bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ketogenic diet for epilepsy control and enhancement in adaptive behavior
Authors: El-Rashidy Omnia Fathy , Nassar May Fouad , Shokair Wafaa Abdelwahab , El Gendy Yasmin Gamal Abdou 
Published: February 2023

AbstractThe Ketogenic Diet (KD) is gaining attention as a management line in childhood drug resistant epilepsy (DRE). The objective of this study was to highlight KD benefits for Ain Shams University (ASU) Children’s Hospital patients. This cross-sectional study included all patients at the Ketoclinic of ASU Children’s Hospital since it started. Anthropometric measurements and laboratory data were recorded. Chalfont severity score and daily frequency of epileptic attacks were used to evaluate KD efficacy. Vineland test was used to demonstrate the adaptive behavior of a selected group of patients. ASU Children’s Hospital Ketoclinic records included 143 patients. During KD therapy, the weight and height/length assessment showed significant increase with significant decrease in the severity of seizures and its frequency. There were no significant changes in the lipid profile of the patients. Vineland test showed significant improvement in the adaptive behavior in 65% of patients. The Ketoclinic data proves that KD is a tolerable, safe, and effective line of therapy for DRE in children without significant negative impact on their anthropometric measurements or lipid profile. Furthermore, the enhancement in adaptive behavior is a promising finding. It is prudent to recommend wider scale studies for longer duration to demonstrate additional cognitive benefits of KD in pediatric age group.
Synthesis, characterization, and evaluation of Hesperetin nanocrystals for regenerative dentistry
Authors: Alipour Mahdieh , Sharifi Simin , Samiei Mohammad , Shahi Shahriar , Aghazadeh Marziyeh , Dizaj Solmaz Maleki 
Published: February 2023

AbstractHesperetin (HS), a metabolite of hesperidin, is a polyphenolic component of citrus fruits. This ingredient has a potential role in bone strength and the osteogenic differentiation. The bone loss in the orofacial region may occur due to the inflammation response of host tissues. Nanotechnology applications have been harshly entered the field of regenerative medicine to improve the efficacy of the materials and substances. In the current study, the hesperetin nanocrystals were synthesized and characterized. Then, the anti-inflammatory and antioxidative effects of these nanocrystals were evaluated on inflamed human Dental Pulp Stem Cells (hDPSCs) and monocytes (U937). Moreover, the osteoinduction capacity of these nanocrystals was assessed by gene and protein expression levels of osteogenic specific markers including RUNX2, ALP, OCN, Col1a1, and BSP in hDPSCs. The deposition of calcium nodules in the presence of hesperetin and hesperetin nanocrystals was also assessed. The results revealed the successful fabrication of hesperetin nanocrystals with an average size of 100 nm. The levels of TNF, IL6, and reactive oxygen species (ROS) in inflamed hDPSCs and U937 significantly decreased in the presence of hesperetin nanocrystals. Furthermore, these nanocrystals induced osteogenic differentiation in hDPSCs. These results demonstrated the positive and effective role of fabricated nanocrystal forms of this natural ingredient for regenerative medicine purposes.
Exogenous melatonin alleviates neuropathic pain-induced affective disorders by suppressing NF-κB/ NLRP3 pathway and apoptosis
Authors: Mokhtari Tahmineh , Yue Lu-Peng , Hu Li 
Published: February 2023

AbstractIn this study, we aimed to evaluate the anti-inflammatory and anti-apoptotic effects of melatonin (MLT) on neuropathic pain (NP)-induced anxiety and depression in a rat model. Adult male rats were separated into four groups, i.e., Sham-VEH: healthy animals received a vehicle, Sham-MLT (10 mg/kg), and chronic constrictive injury (CCI)-VEH: nerve ligation received the vehicle, and CCI-MLT. Next, we used behavioral tests to evaluate pain severity, anxiety, and depression. Finally, rats were sacrificed for molecular and histopathological studies. Behavioral tests showed that NP could induce depressive- and anxiety-like behaviors. NP activated NF-κB/NLRP3 inflammasome pathways by upregulating NF-κB, NLRP3, ASC, active Caspase-1, also enhancing the concentrations of cytokines (IL-1β and IL-18) in the prefrontal cortex (PFC) and hippocampus (HC). NP upregulated Bax, downregulated Bcl2, and increased cell apoptosis in the HC and PFC. The rats treated with MLT eliminated the effects of NP, as the reduced pain severity, improved anxiety- and depressive-like behaviors, ameliorated NF-κB/NLRP3 inflammasome pathways, and modulated levels of cytokines in the HC and PFC. MLT could promote cell survival from apoptosis by modulating Bax and Bcl2. Therefore, it might be inferred that its anti-inflammatory and anti-apoptotic properties mediate the beneficial effects of MLT in NP-induced affective disorders.
Serum levels of anti-Müllerian hormone influence pregnancy outcomes associated with gonadotropin-releasing hormone antagonist treatment: a retrospective cohort study
Authors: Hou Yanru , Wang Lu , Li Yian , Ai Jiajia , Tian Li 
Published: February 2023

AbstractAs a specific predictor of ovarian reserve, serum anti-Müllerian hormone (AMH) has become an area of intense research interest in the field of assisted reproductive technology. We assessed the relationship between AMH levels and pregnancy outcomes in Chinese patients and investigate the influencing factors of cumulative live birth in patients with high AMH levels. A total of 1379 patients starting their IVF/ICSI cycle were divided into normal (Group A, 1.1–4.0 ng/ml, n = 639) and high (Group B, > 4.0 ng/ml, n = 740) groups by serum AMH levels. Live birth rate (LBR), cumulative live birth rate (CLBR) and cumulative clinical pregnancy rate (CCPR) were also investigated. Compared with Group A, Group B had a significantly higher CLBR (65.80% vs. 43.95%) and CCPR (76.77% vs. 57.14%), respectively. Binomial logistic regression analysis showed that age over 40 years, LH/FSH > 2.5, total Gn dose and Gn duration, and greater than 4000 ng/ml serum E2 levels on HCG day were significantly associated with CLBR in Group B. The AUC value of CLBR averaged 0.664 (ranging from 0.621 to 0.706) (p < 0.001). The patients with high AMH levels had higher CPR, higher LBR, and lower MR with no statistically significant differences, although there were significant improvements in CLBR. Advanced age (> 40 years) still impacted CLBR, even in women with good ovarian reserves. Consequently, it is still recommended that patients over 40 years old with high AMH levels actively receive IVF treatment if they seek to become pregnant. PCOS diagnoses did not influence the CLBR. In summary, this study showed that serum AMH levels could positively predict patient ovarian responses and further affect pregnancy outcomes.
Machine learning classifiers predict key genomic and evolutionary traits across the kingdoms of life
Authors: Hallee Logan , Khomtchouk Bohdan B. 
Published: February 2023

AbstractIn this study, we investigate how an organism’s codon usage bias can serve as a predictor and classifier of various genomic and evolutionary traits across the domains of life. We perform secondary analysis of existing genetic datasets to build several AI/machine learning models. When trained on codon usage patterns of nearly 13,000 organisms, our models accurately predict the organelle of origin and taxonomic identity of nucleotide samples. We extend our analysis to identify the most influential codons for phylogenetic prediction with a custom feature ranking ensemble. Our results suggest that the genetic code can be utilized to train accurate classifiers of taxonomic and phylogenetic features. We then apply this classification framework to open reading frame (ORF) detection. Our statistical model assesses all possible ORFs in a nucleotide sample and rejects or deems them plausible based on the codon usage distribution. Our dataset and analyses are made publicly available on GitHub and the UCI ML Repository to facilitate open-source reproducibility and community engagement.
Simple curettage and allogeneic cancellous bone chip impaction grafting in solitary enchondroma of the short tubular bones of the hand
Authors: Park Ho Youn , Joo Min Wook , Choi Youn-Ho , Chung Yang-Guk , Park Chan Jin 
Published: February 2023

AbstractEnchondroma is the most common bone tumor in the hand. While standard surgical procedure is intra-lesional excision and bone grafting, there is a dispute between allogeneic bone, autogenous bone, and synthetic bone substitute grafting. Diverse adjuvant treatments have been introduced to reduce recurrence, but results are mixed with controversies. Meanwhile, whether existing descriptive classification could predict treatment outcome remains unclear. Thus, we reviewed patients with solitary enchondroma of the hand who underwent simple curettage followed by allogeneic cancellous bone chip impaction grafting. Eighty-eight patients with more than 5 years of follow-up were enrolled. Demographic data, local recurrence, and complications were reviewed. Duration of consolidation and the difference according to Takigawa classification were assessed. Range of motion (ROM), and functional scores were also evaluated. There were 51 women and 37 men, with a mean age of 37.9 years. Mean follow-up was 10.2 years. Recurrence occurred only in one patient. There was no complication. Mean postoperative total active motions of fingers and thumb were 239° and 132.9°. Mean modified Disabilities of the Arm, Shoulder, Hand score, and Musculoskeletal Tumor Society Score were 1.63, and 99.2 at the last follow-up. Consolidation, ROM, and functional scores according to Takigawa classification showed no significant differences. This study suggests that simple curettage with impaction grafting of allogeneic cancellous bone chip is a feasible method for treating solitary enchondromas involving short tubular bone of the hand with good long-term outcomes. Postoperative recurrence and complication rates were very low. Radiographic and clinical results were good regardless of the previous radiological classification.
Reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach
Authors: Meng Qingxi , Chandak Shubham , Zhu Yifan , Weissman Tsachy 
Published: February 2023

AbstractThe amount of data produced by genome sequencing experiments has been growing rapidly over the past several years, making compression important for efficient storage, transfer and analysis of the data. In recent years, nanopore sequencing technologies have seen increasing adoption since they are portable, real-time and provide long reads. However, there has been limited progress on compression of nanopore sequencing reads obtained in FASTQ files since most existing tools are either general-purpose or specialized for short read data. We present NanoSpring, a reference-free compressor for nanopore sequencing reads, relying on an approximate assembly approach. We evaluate NanoSpring on a variety of datasets including bacterial, metagenomic, plant, animal, and human whole genome data. For recently basecalled high quality nanopore datasets, NanoSpring, which focuses only on the base sequences in the FASTQ file, uses just 0.35–0.65 bits per base which is 3–6$$\times$$
×
lower than general purpose compressors like gzip. NanoSpring is competitive in compression ratio and compression resource usage with the state-of-the-art tool CoLoRd while being significantly faster at decompression when using multiple threads (> 4$$\times$$
×
faster decompression with 20 threads). NanoSpring is available on GitHub at https://github.com/qm2/NanoSpring.
Automated machine learning recognition to diagnose flood resilience of railway switches and crossings
Authors: Sresakoolchai Jessada , Hamarat Mehmet , Kaewunruen Sakdirat 
Published: February 2023

AbstractThe increase in demand for railway transportation results in a significant need for higher train axle load and faster speed. Weak and sensitive trackforms such as railway switches and crossings (or called ‘turnout’) can suffer from such an increase in either axle loads or speeds. Moreover, railway turnout supports can deteriorate from other incidences due to extreme weather such as floods which undermine cohesion between ballast leading to ballast washaway or loss of support under turnout structures. In this study, new intelligent automation based on machine learning pattern recognition has been built to detect and predict the deterioration of railway turnouts exposed to flooding conditions which is the scope of this study. Since the turnout system is very complex by nature, different features and smart filtering are explored to find the potential features for deep learning. Nonlinear finite element models validated by actual field measurements are used to mimic the dynamic behaviors of turnout supports under flooding conditions. The study exhibits that the novel recognition model can achieve more than 98% accuracy, yielding the potential capability to recognize and classify turnout support deteriorations facing extreme weather conditions which will be beneficial for responsible parties to schedule and plan maintenance activities.
H-CoNiSe2/NC dodecahedral hollow structures for high-performance supercapacitors
Authors: Salehan P. , Ensafi Ali A. , Andikaey Z. , Rezaei B. 
Published: February 2023

AbstractThe synergistic effect between metal ions and increasing the surface area leads to the fabrication of supercapacitor materials with high capacities. It is predicted that transition metal selenide compounds will be ideal electrode materials for supercapacitors. However, the defects of poor conductivity and volume expansion of the compounds are fundamental problems that must be solved. In this work, we successfully synthesized the cobalt–nickel selenide nitrogen-doped carbon (H-CoNiSe2/NC) hollow polyhedral composite structure using ZIF-67 as a precursor. The CoSe2and NiSe2nanoparticles embedded in the NC polyhedral framework offer a wealth of active sites for the whole electrode. Moreover, the presence of the NC structure in the proposed composite can simultaneously lead to improved conductivity and reduce the volume effect created during the cycling procedure. The H-CoNiSe2/NC electrode provides high specific capacity (1131 C/g at 1.0 A/g) and outstanding cyclic stability (90.2% retention after 6000 cycles). In addition, the H-CoNiSe2/NC//AC hybrid supercapacitor delivers ultrahigh energy density and power density (81.9 Wh/kg at 900 W/kg) and excellent cyclic stability (92.1% of the initial capacitance after 6000 cycles). This study will provide a supercapacitor electrode material with a high specific capacity for energy storage devices.Please confirm the corresponding affiliation for the 'Ali A. Ensafi' author is correctly identified.Error during converting author query response. Please check the eproofing link or feedback pdf for details
Evidence of structural segmentation of the Uttarakhand Himalaya and its implications for earthquake hazard
Authors: Mandal Prantik , Prathigadapa Raju , Srinivas D. , Saha Satish , Saha Gokul 
Published: February 2023

AbstractThe earthquake hazard associated with the Main Himalayan Thrust (MHT) is a critical issue for India and its neighbouring countries in the north. We used data from a dense seismic network in Uttarakhand, India, to model the lateral variations in the depths of MHT (2–6% drop in Vsat 12–21 km depths), Moho (a sharp increase in Vs(by ~ 0.5–0.7 km/s) at 39–50 km depths) and lithosphere (a marked decrease in Vs(~ 1–3%) at 136–178 km depths), across the Himalayan collisional front. Our joint inversion of radial PRFs and group velocity dispersion data of Rayleigh waves detects three NNE trending transverse lithospheric blocks segmenting the lithosphere in Uttarakhand Himalaya, which spatially correlate well with the northward extension of the Delhi -Haridwar Indian basement ridge, an inferred tectonic boundary and great boundary fault, respectively. Our radial receiver function imaging detects highly deformed and segmented crustal and lithospheric structures associated with three mapped transverse lithospheric blocks, suggesting a reduction in rupture lengths of future earthquakes, thereby, reducing earthquake hazards in Uttarakhand.
Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms
Authors: Sun Weijie , Kalmady Sunil Vasu , Sepehrvand Nariman , Salimi Amir , Nademi Yousef , Bainey Kevin , Ezekowitz Justin A. , Greiner Russell , Hindle Abram , McAlister Finlay A. , Sandhu Roopinder K. , Kaul Padma 
Published: February 2023

AbstractThe feasibility and value of linking electrocardiogram (ECG) data to longitudinal population-level administrative health data to facilitate the development of a learning healthcare system has not been fully explored. We developed ECG-based machine learning models to predict risk of mortality among patients presenting to an emergency department or hospital for any reason. Using the 12-lead ECG traces and measurements from 1,605,268 ECGs from 748,773 healthcare episodes of 244,077 patients (2007–2020) in Alberta, Canada, we developed and validated ResNet-based Deep Learning (DL) and gradient boosting-based XGBoost (XGB) models to predict 30-day, 1-year, and 5-year mortality. The models for 30-day, 1-year, and 5-year mortality were trained on 146,173, 141,072, and 111,020 patients and evaluated on 97,144, 89,379, and 55,650 patients, respectively. In the evaluation cohort, 7.6%, 17.3%, and 32.9% patients died by 30-days, 1-year, and 5-years, respectively. ResNet models based on ECG traces alone had good-to-excellent performance with area under receiver operating characteristic curve (AUROC) of 0.843 (95% CI: 0.838–0.848), 0.812 (0.808–0.816), and 0.798 (0.792–0.803) for 30-day, 1-year and 5-year prediction, respectively; and were superior to XGB models based on ECG measurements with AUROC of 0.782 (0.776–0.789), 0.784 (0.780–0.788), and 0.746 (0.740–0.751). This study demonstrates the validity of ECG-based DL mortality prediction models at the population-level that can be leveraged for prognostication at point of care.
Analytical modelling of salient pole synchronous generators under eccentricity faults by including stator slotting effect
Authors: Nasiri Samaneh , Ojaghi Mansour 
Published: February 2023

AbstractHere, a dynamic analytical model is provided for salient pole synchronous generators (SPSGs) under different eccentricity faults. A useful technique is developed first to describe the rotor position‐dependent non‐uniform air gap distribution by a proper function in the healthy state, which includes the stator slotting effect. Then, the exact air gap function is used along with the modified winding function theory to extract non‐integral equations for computing the SPSG various inductances that are playing critical role during analytical modelling and simulation of the machine. Afterword, the air gap function and the inductance equations are modified to include all types of the eccentricity fault. A 3 kW SPSG is simulated and then tested in laboratory under the healthy and the mixed eccentricity (ME) conditions. There are good accordance between the simulation and corresponding experimental results; they show that some harmonic components are introduced in the rotor and the stator currents due to the ME fault whose frequencies are integer multiples of the rotor speed frequency and whose amplitudes increase by increasing the fault severity. The load level change also affects the amplitudes of the harmonics.
Stationsleitung 4.0
Authors: Roßius Sabrina , Reimer Ann-Christin 
Published: February 2023

ZusammenfassungWie ein Pilotprojekt am Alexianer Krankenhaus Hedwigshöhe ein starkes, autark handelndes Pflegemanagement fördert und warum der Schraubendreher nicht zum Sägen taugt.
Advancing Reproductive Health through Policy-Engaged Research in Abortion Care
Authors: Munro Sarah B. , Dunn Sheila , Guilbert Edith R. , Norman Wendy V. 
Published: February 2023

AbstractMifepristone medication abortion was first approved in China and France more than 30 years ago and is now used in more than 60 countries worldwide. It is a highly safe and effective method that has the potential to increase population access to abortion in early pregnancy, closer to home. In both Canada and the United States, the initial regulations for distribution, prescribing, and dispensing of mifepristone were highly restricted. However, in Canada, where mifepristone was made available in 2017, most restrictions on the medication were removed in the first year of its availability. The Canadian regulation of mifepristone as a normal prescription makes access possible in community primary care through a physician or nurse practitioner prescription, which any pharmacist can dispense. In this approach, people decide when and where to take their medication. We explore how policy-maker-engaged research advanced reproductive health policy and facilitated this rapid change in Canada. We discuss the implications of these policy advances for self-management of abortion and demonstrate how in Canada patients “self-manage” components of the abortion process within a supportive health care system.
Emergency politics, mass sentiment and the EU during Covid
Authors: Wang Chendi , Bojar Abel , Oana Ioana-Elena , Truchlewski Zbigniew 
Published: February 2023

AbstractDuring crises, do emergency politics impair the EU polity by alienating Europeans? Recent literature suggests that executive decisions in hard times can spur negative European sentiment, increase polarisation in the public and thus create more problems than solutions. The Covid-19 pandemic offers an ideal opportunity to study this important issue. However, studying mass sentiment towards the EU is mostly constrained by imperfect survey data. We tackle this challenge with an empirical strategy that combines two original data sources: first, we use policy process analysis to identify key EU decisions; second, we leverage Twitter data to measure sentiment. As a result, we can study whether key EU decisions impacted EU sentiment and whether this impact is conditional on the level of EU competence, prior politicisation and problem pressure. We find that EU decisions impact EU sentiment positively and do not polarise it (even among highly politicised decisions). Low prior politicisation and healthcare-related decisions increase the positive impact of EU actions. There is thus no punishment of the EU for acting outside its remit. Our findings have important implications for the politics of polity maintenance in the EU.