bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence-Based Policy Making: Insights and Policy Recommendations for the Implementation of a Clean Energy Transition in Kenya.
Authors: Fields Neve , Ryves David B , Yeganyan Rudolf , Cannone Carla , Tan Naomi , Howells Mark 
Published: April 2023

Abstract

With ambitious targets to drastically increase economic activity over the next decade in order to propel itself to become a middle-income country, Kenya’s future is undoubtedly energy intensive. Through the achievement of its bold and aspiring goals, Kenya is poised to become a regional economic giant with the capacity to strengthen its position as a global leader in renewable energy production. However, current energy capacity expansion plans will see Kenya drastically ramp up fossil fuel generation, significantly increasing emissions and regressing progress made towards its climate and renewable energy targets. Therefore, Kenya is at a crucial stage of its national development with critical decisions to make regarding its future energy expansion and production. The use of energy systems modelling as a method to provide key insights for evidence-based policy making has risen in importance in energy planning globally. Such an approach can provide crucial insights and projections on the impact of potential policy decisions, creating pathways to be adopted within policy. As a result, this study employs long-term energy systems modelling to explore a series of potential future scenarios for Kenya’s power sector, providing insights into their generation, total production, and costs that can assist national policy making. Specifically, this research utilises OSeMOSYS modelling software to produce a Clean Energy Transition scenario (CET) as one possible future for Kenya’s power sector to increase renewable energy production under rapidly intensifying demand. The critical insights gained in this research were employed to suggest seven key policy recommendations for Kenya’s power sector.
Application of three-dimensional reconstruction in partial nephrectomy, a systematic review and meta‑analysis
Authors: Jia Li , Xinliang Yang , Jingzhen Zhu , Xiaobing Liu , Jiang Zhao , Bishao Sun , Xing Luo , Ji Zheng , Zhenqiang Fang 
Published: April 2023

Abstract
Three dimensional (3D) reconstruction is widely used in complicated renal surgery. This article focus on investigating the role of three-dimensional reconstruction participated in partial nephrectomy (PN) from a systematic review and meta-analysis. We searched the published studies that reported the relationship between 3D reconstruction and PN using PubMed, Embase and medline up to December 8, 2022. STATA version 12.0 was used to conduct all analyses. studies were finally progressed to data extraction, Meta-analysis indicated a significant reduction in operation time ([SMD] =-0.34; confidence interval [CI]: -0.59 to -0.09), global ischemia time ([SMD] =-0.42; CI: -0.64 to -0.21) and opening collecting system rate (OR 0.26, 95% CI 0.14 to 0.47). Estimated blood loss, GFR change, positive surgical margin, length of hospital stay, intraoperative complication were no statistically significant differences between 3d reconstruction assisted PN and 2D control group. Our study provides evidence that 3D reconstruction played an important role in PN, especially for complex renal tumors. However, more high-quality, larger sample size and more rigorous design randomized controlled trials which report this topic are still needed to support our conclusions.
Performance Evaluation of Cordex-sea Dataset Based on Multi-metrics and Weighted Ensemble Mean
Authors: Aminoto Tugiyo , Perdinan Perdinan , Faqih Akhmad , Koesmaryono Yonny , Dasanto Bambang Dwi 
Published: April 2023

AbstractComprehensive performance evaluation of climate models on historical periods is crucial in achieving more accurate climate projections. This study aimed to evaluate the precipitation performance of nine regional climate models in the Coordinated Regional Climate Downscaling Experiment–Southeast Asia (CORDEX-SEA) dataset on spatiotemporal aspects and proposed schemes of implementing weighting factors to gain an ensemble mean with a better performance. Multi-metrics were used to measure the model skills. In the IPSL and GFDL regional climate models, extreme values in the category of errors were found. They uniquely occurred only at the lon_max boundary and only in certain months. The causes of such errors were further investigated. Hence, the maximum value screening must be carried out in the early model evaluation stage. Such errors may not be visible if the evaluation is only based on the mean value approach. Based on the Taylor diagram CNRM has the highest performance, followed by HadGEM2 and NorESM1, and the ensemble mean outperforms all those individual models. The implementation of the weighting factors shows that the weighted ensemble means produced better performances in terms of standard deviation ratio (0.98 to 1.19) than the unweighted ensemble mean (1.20). For the zonal mean, the weighted ensemble means (0.95) also outperforms other models (< 0.90). Even though the wavelet analysis indicates that all models and those ensemble means have deficient performances, especially in capturing interannual-to-decadal variability, the Fast Fourier Transform (FFT) analysis shows different results. In addition, the effect of bias correction is also confirmed.
The impact of the COVID-19 pandemic on centre-based cardiac rehabilitation outcomes: An interrupted time series analysis
Authors: Jug Borut , Tršan Jure , Novaković Marko , Tasič Jerneja , Krevel Barbara , Tršan Uroš , Fras Zlatko , Lainščak Mitja , Farkaš Jerneja 
Published: April 2023

Abstract
We sought to assess how the coronavirus-19 (COVID-19) pandemic affected the quality of centre-based cardiac rehabilitation (CR).
Data CR outcomes for 1,452 patients (mean age 59 years, 77% men) were extracted from the National CR Registry and aggregated over monthly time units. We constructed an interrupted time-series (52 months with breakpoint March 2020) with segmented regression to estimate change in level (% points) and trend (% points/month) with 95% confidence intervals [95%CI] of selected CR outcomes.
The outbreak of COVID-19 pandemic affected the majority of selected outcomes. We detected a significant increase in level (6.97; 95%CI 0.32, 13.6%, p=0.040) and trend (0.79; 95% 0.21, 1.36%, p=0.008) for smoking; a significant decrease in level for health-related quality of life (-16.3; 95%CI -27.2, -5.4%, p=0.005); a significant increase in trend for exercise capacity (1.68; 95%CI 0.51, -2.85%/month, p=0.006), and decrease in trends for triglyceride control (-1.46; 95%CI -0.61,-2.31%/month, p<0.001), systolic blood pressure control (-1.93; -3.05, -0.81%/month, p<0.001), high-potency statins uptake (-1.21; 95%CI -1.81,-0.61%/month, p<0.001), and BMI (-1.46; 95%CI -2.48, -0.45, p=0.006).
The COVID-19 pandemic has affected the quality of centre-based CR. Especially unfavourable trends in risk factors and lifestyle measures should be intensively addressed in the post-pandemic period.
Peptidyl Nitroalkene Inhibitors of Main Protease (Mpro) rationalized by Computational/Crystallographic Investigations as Antivirals against SARS-CoV-2
Authors: Medrano Francisco , Hoz-Rodríguez Sergio de la , Martí Sergio , Arafet Kemel , Schirmeister Tanja , Hammerschmidt Stefan , Müller Christin , González-Martínez Águeda , Heras Elena Santillana , Ziebuhr John , Garrido Antonio Romero , Lodola Alessio , Swiderek Katarzyna , Moliner Vicent , González Florenci 
Published: April 2023

Abstract
The coronavirus disease 2019 (COVID-19) pandemic continues to represent a global public health issue. The viral main protease (Mpro) represents one of the most attractive targets for the development of antiviral drugs. Herein we report peptidyl nitroalkenes exhibited enzyme inhibitory activity against Mpro (Ki: 1-10 micM) and three of them good anti-SARS-CoV-2 infection activity in the low micromolar range (EC50: 1-12 micM) without significant toxicity. Additional kinetic studies of compounds FGA145, FGA146 and FGA147 show that all three compounds inhibit Cathepsin L, denoting a possible multitarget effect of these compounds in the antiviral activity. QM/MM computer simulations assisted in the design and in elucidating the way of action. Finally, structural analysis shows, in agreement with the computer predictions, the binding mode of FGA146 and FGA147 to the active site of the protein. Our results illustrate that peptidyl nitroalkenes are potent covalent reversible inhibitors of the Mpro and cathepsin L, and that inhibitors FGA145, FGA146 and FGA147 prevent infection becoming promising drugs against SARS-CoV-2.
Virtual reality in the management of health conditions for people aged 65 years and older: A retrospective analysis.
Authors: Orr Eran , Arbel Tal , Levy Miki , Sela Yaron , Weissberger Omer , Lewis Jeremy 
Published: April 2023

Abstract

Background: Globally, the population of people over the age of 60 years is increasing, and the reproduction rate is declining. This will lead to a substantially higher burden for healthcare professionals caring for this patient population. Virtual reality (VR) has been increasingly used in this population group across myriad health conditions.
Methods: A retrospective analysis of health records was conducted for older people for a range of health conditions who were treated in the metaverse using VR. The main aims of our study were to determine if it was achievable, safe, that outcome measures could be collected remotely, and any early evidence of effectiveness.
Results: The health records of 164 participants, whose mean age was 72.7 (SD = 6.6) years were identified. No adverse effects were reported, the treatment appeared to be well tolerated and appropriate outcomes could be collected. The 30 second sit to stand test significantly improved following treatment (p < 0.001), as did shoulder abduction range for the left (p = 0.03) and right (p = 0.02) upper limbs, and the Activities Specific Balance Confidence Scale (p = 0.05). No deterioration in any outcomes were reported during the time of treatment.
Conclusion: These data suggest that this method of treatment was feasible and safe, and that a large selection of patient reported, and software acquired outcomes could be collected.
Trial registration: This protocol received an exempt status with a waiver of consent from the Biomedical Research Alliance of New York (BRANY) IRB Protocol #22-12-618-947.
A bioengineered immunocompetent human leukemia chip for preclinical screening of CAR T cell immunotherapy
Authors: Chen Weiqiang , Ma Chao , Wang Huishu , Liu Lunan , Tong Jie , Witkowski Matthew , Aifantis Iannis , Ghassemi Saba 
Published: April 2023

Abstract
Chimeric antigen receptor (CAR) T cell immunotherapy is promising for treatment of blood cancers; however, clinical benefits remain unpredictable, necessitating development of optimal CAR T cell products. Unfortunately, current preclinical evaluation platforms are inadequate due to their limited physiological relevance to humans. We herein engineered an organotypic immunocompetent chip that recapitulates microarchitectural and pathophysiological characteristics of human leukemia bone marrow stromal and immune niches for CAR T cell therapy modeling. This leukemia chip empowered real-time spatiotemporal monitoring of CAR T cell functionality, including T cell extravasation, recognition of leukemia, immune activation, cytotoxicity, and killing. We next on-chip modelled and mapped different responses post CAR T cell therapy, i.e., remission, resistance, and relapse as observed clinically and identify factors that potentially drive therapeutic failure. Finally, we developed a matrix-based analytical and integrative index to demarcate functional performance of CAR T cells with different CAR designs and generations produced from healthy donors and patients. Together, our chip introduces an enabling ‘(pre-)clinical-trial-on-chip’ tool for CAR T cell development, which may translate to personalized therapies and improved clinical decision-making.
Functional analysis of ESM1 by shRNA-mediated knockdown of its expression in papillary thyroid cancer cells
Authors: XIE LIJUN , WU YING , WANG HAO , ZHANG WEI 
Published: April 2023

Abstract
Endothelial specific molecule-1 (ESM1) is implicated as an oncogene in multiple human cancers. However, the function of ESM1 in papillary thyroid cancer (PTC) is not well understood. The current study aimed to investigate the effect of ESM1 on the growth, migration, and invasion of PTC to provide a novel perspective for PTC treatment. The expression levels of ESM1 in PTC tissues were detected by immunohistochemical analysis. Knockdown of ESM1 expression in TPC-1 and SW579 cell lines was established to investigate its role in PTC. Moreover, cell proliferation, apoptosis, wound healing, and transwell assays were conducted in vitro to assess cell proliferation, migration and invasion. The findings revealed that ESM1 expression was significantly higher in PTC tissues than that found in paraneoplastic tissues. Knockdown of ESM1 expression inhibited the proliferation, migration, and invasion of TPC-1 and SW579 cells in vitro. Compared with the control group, the mRNA and protein levels of ESM1 in PTC cells were significantly reduced following knockdown of its expression. In addition, ESM1-knockdown cells indicated decreased proliferation and decreased migratory and invasive activities. Overall, ESM1 was identified as a major gene in the occurrence and progression of PTC, which could increase the proliferation, migration, and invasion of PTC cells. It may be a promising diagnostic and therapeutic target gene.
Evolutionary multi-objective molecule optimization in implicit chemical space
Authors: Su Yansen , Xia Xin , Zheng Chunhou , Liu Yiping , Wu Qingwen , Zeng Xiangxiang 
Published: April 2023

Abstract
Optimization techniques play a pivotal role in advancing molecular optimization, prompting the development of numerous generative methods tailored to efficiently design optimized molecules derived from existing lead compounds. However, these methodologies often encounter difficulties in generating diverse, novel, and high-quality molecules when addressing multi-property tasks. Consequently, efficiently searching for diverse optimized candidates that simultaneously satisfy multiple properties remains a significant challenge in molecule optimization. To address this problem, we propose a multi-objective molecule optimization framework (MOMO). MOMO employs a specially designed Pareto dominance-based multi-property evaluation strategy at the molecular sequence level, specifically designed to guide the evolutionary search in a latent molecular space to optimize multiple molecular properties. A comparative analysis of MOMO with extant state-of-the-art baselines across three multi-property molecule optimization tasks reveals that MOMO markedly outperforms them all. These results suggest the efficacy of the proposed MOMO framework for simultaneous optimization of multiple properties in molecule optimization.
Peridroplet mitochondria in fatty liver and their role in the prevention of NAFLD by diethyldithiocarbamate
Authors: Liu Tianhui , Sun Xiangyun , Kang Bilian , Yu Qinghong , Qi Yifei , Zhao Xinyan , Liu Lin , Wang Ping , Cong Min 
Published: April 2023

Abstract
Mitochondria can contact lipid droplets (LDs) to form peridroplet mitochondria (PDM). However, the role of PDM in nonalcoholic fatty liver disease (NAFLD) is still unknown. Here, we explored the features of PDM in NAFLD and the role of PDM in the treatment of diethyldithiocarbamate (DDC) on NAFLD. For the first time, we show that the number of PDM in mouse liver varies with the severity of NAFLD, indicating that PDM might be associated with the progression of NAFLD. PDM and cytosolic mitochondria (CM) were isolated from fatty liver of NAFLD, and analyzed by quantitative proteomics. Compared with CM, PDM have enhanced mitochondrial respiration and ATP synthesis. In addition, we provide the evidence that the formation of PDM can be regulated in vivo and contributes to the therapeutic effect of DDC on NAFLD. Our findings suggest that regulation of PDM may be a new pharmacological strategy for NAFLD.
Influence Of hydrogen bonding on the Photo-physical properties of Diethylamino hydroxybenzoyl hexyl benzoate
Authors: Zhang Qianjie , Lv Qing , Zhang Dongmei , Jiang Wen , Zhang Huiwen , Zhang Wanping 
Published: April 2023

Abstract
In this paper, the effects of different hydrogen bond types on the photophysical properties of DHHB were investigated by systematically investigating the changes of spectral properties of Diethylamino hydroxybenzoyl hexyl benzoate in protonic and aprotic solvents, and the formation and stability of hydrogen bonds were further studied. Studies have shown that different solvent types and solute concentrations would affected the type of hydrogen bonds, and temperature changes would affected the stability of hydrogen bonds. In aprotic solvents, DHHB could only formed intramolecular hydrogen bonds and DHHB-DHHB intermolecular hydrogen bonds. At low concentration (≤ 5µg/mL), the system mainly existed in the form of intramolecular hydrogen bonds. At this time, the fluorescence intensity and UV molar extinction coefficient changed little, indicating that intramolecular hydrogen bonds have little effected on the spectral properties of DHHB. With the increase of concentration, the number of intermolecular hydrogen bonds increased, UV molar extinction coefficient increased significantly, indicating that intermolecular hydrogen bonds were conducive to improving the UV absorption properties of DHHB. With the increase of temperature, the molar extinction coefficient of the system decreased, indicating that the increase of temperature would led to the decrease of the stability of hydrogen bond fracture between DHHB molecules and reduced the UV absorption performance of DHHB. In the protic solvent, the system also has DHHB-solvent intermolecular hydrogen bonds. With the increase of the proportion of protonic solvent in the system, the fluorescence intensity of the system decreased significantly and the UV integral area increased significantly, indicating that the hydrogen bond between DHHB-solvent molecules was beneficial to improve the UV absorption performance of DHHB.
Fatigue and physical activity levels in Poles living in Poland and the United Kingdom in the futher year of the COVID-19 pandemic: a pilot study
Authors: Zalewska Anna , Gałczyk Monika , Mierzejewska Aneta 
Published: April 2023

Abstract

Objectives The aim of this study was to conduct a preliminary assessment of the prevalence of fatigue and level of physical activity, as well as the relationship between fatigue and physical activity among Poles living in Poland and the United Kingdom in the futher year in the COVID-19 pandemic.Methods A web-based online survey was conducted among Poles living permanently in Poland and the United Kingdom in January 2023. Responses were obtained from 200 respondents aged 18–69 years. The level of fatigue was assessed by the Modified Fatigue Impact Scale (MFIS). The level of physical activity was measured by the International Physical Activity Questionnaire (IPAQ).Results The median for the total fatigue score was equal to 17 points out of a possible 105 which is a quite low level. 13.5% of the subjects had a low level of physical activity, 57% had a sufficient level and 29.5% had a high level. As the scores of the MFIS questionnaire scales and its summary score increased, the MET scores and the level of physical activity decreased. The respondents’ country of residence is not statistically significantly associated with activity level. Poles living in Poland had statistically significantly higher mean scores on the cognitive scale.Conclusions Further experimental studies on the physiological mechanism of differences in fatigue and physical activity are needed. In relation to the findings of our own research, physical activity interventions are recommended to address the unequal distribution of fatigue prevalence between people with high and low levels of physical activity.
Unveiling the molecular recognition process between USP7 N-terminal TRAF-like domain and β-catenin for small molecule discovery
Authors: Asthana Shailendra , Srivast Mitul , Mathur Rajani 
Published: April 2023

Abstract
Protein-protein interactions drive the majority of biological processes, but their poorly characterized molecular recognition mechanism serves as bottleneck for therapeutic interventions. Recognition of substrates via specific sites induce regulation in the protein’s activity which instigates abnormalities in cellular processes. Ubiquitin specific protease-7 (USP7), a negative regulator of Wnt-signaling pathway, deubiquitinates β-catenin and causes colorectal cancer (CRC). USP7 N-terminal TRAF-like domain’s (NTLD) orthosteric site serves as hub for the recognition of substrates, however, its role for β-catenin is still elusive. Furthermore, the pivotal structural determinant and signature residues that drives recognition process between USP7 and β-catenin is unexplored. The NTLD is an unchartered territory of USP7 as no small molecules are reported by targeting its orthosteric site. Here, we underscore the key structural determinants and thermodynamic components that possibly drive the recognition of USP7-β-catenin by using extensive computational approaches. By characterizing this site, six potential hits are identified from the library of 1.1 million compounds through structure-guided virtual screening. Among six dynamically stable hits, H1 and H6 mimics the orientation and interaction map with endogenous substrate peptides at an atomic level without using any biased approach. Consequently, our approach put-forth a novel route to design potent USP7 inhibitors by targeting NTLD.
Automated analysis and detection of epileptic seizures in video recordings using artificial intelligence
Authors: Rai Pragya , Knight Andrew , Hiillos Matias , Morales Elizabeth , Terney Daniella , Larsen Sidsel Armand , Østerkjerhuus Tim , Peltola Jukka , Beniczky Sándor 
Published: April 2023

Abstract
Automated seizure detection promises to aid in the prevention of SUDEP and improve the quality of care by assisting in epilepsy diagnosis and treatment adjustment. In this phase 2 validation, the algorithmic model performance of a contactless, marker-free video-based motor seizure detection system is evaluated against video-electroencephalographic monitoring (VEM) from two Danish epilepsy monitoring units. Detection performance of five categories of motor epileptic seizures (tonic-clonic, hyperkinetic, tonic, unclassified motor, automatisms) and psychogenic non-epileptic seizures (PNES) with a motor behavioral component lasting for >10 seconds were assessed. 230 patients were recruited in the validation set, with 340 motor seizures identified by VEM. The control threshold was evaluated at a range of values to compare the sensitivity and false detection rate (FDR). At optimal thresholds, the performance of seizure groups in terms of sensitivity (CI) and FDR/hr (CI): tonic-clonic- 95.2% (77.3%, 99.2%); 0.084 (0.081, 0.11), hyperkinetic- 92.9% (68.5%, 98.7%); 0.62 (0.57, 0.67), tonic- 78.3% (64.4%, 87.7%); 5.81 (5.46, 6.19), automatism- 87% (74.3%, 93.9%); 3.30 (3.08, 3.54), unclassified motor seizures- 77.7% (70.8%, 83.4%); 4.79 (4.48, 5.12), and PNES- 95.6% (85.2%, 98.8%); 1.70 (1.59, 1.83). A generic threshold recommended for all motor seizures under study asserted 87.8% sensitivity and 6.48 FDR/hr. These results indicate the system’s achievable performance at pre-specified thresholds that is clinically applicable for use as a seizure screening solution in diagnostic workflows.