bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of a ketogenic diet on nonalcoholic fatty liver disease (NAFLD) progression: a randomized controlled trial
Authors: Chirapongsathorn Sakkarin , Rintaravitoon Wiwit , Tangjaturonrasme Bhagawat , Chotsriluecha Samitti , Pumsutas Yanisa , Kanchanapradith Achariya , Treeprasertsuk Sombat 
Published: July 2023

Abstract
Background
Despite the popularity of a ketogenic diet, no randomized, controlled trials have evaluated its efficacy on nonalcoholic fatty liver (NAFLD) progression.
Methods
We conducted 8-week, open-label randomized controlled trial involving 24 patients with NAFLD who were randomly assigned to either the home delivery ketogenic diet or general lifestyle advice counselling DASH diet. The primary outcome was reduction of hepatic steatosis as measured by transient elastography. Secondary outcome included metabolic profiles, and anthropometrics.
Results
There were no significant differences between groups in liver stiffness and steatosis measurement after dietary interventions. Subjects on a ketogenic diet had lost more weight than subjects in control group at 8 weeks (mean change [95% CI], -6.16 [-7.22, -5.10] vs. -2.14 [-4.49, 0.21] kg; P=0.001). The decrease in waist circumference, systolic blood pressure, fat mass and visceral fat area were significantly greater among subjects on a ketogenic diet than among those in control group. Laboratory parameters including AST, triglyceride and HDL were also significantly decreased among subjects on a ketogenic diet than among those in control group.
Conclusions
A ketogenic diet produced a significantly greater weight loss (absolute difference, approximately 4 percent) than did the general lifestyle advice intervention for the first 8 weeks. A ketogenic diet was associated with a greater improvement in some risk factors for coronary heart disease and NAFLD. However, a ketogenic diet did not reduce steatosis but not worsen NAFLD progression. Longer and larger studies are required to determine the long-term safety and efficacy of the ketogenic diet.
First registration 26/04/2022, Clinical trial registration number: TCTR20220426005.
The impact of biosolids biochar on biomethane production from the anaerobic digestion of chicken manure
Authors: Hassan Soulayma , Ngo Tien , Khudur Leadin S. , Krohn Christian , Dike Charles Chinyere , Hakeem Ibrahim Gbolahan , Shah Kalpit , Surapaneni Aravind , Ball Andrew S. 
Published: July 2023

Abstract
This is the first study that specifically investigated biosolid-derived biochar for mitigating ammonia stress and methane production during the anaerobic digestion of chicken manure, using both pristine and modified biochar with potassium hydroxide (KOH) solution. Batch mesophilic anaerobic digestion (37 ℃) was carried out over 18 days. Compared to chicken-manure-only controls, a significant increase in methane formation was observed in digesters amended with biochar and KOH-modified biochar, producing 220 L kg-1-VS and 262L kg-1-VS of methane, respectively, compared to 139 L kg-1 VS from control digesters. Moreover, the use of biochar and KOH-modified biochar resulted in a significant reduction of 8 days in the lag phase. Total Ammonia Nitrogen (TAN) concentration was reduced in digesters with biochar and KOH-modified biochar by 25% and 35.5%. respectively. QPCR data revealed that the number of 16S rRNA gene copies was around 50,000 and 41,000 times higher in biochar and KOH-modified biochar digesters, respectively, compared to control digesters on day 18. In addition, adding biochar and alkali-modified biochar to digesters created a mixture of pathways (acetoclastic, hydrogenotrophic and methylation), leading to a robust archaeal community. The results showed that biosolids biochar additives enhance the anaerobic
Online Short-term Ship Response Prediction with Dynamic Buffer Window Using Transient Free Switching Filter
Authors: Majidiyan Hamed , Majidiyan Hamed , Enshaei Hossein , Howe Damon 
Published: July 2023

Abstract

Ship response prediction is one of the emerging interests in seakeeping, given the extensive range of applications for autonomous control of marine vehicles. In particular, the shortterm prediction and online updates of the ship response have been in the practical attention span. Despite a body of studies on different predictors, the asymptotic properties of estimators concerning the time series sample size have not been addressed specifically. The predictors only have been analysed for a fixed observation window regardless of the intrinsic statistical characteristics obtainable in the time series. To this end, the current research has considered the performance of two nonlinear and linear based regressors: support vector regression (SVR) and the adaptive Seasonal Auto-Regressive and Integrated Moving Average (SARIMA) model on the time series data obtained from a simulated semisubmersible platform in different sea states. The experiment demonstrated that the prediction accuracy highly depends on the observation window length with respect to the statistical properties of the responses in various wave conditions. Therefore, an innovative filter using the weighted average of the proposed functions has been introduced to dynamically adjust the buffer window based on the signal statistical characteristics. The promising results showed that the filter not only could contribute to promoting any predictors used in autonomous onboard decision-making, guidance, and stabilization systems for present and future intelligent onboard control systems, but the proposed mechanism can be employed in dynamic systems in other disciplines too.
Identifying the multiple drivers of Cactus diversification
Authors: Thompson Jamie , Hernández-Hernández Tania , Keeling Georgia , Priest Nicholas 
Published: July 2023

Abstract

Our understanding of the complexity of forces at play in the rise of major angiosperm lineages remains incomplete. The diversity and heterogeneous distribution of most angiosperm lineages is so extraordinary that it confounds our ability to identify simple drivers of diversification. Using Machine Learning in combination with phylogenetic modelling, we show that 11 separate abiotic and biotic variables significantly contribute to the diversification of Cactaceae. We reconstruct a comprehensive phylogeny, build a dataset of 39 abiotic and biotic variables, and predict the variables of central importance, accounting for interactions. We use state-dependent diversification models to confirm that a rich range of eleven abiotic and biotic variables shape Cactus diversification. Of highest importance is latitude, plant size, and growth form, with lesser importance identified in soil composition, bioclimate, topography, geographic range size, and chromosome count. Our results reveal the need to account for the complexity underlying macroevolution of iconic angiosperm families.
Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans
Authors: Iwata Takamitsu , Ikegaya Yuji , Smallwood Jonathan , Fukuma Ryohei , Oshino Satoru , Tani Naoki , Khoo Hui , Kishima Haruhiko , Yanagisawa Takufumi 
Published: July 2023

Abstract

Core features of human cognition, for example, the experience of mind wandering, highlight the importance of the capacity to focus on information separate from the here and now. However, the brain mechanisms that underpin these self-generated states remain unclear. An emerging hypothesis is that self-generated states depend on the process of memory replay, which, in animals, is linked to sharp-wave ripples (SWRs) originating in the hippocampus. SWRs are transient high-frequency oscillations that exhibit circadian fluctuations and, in the laboratory, are important for memory and planning. Local field potentials were recorded from the hippocampus of 11 patients with epilepsy for up to 15 days, and experience sampling was used to describe their association with ongoing thought patterns. SWRs were correlated with patterns of vivid, intrusive ongoing thoughts unrelated to the task being performed, establishing their contribution to the ongoing thoughts that humans experience in daily life.
Assessing the Prevalence of Anemia Post-COVID-19 Infection in Adult Members of a Southeastern U.S. Integrated Healthcare System
Authors: Hudgins Alexander F. , McDonald Bennett , Bush Patricia A. , Harding Jessica L , Kolailat Imanii , Martinez Monica , Segall Marni , Thompson Sierra G. , Patzer Rachel E , Han Jenny E. , Cribbs Sushma K. , Walker Tiffany A. , Wiley Zanthia , Neuman Robert , Pigott Terri , Ofotokun Igho , Gander Jennifer C. 
Published: July 2023

Abstract

Background
COVID-19 may cause or worsen anemia, leading to fatigue, lower quality of life, increased risk of comorbidities, and significantly associated with worse outcomes in patients hospitalized with COVID-19. Little is known among a community-based population. We aimed to investigate the incidence and risk factors of anemia post-COVID diagnosis in a community-based population.
Methods
We identified all adult members of KPGA with a confirmed diagnosis of COVID-19 between January 2020 and March 2022 and followed through March 2023. Anemia was defined using hemoglobin (Hgb) labs 180-days (±30-days) and 365-days (±30-days) after COVID-19 diagnosis and sex-specific thresholds. Potential risk factors included demographics and clinical characteristics (defined by diagnosis codes) at the time of COVID-19 diagnosis. Hospitalization with COVID-19 was used as a marker of COVID-19 severity. Logistic regression among individuals not diagnosed with anemia pre-COVID investigated the association between each risk factor and anemia 180- and 365-days post-COVID-19 infection. We stratified fully adjusted model by hospitalization with COVID-19 to assess effect modification.
Results
We included 3,450 and 3,043 individuals who met the inclusion criteria and had Hgb results available 180- and 365- days post-COVID-19 diagnosis. One-third of our population had anemia 180-days (n=1,100, 32.17%) and 365-days (n=1,007, 33.09%) post-COVID-19, with approximately 11% of the cohort being newly diagnosed cases of anemia. In the fully adjusted models females (vs. males) (OR=1.71, 95% CI: 1.42, 2.06), Black or African American individuals (vs. non-Black individuals) (OR=2.34, 95% CI: 1.98, 2.76), adults diagnosed with kidney disease (OR=1.79, 95% CI: 1.42, 2.25) or diabetes (OR=1.26, 95% CI: 1.12, 1.64), and adults hospitalized with COVID-19 (OR=1.43, 95% CI: 1.15, 1.78) were more likely to be diagnosed with anemia 365-days after COVID-19 diagnosis. Analyses stratified by hospitalization status showed a possible effect modification between hospitalization status and post-COVID-19 anemia.
Discussion
Our study showed that one in three people in a community-based population have anemia 180-days and 365-days after their first COVID-19 diagnosis. Anemia can cause fatigue, a lingering symptom of COVID-19 infection. Though more research is needed, ongoing surveillance of COVID-19 patients for anemia may be an important component of management of long COVID-19.
Graph Neural Networks for Neurological Diseases Detection in EEG Signals
Authors: Awais Muhammad , Belhaouari Samir Brahim , Kassoul Khelil 
Published: July 2023

Abstract
Epilepsy is a neurological disorder that affects a large portion of the world's population1. It is characterized by recurrent seizures2, which are caused by abnormal electrical activity in the brain3. This condition can lead to various symptoms, such as muscle contractions, loss of consciousness, and convulsions. Here, we present a novel approach for detecting seizures and other neurological diseases in electroencephalogram (EEG) signals and highlight the potential of graph neural networks in EEG signal analysis, suggesting that this method could effectively tackle various challenges related to EEG data processing and analysis. The method involves constructing a graph representation of the EEG signal by extracting frequency-based, statistical-based, and Daubechies wavelet transform features from the EEG signals, using a sliding window with 30% overlap. A Graph Convolutional Network (GCN) model, combined with Long Short-Term Memory (LSTM) architecture (GCN-LSTM) and Balanced Random Forest (GCN-BRF), is then employed to process the EEG signals and improve the accuracy of seizure detection. Our experimental findings show that both the GCN-LSTM and GCN-BRF models significantly improved the accuracy of seizure detection, surpassing the performance of previously published methods. Despite reducing the complexity of our approach by decreasing the number of channels used, we observed that its performance remains unchanged. This means that even with fewer channels, our approach continues to deliver comparable results without compromising its effectiveness. We anticipate our work to be a significant step forward in the field of neurodegenerative diseases, illustrating the ability of GCN-LSTM and GCN-BRF models to accurately detect seizures in EEG signals. Our findings highlight the promising potential of graph neural networks in EEG signal analysis, providing a new avenue for future research. Furthermore, the utilization of graph representation offers a clear and visually distinguishable method to differentiate seizure signals from normal signals.
Eco-friendly biosynthesis and characterization of silver nanoparticles from Solanum lycopersicum (Tomato) peel waste and its application in disinfecting metallic surfaces
Authors: Ali Esraa , Abd-Elhalim Basma T. , Hesham Esraa , Ahmed Shimaa , Mostafa Habiba , Gamal Ahmed , El-Sayed Salwa M. , Hemdan Bahaa , Bakry Ashraf , Ebeed Naglaa , Elhariry Hesham , Galal Ahmed , Abu-Hussien Samah H. 
Published: July 2023

Abstract
According to their special physio-chemical properties, Nanoparticles have gained worldwide attention as a new bio-alternative for chemical control agents. This investigation aims to the eco-friendly synthesis of nanosilver particles from tomato peel extract (TPE-AgNPs) and evaluates their characteristics and inhibitory activities against pathogenic bacteria and fungi as well as their role in metallic surface disinfecting. To initiate biosynthesis, tomato peel extract was mixed with silver nitrate (AgNO3) solution until the color changes to reddish brown. Ultraviolet (UV-Visible) spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) analysis, and transmission electron microscopy (TEM) techniques were used to characterize biosynthesized TPE-AgNPs. Results recorded that obtained TPE-AgNPs had a strong score (238nm) of Plasmon resonance (SPR) by SPR of 4.5. Functional groups of carboxyl, hydroxyl, and phenolic groups existed and were detected by the FTIR spectrum. The synthesized TPE-AgNPs had an amorphous nature which was confirmed by XRD analysis. TEM analysis showed spherical TPE-AgNPs sized from 4.44-27.59nm. The biosynthesized TPE-AgNPs had a negative zeta potential of -68.44 mV. The inhibitory activities of synthesized TPE-AgNPs were evaluated against eleven microbial pathogenic using well diffusion method, inhibition zone diameter (IZD) was measured in centimeters. Results showed that B. subtilis and E.coli was the most sensitive pathogens with IZD of 4.0 and 0.92cm, respectively However, L. monocytogenes and S. sonnei were the most resistant pathogens with IZD of 0.92 and 0.90 cm, respectively. Synthesized TPE-AgNPs from tomato peels had good inhibitory potentials against pathogenic fungi with IZD of 3.0 and 0.92cm against A. solani and C. albicans, respectively. Applying the use of TPE-AgNPs as bio disinfectant significantly decreased the microbial load of metallic blades and proves its efficiency as a disinfectant agent after 120min. of contacting. So, more applications on disinfecting metallic surfaces such as dentistry are indeed needed.
Climate Change Impacts on Agricultural Trade and Food Security in Emerging Economies: Case of Southern Africa
Authors: Sabola Gift Andrew 
Published: July 2023

Abstract

Climate change has been a significant threat to sustainable agriculture impacting trade and food security. This research investigates the impacts of climate change on agricultural trade and food security in emerging economies focusing on Southern Africa. The research employed the panel Generalised Method of Moments (GMM) using times series data for the period 2012 to 2021 obtained from a sample of 12 Southern African countries selected based on data availability. The main independent variable to the research was climate change variables (temperature and precipitation). Other control variables included were population growth, food inflation and agricultural growth. The study found significant negative effects of climate change on agriculture trade. Whilst temperature changes were found to have insignificant effects, precipitation changes were found to have significant positive effects. The research recommends concerted efforts towards climate change adaptation and mitigation for sustainable agriculture.
Hair cortisol and endocannabinoids measurement in patients with adrenal incidentalomas: A case-control study
Authors: Mytareli Chrysoula , Athanasouli Fani , Andreadaki Evangelia , Thanasoula Foteini , Angelousi Anna 
Published: July 2023

Abstract
Purpose
The role of endocannabinoids (ECs) in the regulation of the hypothalamo-pituitary-adrenocortical axis has been already studied; however, data are scarce in humans. The aim of our study was to analyse the ECs [anandamide (AEA) and 2-arachidonoylglycerol (2-AG)] and cortisol (F) levels in the hair samples of patients with adrenal incidentalomas (AIs) in comparison with controls and assess their association with the hormone profile.
Methods
Forty-four patients with AIs [32 with non-functioning AIs (NFAIs) and 12 with possible autonomous secretion (PACS)] and 44 controls were recruited. Basal and post-1mg overnight dexamethasone suppression test (ODST) F, adrenocorticotropic hormone, dehydroepiandrosterone sulfate and 24-h urinary free cortisol were analysed. After hair collection, EC and F levels were measured by liquid chromatography tandem-mass spectrometry.
Results
There was no difference between the groups regarding the age, sex and metabolic status. Significantly decreased hair AEA and 2-AG levels were found in patients with AIs compared to controls (p < 0.001 and p = 0.002 respectively) as well as between NFAI or PACS and controls (p < 0.001 or p = 0.002 and p = 0.038 or p = 0.02 respectively). Among the AI patients, EC levels tended to be lower in PACS group. AEA hair levels were negatively correlated with F levels post-1mg ODST (rs=-0.257, p = 0.033). We did not find any significant difference comparing hair F between the groups.
Conclusion
Our findings suggest that hair ECs measurement could be a potential biomarker in the evaluation of patients with AIs, while hair F analysis is not a useful diagnostic test for mild hypercortisolemia.
Percutaneous nephrolithotomy or flexible ureteral lithotripsy, which one is better for patients with upper ureteral calculi of 1.5-2.0cm in diameter
Authors: Chen Wenpu , Hu Hengda , yu Guofeng 
Published: July 2023

Abstract
Purpose
To evaluate the clinical efficacy and safety of flexible ureteral lithotripsy (FURSL) and percutaneous nephrolithotomy (PCNL) in the treatment of upper ureteral impacted calculi (1.5cm to 2.0cm in diameter).
Methods
From December 2018 to October 2022, 104 patients with calculi in the upper ureter received percutaneous nephrolithotomy (PCNL)or flexible ureteroscopic lithotripsy (FURSL) in our institution. The clinical data of the patients in the two groups were retrospectively searched. Stone removal rate, operation time, blood loss, postoperative pain score, postoperative inflammatory factor, postoperative complication rates were compared between the two groups.
Results
A total of 104 patients were included in the study. The stone clearance rate and the secondary surgery rate were 88.89% and 7.41% in the FURSL group, the figures were 97.96% and 2.0% in the PCNL group (p=0.067, 0.198).Compared to patients in FURSL group, patients in the PCNL group had shorter operation time(PCNL 71.81±18.94minutes vs FURSL 86.80±22.49minutes, p=0.0004), fewer complications(PCNL 20.37% vs FURSL 6.12%), and lower postoperative inflammatory factor（p=0.0004）, yet they got more hemoglobin drop（PCNL 13.14±9.81g/L vs FURSL 4.77±3.55g/L, p<0.0001）, higher postoperative pain scores (p=0.0017) in the first three postoperative days.
Conclusion
Both FURSL and PCNL were effective methods for treating upper ureteral stones of 1.5-2.0cm in diameter given that there was an extremely high stone clearance rate and a very low secondary surgery rate. While PCNL effectively reduced operative time, postoperative inflammatory factor and the risk of postoperative complications, it had more hemoglobin drop and postoperative pain scores comparing with FURSL.
Geophysical studies of landslides by electrical resistivity tomography method located in Melekaboud village, Sarpolzahab city, Kermanshah province, Iran.
Authors: salami payam 
Published: July 2023

Abstract

This article focuses on geophysical studies conducted using the geoelectrical method in the vicinity of the Meleh Kaboud landslide near Sarpol Zahab city in Kermanshah province. Due to the extensive and inaccessible nature of the area, a comprehensive and detailed investigation of the region was deemed necessary. To accomplish this, 25 sections, each measuring 200 meters, were meticulously designed and surveyed using a dipole-dipole array. The geoelectric studies revealed that the landslide is situated at a relatively shallow depth, approximately 15 meters from the Earth's surface. Saturated layers with low resistance were identified in the geoelectric sections, indicating the presence of underground water or moist zones within the study area. The integrated image of the region was also examined, providing insights into the location of cracks and waterways. These findings were consistent with the results obtained through the inverse solution and were instrumental in the interpretation of the sections. Subsequently, the article presents a geological analysis of the area, followed by the presentation of results obtained using the dipole-dipole array. After interpreting the 2D sections, the article concludes by discussing the construction of a 3D model based on the obtained data.
Non-coding mutations at enhancer clusters contribute to pancreatic ductal adenocarcinoma
Authors: Wang Jun , Patel Minal , Maniati Eleni , Atanur Santosh , Pal Debosree , Rio-Machin Ana , Heward James , Kocher Hemant , Fitzgibbon Jude , Pradeepa Madapura 
Published: July 2023

Abstract
Non-coding mutations (NCMs) that perturb the function of cis-regulatory elements (CRE, enhancers) contribute to cancer. Due to the vast search space, mutation abundance and indirect activity of non-coding sequences, it is challenging to identify which somatic NCMs are contributing to tumour development and progression. Here, we focus our investigation on the somatic NCMs that are enriched at enhancers from 659 pancreatic ductal adenocarcinoma (PDAC) tumours. We identify cis-regulatory NCMs within PDAC-specific enhancers derived from high and low-grade PDAC cell lines and patient derived organoids using two independent computational approaches. Five such CREs enriched for PDAC associated NCMs are also frequently mutated in other common solid tumours. Functional validation using STARR-seq reporter assays enables the prioritisation of 43 NCMs (7.3%) from a pool of 587 NCMs with 6,082 oligos, that significantly alter reporter enhancer activity compared to wild-type sequences. CRISPRi perturbation of an enhancer cluster harbouring NCMs over long non-coding RNA gene MIR100HG, which hosts a microRNA cluster (mir100-let7a-2-125b-1), leads to the downregulation of MIR100HG accompanied by a significant reduction in the TGF-b pathway (known to induce MIR100HG) and other PDAC critical pathways, including KRAS, p53, MTOR and TNFa signalling. Collectively, we have reported here cis-regulatory NCMs in PDAC proximal to many cancer-relevant genes, and our integrated approach paves way to explore CRE-associated NCMs in other human cancer genomes.