bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulation study of water and gas injection process into the Azadegan reservoir for enhanced oil recovery
Authors: Farahbod Farshad 
Published: June 2023

AbstractIt is necessary to improve oil production from reservoirs. Various methods have been proposed to increase oil extraction from reservoir. Each method has specific challenges. In this research, the effect of water and gas injection in to Azadegan reservoir has been analyzed. Azadegan oil field is located south of Iran. In this study, water, immiscible gas and water alternating gas injected to reservoir and its effect on enhanced oil recovery have been investigated. Finally, a comparison between results of methods is provided. Results show that effective method for enhanced oil recovery is immiscible gas injection with 46% oil production efficiency and water alternating gas injection with 36% oil production efficiency. This study shows that oil production efficiency can be increased if duration of gas injection is increased. This study shows, increasing viscosity of water in water alternating gas scenario did not improve the production of Azadegan reservoir.
Fractures in people with epilepsy: A nationwide population‐based cohort study
Authors: Babunovska Marija , Jovanovski Aleksandar , Boskovski Bojan , Foteva Marta , Kuzmanovski Igor , Trencevska Gordana Kiteva , Cvetkovska Emilija 
Published: June 2023

AbstractObjectiveThe objective of this study was to determine the age, gender, and site‐specific prevalence of fractures in people with epilepsy (PWE) and matched general population comparators in a nationwide study in North Macedonia between 2015 and 2018.MethodsPWE and matched controls were selected through a systematic search of the electronic National Health System (eNHS). We determined the period prevalence (PP) of all site‐specific fractures. We also calculated gender and age‐specific incidence rate ratios (IRR) for various fractures. Odds ratios (ORs) and risk ratios (RR) were estimated for the number and type of ASM as well as comorbid conditions.ResultsOut of 13 818 prevalent epilepsy cases, 6383 (46.2%) were females, and 7435 (53.8%) were males. 109 PWE out of 1000 had at least one fracture during the study period and ~8 people out of 1000 in the general population. The most frequent sites in terms of PP both in PWE and controls, were fractures of the lower arm, hip and femur, and lower leg. Significant differences in PP for all fracture locations were observed between PWE and controls (P < 0.001). The noticeable differences of ∼100 times higher PP were observed for fractures of the skull and jaw in PWE. IRR of any fracture in PWE was 272.84/10 000 person‐years; higher in the older age groups and among people who received >2 ASM. Fracture risk was increased with the use of >2 ASM (OR: 1.56; 95% CI: 1.32‐1.84 and RR: RR: 1.32). The presence of comorbidities also increased fractures risk (OR: 1.24; 95% CI: 1.10‐1.38).SignificanceThis population‐based study depicts a higher fracture prevalence in PWE compared to the general population. A higher number of ASM and the presence of comorbidities increase the risk of fractures and targeted prevention might be needed in those subgroups of PWE.
An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1‐weighted images
Authors: Wang Yida , He Naying , Zhang Chunyan , Zhang Youmin , Wang Chenglong , Huang Pei , Jin Zhijia , Li Yan , Cheng Zenghui , Liu Yu , Wang Xinhui , Chen Chen , Cheng Jingliang , Liu Fangtao , Haacke Ewart Mark , Chen Shengdi , Yang Guang , Yan Fuhua 
Published: June 2023

AbstractParkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution in deep gray matter (DGM) nuclei. We hypothesized that deep learning (DL) could be used to automatically segment all DGM nuclei and use relevant features for a better differentiation between PD and healthy controls (HC). In this study, we proposed a DL‐based pipeline for automatic PD diagnosis based on QSM and T1‐weighted (T1W) images. This consists of (1) a convolutional neural network model integrated with multiple attention mechanisms which simultaneously segments caudate nucleus, globus pallidus, putamen, red nucleus, and substantia nigra from QSM and T1W images, and (2) an SE‐ResNeXt50 model with an anatomical attention mechanism, which uses QSM data and the segmented nuclei to distinguish PD from HC. The mean dice values for segmentation of the five DGM nuclei are all >0.83 in the internal testing cohort, suggesting that the model could segment brain nuclei accurately. The proposed PD diagnosis model achieved area under the the receiver operating characteristic curve (AUCs) of 0.901 and 0.845 on independent internal and external testing cohorts, respectively. Gradient‐weighted class activation mapping (Grad‐CAM) heatmaps were used to identify contributing nuclei for PD diagnosis on patient level. In conclusion, the proposed approach can potentially be used as an automatic, explainable pipeline for PD diagnosis in a clinical setting.
Estimating health care costs at scale in low‐ and middle‐income countries: Mathematical notations and frameworks for the application of cost functions
Authors: d’Elbée Marc , Terris‐Prestholt Fern , Briggs Andrew , Griffiths Ulla Kou , Larmarange Joseph , Medley Graham Francis , Gomez Gabriella Beatriz 
Published: June 2023

AbstractAppropriate costing and economic modeling are major factors for the successful scale‐up of health interventions. Various cost functions are currently being used to estimate costs of health interventions at scale in low‐ and middle‐income countries (LMICs) potentially resulting in disparate cost projections. The aim of this study is to gain understanding of current methods used and provide guidance to inform the use of cost functions that is fit for purpose. We reviewed seven databases covering the economic and global health literature to identify studies reporting a quantitative analysis of costs informing the projected scale‐up of a health intervention in LMICs between 2003 and 2019. Of the 8725 articles identified, 40 met the inclusion criteria. We classified studies according to the type of cost functions applied—accounting or econometric—and described the intended use of cost projections. Based on these findings, we developed new mathematical notations and cost function frameworks for the analysis of healthcare costs at scale in LMICs setting. These notations estimate variable returns to scale in cost projection methods, which is currently ignored in most studies. The frameworks help to balance simplicity versus accuracy and increase the overall transparency in reporting of methods.
Pelvic floor ultrasound evaluation in the diagnosis of exposure of synthetic implanted materials in the lower urinary tract
Authors: Frigerio Matteo , Barba Marta , Marino Giuseppe , Volonte Silvia , Cola Alice 
Published: June 2023

AbstractObjectiveTo evaluate the diagnostic performance of pelvic floor ultrasound (PFUS) to recognize prosthetics exposure in the bladder and/or urethra in women with lower urinary tract symptoms (LUTS).MethodsA cross‐sectional study evaluating patients with LUTS after mesh/sling surgery. PFUS was performed with both transvaginal (TVUS) and translabial (TLUS) approaches. A distance of 1 mm or less from the bladder and/or urethra was considered highly suspect for mesh exposure. After PFUS, patients underwent diagnostic urethrocystoscopy.ResultsA total of 100 consecutive women were analyzed. According to urethrocystoscopy, the rate of tape exposure in the lower urinary tract was 3%. PFUS showed 100% sensitivity and 98%–100% specificity in detecting lower urinary tract mesh exposure. The negative predictive value was 100% and the positive predictive value ranged from 33% to 50% for urethral and 100% for bladder exposure.ConclusionsPFUS represents an effective and reliable non‐invasive screening test to exclude prosthetics exposure in the bladder and/or urethra in women with LUTS.
Lobeline: A multifunctional alkaloid modulates cholinergic and glutamatergic activities
Authors: Remya Chandran , Dileep Kalarickal V. , Variyar Elessery J. , Omkumar Ramakrishnapillai V. , Sadasivan Chittalakkottu 
Published: June 2023

AbstractDeveloping drugs for Alzheimer's disease (AD) is an extremely challenging task due to its devastating pathology. Previous studies have indicated that natural compounds play a crucial role as lead molecules in the development of drugs. Even though, there are remarkable technological advancements in the isolation and synthesis of natural compounds, the targets for many of them are still unknown. In the present study, lobeline, a piperidine alkaloid has been identified as a cholinesterase inhibitor through chemical similarity assisted target fishing method. The structural similarities between lobeline and donepezil, a known acetylcholinesterase (AChE) inhibitor encouraged us to hypothesize that lobeline may also exhibit AChE inhibitory properties. It was further confirmed by in silico, in vitro and biophysical studies that lobeline could inhibit cholinesterase. The binding profiles indicated that lobeline has a higher affinity for AChE than BChE. Since excitotoxicity is one of the major pathological events associated with AD progression, we also investigated the neuroprotective potential of lobeline against glutamate mediated excitotoxicity in rat primary cortical neurons. The cell based NMDA receptor (NMDAR) assay with lobeline suggested that neuroprotective potential of lobeline is mediated through the blockade of NMDAR activity.
Aspirin deprescribing in patients on oral anticoagulation for atrial fibrillation or venous thromboembolism: A national survey of clinician practices
Authors: Ou Sylvia , Pozzolano Erin , Datta Avisek , Bhaumik Dulal , Shapiro Nancy 
Published: June 2023

AbstractIntroductionConcomitant use of oral anticoagulation (OAC) and aspirin increases bleeding risk without decreasing thromboembolic events compared with OAC monotherapy. Weak guideline recommendations and limited data exist for deprescribing aspirin for primary prevention or stable coronary artery disease in patients already on OAC for atrial fibrillation (AF) or venous thromboembolism (VTE).ObjectivesThe objective of this study was to identify aspirin deprescribing practices among clinicians for patients on OAC for AF or VTE and concomitant aspirin for non‐compelling reasons.MethodsA cross‐sectional, national survey was electronically distributed to pharmacists and non‐pharmacists (physicians, nurse practitioners, physician assistants). Co‐primary end points were composite aspirin discontinuation rates in patients on OAC for AF or VTE in primary prevention and stable coronary artery disease (CAD) cases. Key secondary end points were clinician comfort level with deprescribing aspirin and availability of institutional protocols.ResultsThree hundred four responses were included: 212 (69.7%) pharmacists and 92 (30.3%) non‐pharmacists. Mean age of respondents was 35.4 years, and 37.4% male. In the primary prevention cases, pharmacists were more likely to discontinue aspirin than non‐pharmacists (76.7% vs. 54.6%, p < 0.001). In the stable CAD cases, composite rates of aspirin discontinuation by pharmacists and non‐pharmacists were similar (41.7% vs. 40.1%, p = 0.140). More pharmacists than non‐pharmacists stated that their aspirin deprescribing decisions were independent of the type of OAC that was used (60.4% vs. 35.9%, p < 0.001). Pharmacists were more likely to discontinue aspirin after discussing with patients compared with non‐pharmacists (62.7% vs. 47.8%, p = 0.017). 27.3% of clinicians reported having a protocol to deprescribe aspirin at their institution/clinic.ConclusionThere are variations in aspirin deprescribing practices among clinicians in patients on OAC for AF or VTE and without compelling indications for aspirin. Further studies and stronger recommendations are warranted to guide clinicians regarding optimal antithrombotic therapy in these scenarios. Lack of institutional protocols for aspirin deprescribing creates opportunities for future quality improvement initiatives.
Breast cancer, alcohol, and phosphate toxicity
Authors: Brown Ronald B. , Bigelow Philip , Dubin Joel A. , Neiterman Elena 
Published: June 2023

AbstractAlcohol consumption is associated with an increased risk of breast cancer, even at low alcohol intake levels, but public awareness of the breast cancer risk associated with alcohol intake is low. Furthermore, the causative mechanisms underlying alcohol's association with breast cancer are unknown. The present theoretical paper uses a modified grounded theory method to review the research literature and propose that alcohol's association with breast cancer is mediated by phosphate toxicity, the accumulation of excess inorganic phosphate in body tissue. Serum levels of inorganic phosphate are regulated through a network of hormones released from the bone, kidneys, parathyroid glands, and intestines. Alcohol burdens renal function, which may disturb the regulation of inorganic phosphate, impair phosphate excretion, and increase phosphate toxicity. In addition to causing cellular dehydration, alcohol is an etiologic factor in nontraumatic rhabdomyolysis, which ruptures cell membranes and releases inorganic phosphate into the serum, leading to hyperphosphatemia. Phosphate toxicity is also associated with tumorigenesis, as high levels of inorganic phosphate within the tumor microenvironment activate cell signaling pathways and promote cancer cell growth. Furthermore, phosphate toxicity potentially links cancer and kidney disease in onco‐nephrology. Insights into the mediating role of phosphate toxicity may lead to future research and interventions that raise public health awareness of breast cancer risk and alcohol consumption.
Antidementia medication acetylcholinesterase inhibitors have therapeutic benefits on osteoporotic bone by attenuating osteoclastogenesis and bone resorption
Authors: Li Shangfu , Teguh Dian , Wu Depeng , Liu Lesong , Hu Chaofeng , Yuan Jinbo , Inderjeeth Charles A. , Xu Jiake 
Published: June 2023

AbstractThis study was designed to determine whether the use of acetylcholinesterase inhibitors (AChEIs), a group of drugs that stimulate acetylcholine receptors and are used to treat Alzheimer's disease (AD), is associated with osteoporosis protection and inhibition of osteoclast differentiation and function. Firstly, we examined the effects of AChEIs on RANKL‐induced osteoclast differentiation and function with osteoclastogenesis and bone resorption assays. Next, we investigated the impacts of AChEIs on RANKL‐induced nuclear factor κB and NFATc1 activation and expression of osteoclast marker proteins CA‐2, CTSK and NFATc1, and dissected the MAPK signaling in osteoclasts in vitro by using luciferase assay and Western blot. Finally, we assessed the in vivo efficacy of AChEIs using an ovariectomy‐induced osteoporosis mouse model, which was analyzed using microcomputed tomography, in vivo osteoclast and osteoblast parameters were assessed using histomorphometry. We found that Donepezil and Rivastigmine inhibited RANKL‐induced osteoclastogenesis and impaired osteoclastic bone resorption. Moreover, AChEIs reduced the RANKL‐induced transcription of Nfatc1, and expression of osteoclast marker genes to varying degrees (mainly Donepezil and Rivastigmine but not Galantamine). Furthermore, AChEIs variably inhibited RANKL‐induced MAPK signaling accompanied by downregulation of AChE transcription. Finally, AChEIs protected against OVX‐induced bone loss mainly by inhibiting osteoclast activity. Taken together, AChEIs (mainly Donepezil and Rivastigmine) exerted a positive effect on bone protection by inhibiting osteoclast function through MAPK and NFATc1 signaling pathways through downregulating AChE. Our findings have important clinical implications that elderly patients with dementia who are at risk of developing osteoporosis may potentially benefit from therapy with the AChEI drugs. Our study may influence drug choice in those patients with both AD and osteoporosis.
Synthesis of nalbuphine and investigation of several mixtures of nalbuphine with other drugs for BALB/c mice anesthesia
Authors: Taghizadeh Mohammad Javad , Hajizade Abbas 
Published: June 2023

AbstractIn this research, the conversion of thebaine into oxycodone was achieved using oxidizing reagents, with a yield of 80%. Subsequently, oxycodone was converted into oxymorphone in the presence of an acidic environment, resulting in a yield of 55%. The synthesized oxymorphone was then de‐methylated using ethyl chloroformate to obtain the intermediate noroxymorphone. The latter was further transformed into nalbuphone using cyclobutyl methyl bromide reagent, with a yield of 82%. Finally, nalbuphone was converted into nalbuphine using a reducing reagent, with a yield of 75%. The identification of all intermediates was ensured through the use of NMR, FT‐IR, Mass, and HPLC spectroscopy. The chemical transformations were primarily associated with the formation of noroxymorphone, which served as a crucial intermediate in the synthesis of nalbuphin. Additionally, the effects of three drugs, namely azaperone, medetomidine, and nalbuphine, were investigated on BALB/c mice. The results showed that the best formulation for short‐term anesthesia of mice was a combination of the three drugs, each at a concentration of 1 mg/kg of body weight.
Brain‐derived neurotrophic factor in degenerative retinal diseases: Update and novel perspective
Authors: Zhang Qing‐Qing , Qu Yi 
Published: June 2023

AbstractDysfunction and death of neuronal cells are cardinal features of degenerative retinal diseases that are known to arise as the disease progresses. Increasingly evidence suggests that abnormal expression of brain‐derived neurotrophic factor (BDNF) may serve as an obligatory relay of the dysfunction and death of neuronal cells in degenerative retinal diseases. Although disorder of BDNF, whether depletion or augmentation, has been connected with neuronal apoptosis and neuroinflammation, the exact mechanisms underlying the effect of impaired BDNF expression on degenerative retinal diseases remain unclear. Here, we present an overview of how BDNF is linked to pathological mechanism of retinal degenerative diseases, summarize BDNF‐based treatment strategies, and discuss possible research perspectives in the future.
Extrinsic Laryngeal Muscle Tension in Primary Muscle Tension Dysphonia with Shear Wave Elastography
Authors: Shembel Adrianna C. , Morrison Robert A. , Fetzer David T. , Patterson‐Lachowicz Amber , McDowell Sarah , Comstock Smeltzer Julianna C. , Mau Ted 
Published: June 2023

ObjectivesIt has been assumed that patients with primary muscle tension dysphonia (pMTD) have more extrinsic laryngeal muscle (ELM) tension, but tools to study this phenomenon lack. Shear wave elastography (SWE) is a potential method to address these shortcomings. The objectives of this study were to apply SWE to the ELMs, compare SWE measures to standard clinical metrics, and determine group differences in pMTD and typical voice users before and after vocal load.MethodsSWE measurements of the ELMs from ultrasound examinations of the anterior neck, supraglottic compression severities from laryngoscopic images, cepstral peak prominences (CPP) from voice recordings, and self‐perceptual ratings of vocal effort and discomfort were obtained in voice users with (N = 30) and without (N = 35) pMTD, before and after a vocal load challenge.ResultsELM tension significantly increased from rest‐to‐voiced conditions in both groups. However, the groups were similar in their ELM stiffness levels at SWE at baseline, during vocalization, and post‐vocal load. Levels of vocal effort and discomfort and supraglottic compression were significantly higher and CPP was significantly lower in the pMTD group. Vocal load had a significant effect on vocal effort and discomfort but not on laryngeal or acoustic patterns.ConclusionSWE can be used to quantify ELM tension with voicing. Although the pMTD group reported significantly higher levels of vocal effort and vocal tract discomfort and, on average, exhibited significantly more severe supraglottic compression and lower CPP values, there were no group differences in levels of ELM tension using SWE.Level of Evidence2 Laryngoscope, 133:3482–3491, 2023
Adapting model‐based deep learning to multiple acquisition conditions: Ada‐MoDL
Authors: Pramanik Aniket , Bhave Sampada , Sajib Saurav , Sharma Samir D. , Jacob Mathews 
Published: June 2023

PurposeThe aim of this work is to introduce a single model‐based deep network that can provide high‐quality reconstructions from undersampled parallel MRI data acquired with multiple sequences, acquisition settings, and field strengths.MethodsA single unrolled architecture, which offers good reconstructions for multiple acquisition settings, is introduced. The proposed scheme adapts the model to each setting by scaling the convolutional neural network (CNN) features and the regularization parameter with appropriate weights. The scaling weights and regularization parameter are derived using a multilayer perceptron model from conditional vectors, which represents the specific acquisition setting. The perceptron parameters and the CNN weights are jointly trained using data from multiple acquisition settings, including differences in field strengths, acceleration, and contrasts. The conditional network is validated using datasets acquired with different acquisition settings.ResultsThe comparison of the adaptive framework, which trains a single model using the data from all the settings, shows that it can offer consistently improved performance for each acquisition condition. The comparison of the proposed scheme with networks that are trained independently for each acquisition setting shows that it requires less training data per acquisition setting to offer good performance.ConclusionThe Ada‐MoDL framework enables the use of a single model‐based unrolled network for multiple acquisition settings. In addition to eliminating the need to train and store multiple networks for different acquisition settings, this approach reduces the training data needed for each acquisition setting.