts model, offering alternative program components such as reduced pay, longer residency or replacement in order to allow rest. We compared those who support the new model to those who objected to identify common characteristics to draw a resident profile for acceptance of change. Results Overall, 151 physicians answer the questionnaire. 70.2% support the shorter shifts model. Residents above 35 years old and those reaching completion of residency, significantly less support the shortening shifts model. No other demographic nor professional parameters were different between the supporters and non-supporters. Option of reduced pay or longer residency dramatically reduced the support rate to less than 30% and 20%, respectively. Replacement by other physician (resident or senior physician) in order to allow rest was supported by only 40%. Conclusion Residents’ standpoints regarding a desirable change are crucial to plan a successful implementation. A national survey is required before a new model is introduced, to achieve an optimal transparent efficient process.
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• Department of Chemistry
• Department of Mathematics
• Faculty of Life Sciences
• Department of Psychology
• School of Communication
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