bluuebunny/crossref_metadata_2025_split huggingface dataset:
The bZIP transcription factor ATF1 regulates blue light and oxidative stress responses in Trichoderma guizhouense
Authors: Li Yifan , Li Yanshen , Lu Huanhong , Sun Tingting , Gao Jia , Zhang Jian , Shen Qirong , Yu Zhenzhong 
Published: December 2023

AbstractIn several filamentous fungi, incident light and environmental stress signaling share the mitogen‐activated protein kinase (MAPK) HOG (SAK) pathway. It has been revealed that short‐term illumination with blue light triggers the activation of the HOG pathway in Trichoderma spp. In this study, we demonstrate the crucial role of the basic leucine zipper transcription factor ATF1 in blue light responses and signaling downstream of the MAPK HOG1 in Trichoderma guizhouense. The lack of ATF1 severely impaired photoconidiation and delayed vegetative growth and conidial germination. Upon blue light or H2O2 stimuli, HOG1 interacted with ATF1 in the nucleus. Genome‐wide transcriptome analyses revealed that 61.8% (509 out of 824) and 85.2% (702 out of 824) of blue light‐regulated genes depended on ATF1 and HOG1, respectively, of which 58.4% (481 out of 824) were regulated by both of them. Our results also show that blue light promoted conidial germination and HOG1 and ATF1 played opposite roles in controlling conidial germination in the dark. Additionally, the lack of ATF1 led to reduced oxidative stress resistance, probably because of the downregulation of catalase‐encoding genes. Overall, our results demonstrate that ATF1 is the downstream component of HOG1 and is responsible for blue light responses, conidial germination, vegetative growth, and oxidative stress resistance in T. guizhouense.
A novel loss function to reproduce texture features for deep learning‐based MRI‐to‐CT synthesis
Authors: Yuan Siqi , Liu Yuxiang , Wei Ran , Zhu Ji , Men Kuo , Dai Jianrong 
Published: December 2023

AbstractBackgroundStudies on computed tomography (CT) synthesis based on magnetic resonance imaging (MRI) have mainly focused on pixel‐wise consistency, but the texture features of regions of interest (ROIs) have not received appropriate attention.PurposeThis study aimed to propose a novel loss function to reproduce texture features of ROIs and pixel‐wise consistency for deep learning‐based MRI‐to‐CT synthesis. The method was expected to assist the multi‐modality studies for radiomics.MethodsThe study retrospectively enrolled 127 patients with nasopharyngeal carcinoma. CT and MRI images were collected for each patient, and then rigidly registered as pre‐procession. We proposed a gray‐level co‐occurrence matrix (GLCM)‐based loss function to improve the reproducibility of texture features. This novel loss function could be embedded into the present deep learning‐based framework for image synthesis. In this study, a typical image synthesis model was selected as the baseline, which contained a Unet trained mean square error (MSE) loss function. We embedded the proposed loss function and designed experiments to supervise different ROIs to prove its effectiveness. The concordance correlation coefficient (CCC) of the GLCM feature was employed to evaluate the reproducibility of GLCM features, which are typical texture features. Besides, we used a publicly available dataset of brain tumors to verify our loss function.ResultsCompared with the baseline, the proposed method improved the pixel‐wise image quality metrics (MAE: 107.5 to 106.8 HU; SSIM: 0.9728 to 0.9730). CCC values of the GLCM features in GTVnx were significantly improved from 0.78 ± 0.12 to 0.82 ± 0.11 (p < 0.05 for paired t‐test). Generally, > 90% (22/24) of the GLCM‐based features were improved compared with the baseline, where the Informational Measure of Correlation feature was improved the most (CCC: 0.74 to 0.83). For the public dataset, the loss function also shows its effectiveness. With our proposed loss function added, the ability to reproduce texture features was improved in the ROIs.ConclusionsThe proposed method reproduced texture features for MRI‐to‐CT synthesis, which would benefit radiomics studies based on image multi‐modality synthesis.
Image factory: A method for synthesizing novel CT images with anatomical guidance
Authors: Krishna Arjun , Yenneti Shanmukha , Wang Ge , Mueller Klaus 
Published: December 2023

AbstractBackgroundDeep learning in medical applications is limited due to the low availability of large labeled, annotated, or segmented training datasets. With the insufficient data available for model training comes the inability of these networks to learn the fine nuances of the space of possible images in a given medical domain, leading to the possible suppression of important diagnostic features hence making these deep learning systems suboptimal in their performance and vulnerable to adversarial attacks.PurposeWe formulate a framework to address this lack of labeled data problem. We test this formulation in computed tomographic images domain and present an approach that can synthesize large sets of novel CT images at high resolution across the full Hounsfield (HU) range.MethodsOur method only requires a small annotated dataset of lung CT from 30 patients (available online at the TCIA) and a large nonannotated dataset with high resolution CT images from 14k patients (received from NIH, not publicly available). It then converts the small annotated dataset into a large annotated dataset, using a sequence of steps including texture learning via StyleGAN, label learning via U‐Net and semi‐supervised learning via CycleGAN/Pixel‐to‐Pixel (P2P) architectures. The large annotated dataset so generated can then be used for the training of deep learning networks for medical applications. It can also be put to use for the synthesis of CT images with varied anatomies that were nonexistent within either of the input datasets, enriching the dataset even further.ResultsWe demonstrate our framework via lung CT‐Scan synthesis along with their novel generated annotations and compared it with other state of the art generative models that only produce images without annotations. We evaluate our framework effectiveness via a visual turing test with help of a few doctors and radiologists.ConclusionsWe gain the capability of generating an unlimited amount of annotated CT images. Our approach works for all HU windows with minimal depreciation in anatomical plausibility and hence could be used as a general purpose framework for annotated data augmentation for deep learning applications in medical imaging.
2D antiscatter grid and scatter sampling based CBCT method for online dose calculations during CBCT guided radiation therapy of pelvis
Authors: Bayat Farhang , Miller Brian , Park Yeonok , Yu Zhelin , Alexeev Timur , Thomas David , Stuhr Kelly , Kavanagh Brian , Miften Moyed , Altunbas Cem 
Published: December 2023

AbstractBackgroundOnline dose calculations before the delivery of radiation treatments have applications in dose delivery verification, online adaptation of treatment plans, and simulation‐free treatment planning. While dose calculations by directly utilizing CBCT images are desired, dosimetric accuracy can be compromised due to relatively lower HU accuracy in CBCT images.PurposeIn this work, we propose a novel CBCT imaging pipeline to enhance the accuracy of CBCT‐based dose calculations in the pelvis region. Our approach aims to improve the HU accuracy in CBCT images, thereby improving the overall accuracy of CBCT‐based dose calculations prior to radiation treatment delivery.MethodsAn in‐house developed quantitative CBCT pipeline was implemented to address the CBCT raw data contamination problem. The pipeline combines algorithmic data correction strategies and 2D antiscatter grid‐based scatter rejection to achieve high CT number accuracy. To evaluate the effect of the quantitative CBCT pipeline on CBCT‐based dose calculations, phantoms mimicking pelvis anatomy were scanned using a linac‐mounted CBCT system, and a gold standard multidetector CT used for treatment planning (pCT). A total of 20 intensity‐modulated treatment plans were generated for five targets, using 6 and 10 MV flattening filter‐free beams, and utilizing small and large pelvis phantom images. For each treatment plan, four different dose calculations were performed using pCT images and three CBCT imaging configurations: quantitative CBCT, clinical CBCT protocol, and a high‐performance 1D antiscatter grid (1D ASG). Subsequently, dosimetric accuracy was evaluated for both targets and organs at risk as a function of patient size, target location, beam energy, and CBCT imaging configuration.ResultsWhen compared to the gold‐standard pCT, dosimetric errors in quantitative CBCT‐based dose calculations were not significant across all phantom sizes, beam energies, and treatment sites. The largest error observed was 0.6% among all dose volume histogram metrics and evaluated dose calculations. In contrast, dosimetric errors reached up to 7% and 97% in clinical CBCT and high‐performance ASG CBCT‐based treatment plans, respectively. The largest dosimetric errors were observed in bony targets in the large phantom treated with 6 MV beams. The trends of dosimetric errors in organs at risk were similar to those observed in the targets.ConclusionsThe proposed quantitative CBCT pipeline has the potential to provide comparable dose calculation accuracy to the gold‐standard planning CT in photon radiation therapy for the abdomen and pelvis. These robust dose calculations could eliminate the need for density overrides in CBCT images and enable direct utilization of CBCT images for dose delivery monitoring or online treatment plan adaptations before the delivery of radiation treatments.
Simultaneous catheter and multicriteria optimization for HDR cervical cancer brachytherapy with a complex intracavity/interstitial applicator
Authors: Bélanger Cédric , Aubin Sylviane , Lavallée Marie‐Claude , Beaulieu Luc 
Published: December 2023

AbstractBackgroundComplex intracavity and interstitial (IC/IS) applicators, such as the Venezia applicator, can improve the HR‐CTV coverage while adequately protecting organs at risk in the treatment of cervical cancer with high‐dose‐rate (HDR) brachytherapy. Although the Venezia applicator offers more choice for catheter selection, commercially available catheter and dose optimization algorithms are still missing for complex applicators. Moreover, studies on catheter and dose optimization for IC/IS implants in the treatment of cervical cancer are still limited.PurposeThis work aims to combine a GPU‐based multi‐criteria optimization (gMCO) algorithm with a sparse catheter (SC) optimization algorithm for the Venezia applicator.MethodsFifty‐eight cervical cancer patients who received 28 Gy in 4 fx of HDR brachytherapy with the Venezia applicator (combination to external beam radiation therapy) are retrospectively revisited. The modelization of the applicator is done by virtually reconstructing all the IS catheters passing through the ring. Template catheters are reconstructed using an in‐house python script. To perform simultaneous MCO and SC optimization (SC+MCO), the objective function includes aggregated dose objectives in a weighted sum and a group sparsity term that individually penalizes the contribution of IS catheters. Plans generated with the SC+MCO algorithm are compared with plans generated with MCO using clinical catheters (CC+MCO) and the clinical plans (CP). The EMBRACE II soft constraints (planning aims) and hard constraints (limits for prescribed dose) are used as plan evaluation criteria.ResultsCC+MCO gives the most important gain with an increase up to 20.7% in meeting all EMBRACE II soft constraints compared with CP. The SC+MCO algorithm (adding catheter optimization to MCO) provides a second order increase (up to 12.1% with total acceptance rate of 60.3% or 35/58) in the acceptance rate versus CC+MCO (total increase of 32.8% vs. CP). Acceptance rate in EMBRACE II hard constraints is 98.3% (57/58) for both CC+MCO and SC+MCO versus 91.4% (53/58) for CP. The median SC+MCO optimization time is 11 s to generate a total of 5000 Pareto‐optimal plans with different catheter configurations (position and number) for each fraction.ConclusionsSimultaneous catheter and MCO optimization is clinically feasible for HDR cervical cancer brachytherapy using the Venezia applicator. Clinical catheter configurations could be improved and/or the catheter number could be reduced without decreasing plan quality using SC+MCO compared with the CP.
Explanatory sequential mixed‐methods approach to understand how registered dietitians implemented computed tomography skeletal muscle assessments in clinical practice
Authors: Martin Lisa , Tom Mei , Basualdo‐Hammond Carlota , Baracos Vickie E. , Gramlich Leah 
Published: December 2023

AbstractBackgroundThere is a need to adopt valid techniques to assess skeletal muscle (SM) in clinical practice. SM can be precisely quantified from computed tomography (CT) images. This study describes how registered dietitians (RDs), trained to quantify SM from CT images, implemented this technique in clinical practice.MethodsThis was an explanatory sequential mixed‐methods design with a quantitative and a qualitative phase. RDs collected data describing how they implemented CT SM assessments in clinical practice, followed by a focus group exploring barriers and enablers to using CT SM assessments.ResultsRDs (N = 4) completed 96 CT SM assessments, with most (94%, N = 90/96) taking <15 min to complete. RDs identified reduced muscle mass in 63% (N = 45/72) of men and 71% (N = 17/24) of women. RDs used results of CT SM assessments to increase protein composition of the diet/nutrition support, advocate for initiation or longer duration of nutrition support, coordinate nutrition care, and provide nutrition education to patients and other health service providers. The main barriers to implementing CT SM assessments in clinical practice related to cumbersome health system processes (ie, CT image acquisition) and challenges integrating CT image analysis software into the health system computing environment.ConclusionPreliminary results suggest RDs found CT SM assessments positively contributed to their nutrition care practice, particularly in completing nutrition assessments and in planning, advocating for, and implementing nutrition interventions. Use of CT SM assessments in clinical practice requires innovative IT solutions and strategies to support skill development and use in clinical nutrition care.
Effects of real‐time VR clinical practice on reducing the stigma toward dementia among students of occupational therapy: A randomized controlled trial
Authors: Ueno Keita , Tanaka Hiroyuki , Niki Kazuyuki , Ueda Masaya , Tanaka Ayumi , Yokoi Katsushi , Naito Yasuo , Ishii Ryouhei 
Published: December 2023

AbstractAimThis study aimed to examine the effects of real‐time online clinical practice using real‐time virtual reality (VR) compared with 2D PC screening on reducing stigma toward dementia, and to investigate the feasibility of online clinical practice using VR.MethodsA single‐center, open‐label, randomized controlled trial was conducted. Occupational therapy students were randomized to view occupational therapy evaluation screens for dementia patients using a VR headset or 2D monitor. The Attitudes Toward Dementia Scale (ADS), the Dementia Knowledge Scale (DKS), and Images of the Elderly with Dementia (IED) were assessed before and after the intervention. The level of clinical practice satisfaction and the System Usability Scale (SUS) were also assessed.ResultsThe number of subjects in the intervention and control groups was 10 and 9, respectively. In ADS scores and IED, the main effect was shown in both groups and did not show interactions. In DKS scores, the main effect and interaction were not shown. The VR headset tended to be more usable than the 2D monitor in terms of usability. Satisfaction ratings indicated the characteristics of a realistic clinical experience through real‐time VR viewing.ConclusionReal‐time VR and 2D online clinical practice could reduce the stigma toward dementia, but there were no significant differences between the types. The real‐time VR experience was more similar to actual clinical practice than a 2D PC screening due to the sense of immersion, but issues in blinding and lack of audio and video quality were found.
Triangulating the path: Globalization, development, and migration in developing countries
Authors: Ullah A. K. M. Ahsan , Ferdous Jannatul 
Published: December 2023

AbstractThe purpose of this paper is to analyze how globalization responds to migration and development. Migration, globalization, and development are interconnected forces shaping our world, where the movement of people across borders, the spread of ideas and technologies, and socioeconomic progress influence and transform societies on a global scale. We argue that the interaction between globalization, migration, and development is three‐way, and that globalization does not always promote migration. To support our argument, we conducted an extensive review of the relevant literature. Content and contextual analyses were also conducted to provide a good overview of contemporary discourse on the three concepts: globalization, migration, and development. Of course, the interaction between globalization and development is controversial. Some argue that globalization has a negative impact on development. Others believe that globalization has been an important factor in reducing poverty and has led to faster improvements in life expectancy and other indicators of progress. We attempt to provide a theoretical framework to explain how globalization, migration, and development affect each other. This study has significant policy implications for both the Global South and the North.
Topographic correction of visible near‐infrared reflectance spectra for horizon‐scale soil organic carbon mapping
Authors: Duro Alyssa M. , Hirmas Daniel R. , Ajami Hoori , Billings Sharon A. , Zhang Xi , Li Li , Flores Alejandro , Moreno Victoria , Cao Xiaoyang , Guilinger James , Oleghe Ewan , Giménez Daniel , Gray Andrew , Sullivan Pamela L. 
Published: December 2023

AbstractUnderstanding soil organic carbon (SOC) response to global change has been hindered by an inability to map SOC at horizon scales relevant to coupled hydrologic and biogeochemical processes. Standard SOC measurements rely on homogenized samples taken from distinct depth intervals. Such sampling prevents an examination of fine‐scale SOC distribution within a soil horizon. Visible near‐infrared hyperspectral imaging (HSI) has been applied to intact monoliths and split cores surfaces to overcome this limitation. However, the roughness of these surfaces can influence HSI spectra by scattering reflected light in different directions posing challenges to fine‐scale SOC mapping. Here, we examine the influence of prescribed surface orientation on reflected spectra, develop a method for correcting topographic effects, and calibrate a partial least squares regression (PLSR) model for SOC prediction. Two empirical models that account for surface slope, aspect, and wavelength and two theoretical models that account for the geometry of the spectrometer were compared using 681 homogenized soil samples from across the United States that were packed into sample wells and presented to the spectrometer at 91 orientations. The empirical approach outperformed the more complex geometric models in correcting spectra taken at non‐flat configurations. Topographically corrected spectra reduced bias and error in SOC predicted by PLSR, particularly at slope angles greater than 30°. Our approach clears the way for investigating the spatial distributions of multiple soil properties on rough intact soil samples.
Designing power‐efficient SRAM cells with SGFinFETs using LECTOR technique
Authors: Sankranti Sivaiah , Roji Marjorie S. 
Published: December 2023

AbstractStatic random‐access memory (SRAM) plays a vital component of digital systems. The main issue of SRAM cells is power leakage, which results in an increase in chip area. Therefore this manuscript proposes a shorted‐gate fin‐type field‐effect transistor based SRAM cell utilizing leakage control transistor technique (SGFinFETs‐SRAM‐LECTOR) for decreasing the leakage power delay by improving the static noise margins (SNMs) together with power delay product (PDP). Here, the SGFinFETs‐SRAM‐LECTOR is primarily applied to stacking enhancement for lessening the leakage power dissipation (LPD). Two more transistors are used in LECTOR for reducing the leakage current with delay, which is based on transistor stacking. LECTOR employs two more transistors that are connected in series between pull‐up and pull‐down networks that means additional SG FinFETs PMOS transistor insertions amongst the pull‐up network and output terminal, additional SG FinFETs NMOS transistor insertions amidst the pull down network and output terminal. These additional transistors can decrease the leakage current. The simulation of the proposed approach is implemented in HSPICE simulation tool. Some metrics are computed to validate the efficacy of the proposed approach. Finally, the proposed technique reaches 11.31%, 51.47%, 45.46% less read delay, 44.44%, 26.33%, 33.45% less write delay, 36.12%, 45.28%, 26.45% less read power, 34.5%, 33.56%, 22.41% less write power, 37.4%, 15.3%, 26.54% high read SNM, 33.67%, 35.8%,12.09% high write SNM when analyzed to the existing models.
Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment
Authors: Padulo Caterina , Sestieri Carlo , Punzi Miriam , Picerni Eleonora , Chiacchiaretta Piero , Tullo Maria Giulia , Granzotto Alberto , Baldassarre Antonello , Onofrj Marco , Ferretti Antonio , Delli Pizzi Stefano , Sensi Stefano L. ,   for the Alzheimer's Disease Neuroimaging Iniziative
Published: December 2023

AbstractIntroductionAccumulating evidence indicates that the amygdala exhibits early signs of Alzheimer's disease (AD) pathology. However, it is still unknown whether the atrophy of distinct subfields of the amygdala also participates in the transition from healthy cognition to mild cognitive impairment (MCI).MethodsOur sample was derived from the AD Neuroimaging Initiative 3 and consisted of 97 cognitively healthy (HC) individuals, sorted into two groups based on their clinical follow‐up: 75 who remained stable (s‐HC) and 22 who converted to MCI within 48 months (c‐HC). Anatomical magnetic resonance (MR) images were analyzed using a semi‐automatic approach that combines probabilistic methods and a priori information from ex vivo MR images and histology to segment and obtain quantitative structural metrics for different amygdala subfields in each participant. Spearman's correlations were performed between MR measures and baseline and longitudinal neuropsychological measures. We also included anatomical measurements of the whole amygdala, the hippocampus, a key target of AD‐related pathology, and the whole cortical thickness as a test of spatial specificity.ResultsCompared with s‐HC individuals, c‐HC subjects showed a reduced right amygdala volume, whereas no significant difference was observed for hippocampal volumes or changes in cortical thickness. In the amygdala subfields, we observed selected atrophy patterns in the basolateral nuclear complex, anterior amygdala area, and transitional area. Macro‐structural alterations in these subfields correlated with variations of global indices of cognitive performance (measured at baseline and the 48‐month follow‐up), suggesting that amygdala changes shape the cognitive progression to MCI.DiscussionOur results provide anatomical evidence for the early involvement of the amygdala in the preclinical stages of AD.Highlights
Amygdala's atrophy marks elderly progression to mild cognitive impairment (MCI).
Amygdala's was observed within the basolateral and amygdaloid complexes.
Macro‐structural alterations were associated with cognitive decline.
No atrophy was found in the hippocampus and cortex.