bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical evolution of patients with pre-existing panic disorder during the COVID- 19 pandemic: Two-year longitudinal follow-up in Morocco
Authors: oumary Omar El , Lahlou Laila , Ouhamou Mina , Laaraj Hicham , Salehddine Zineb , McCormack Dawn , Doufik Jalal , Mouhadi Khalid , Rammouz Ismail 
Published: August 2023

Abstract
Background
Several studies have been conducted on the impact of the COVID-19 pandemic on the general population, but few have examined the longitudinal evolution of psychopathology in patients with mental health disorders at different stages of the pandemic. This study sought to answer these questions by assessing the trajectory of mental health in patients with pre-existing panic disorder in a COVID-19 pandemic setting while evaluating socio-demographic and clinical factors associated with outcomes.
Methods
This was a longitudinal study of panic disorder patients followed during three waves of the COVID-19 pandemic. Change assessed in mental health status used five validated scales: the Beck Depression Inventory-II (BDI-II), the Beck Anxiety Inventory (BAI), the Impact of Event Scale-revised (IES-R), The Mini International Neuropsychiatric Interview (MINI) for suicidal risk and the Panic Disorder Severity Scale Self Report version (PDSS-SR). Predictors of mental health symptom progression were assessed using multivariate analysis.
Results
There was a significant wave-to-wave reduction in depressive symptoms, post-traumatic stress, panic disorder severity and suicidal risk. Concerning anxiety symptoms, patients felt better and better during successive waves of the pandemic, with a statistically significant decrease from the first to the second wave of the COVID-19 pandemic. The analytical strategy also enabled the identification of the various socio-demographic and clinical factors likely to be associated with higher panic disorder severity.
Conclusion
It is timely to raise a series of questions that this research attempts to answer, and to develop personalized strategies for future pandemics in order to minimize the risk of aggravation or relapse in patients with panic disorder in particular, who may be more sensitive to multiple aspects of the pandemic.
Ambient Floor Vibration Sensing Advances Accessibility of Functional Gait Assessment for Children with Muscular Dystrophies
Authors: Dong Yiwen , Iammarino Megan , Liu Jingxiao , Codling Jesse , Fagert Jonathon , Mirshekari Mostafa , Lowes Linda , Zhang Pei , Noh Haeyoung 
Published: August 2023

Abstract

Muscular dystrophies (MD) are a group of genetic neuromuscular disorders that cause progressive weakness and loss of muscles over time, influencing 1 in 3500 to 5000 children worldwide. New and exciting treatment options have led to a critical need for a clinical post-marketing surveillance tool to confirm the efficacy and safety of these treatments after individuals receive them in a commercial setting. For MDs, functional gait assessment is a common approach to evaluate the efficacy of the treatments because muscle weakness is reflected in individuals' walking patterns. However, there is little incentive for the family to continue to travel for such assessments due to the lack of access to specialty centers. While various existing sensing devices, such as cameras, force plates, and wearables can assess gait at home, they are limited by privacy concerns, area of coverage, and discomfort in carrying devices, which is not practical for long-term, continuous monitoring in daily settings. In this study, we introduce a novel functional gait assessment system using ambient floor vibrations, which is non-invasive and scalable, requiring only low-cost and sparsely deployed geophone sensors attached to the floor surface, suitable for in-home usage. Our system captures floor vibrations generated by footsteps from patients while they walk around and analyzes such vibrations to extract essential gait health information. To enhance interpretability and reliability under various sensing scenarios, we translate the signal patterns of floor vibration to pathological gait patterns related to MD, and develop a hierarchical learning algorithm that aggregates insights from individual footsteps to estimate a person's overall gait performance. When evaluate through real-world experiments with 36 subjects (including 15 patients with MD), our floor vibration sensing system achieves a 94.8% accuracy in predicting functional gait stages for patients with MD. Our approach enables accurate, accessible, and scalable functional gait assessment, bringing MD progressive tracking into real life.
Prevalence, patterns, and impacts of multimorbidity on adverse clinical outcomes in chronic kidney disease
Authors: Chowdhury Samin 
Published: August 2023

Abstract
Background
Multimorbidity is the concurrent presence of two or more long-term health conditions in the same individual. It fragments healthcare delivery and affects quality of life. Chronic kidney disease (CKD) often occurs with multimorbidity. The prevalence of CKD is rising. However, there is a lack of evidence on the prevalence, patterns, and impacts of multimorbidity on adverse clinical outcomes in patients with CKD.
Methods
This was a systematically conducted literature review. A search was conducted in EMBASE, MEDLINE, CINAHL, and SCOPUS (2019–2023). The main search terms were “chronic kidney disease” and “multimorbidity.” The eligibility criteria were observational studies with adult participants with all stages of CKD (CKD stage 1–5 including those on renal replacement therapy). The exposure was multimorbidity quantified by measures. All-cause mortality, kidney disease progression, hospitalisation, and cardiovascular events were outcomes. The Joanna Briggs Institute (JBI) checklist was used for the risk of bias assessment. Due to heterogeneity in design and methods, Jennie Popay’s narrative synthesis was used for data synthesis.
Results
Of 6879 papers, nine papers met the inclusion criteria. Most studies included participants with all stages of CKD (CKD stage 1–5). The prevalence of multimorbidity ranged from 86.6–99.1%. Hypertension was the most prevalent comorbidity. The combination of concordant multimorbidity (hypertension, diabetes, and cardiovascular diseases) was highly prevalent. Multimorbidity was significantly associated with mortality, cardiovascular events, kidney disease progression, and hospitalisation. While older people had more multimorbidity burdens, younger patients with CKD were at a higher risk of death from multimorbidity. Severe CKD with clusters of cardiovascular diseases, diabetes, chronic pain, and depression was significantly associated with all-cause mortality.
Conclusion
There are associations between multimorbidity and adverse clinical outcomes in patients with CKD. However, there is a lack of data on Black, Asian, and Minority Ethnic participants and from low- and middle-income countries. Further research is needed to investigate the high prevalence of chronic pain and depression in chronic kidney disease.
The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly
Authors: Hader Daniel , Patitz Matthew 
Published: August 2023

Abstract
Motivated by applications in DNA-nanotechnology, theoretical investigations in algorithmic tile-assembly have blossomed into a mature theory. In addition to computational universality, the abstract Tile Assembly Model (aTAM) was shown to be intrinsically universal (FOCS 2012), a strong notion of completeness where a single tile set is capable of simulating the full dynamics of all systems within the model; however, this construction fundamentally required non-deterministic tile attachments. This was confirmed necessary when it was shown that the class of directed aTAM systems, those where all possible sequences of tile attachments result in the same terminal assembly, is not intrinsically universal (FOCS 2016). Furthermore, it was shown that the non-cooperative aTAM, where tiles only need to match on 1 side to bind rather than 2 or more, is not intrinsically universal (SODA 2014) nor computationally universal (STOC 2017). Building on these results to further investigate the other dynamics, Hader et al. examined several tile-assembly models which varied across (1) the numbers of dimensions used, (2) how tiles diffused through space, and (3) whether each system is directed, and determined which models exhibited intrinsic universality (SODA 2020). In this paper we extend those results to provide direct comparisons of the various models against each other by considering intrinsic simulations between models. Our results show that in some cases, one model is strictly more powerful than another, and in others, pairs of models have mutually exclusive capabilities. This paper is a greatly expanded version of that which appeared in ICALP 2023.
Fake News Detection through Graph-based Neural Networks: A Survey
Authors: Gong Shuzhi , Sinnott Richard , Qi Jianzhong , Paris Cecile 
Published: August 2023

Abstract
The popularity of online social networks has enabled rapid dissemination of infor- mation. People now can share and consume information much more rapidly than ever before. However, low-quality and/or accidentally/deliberately fake information can also spread rapidly. This can lead to considerable and negative impacts on society. Identifying, labelling and debunking online misinformation as early as possible has become an increasingly urgent problem.
Many methods have been proposed to detect fake news including many deep learning and graph-based approaches. In recent years, graph-based methods have yielded strong results, as they can closely model the social context and propagation process of online news. In this paper, we present a systematic review of fake news detection studies based on graph-based and deep learning-based techniques. We classify existing graph-based methods into knowledge-driven methods, propagation-based methods, and heterogeneous social context-based methods, depending on how a graph structure is constructed to model news related information flows. We further discuss the challenges and open problems in graph-based fake news detection and identify future research directions.
Nitrite excretion by cyanobacteria is controlled by the small protein NirP1
Authors: Hess Wolfgang , Kraus Alexander , Spät Philipp , Timm Stefan , Wilson Amy , Schumann Rhena , Hagemann Martin , Macek Boris 
Published: August 2023

Abstract
When the supply of inorganic carbon is limiting, photosynthetic cyanobacteria excrete nitrite, a toxic intermediate in the ammonia assimilation pathway from nitrate. While it has been hypothesized that the excreted nitrite represents excess nitrogen that could not be further assimilated due to the missing carbon, the underlying molecular mechanism has remained enigmatic. Here, we characterized a hitherto unannotated gene with homologs in the genomes of 485 different cyanobacteria that is upregulated under low carbon conditions and controlled by the transcription factor NtcA, a central regulator of nitrogen homeostasis. To understand its function, we ectopically overexpressed it in Synechocystis sp. PCC 6803, which resulted in a chlorotic phenotype, delayed growth, severe changes in amino acid pools, and nitrite excretion. Coimmunoprecipitation experiments revealed that this protein targets nitrite reductase, a central enzyme in the assimilation of ammonia from nitrate/nitrite, and was re-named to nitrite reductase regulator protein 1 (NirP1). Our results reveal that NirP1 is widely conserved in cyanobacteria and plays a crucial role in the coordination of C/N primary metabolism by targeting one of the central enzymes. In natural environments, the excreted nitrite will be utilized by other microorganisms; therefore, NirP1 ultimately impacts the activities and composition of the surrounding microbiome.
Extracellular vesicles from bodily fluids for the accurate diagnosis of Parkinson’s disease and related disorders: A systematic review and meta-analysis
Authors: Taha Hash Brown , Bogoniewski Aleksander 
Published: August 2023

Abstract
Parkinsonian disorders, including Parkinson's disease (PD), multiple system atrophy (MSA), dementia with Lewy body (DLB), corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are often misdiagnosed due to overlapping symptoms and the absence of precise biomarkers. Furthermore, there are no current methods to ascertain the progression and conversion of prodromal conditions such as REM behavior disorder (RBD). Extracellular vesicles (EVs), containing a mixture of biomolecules, have emerged as potential sources for parkinsonian diagnostics. However, inconsistencies in previous studies have left their diagnostic potential unclear. We conducted a meta-analysis, following PRISMA guidelines, to assess the diagnostic accuracy of general EVs isolated from various bodily fluids, including cerebrospinal fluid (CSF), plasma, serum, urine or saliva, in differentiating patients with parkinsonian disorders from healthy controls (HCs). The meta-analysis included 21 studies encompassing 1,285 patients with PD, 24 with MSA, 105 with DLB, 99 with PSP, 101 with RBD, and 783 HCs. Analyses were conducted only for patients with PD vs. HCs, given the limited number for other comparisons. Using bivariate and hierarchal receiver operating characteristics (HSROC) models, the meta-analysis revealed moderate diagnostic accuracy in distinguishing PD from HCs, with substantial heterogeneity and publication bias detected. The trim-and-fill method revealed at least two missing studies with null or low diagnostic accuracy. CSF-EVs showed better overall diagnostic accuracy, while plasma-EVs had the lowest performance. General EVs demonstrated higher diagnostic accuracy compared to CNS-originating EVs, which are more time-consuming, labor- and cost-intensive to isolate. In conclusion, while holding promise, utilizing biomarkers in general EVs for PD diagnosis remains unfeasible due to existing challenges. The focus should shift toward harmonizing the field through standardization, collaboration, and rigorous validation. Current efforts by ISEV aim to enhance the accuracy and reproducibility of EV-related research through rigor and standardization, aiming to bridge the gap between theory and practical clinical application.
Parental deprivation in early childhood impacts gene expression on brain development as a lifelong effect
Authors: Shinohara Haruka , Meguro-Horike Makiko , Inoue Takashi , Shimazu Miyuki , Hattori Machiko , Hibino Hitoshi , Fukasawa Kazumasa , Sasaki Erika , Horike Shin-ichi 
Published: August 2023

Abstract
Early life experiences, such as parental loss, neglect, and child abuse, are well-established risk factors for neurological disorders later in life, including depression, anxiety disorders, and post-traumatic stress disorder. However, the molecular mechanisms underlying the impact of adverse childhood experiences on neurophysiological systems throughout life remain incompletely understood. Common marmosets, which are non-human primates, typically give birth to 2–4 offspring, but only two usually survive. Therefore, human hand-rearing is employed to ensure the survival of the offspring. However, marmosets that are raised by humans often exhibit behavioral abnormalities, including abnormal vocalizations, excessive attachment to the caretaker, and aggressive behavior. Hence, our study aimed to investigate the hypothesis that human hand-rearing induces alterations in gene expression within the brains of infant marmosets, and that these changes persist into adulthood and are associated with behavioral abnormalities. Our analyses revealed consistent alterations in a subset of genes, including those related to neurodevelopmental diseases, across different developmental stages, indicating their continuous susceptibility to the effects of early parental deprivation. These findings highlight the dynamic nature of gene expression in response to early life experiences and suggest that the impact of early parental deprivation on gene expression may vary across different stages of development.
The Effect of Emotional Intelligence and Psychological Security on Digital Learning Readiness
Authors: Abdelfattah Fadi , ALAlawi Abrar , Mashaikhya Najla Yahya Al , Saleh Ayman AL 
Published: August 2023

Abstract

The purpose of this study is to examine the factors affecting students’ digital learning readiness, including emotional intelligence and student’s perceived psychological security as a mediator. The conceptual model has been drawn per the findings of previous studies. This study used quantitative data collected from one hundred thirty student via random sampling technique. Based on this study empirical investigation, the student’s digital readiness is significantly related to their emotional intelligence when dealing with digital learning. Moreover, this research highlights the critical mediating role of perceived psychological security in the relationship between emotional intelligence and digital learning readiness. This study will assist scholars, Higher Educational Institutions (HEIs), decision-makers, and practitioners in understanding and dealing with the learning mode changes from different perspectives, including the quality of the learning program and students’ psychological health.
Analyzing perceived caregiving burden and assessment of sociodemographic correlates among informal caregivers of Schizophrenia patients: a descriptive cross-sectional study
Authors: Qalb-I-Hyder Syed , Channa Summaira , Laghari Daryakhan , Moin Ghazal , Ansari Moin Ahmed , Qureshi Asra 
Published: August 2023

Abstract

Objective: Informal Caregivers experience various circumstances during patient care. Such instances could potentially lead to physical, emotional, and economical challenges. The aim of this study was to investigate caregiving burden among informal caregivers of schizophrenia patients and to find out factors that corroborate increment in caregiver’s burden. Participants and Methods: Schizophrenia patients and their informal caregivers were recruited from outpatient clinics of the largest public sector psychiatric hospital in the country. Data was collected on a pre-designed questionnaire through face-to-face interviews. Caregivers were evaluated for caregiving burden usingBurden Assessment Scale (BAS).Bivariate analysis and correlation coefficients were the focus methods of analysis to examine the association between burden of caregiving and corroborating factors. Results The mean age of Schizophrenia patients was 30.7 ± 10.3 years and, n:358(94%) were male. The mean age of informal caregivers was 42.3 ± 13.1 years and, 78% of them were male. The highest number of caregivers were parents n:156(41%) and the average duration of caregiving computed was 6.3 ± 4.9 years. The Mean Burden assessment Score (BAS) of caregivers was 49.6 ± 14.0 and 51% (n:196) of the caregivers were found with higher caregiving burden. Conclusion A strong advocacy support is needed at local level to offer social support and psychoeducational services for care providers. Additionally, it is crucial that such families or communities at large consider opportunities to identify that how support and task sharing for routine life responsibilities could help informal care providers to enjoy their role and contribute as an effective member of the society.
Construction and application of a cleaner production evaluation index system for the apple industry in China
Authors: Zhao Li , Shao Shuai , Wang Yingda , Gao Qiufeng , Zhang Yun , Bao Yining , Zhang Zhao 
Published: August 2023

Abstract
It is very important to establish a relatively complete evaluation index system for cleaner production in the apple industry in China. Based on interviews with apple experts, extensive apple industry data, and the national apple development plan and related national standards, this study constructed a CP evaluation index system for apples in China. The system included 6 first-grade indicators and 19 second-grade indicators of resource and energy consumption, product characteristics, production technology characteristics, pollutant generation, comprehensive utilisation of resources and cleaner production management. The weights of indicators at all levels were determined by analytic hierarchy processing and expert scoring, and a fuzzy comprehensive evaluation model and an accompanying two-tuple linguistic evaluation method were established. Finally, this study selected three apple orchards as case studies to verify the accuracy and feasibility of this index system, and based on the results of the evaluation, specific cleaner production improvement measures were proposed for the three orchards.
Effect of Eucalyptus Tree on Selected Soil Physico-Chemical Properties in Gidami District, West Ethiopia
Authors: Daka Yohannes Shifera , Geleta Zelalem Telila 
Published: August 2023

Abstract

The study was conducted in district of Gidami, western Oromia region, Ethiopia. The aim was to investigate effects of Eucalyptus tree (Eucalyptus camaldulensis) on soil physico-chemical properties. Eucalyptus is widely planted in farmland in the study area largely because of construction purpose and financial income. However, the cultivation of eucalyptus is becoming a major concern because of its long-term site impact. Long-term consequences have been observed, including drying up of water courses, effects on soil physico-chemical characteristics, ability to drain soil nutrients and fertility, suppression of other plants, forest biodiversity decline, and reduced agricultural yields in agroforestry systems. However, Eucalyptus plantations on study area farmland are expanding regardless of its impacts on soil fertility and competition for crop land. On the other hand, human population is increasing from time to time and hence the demand for agricultural crop is increasing, however; the environment is degrading. Therefore, this study was conducted with the aim to study the effects of Eucalyptus tree on selected soil physico-chemical properties in Gidami District, West Ethiopia. For this study, randomized complete block design (RCBD) was used. Three farmers land 50m by 50m Eucalyptus plantation forest having similar age was selected, which served as experimental plot. Each experimental plot (farmland) was subdivided into 5 sub blocks. Then, sampling points (treatments) were randomly assigned to each block. Soil samples were collected by using auger at five different sampling points (at middle of canopy, 5m, 10m, 15m and, 40m distances) with two depths (0-15cm and 15-30 cm). 10 soil samples were collected from each block and a total composite soil samples collected were 30. Each composite sample soil was prepared by mixing three sub samples. Soils sampled at 40m distance were used as control group. Soil physico-chemical property analyses were conducted in Nekemt soil laboratory. The two ways ANOVAs were carried out by SAS version 9.0. The effects of Eucalyptus tree were insignificant on soil bulk density, exchangeable acidity, organic matter, exchangeable base, organic C, and Pat different distance, and pH with depth. Soil moisture, pH, CEC increased in further distance from the Eucalyptus trees. However, total N decreased as distance increased further from Eucalyptus tree. Surface soils (0-15 cm) were higher in total N, K, C, and organic matter than sub soil (15-30 cm) depth.