bluuebunny/crossref_metadata_2025_split huggingface dataset:
InR and Pi3K maintain intestinal homeostasis through STAT/EGFR and Notch signaling in enteroblasts
Authors: Wang Jiewei , Xue Hongmei , Yi Xinyu , Kim Hyonil , Hao Yangguang , Jin Li Hua 
Published: March 2024

AbstractTo maintain the integrity of the adult gut, the proliferation and differentiation of stem cells must be strictly controlled. Several signaling pathways control the proliferation and differentiation of Drosophila intestinal epithelial cells. Although the modulatory effects of insulin pathway components on cell proliferation have been characterized, their specific role in which cell type and how these components interact with other regulatory signaling pathways remain largely unclear. In this study, we found that InR/Pi3K has major functions in enteroblasts (EBs) that were not previously described. The absence of InR/Pi3K in progenitors leads to a decrease in the number of EBs, while it has no significant effect on intestinal stem cells (ISCs). In addition, we found that InR/Pi3K regulates Notch activity in ISCs and EBs in an opposite way. This is also the reason for the decrease in EB. On the one hand, aberrantly low levels of Notch signaling in ISCs inhibit their proper differentiation into EBs; on the other hand, the higher Notch levels in EBs promote their excessive differentiation into enterocytes (ECs), leading to marked increases in abnormal ECs and decreased proliferation. Moreover, we found that Upd/JAK/STAT signaling acts as an effector or modifier of InR/Pi3K function in the midgut and cooperates with EGFR signaling to regulate cell proliferation. Altogether, our results demonstrate that InR and Pi3K are essential for coordinating stem cell differentiation and proliferation to maintain intestinal homeostasis.
Multiyear Interval Changes in Aortic Wall Shear Stress in Patients with Bicuspid Aortic Valve Assessed by 4D Flow MRI
Authors: Maroun Anthony , Scott Michael B. , Catania Roberta , Berhane Haben , Jarvis Kelly , Allen Bradley D. , Barker Alex J. , Markl Michael 
Published: March 2024

BackgroundIn patients with bicuspid aortic valve (BAV), 4D flow MRI can quantify regions exposed to abnormal aortic hemodynamics, including high wall shear stress (WSS), a known stimulus for arterial wall dysfunction. However, the long‐term multiscan reproducibility of 4D flow MRI‐derived hemodynamic parameters is unknown.PurposeTo investigate the long‐term stability of 4D flow MRI‐derived peak velocity, WSS, and WSS‐derived heatmaps in patients with BAV undergoing multiyear surveillance imaging.Study TypeRetrospective.Population20 BAV patients (mean age 48.4 ± 13.9 years; 14 males) with five 4D flow MRI scans, with intervals of at least 6 months between scans, and 125 controls (mean age: 50.7 ± 15.8 years; 67 males).Field Strength/Sequence1.5 and 3.0T, prospectively ECG and respiratory navigator‐gated aortic 4D flow MRI.AssessmentAutomated AI‐based 4D flow analysis pipelines were used for data preprocessing, aorta 3D segmentation, and quantification of ascending aorta (AAo) peak velocity, peak systolic WSS, and heatmap‐derived relative area of elevated WSS compared to WSS ranges in age and sex‐matched normative control populations. Growth rate was derived from the maximum AAo diameters measured on the first and fifth MRI scans.Statistical TestsOne‐way repeated measures analysis of variance. P < 0.05 indicated significance.ResultsOne hundred 4D flow MRI exams (five per patient) were analyzed. The mean total follow‐up duration was 5.5 ± 1.1 years, and the average growth rate was 0.3 ± 0.2 mm/year. Peak velocity, peak systolic WSS, and relative area of elevated WSS did not change significantly over the follow‐up period (P = 0.64, P = 0.69, and P = 0.35, respectively). The patterns and areas of elevated WSS demonstrated good reproducibility on semiquantitative assessment.Conclusion4D flow MRI‐derived peak velocity, WSS, and WSS‐derived heatmaps showed good multiyear and multiscan stability in BAV patients with low aortic growth rates. These findings underscore the reliability of these metrics in monitoring BAV patients for potential risk of dilation.Level of Evidence3Technical EfficacyStage 1
“Top 20” residency‐trained academic orthopaedic surgeons have higher academic productivity and funding in their careers
Authors: Mendiratta Dhruv , Herzog Isabel , Liggio Daniel F. , Ahn David , Vosbikian Michael , Kaushal Neil , Chu Alice 
Published: March 2024

Abstract“Top 20” status on Doximity, an online networking service for medical professionals, is an indicator of the reputation of a residency program. The study assesses how training at a Top 20 (T20) orthopaedic residency program impacts career productivity and funding. Fellowship and Residency Electronic Interactive Database was used in 2022 to identify active orthopaedic residency programs. Demographic and training data was collected for each orthopaedic surgeon using institutional websites and Doximity. The Residency Navigator feature on Doximity was used to rank residency programs by “reputation.” Programs were categorized as either T20 or non‐T20. The relative citation ratio (RCR) was calculated using the NIH iCite tool and Hirsch index (h‐index) was calculated using Scopus. Industry funding was collected from the Centers for Medicare & Medicaid Services Open Payments Program (CMS) for all available years (2014–2020). A total of 2812 academic orthopaedic surgeons were included in the study. Among academic orthopaedic surgeons in the United States, T20 trained orthopedists had more publications and citations (p < 0.001), along with higher h‐indices (p < 0.001), RCR (p < 0.001), and industry funding (p = 0.043). Additionally, T20 trained orthopedists were 1.375 times more likely to obtain professor status (95% confidence interval: 1.150–1.645, p < 0.001). Even after propensity‐matched analysis, T20 trained orthopedists maintained these differences. Training at a T20 residency program is associated with promotion, productivity, and funding. These findings are especially of concern to medical students who must consider the importance of a residency program's reputation when deciding where to apply for residency.
Comparison of energy intake in critical illness survivors, general medical patients, and healthy volunteers: A descriptive cohort study
Authors: Viner Smith Elizabeth , Kouw Imre W. K. , Summers Matthew J. , Louis Rhea , Trahair Laurence , O'Connor Stephanie N. , Jones Karen L. , Horowitz Michael , Chapman Marianne J. , Chapple Lee‐anne S. 
Published: March 2024

AbstractBackgroundIntensive care unit (ICU) survivors have reduced oral intake; it is unknown whether intake and associated barriers are unique to this group.ObjectiveTo quantify energy intake and potential barriers in ICU survivors compared with general medical (GM) patients and healthy volunteers.DesignA descriptive cohort study in ICU survivors, GM patients, and healthy volunteers. Following an overnight fast, participants consumed a 200 ml test‐meal (213 kcal) and 180 min later an ad libitum meal to measure energy intake (primary outcome). Secondary outcomes; taste recognition, nutrition‐impacting symptoms, malnutrition, and quality of life (QoL). Data are mean ± SD, median (interquartile range [IQR]) or number [percentage]).ResultsTwelve ICU survivors (57 ± 17 years, BMI: 30 ± 6), eight GM patients (69 ± 19 years, BMI: 30 ± 6), and 25 healthy volunteers (58 ± 27 years, BMI: 25 ± 4) were included. Recruitment ceased early because of slow recruitment and SARS‐CoV‐2. Energy intake was lower in both patient groups than in health (ICU: 289 [288, 809], GM: 426 [336, 592], health: 815 [654, 1165] kcal). Loss of appetite was most common (ICU: 78%, GM: 67%). For ICU survivors, GM patients and healthy volunteers, respectively, severe malnutrition prevalence; 40%, 14%, and 0%; taste identification; 8.5 [7.0, 11.0], 8.5 [7.0, 9.5], and 8.0 [6.0, 11.0]; and QoL; 60 [40–65], 50 [31–55], and 90 [81–95] out of 100.ConclusionsEnergy intake at a buffet meal is lower in hospital patients than in healthy volunteers but similar between ICU survivors and GM patients. Appetite loss potentially contributes to reduced energy intake.
Phase‐dependent red fox expansion into the tundra: implications for management
Authors: Wilkinson Caitlin , Vigués Jan , Stoessel Marianne , Vinka Mikael , Angerbjörn Anders , Norén Karin 
Published: March 2024

AbstractExpansion of boreal species into tundra ecosystems is a consequence of climate change and human exploitation that threatens local species through increased predation, competition, and pathogen transmission. Under these circumstances, efficient control of expanding boreal species may be necessary, but the efficiency of such action depends on understanding the ecological influences of expansion. The red fox (Vulpes vulpes) is expanding into the tundra across the Arctic. In Scandinavia, red foxes threaten local tundra species and communities including the endangered Arctic fox (V. lagopus). The ecological dynamics in the tundra are influenced by small rodent cycles (classified into different phases based on seasonal abundance fluctuations), which can affect red fox expansion, distribution, and abundance. We used a 17‐year (2004–2020) dataset from the tundra in Sweden, consisting of raw snow track data, to test how cyclic prey influenced red fox distribution and abundance, and subsequently red fox control. The winter abundance of red fox was influenced by small rodent phase, with higher abundance during high prey availability (i.e., increased number of prey numbers) with no support for a time lag between red fox and small rodent abundance. This suggests that high prey availability attracts red foxes to the tundra and that higher immigration from the boreal zone can be expected in response to increased prey abundances. There was no relationship between red fox control and small rodent availability, but control was influenced by red fox abundance during the previous year, which highlights an opportunistic control strategy. We recommend an adaptive management strategy where authorities include small rodent dynamics in the planning and execution of red fox control.
An adaptation of dual‐frame sampling for estimating bat population trends in multi‐hibernacula systems
Authors: Weller Theodore J. , Smith Katrina J. , Thomas Shawn C. , Baldwin James A. 
Published: March 2024

AbstractReliable estimates of population trends are important for prioritizing and implementing wildlife management actions. Abundance estimates are the most informative metric of population status but are difficult and costly to achieve for rare or elusive species. For bat species that are highly mobile and nocturnal, abundance estimates are usually only possible at their roosts. Although they are relatively easy to census in individual roosts, it is often unclear whether observed trends are representative of broader populations trends. Dual‐frame sampling is useful for monitoring wildlife populations that exhibit site fidelity and are highly visible but where the proportion of the population in known sites is unknown. We adapted a dual‐frame sampling approach to estimate abundance of Townsend's big‐eared bats (Corynorhinus townsendii) hibernating in a system of >800 caves at Lava Beds National Monument (LBNM) in northern California, USA, in 2013–2022. Beginning with a list of opportunistically discovered hibernacula, we expanded inference to the entire system by randomly selecting sites and stratifying survey effort according to number of bats observed during previous counts. Following 4 years of surveys, we began substituting survey‐informed estimates for some site types to improve efficiency of the monitoring effort. We estimated that a mean of 2,216 ± 112 (SE) bats hibernated at the study site annually and observed fluctuations of up to 22% around the mean population estimate and as much as 21% from the previous year. Despite annual fluctuations, we did not detect a trend in the number of hibernating bats at LBNM over the study period, underlining the challenges of detecting population trends in long‐lived species not exposed to pronounced stressors. Because our analytical approach generates reliable estimates of trend while accommodating annual variability in survey effort among years, it should be attractive to wildlife managers faced with shifting priorities and resources.
Evaluation of the impact of wastewater irrigation on the soil's dielectric parameters
Authors: Palta Prachi , Kumar Ankur , Kaur Prabhdeep 
Published: March 2024

AbstractThis study investigates the impact of wastewater irrigation on soil dielectric parameters, focusing on the often‐overlooked aspect of dielectric properties in contaminated soil. Wastewater, a significant contributor to soil and groundwater degradation, has long‐term effects on soil physical, chemical, and dielectric characteristics. Experimental measurements conducted overtime at 2.45 and 5.8 GHz frequencies reveal a correlation between wastewater irrigation and changes in dielectric properties. Emphasizing time variation as a pivotal independent variable, the study sheds light on its substantial influence on soil dielectric behavior. Notably, the research introduces an alternative methodology for the comprehensive evaluation of wastewater‐induced pollution effects on soil properties. This approach is substantiated by meticulous physicochemical analyses conducted on both pollution sources and the affected soil. The study further presents a robust response surface method‐based model, showcasing impressive accuracy with dielectric properties (ε′ and ε″) and penetration depth with R2 values of 0.9845, 0.9831, and 0.9528, respectively. Beyond unveiling crucial insights into the intricate interplay of wastewater and soil dielectric behavior, this research contributes to the development of effective strategies for pollution monitoring and management in soil ecosystems.
Proactive esophageal cooling during laser cardiac ablation: A computer modeling study
Authors: Gomez Bustamante Tatiana , Mercado Montoya Marcela , Berjano Enrique , González‐Suárez Ana , Kulstad Erik 
Published: March 2024

AbstractBackground and ObjectivesLaser ablation is increasingly used to treat atrial fibrillation (AF). However, atrioesophageal injury remains a potentially serious complication. While proactive esophageal cooling (PEC) reduces esophageal injury during radiofrequency ablation, the effects of PEC during laser ablation have not previously been determined. We aimed to evaluate the protective effects of PEC during laser ablation of AF by means of a theoretical study based on computer modeling.MethodsThree‐dimensional mathematical models were built for 20 different cases including a fragment of atrial wall (myocardium), epicardial fat (adipose tissue), connective tissue, and esophageal wall. The esophagus was considered with and without PEC. Laser‐tissue interaction was modeled using Beer–Lambert's law, Pennes' Bioheat equation was used to compute the resultant heating, and the Arrhenius equation was used to estimate the fraction of tissue damage (FOD), assuming a threshold of 63% to assess induced necrosis. We modeled laser irradiation power of 8.5 W over 20 s. Thermal simulations extended up to 250 s to account for thermal latency.ResultsPEC significantly altered the temperature distribution around the cooling device, resulting in lower temperatures (around 22°C less in the esophagus and 9°C in the atrial wall) compared to the case without PEC. This thermal reduction translated into the absence of transmural lesions in the esophagus. The esophagus was thermally damaged only in the cases without PEC and with a distance equal to or shorter than 3.5 mm between the esophagus and endocardium (inner boundary of the atrial wall). Furthermore, PEC demonstrated minimal impact on the lesion created across the atrial wall, either in terms of maximum temperature or FOD.ConclusionsPEC reduces the potential for esophageal injury without degrading the intended cardiac lesions for a variety of different tissue thicknesses. Thermal latency may influence lesion formation during laser ablation and may play a part in any collateral damage.
A programmable solar‐powered radio frequency transmitter
Authors: Chen Qian , Qiao Zilin , Lv Juliang , Ye Yong , Ren Xingang , Wang Wei , Huang Zhixiang , Yang Lixia , Li Yingsong 
Published: March 2024

AbstractThis paper proposes a programmable solar‐powered radio frequency (RF) transmitter. It employs a novel five‐layer structure that effectively integrates solar cells, active circuits, and broadband antenna. This design can directly emit RF signals without the need for additional power supply, enabling efficient energy conversion and transmission. In addition, a U‐shaped coupling line model is introduced to evaluate the performance of the active circuit. We fabricated a sample and measured it. The results of the measurements indicate that the proposed RF transmitter can achieve self‐powering and programmable output at any frequency within the range of 2.08–4.1 GHz, with an output power of no less than 14 dBm. Moreover, the solar cells are placed on both sides of the circuits and antenna for energy harvesting, achieving 100% sunlight insolation with a 75.5% coverage ratio. This design can be used for self‐powered green wireless system applications.
Transformaer‐based model for lung adenocarcinoma subtypes
Authors: Du Fawen , Zhou Huiyu , Niu Yi , Han Zeyu , Sui Xiaodan 
Published: March 2024

AbstractBackgroundLung cancer has the highest morbidity and mortality rate among all types of cancer. Histological subtypes serve as crucial markers for the development of lung cancer and possess significant clinical values for cancer diagnosis, prognosis, and prediction of treatment responses. However, existing studies only dichotomize normal and cancerous tissues, failing to capture the unique characteristics of tissue sections and cancer types.PurposeTherefore, we have pioneered the classification of lung adenocarcinoma (LAD) cancer tissues into five subtypes (acinar, lepidic, micropapillary, papillary, and solid) based on section data in whole‐slide image sections. In addition, a novel model called HybridNet was designed to improve the classification performance.MethodsHybridNet primarily consists of two interactive streams: a Transformer and a convolutional neural network (CNN). The Transformer stream captures rich global representations using a self‐attention mechanism, while the CNN stream extracts local semantic features to optimize image details. Specifically, during the dual‐stream parallelism, the feature maps of the Transformer stream as weights are weighted and summed with those of the CNN stream backbone; at the end of the parallelism, the respective final features are concatenated to obtain more discriminative semantic information.ResultsExperimental results on a private dataset of LAD showed that HybridNet achieved 95.12% classification accuracy, and the accuracy of five histological subtypes (acinar, lepidic, micropapillary, papillary, and solid) reached 94.5%, 97.1%, 94%, 91%, and 99% respectively; the experimental results on the public BreakHis dataset show that HybridNet achieves the best results in three evaluation metrics: accuracy, recall and F1‐score, with 92.40%, 90.63%, and 91.43%, respectively.ConclusionsThe process of classifying LAD into five subtypes assists pathologists in selecting appropriate treatments and enables them to predict tumor mutation burden (TMB) and analyze the spatial distribution of immune checkpoint proteins based on this and other clinical data. In addition, the proposed HybridNet fuses CNN and Transformer information several times and is able to improve the accuracy of subtype classification, and also shows satisfactory performance on public datasets with some generalization ability.
Two‐stage adversarial learning based unsupervised domain adaptation for retinal OCT segmentation
Authors: Diao Shengyong , Yin Ziting , Chen Xinjian , Li Menghan , Zhu Weifang , Mateen Muhammad , Xu Xun , Shi Fei , Fan Ying 
Published: March 2024

AbstractBackgroundDeep learning based optical coherence tomography (OCT) segmentation methods have achieved excellent results, allowing quantitative analysis of large‐scale data. However, OCT images are often acquired by different devices or under different imaging protocols, which leads to serious domain shift problem. This in turn results in performance degradation of segmentation models.PurposeAiming at the domain shift problem, we propose a two‐stage adversarial learning based network (TSANet) that accomplishes unsupervised cross‐domain OCT segmentation.MethodsIn the first stage, a Fourier transform based approach is adopted to reduce image style differences from the image level. Then, adversarial learning networks, including a segmenter and a discriminator, are designed to achieve inter‐domain consistency in the segmentation output. In the second stage, pseudo labels of selected unlabeled target domain training data are used to fine‐tune the segmenter, which further improves its generalization capability. The proposed method was tested on cross‐domain datasets for choroid or retinoschisis segmentation tasks. For choroid segmentation, the model was trained on 400 images and validated on 100 images from the source domain, and then trained on 1320 unlabeled images and tested on 330 images from target domain I, and also trained on 400 unlabeled images and tested on 200 images from target domain II. For retinoschisis segmentation, the model was trained on 1284 images and validated on 312 images from the source domain, and then trained on 1024 unlabeled images and tested on 200 images from the target domain.ResultsThe proposed method achieved significantly improved results over that without domain adaptation, with improvement of 8.34%, 55.82% and 3.53% in intersection over union (IoU) respectively for the three test sets. The performance is better than some state‐of‐the‐art domain adaptation methods.ConclusionsThe proposed TSANet, with image level adaptation, feature level adaptation and pseudo‐label based fine‐tuning, achieved excellent cross‐domain generalization. This alleviates the burden of obtaining additional manual labels when adapting the deep learning model to new OCT data.