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A sustainable transdisciplinary research network was established through a research practice partnership (RPP) between an urban farm, faculty and staff from a Historically Black College (HBC), and researchers at a medium-sized private university. We investigate student-worker resilience at this urban farm situated on the HBC campus, drawing on literature that explores tensions between informal learning environments and formal spaces, equitable food systems and farming systems, as well as the resilience of farm work, and which is grounded critical food systems education theory. Utilizing a participatory design approach, we conducted semi-structured interviews and deductively analyzed the data. The research questions guiding this paper are: (1) What topics of discussion are most important to the student-workers and staff working on an urban farm, (2) How do student-workers and college staff members perceive and experience resilience on an urban farm? We found that what participants on an urban farm discuss, relating to their experiences, include (1) how participants were eager to "engage" with the local community, (2) how participants demonstrated "resilience" while working on the urban farm, (3) how "power dynamics" played a pivotal role informing the direction of the urban farm, (4) how participants consider community "access" to healthy foods an important mission for the farm, (5) how the college acted as a power wielding entity, perpetuating its "privilege" over the farmers and the farm operations. These findings have the potential to enable community organizing spaces to promote resilience for their volunteers and workers, and for urban farms top partner with their community to promote the mission of increasing access to healthy and affordable food options.

This study aims to determine to what extent preschool teachers include traditional Turkish music within the scope of music activities and what is the effect of this music on children. The study which was designed as qualitative research. A total of 50 preschool teachers, 92% of whom are female (n=46) and 8% are male (n=4), constitute the participants of the study. In the study, "semistructured interview form" prepared by the researchers was used as a data collection tool. The obtained data were analyzed according to thematic analysis technique. The research findings were analyzed under four themes: "Likes and Use", "Teaching", "Developmental Contributions" and "Challenges and Solutions". As a result of the research, it was found that preschool teachers partially included traditional Turkish music in their music activities, they did not receive training on teaching traditional Turkish music during their undergraduate education, children had various difficulties in vocalizing traditional Turkish music, and traditional Turkish music had development areas such as cognitive, psychomotor and language skills on children. It has been concluded that it has positive effects on the development of cultural memory and cultural transmission.

Given the importance of aerosols and clouds and their interactions in the climate system, it is imperative that the global Earth system models accurately represent processes associated with them. This is an important prerequisite if we are to narrow the uncertainties in future climate projections. In practice, this means that continuous model evaluations and improvements grounded in observations are necessary. Numerous studies in the past few decades have shown both the usability and the limitations of utilizing satellite-based observations in understanding and evaluating aerosol–cloud interactions, particularly under varying meteorological and satellite sensor sensitivity paradigms. Furthermore, the vast range of spatio-temporal scales at which aerosol and cloud processes occur adds another dimension to the challenges faced when evaluating climate models. In this context, the aim of this study is two-fold. (1) We evaluate the most recent, significant changes in the representation of aerosol and cloud processes implemented in the EC-Earth3-AerChem model in the framework of the EU project FORCeS compared with its previous CMIP6 version (Coupled Model Intercomparison Project Phase 6; https://pcmdi.llnl.gov/CMIP6/, last access: 13 February 2019). We focus particularly on evaluating cloud physical properties and radiative effects, wherever possible, using a satellite simulator. We report on the overall improvements in the EC-Earth3-AerChem model. In particular, the strong warm bias chronically seen over the Southern Ocean is reduced significantly. (2) A statistical, maximum covariance analysis is carried out between aerosol optical depth (AOD) and cloud droplet (CD) effective radius based on the recent EC-Earth3-AerChem/FORCeS simulation to understand to what extent the Twomey effect can manifest itself in the larger spatio-temporal scales. We focus on the three oceanic low-level cloud regimes that are important due to their strong net cooling effect and where pollution outflow from the nearby continent is simultaneously pervasive. We report that the statistical covariability between AOD and CD effective radius is indeed dominantly visible even at the climate scale when the aerosol amount and composition are favourably preconditioned to allow for aerosol–cloud interactions. Despite this strong covariability, our analysis shows a strong cooling/warming in shortwave cloud radiative effects at the top of the atmosphere in our study regions associated with an increase/decrease in CD effective radius. This cooling/warming can be attributed to the increase/decrease in low cloud fraction, in line with previous observational studies.

Understanding executive functions (EFs) development is of high value to global developmental science. Recent calls for a more inclusive and equitable developmental science argue that tasks and questionnaires that are developed using only a subset of the population are not likely to be appropriate for EFs measurement in global contexts unless explicitly tested. Here, we examined a task commonly used to assess EFs in Western populations in a non-Western sample of Jordanian children. We used the Hearts and Flowers (HF) task to examine (a) its value for assessing EFs development in Jordanian children, and (b) whether task performance was associated with socioeconomic variables and parent report of academic achievement, internalizing, and externalizing behaviors measured with the Arabic Child Behavior Checklist. We report data from N = 93 5.5-8.5 year-old Jordanian children. We found the task to be valuable for distinguishing performance among EFs constructs (working memory, inhibitory control, cognitive flexibility) in this cohort. However, there were no age differences in EFs performance, nor any EFs-specific relationship to any of the parent-report measures of EFs-related constructs. Instead, EFs were related to paternal education and location of residence (Jordanian governorate). We discuss these findings in the context of the expansion of developmental science into global contexts and call for special consideration of measurement and generalizability biases in investigations with human subjects.

Purpose: This paper aims to explore the epistemic connections between three instructional coaches and a first-year in-service teacher during remote planning and debrief meetings. Prior evidence suggests that remote instructional coaching leads to better teaching practices and identifies the instructional coaching moves used to prompt teacher reflection. Design/methodology/approach: In this study, the authors utilized quantitative ethnography and epistemic network analysis (ENA) approaches to explore the epistemic frames of three remote university-based instructional coaches as they supported a first-year in-service teacher. Findings: Quantitative ENA findings shed light on the network connections between instructional coaches and teachers, as well as the epistemic frames observed during planning and debrief meetings. Additionally, the authors provide qualitative findings that complement and reinforce the quantitative results. Research limitations/implications: All data collection occurred via Zoom, and the class was in a hybrid modality, with some students attending class in person and some attending remotely via Zoom. This unique context could have impacted the epistemic connections surrounding technology and logistics. Practical implications: This study provides a practical codebook for use in future studies that explores instructional coaching. Findings from this study can be used to inform instructional coaching decisions. Originality/value: The ENA findings helped deepen the authors' understanding of how instructional coaches can support a first-year in-service teacher during planning and debrief meetings in several ways. Additionally, this study presents a unique context given the COVID-19 pandemic and the remote model of instructional coaching.

This article sheds light on criticism of the increasing degree of formalisation in collating and synthesising research findings in the systematic review format in education. A textual analysis of two systematic reviews produced by the Swedish Institute for Educational Research unpacks the significance of interaction between formalisation and professional judgement. The article also shows that there is a mismatch between the "front-stage" and "back-stage" of the review process. Interestingly, criticism is aimed at the ideal image of scholarly practice rather than the actual review process.

Anthropogenic aerosols play a major role in the Earth–atmosphere system by influencing the Earth's radiative budget and precipitation and consequently the climate. The perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF). In this work, the present-day shortwave (SW), longwave (LW), and total (i.e., SW plus LW) ERF of anthropogenic aerosols is quantified using two different sets of experiments with prescribed sea surface temperatures (SSTs) from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6): (a) time-slice pre-industrial perturbation simulations with fixed SSTs (piClim) and (b) transient historical simulations with time-evolving SSTs (histSST) over the historical period (1850–2014). ERF is decomposed into three components for both piClim and histSST experiments: (a) ERFARI, representing aerosol–radiation interactions; (b) ERFACI, accounting for aerosol–cloud interactions (including the semi-direct effect); and (c) ERFALB, which is due to temperature, humidity, and surface albedo changes caused by anthropogenic aerosols. We present spatial patterns at the top-of-atmosphere (TOA) and global weighted field means along with inter-model variability (1 standard deviation) for all SW, LW, and total ERF components (ERFARI, ERFACI, and ERFALB) and for every experiment used in this study. Moreover, the inter-model agreement and the robustness of our results are assessed using a comprehensive method as utilized in the IPCC Sixth Assessment Report. Based on piClim experiments, the total present-day (2014) ERF from anthropogenic aerosol and precursor emissions is estimated to be −1.11 ± 0.26 W m−2, mostly due to the large contribution of ERFACI to the global mean and to the inter-model variability. Based on the histSST experiments for the present-day period (1995–2014), similar results are derived, with a global mean total aerosol ERF of −1.28 ± 0.37 W m−2 and dominating contributions from ERFACI. The spatial patterns for total ERF and its components are similar in both the piClim and histSST experiments. Furthermore, implementing a novel approach to determine geographically the driving factor of ERF, we show that ERFACI dominates over the largest part of the Earth and that ERFALB dominates mainly over the poles, while ERFARI dominates over certain reflective surfaces. Analysis of the inter-model variability in total aerosol ERF shows that SW ERFACI is the main source of uncertainty predominantly over land regions with significant changes in aerosol optical depth (AOD), with eastern Asia contributing mostly to the inter-model spread of both ERFARI and ERFACI. The global spatial patterns of total ERF and its components from individual aerosol species, such as sulfates, organic carbon (OC), and black carbon (BC), are also calculated based on piClim experiments. The total ERF caused by sulfates (piClim-SO2) is estimated at −1.11 ± 0.31 W m−2, and the OC ERF (piClim-OC) is −0.35 ± 0.21 W m−2, while the ERF due to BC (piClim-BC) is 0.19 ± 0.18 W m−2. For sulfates and OC perturbation experiments, ERFACI dominates over the globe, whereas for BC perturbation experiments ERFARI dominates over land in the Northern Hemisphere and especially in the Arctic. Generally, sulfates dominate ERF spatial patterns, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere (NH), such as North America, Europe, and eastern and southern Asia. Our analysis of the temporal evolution of ERF over the historical period (1850–2014) reveals that ERFACI clearly dominates over ERFARI and ERFALB for driving the total ERF temporal evolution. Moreover, since the mid-1980s, total ERF has become less negative over eastern North America and western and central Europe, while over eastern and southern Asia there is a steady increase in ERF magnitude towards more negative values until 2014.

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to a lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by 14 CMIP6 models, including organic carbon (OC; available in 14 models), black carbon (BC; 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (−1.5 %) and MPI-ESM-1-2-HAM (−1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available component output, underestimate the total PM2.5 concentrations partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by −71.2 % to −37.8 % across the 14 models) and the smallest for BC (−47.9 % to −12.1 %). The multi-model mean (MMM) reproduces the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

Emergency remote and hybrid instructional approaches during the COVID-19 pandemic presented new challenges to science teachers, including how to incorporate authentic, hands-on, and collaborative learning experiences via Zoom™ instruction. Through a school-university partnership, a first-year middle school science teacher, an assistant professor, and two doctoral students collaborated to support student learning despite the constraints imposed by COVID-19. The partners worked together to develop and adapt a six-lesson, integrated science, technology, engineering, and mathematics (STEM) unit for use in a hybrid learning environment. In this article, we describe the unit, which focused on science concepts of force and motion through an engineering context related to helmet design. We highlight the key adaptations that were made to transition this unit to a hybrid format, including the assets brought by each partner. Finally, we discuss lessons learned and implications for teachers.

In this study, it is aimed to determine the effects of active learning activities on viola students' performance and motivation. One group pretest-posttest experimental design was used in the study. The study group consist of 10 students, 7 of them receiving Viola training within the scope of the Individual Instrument course at Gaziosmanpasa University Fine Arts Education Department Music Education Department and 3 students within the scope of Turkish and Western Music Instruments course at Tokat Fine Arts and Sports High School. During the eight-week practice, with the students in the study group, active learning-based activities which are prepared for the viola training were carried out with students in the study group. In the study, as a means of data collection, by adapting 'Exam Performance' dimension of 'Violin Lesson Performance Form' to the viola, the 'Motivation Scale' part of 'Motivated Strategies for Learning Questionnaire' were used. According to the results of the study, it was determined that the activities based on active learning increased viola performance success, and influenced the students' motivation for viola lesson positively.

This study seeks to investigate the marketing activities available through social media platforms that are reflected in the purchase intention of consumers in general. Further, it explores the joint mediation effect of both perceived value (PV) and social brand engagement (SBE) on SMM-PI connection. A convenience sample strategy was employed to gather data from 338 cosmetic product customers in Palestine through a structured online questionnaire survey. Subsequently, the data underwent examination using intelligent (PLS-SEM) analysis. According to the results of the study, there is a positive relationship between marketing activities through social media platforms on consumer’s beneficial impact on brand perception (PV), consumer engagement (SBE), and purchase intention (PI). Moreover, PV and SBE exert substantial direct beneficial impacts on PI. As for the intermediate effects, they were all effective, and the mediation impact of PV (Perceived Value) and SBE (Social Bonding Experiences) on the relation between SMM and PI is partially complimentary.

Agent-based simulations, especially those including communication, are complex to model and execute. To help researchers deal with this complexity and to encourage modular and maintainable research software, the Python-based framework mango (modular python agent framework) has been developed. The framework enables users to quickly implement software agents with different communication protocols and message codecs. Furthermore, mango provides various options for developing an integrated agent simulation. This includes a scheduler module, which can control the agents’ tasks, a (distributed) clock mechanism for time synchronization, and a specific simulation component, which can be coupled with other (co-)simulation software. These features are complemented by modular implementation patterns and a well-evaluated performance with the ability to simulate across multiple computing processes to ensure scalability.

The Coupled Model Intercomparison Project (CMIP) is one of the biggest international efforts aimed at better understanding the past, present, and future of climate changes in a multi-model context. A total of 21 model intercomparison projects (MIPs) were endorsed in its sixth phase (CMIP6), which included 190 different experiments that were used to simulate 40 000 years and produced around 40 PB of data in total. This paper presents the main findings obtained from the CPMIP (the Computational Performance Model Intercomparison Project), a collection of a common set of metrics, specifically designed for assessing climate model performance. These metrics were exclusively collected from the production runs of experiments used in CMIP6 and primarily from institutions within the IS-ENES3 consortium. The document presents the full set of CPMIP metrics per institution and experiment, including a detailed analysis and discussion of each of the measurements. During the analysis, we found a positive correlation between the core hours needed, the complexity of the models, and the resolution used. Likewise, we show that between 5 %–15 % of the execution cost is spent in the coupling between independent components, and it only gets worse by increasing the number of resources. From the data, it is clear that queue times have a great impact on the actual speed achieved and have a huge variability across different institutions, ranging from none to up to 78 % execution overhead. Furthermore, our evaluation shows that the estimated carbon footprint of running such big simulations within the IS-ENES3 consortium is 1692 t of CO2 equivalent. As a result of the collection, we contribute to the creation of a comprehensive database for future community reference, establishing a benchmark for evaluation and facilitating the multi-model, multi-platform comparisons crucial for understanding climate modelling performance. Given the diverse range of applications, configurations, and hardware utilised, further work is required for the standardisation and formulation of general rules. The paper concludes with recommendations for future exercises aimed at addressing the encountered challenges which will facilitate more collections of a similar nature.

Raynaud-Claes syndrome is rare condition characterized with intellectual disability and is caused by X-linked pathogenic variants in CLCN4 gene. Hemizygous missense variant NM_001830.4: c.1597G>A (p.V533M) was detected in a 6-year-old male followed up with intellectual disability, dysmorphism, and epileptic encephalopathy. The mother and one sister of the patient were also carrying the same variant. The clinical picture of the patient was significantly more severe, and the patient exhibited nonconvulsive status. Tonic status was observed with benzodiazepine treatment and the patient was successfully treated with a ketogenic diet. Many types of seizures can be seen in Raynaud-Claes syndrome, some of which can be life-threatening. CLCN4 variants can be investigated in patients who exhibit an increase in tonic seizures with benzodiazepine treatment. However, ketogenic dietary therapy as first-line treatment can be lifesaving in resistant epilepsy cases caused by the CLCN4 gene.

يهدف البحث إلى بيان حجية إثبات التزييف العميق تقنياً وفقهياً في أنظمة الذكاء الاصطناعي، إذ لا يزال كثير من الناس يخشى ضرر هذا التطور في الذكاء الاصطناعي ومحاكاة بصمة الصوت والصورة ونحو ذلك. ويحتوي البحث على مفهوم الذكاء الاصطناعي، ثم التفصيل في طريقة كشف التزييف العميق تقنياً، ثم حجية التزييف العميق فقهياً ، ثم النتيجة وهي: أن القرائن المرجحة تعتبر أحد طرق الإثبات المعتبرة في القضاء في الإسلام، و أن وسائل الإثبات غير محصورة بعدد معين، وبناءً عليه: فإن تلك المقاطع المرئية أو المسموعة والتي تم الكشف عليها من خلال أدوات التزييف العميق ولم يثبت تزييفها أحد القرائن التي تختلف في قوتها وضعفها، وذلك مما يقدره القاضي وخبراء الاختصاص معه، ويترتب على ذلك بحسب القرائن: إثبات حجية الحقوق، أو إسقاطها.

ABSTRACTDendritic cells (DCs) play a key role in the induction of the adaptive immune response. They capture antigens in peripheral tissues and prime naïve T lymphocytes, triggering the adaptive immune response. In the course of inflammatory processes DCs face stressful conditions including hypoxia, low pH and high concentrations of reactive oxygen species (ROS), among others. How DCs survive under these adverse conditions remain poorly understood. Clusterin is a protein highly expressed by tumors and usually associated with bad prognosis. It promotes cancer cell survival by different mechanisms such as apoptosis inhibition and promotion of autophagy. Here, we show that, upon maturation, human monocyte-derived DCs (MoDCs) up-regulate clusterin expression. Clusterin protects MoDCs from ROS-mediated toxicity, enhancing DC survival and promoting their ability to induce T cell activation. In line with these results, we found that clusterin is expressed by a population of mature LAMP3+ DCs, called mregDCs, but not by immature DCs in human cancer. The expression of clusterin by intratumoral DCs was shown to be associated with a transcriptomic profile indicative of cellular response to stress. These results uncover an important role for clusterin in DC physiology.

BackgroundPatients with hepatic metastases from neuroendocrine tumors (NETs) benefit from an early diagnosis, which is crucial for the optimal therapy and management. Diagnostic procedures include morphological and functional imaging, identification of biomarkers, and biopsy. ObjectiveThe aim of six systematic reviews discussed in this study is to assess the predictive value of Ki67 index and other biomarkers, to compare the diagnostic accuracy of morphological and functional imaging, and to define the role of biopsy in the diagnosis and prediction of neuroendocrine tumor liver metastases. MethodsAn objective group of librarians will provide an electronic search strategy to examine the following databases: MEDLINE, EMBASE and The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL), Database of Abstracts of Reviews of Effects). There will be no restriction concerning language and publication date. The qualitative and quantitative synthesis of the systematic review will be conducted with randomized controlled trials (RCT), prospective and retrospective comparative cohort studies, and case-control studies. Case series will be collected in a separate database and only used for descriptive purposes. ResultsThis study is ongoing and presents a protocol of six systematic reviews to elucidate the role of histopathological and biochemical markers, biopsies of the primary tumor and the metastases as well as morphological and functional imaging modalities for the diagnosis and prediction of neuroendocrine liver metastases. ConclusionsThese systematic reviews will assess the value and accuracy of several diagnostic modalities in patients with NET liver metastases, and will provide a basis for the development of clinical practice guidelines. Trial RegistrationThe systematic reviews have been prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO): CRD42012002644; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2644 (Archived by WebCite at http://www.webcitation.org/6LzCLd5sF), CRD42012002647; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2647 (Archived by WebCite at http://www.webcitation.org/6LzCRnZnO), CRD42012002648; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2648 (Archived by WebCite at http://www.webcitation.org/6LzCVeuVR), CRD42012002649; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2649 (Archived by WebCite at http://www.webcitation.org/6LzCZzZWU), CRD42012002650; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2650 (Archived by WebCite at http://www.webcitation.org/6LzDPhGb8), CRD42012002651; http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42012002651#.UrMglPRDuVo (Archived by WebCite at http://www.webcitation.org/6LzClCNff).

Abstract Background House dust mite (HDM) sensitisation can contribute to the development of allergic rhinoconjunctivitis (AR) or allergic asthma (AA). As treatment, allergen immunotherapy (AIT) is a promising approach, since it aims building immunotolerance against allergens, therewith establishing long‐term efficacy. The evaluation of AIT has been investigated in many randomised controlled trials, whereas few real‐world evidence studies are available. Methods We used data from the longitudinal prescription data base IQVIA™ LRx. Data on initial AIT prescriptions against HDM from January 2009 to December 2013 was analysed regarding treatment (subcutaneous AIT with either depigmented polymerised allergen extract [dSCIT] or other allergens [oSCIT], or sublingual immunotherapy [SLIT]) and treatment duration. Treatment groups were compared with a control group of AR patients not receiving AIT. Data on symptomatic medication was collected until February 2017 and progression of AR and AA was compared. Results Data of 7260 patients with AIT prescriptions and of 21,780 control patients was analysed. AIT was associated with a significant decrease of AR medication intake compared with control (dSCIT: −34.0%, p

Summary: Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson’s disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson’s disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson’s brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson’s symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson’s brain-fingerprint aligns with that of neurotransmitter systems affected by the disease’s pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson’s disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson’s disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).

IntroductionIt is unclear whether patients with diabetes are more susceptible to nerve toxicity of local anesthetics or whether nerve blocks can accelerate the progression of diabetic peripheral neuropathy. Bupivacaine is one of the most widely used local anesthetics for regional anesthesia despite many pre-clinical studies demonstrating neurotoxicity. Herein, we report the long-term functional consequences of sciatic nerve block with bupivacaine and liposomal bupivacaine (Exparel®) in an animal model of diabetes.MethodsMale Sprague Dawley rats were subject to standard chow/vehicle or high-fat diet/low-dose streptozotocin to induce a diabetic phenotype. Animals were then subdivided into groups that received repeated sciatic nerve blocks of saline, bupivacaine, or liposomal bupivacaine. Mechanical allodynia and thermal hyperalgesia were assessed prior to and 12 weeks following nerve blocks utilizing the von Frey and Hargreaves tests, respectively. Exploratory and locomotor activity were assessed with open field testing, and nerve conduction velocity testing was conducted prior to the termination of the study at 28 weeks.ResultsAnimals in the diabetic group developed sustained hyperglycemia >200 mg/dl and signs of peripheral neuropathy six weeks after treatment with streptozotocin, which persisted until the end of the study. Twelve weeks after a repeated sciatic nerve block with saline, bupivacaine, or liposomal bupivacaine, results indicate significant interaction effects of the disease group (control vs. diabetic) and local anesthetic treatment. Overall, diabetic status resulted in worse sensorimotor function compared to control animals. Treatment with perineural bupivacaine resulted in worse sensorimotor functions in both control and diabetic animals. Furthermore, bupivacaine treatment in diabetic animals with pre-existing neuropathy exacerbated sensorimotor function in some measures. In contrast, liposomal bupivacaine did not appear to cause any negative effects on functional outcomes for control or diabetic animals.ConclusionOur data indicate that bupivacaine, and not liposomal bupivacaine, causes long-term changes in tactile allodynia, thermal hyperalgesia, locomotor behaviors, and nerve conduction velocity in control as well as a high-fat diet/low-dose streptozotocin rodent model of diabetes. These results highlight the necessity to investigate safe peripheral nerve block strategies to preserve long-term functional independence in patients with or at risk for diabetic peripheral neuropathy.

Abstract Our study investigated the emergence of spatial quasi-bound states (QBSs) in graphene monolayers induced by rectangular potential barriers. By solving the time-independent Dirac equation and using the transfer matrix formalism, we calculated the resonance energies and identify the QBSs based on probability density functions (PDF). We analyzed two types of structures: single and double barriers, and we find that the QBSs are located within the barrier region, at energies higher than the single barrier. Additionally, we observe QBSs in the double barrier and their position depends on the distance and width of the well between the two barriers. The width and height of the barrier significantly impact the QBSs while the well width influences the resonance energy levels of the QBSs in the double barrier. Interestingly, the QBSs can be manipulated in the graphene system, offering potential for optoelectronic devices. Finally, our results demonstrated that the spatial localization of these states is counter-intuitive and holds great promise for future research in optolectronic devices.

This study investigates AI bias in financial technology (FinTech)-based supply chain management in Pakistan. The study employs Structural Equation Modeling (SEM) to analyze data from diverse respondents. Hypotheses examine the relationships between AI integration, algorithm diversity, employee training, data quality, regulatory compliance, organizational culture, and AI bias. The findings reveal that higher AI integration leads to increased AI bias, Algorithm diversity reduces AI bias, while employee training decreases bias, Quality and diversity of data negatively correlate with AI bias, and regulatory compliance lowers bias. In addition, organizational culture mediates the relationship between AI integration and AI bias. This research contributes a holistic understanding of AI bias factors, guiding ethical AI adoption. Policymakers can use these insights to shape regulations, and industry practitioners can make informed decisions.