bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing diverse evidence to improve conservation decision‐making
Authors: Christie Alec P. , Morgan William H. , Salafsky Nick , White Thomas B. , Irvine Robyn , Boenisch Nicolas , Chiaravalloti Rafael M. , Kincaid Kate , Rezaie Ali Mohammad , Yamashita Hiromi , Sutherland William J. 
Published: September 2023

AbstractMeeting the urgent need to protect and restore ecosystems requires effective decision‐making through wisely considering a range of evidence. However, weighing and assessing evidence to make complex decisions is challenging, particularly when evidence is of diverse types, subjects, and sources, and varies greatly in its quality and relevance. To tackle these challenges, we present the Balance Evidence Assessment Method (BEAM), an intuitive way to weigh and assess the evidence relating to the core assumptions underpinning the planning and implementation of conservation projects, strategies, and actions. Our method directly tackles the question of how to bring together diverse evidence whilst assessing its relevance, reliability, and strength of support for a given assumption, which can be mapped, for example to a Theory of Change. We consider how simple principles and safeguards in applying this method could help to respectfully, and equitably, include more local forms of knowledge when assessing assumptions, such as by ensuring diverse groups of individuals contribute and assess evidence. The method can be flexibly applied within existing decision‐making tools, platforms, and frameworks whenever assumptions (i.e., claims and hypotheses) are made. This method could greatly facilitate and improve the weighing of diverse evidence to make decisions in a range of situations, from local projects to global policy platforms.
Letters away from the looking glass: Developmental trajectory of mirrored and rotated letter processing within words
Authors: Fernandes Tânia , Velasco Sofia , Leite Isabel 
Published: September 2023

AbstractDiscrimination of reversible mirrored letters (e.g., d and b) poses a challenge when learning to read as it requires overcoming mirror invariance, an evolutionary‐old perceptual tendency of processing mirror images as equivalent. The present study investigated when, in reading development, mirror‐image discrimination becomes automatic during visual word recognition. The developmental trajectory of masked priming effects was investigated from 2nd to 6th grade and in adults, by manipulating letter type (nonreversible; reversible) and prime condition (control; identity; mirrored; rotated). Standardized identity priming increased along reading development. Beginning readers showed mirror invariance during reversible and nonreversible letter processing. A mirror cost (slower word recognition in mirrored‐letter than identity prime condition) was found by 5th‐grade but only for reversible letters. By 6th grade, orthographic processing was no longer captive of mirror invariance. A multiple linear regression showed that letter representations, but not phonological processes or age, were a reliable predictor of the rise of mirror‐image discrimination in 2nd–4th‐graders. The present results suggest a protracted development of automatic mirror‐image discrimination during orthographic processing, contingent upon the quality of abstract letter representations.Research Highlights
We traced the developmental trajectory of mirrored‐letter and rotated‐letter priming effects (e.g., ibea and ipea as primes of IDEA) in visual word recognition.
Beginning readers (2nd–4th‐graders) showed mirror invariance and plane‐rotation sensitivity in orthographic processing, thus still being susceptible to the perceptual biases in charge in object recognition.
A mirror cost was found in 5th‐graders but only for reversible letters; orthographic processing was no longer captive of mirror invariance by 6th‐grade.
The automation of mirror‐image discrimination during orthographic processing depends on the quality of letter representations but not on phonological processes or age.
Type 1 diabetes in the pancreas: A histological perspective
Authors: Leete Pia 
Published: September 2023

AbstractAimsThis review aims to introduce research in the pancreas to a broader audience. The pancreas is a heterocrine gland residing deep within our abdominal cavity. It is the home to our islets, which play a pivotal role in regulating metabolic homeostasis. Due to its structure and location, it is an impossible organ to study, in molecular detail, in living humans, and yet, understanding the pancreas is critical if we aim to characterise the immunopathology of type 1 diabetes (T1D) and one day prevent the triggering of the autoimmune attack associated with ß‐cell demise.MethodsOver a 100 years ago, we began studying pancreatic histology using cadaveric samples and clever adaptations to microscopes. As histologists, some may say nothing much has changed. Nevertheless, our microscopes can now interrogate multiple proteins at molecular resolution. Images of pancreas sections are no longer constrained to a single field of view and can capture a thousands and thousands of cells. AI‐image‐analysis packages can analyse these massive data sets offering breakthrough findings.ConclusionThis narrative review will provide an overview of pancreatic anatomy, and the importance of research focused on the pancreas in T1D. It will range from histological breakthroughs to briefly discussing the challenges associated with characterising the organ. I shall briefly introduce a selection of the available global biobanks and touch on the distinct pancreatic endotypes that differ immunologically and in ß‐cell behaviour. Finally, I will introduce the idea of developing a collaborative tool aimed at developing a cohesive framework for characterising heterogeneity and stratifying endotypes in T1D more readily.
The impact of diabetes and obesity on fertility and the potential role of gut hormones as treatment
Authors: Sridhar Ananyaa , Khan Dawood , Moffett R. Charlotte 
Published: September 2023

AbstractAimsAlongside its metabolic implications, obesity and associated diabetes impair female reproductive function, causing infertility and polycystic ovarian syndrome (PCOS). Recently, gut hormones and their receptors have been identified in various reproductive organs indicating their potential regulatory effects on reproductive function. This review aims to give an overview of their potential effects.MethodsThis review focuses on literature that outlines modifications during obesity, diabetes and related infertility with an emphasis on gut hormones and their therapeutic potential.ResultsEvidence suggests that bariatric surgery has positive effects on fertility and PCOS where major alterations in metabolism occurs through restoration of gut hormone levels. This is thought to be due to the indirect effect weight loss and regulation of blood glucose has on the hypothalamic–pituitary–ovarian and hypothalamic–pituitary–adrenal axis influencing reproduction.ConclusionsFurther research is required to elucidate the cellular mechanisms involved in the direct effects of gut hormone receptor activation on reproductive tissues. Current observations suggest a therapeutic role for gut hormones in infertility/PCOS associated with metabolic pathophysiology.
Teaching root cause analysis in healthcare management with Grey's Anatomy
Authors: Gray Natallia , Petrova Olga 
Published: September 2023

AbstractOver the past 20 years, root cause analysis (RCA) has become one of the most widely used retrospective methods for detecting safety hazards in medicine and healthcare. Despite its wide use in management practice and growing popularity in academic research, there is currently a dearth of coverage of RCA in popular healthcare management textbooks and pedagogical publications. This paper addresses this gap by presenting innovative instructional materials and recommendations for teaching RCA in healthcare management. Using an episode of Grey's Anatomy TV show, this experiential learning exercise takes students through the steps of RCA and makes use of a range of RCA tools, including high‐level flowchart, fishbone diagram, “five whys”, corrective action plan, and others. The exercise, which was classroom tested and received positive student feedback, can be adapted to a range of healthcare management classes. Because RCA can have widespread, lifesaving consequences, healthcare management courses can significantly benefit from integrating this exercise into classroom pedagogies.
Predicting the fine‐scale spatial distribution of zoonotic reservoirs using computer vision
Authors: Layman Nathan C. , Basinski Andrew J. , Zhang Boyu , Eskew Evan A. , Bird Brian H. , Ghersi Bruno M. , Bangura James , Fichet‐Calvet Elisabeth , Remien Christopher H. , Vandi Mohamed , Bah Mohamed , Nuismer Scott L. 
Published: September 2023

AbstractZoonotic diseases threaten human health worldwide and are often associated with anthropogenic disturbance. Predicting how disturbance influences spillover risk is critical for effective disease intervention but difficult to achieve at fine spatial scales. Here, we develop a method that learns the spatial distribution of a reservoir species from aerial imagery. Our approach uses neural networks to extract features of known or hypothesized importance from images. The spatial distribution of these features is then summarized and linked to spatially explicit reservoir presence/absence data using boosted regression trees. We demonstrate the utility of our method by applying it to the reservoir of Lassa virus,Mastomys natalensis, within the West African nations of Sierra Leone and Guinea. We show that, when trained using reservoir trapping data and publicly available aerial imagery, our framework learns relationships between environmental features and reservoir occurrence and accurately ranks areas according to the likelihood of reservoir presence.
An optimized deep learning model for human activity recognition using inertial measurement units
Authors: Challa Sravan Kumar , Kumar Akhilesh , Semwal Vijay Bhaskar , Dua Nidhi 
Published: September 2023

AbstractHuman activity recognition (HAR) has recently gained popularity due to its applications in healthcare, surveillance, human‐robot interaction, and various other fields. Deep learning (DL)‐based models have been successfully applied to the raw data captured through inertial measurement unit (IMU) sensors to recognize multiple human activities. Despite the success of DL‐based models in human activity recognition, feature extraction remains challenging due to class imbalance and noisy data. Additionally, selecting optimal hyperparameter values for DL models is essential since they affect model performance. The hyperparameter values of some of the existing DL‐based HAR models are chosen randomly or through the trial‐and‐error method. The random selection of these significant hyperparameters may be suitable for some applications, but sometimes it may worsen the model's performance in others. Hence, to address the above‐mentioned issues, this research aims to develop an optimized DL model capable of recognizing various human activities captured through IMU sensors. The proposed DL‐based HAR model combines convolutional neural network (CNN) layers and bidirectional long short‐term memory (Bi‐LSTM) units to simultaneously extract spatial and temporal sequence features from raw sensor data. The Rao‐3 metaheuristic optimization algorithm has been adopted to identify the ideal hyperparameter values for the proposed DL model in order to enhance its recognition performance. The proposed DL model's performance is validated on PAMAP2, UCI‐HAR, and MHEALTH datasets and achieved 94.91%, 97.16%, and 99.25% accuracies, respectively. The results reveal that the proposed DL model performs better than the existing state‐of‐the‐art (SoTA) models.
Characteristics of Hispanic patients with nonmelanoma skin cancer undergoing Mohs micrographic surgery: a review of the literature
Authors: Camacho Isabella , Biro Mark , Stevenson Mary L. , Deng Min 
Published: September 2023

AbstractBackgroundNonmelanoma skin cancer (NMSC) is the most common cancer worldwide and is frequently treated with Mohs micrographic surgery (MMS); however, data regarding characteristics of Hispanic patients undergoing MMS for NMSC are limited.ObjectiveTo review the characteristics of Hispanic patients undergoing MMS for NMSC in the United States.MethodsA systematic review of PubMed articles from inception through September 2022 providing data for Hispanic patients undergoing MMS for NMSC was completed.ResultsOverall, six publications met inclusion criteria and provided data for 2,856 Hispanic patients that underwent MMS for 2,955 NMSCs. Results demonstrate 60% of Hispanic patients were male, and the majority of NMSCs were basal cell carcinoma (BCC) (71%), followed by squamous cell carcinoma (SCC) (21%). Additionally, a larger percentage of pigmented BCC was found in the Hispanic population. While there is conflicting data in the literature, Hispanic patients may also have larger MMS defects when controlled for additional variables. Finally, over 64% of NMSCs in Hispanic patients were in high‐risk locations.ConclusionLiterature regarding the characteristics of Hispanic patients undergoing MMS for NMSC demonstrates most patients were male, BCC was the most common tumor subtype, and the majority of NMSCs were in high‐risk locations.
Effects of evidence‐based care on diabetic foot ulcers: A meta‐analysis
Authors: Sun Cui‐Zhen , He Dian‐Ju , Cao Sheng‐Hua , Qi Yong‐Hua 
Published: September 2023

AbstractThis analysis systematically reviewed the efficacy of evidence‐based care on diabetic foot ulcers. A computerised literature search was conducted for randomised controlled studies (RCTs) of evidence‐based care interventions for the treatment of diabetic foot ulcers using the PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM) and Wanfang databases from the date of inception of each database to June 2023. The articles were independently screened, data were extracted by two researchers, and the quality of each study was assessed using the Cochrane bias assessment tool. Meta‐analysis of the data was performed using RevMan 5.4 software. Twenty‐five RCTs with a total of 2272 patients were included. Meta‐analysis showed that, compared with other care methods, evidence‐based care significantly improved the treatment efficacy of diabetic foot ulcers (odds ratio: 3.91, 95% confidence interval [CI]: 2.76 to 5.53, p < 0.001) and significantly reduced their fasting plasma glucose (mean difference [MD]: −1.10, 95% CI: −1.24 to −0.96, p < 0.001), 2‐h postprandial glucose (2hPG) (MD: −1.69, 95% CI: −2.07 to −1.31, p < 0.001) and glycated haemoglobin (HbA1c) (MD: −0.71, 95% CI: −0.94 to −0.48, p < 0.001). Evidence‐based care intervention is effective at reducing FPG, 2hPG and HbA1c levels and improving treatment efficacy in patients with diabetic foot ulcers.
Oxidation kinetics of silicon carbide‐containing refractory diborides, I: Revised model
Authors: Mogilevsky Pavel , Cinibulk Michael K. 
Published: September 2023

AbstractThe original model by Parthasarathy et al. for oxidation of MeB₂–SiC ultra‐high temperature ceramics (UHTCs) has been further expanded to include oxidation by water vapor and oxygen/water vapor mixtures. The revised model offers a more representative analysis of the composition of the glass phase and a thermodynamically consistent formulation for the processes governing the formation of the internal depletion zone. A key feature of the revised model is that it explicitly incorporates the out‐diffusion of CO(g) through the scale as a rate‐controlling parameter that defines the formation of internal depletion zone. In its present form, the expanded model explains some of the experimentally observed phenomena of oxidation of MeB₂–SiC UHTCs, such as the formation of MeO₂/B₂O₃ scale with embedded partially oxidized SiC at lower temperatures and limited growth of ZrO₂/borosilicate layer compared with the SiC‐depleted layer and the outer borosilicate layer in static oxidation at high temperatures. Application of the revised model to the experimental data from literature on oxidation of ZrB₂–SiC materials in air and water vapor is demonstrated and discussed.
New insights on the potential anti‐epileptic effect of metformin: Mechanistic pathway
Authors: Alnaaim Saud A. , Al‐kuraishy Hayder M. , Al‐Gareeb Ali I. , Ali Naif H. , Alexiou Athanasios , Papadakis Marios , Saad Hebatallah M. , Batiha Gaber El‐Saber 
Published: September 2023

AbstractEpilepsy is a chronic neurological disease characterized by recurrent seizures. Epilepsy is observed as a well‐controlled disease by anti‐epileptic agents (AEAs) in about 69%. However, 30%–40% of epileptic patients fail to respond to conventional AEAs leading to an increase in the risk of brain structural injury and mortality. Therefore, adding some FDA‐approved drugs that have an anti‐seizure activity to the anti‐epileptic regimen is logical. The anti‐diabetic agent metformin has anti‐seizure activity. Nevertheless, the underlying mechanism of the anti‐seizure activity of metformin was not entirely clarified. Henceforward, the objective of this review was to exemplify the mechanistic role of metformin in epilepsy. Metformin has anti‐seizure activity by triggering adenosine monophosphate‐activated protein kinase (AMPK) signalling and inhibiting the mechanistic target of rapamycin (mTOR) pathways which are dysregulated in epilepsy. In addition, metformin improves the expression of brain‐derived neurotrophic factor (BDNF) which has a neuroprotective effect. Hence, metformin via induction of BDNF can reduce seizure progression and severity. Consequently, increasing neuronal progranulin by metformin may explain the anti‐seizure mechanism of metformin. Also, metformin reduces α‐synuclein and increases protein phosphatase 2A (PPA2) with modulation of neuroinflammation. In conclusion, metformin might be an adjuvant with AEAs in the management of refractory epilepsy. Preclinical and clinical studies are warranted in this regard.
Identification and validation of voltage‐dependent anion channel 1‐related genes and immune cell infiltration in diabetic nephropathy
Authors: Lin Jiaqun , Weng Mengjie , Zheng Jing , Nie Kun , Rao Siyi , Zhuo Yongjie , Wan Jianxin 
Published: September 2023

ABSTRACTAims/IntroductionThis study investigated the roles of voltage‐dependent anion channel 1‐related differentially expressed genes (VRDEGs) in diabetic nephropathy (DN).Materials and MethodsWe downloaded two datasets from patients with DN, namely, GSE30122 and GSE30529, from the Gene Expression Omnibus database. VRDEGs associated with DN were obtained from the intersection of voltage‐dependent anion channel 1‐related genes from the GeneCards database, and differentially expressed genes were screened according to group (DN/healthy) in the two datasets. The enriched pathways of the VRDEGs were analyzed. Hub genes were selected using a protein–protein interaction network, and their predictive value was verified through receiver operating characteristic curve analysis. The CIBERSORTx software examined hub genes and immune cell infiltration associations. The protein expression of hub genes was verified through immunohistochemistry in 16‐week‐old db/db mice for experimentation as a model of type 2 DN. Finally, potential drugs targeting hub genes that inhibit DN development were identified.ResultsA total of 57 VRDEGs were identified. The two datasets showed high expression of the PI3K, Notch, transforming growth factor‐β, interleukin‐10 and interleukin‐17 pathways in DN. Five hub genes (ITGAM, B2M, LYZ, C3 and CASP1) associated with DN were identified and verified. Immunohistochemistry showed that the five hub genes were highly expressed in db/db mice, compared with db/m mice. The infiltration of immune cells was significantly correlated with the five hub genes.ConclusionsFive hub genes were significantly correlated with immune cell infiltration and might be crucial to DN development. This study provides insight into the mechanisms involved in the pathogenesis of DN.
Effects of the Informed Health Choices secondary school intervention: A prospective meta‐analysis
Authors: Chesire Faith , Mugisha Michael , Ssenyonga Ronald , Rose Christopher J. , Nsangi Allen , Kaseje Margaret , Sewankambo Nelson K. , Oxman Matt , Rosenbaum Sarah E. , Moberg Jenny , Dahlgren Astrid , Lewin Simon , Oxman Andrew D. 
Published: September 2023

AbstractAimThe aim of this prospective meta‐analysis was to synthesize the results of three cluster‐randomized trials of an intervention designed to teach lower‐secondary school students (age 14–16) to think critically about health choices.MethodsWe conducted the trials in Kenya, Rwanda, and Uganda. The intervention included a 2‐ to 3‐day teacher training workshop, digital resources, and ten 40‐min lessons. The lessons focused on nine key concepts. We did not intervene in control schools. The primary outcome was a passing score on a test (≥9 of 18 multiple‐choice questions answered correctly). We performed random effects meta‐analyses to estimate the overall adjusted odds ratios. Secondary outcomes included effects of the intervention on teachers.ResultsAltogether, 244 schools (11,344 students) took part in the three trials. The overall adjusted odds ratio was 5.5 (95% CI: 3.0–10.2;p < 0.0001) in favor of the intervention (high certainty evidence). This corresponds to 33% (95% CI: 25–40%) more students in the intervention schools passing the test. Overall, 3397 (58%) of 5846 students in intervention schools had a passing score. The overall adjusted odds ratio for teachers was 13.7(95% CI: 4.6–40.4;p < 0.0001), corresponding to 32% (95% CI: 6%–57%) more teachers in the intervention schools passing the test (moderate certainty evidence). Overall, 118 (97%) of 122 teachers in intervention schools had a passing score.ConclusionsThe intervention led to a large improvement in the ability of students and teachers to think critically about health choices, but 42% of students in the intervention schools did not achieve a passing score.
Ceramic veneer shade evaluation using a multicolored 3D‐printed model—A case report
Authors: An Hongseok 
Published: September 2023

AbstractObjectiveThis article demonstrates the use of a multicolored 3D‐printed model for laboratory shade evaluation of ceramic veneers.Clinical ConsiderationsA young female patient presented with peg lateral incisors and diastemata between her maxillary incisors. Four ceramic veneers for her maxillary incisors were fabricated using a digital workflow. A multicolored 3D‐printed model was manufactured using material jetting technology. The multicolored model and try‐in pastes were used to evaluate and adjust the shade of the veneers. Clinically acceptable color matching was achieved, the veneers were delivered without further chairside shade adjustments.ConclusionsSuccessful color evaluation and adjustment were achieved using the combination of multicolored 3D‐printed model and try‐in pastes. The use of this approach saved time for stump shade taking and fabrication of tooth‐colored dies.Clinical SignificanceA multicolored 3D‐printed model can be a useful tool for color evaluation and adjustment of ceramic restorations.