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JOURNAL ARTICLE
Cesar Alexander Ortiz Rojas, Diego Antonio Pereira-Martins, Candy Christie Bellido More, Dominique Sternadt, Isabel Weinhäuser, Jacobien R Hilberink, Juan Luiz Coelho-Silva, Carolina Hassibe Thomé, Germano Aguiar Ferreira, Emanuele Ammatuna, Gerwin Huls, Peter J Valk, Jan Jacob Schuringa, Eduardo Magalhães Rego
Despite advancements in utilizing genetic markers to enhance acute myeloid leukaemia (AML) outcome prediction, significant disease heterogeneity persists, hindering clinical management. To refine survival predictions, we assessed the transcriptome of non-acute promyelocytic leukaemia chemotherapy-treated AML patients from five cohorts (n = 975). This led to the identification of a 4-gene prognostic index (4-PI) comprising CYP2E1, DHCR7, IL2RA and SQLE. The 4-PI effectively stratified patients into risk categories, with the high 4-PI group exhibiting TP53 mutations and cholesterol biosynthesis signatures...
April 23, 2024: British Journal of Haematology
#2
JOURNAL ARTICLE
Naveen Paluru, Raji Susan Mathew, Phaneendra K Yalavarthy
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability...
April 22, 2024: NMR in Biomedicine
#3
JOURNAL ARTICLE
Gabor Nagy, Søren Vrønning Hoffmann, Nykola C Jones, Helmut Grubmüller
Circular dichroism (CD) spectroscopy is an analytical technique that measures the wavelength-dependent differential absorbance of circularly polarized light and is applicable to most biologically important macromolecules, such as proteins, nucleic acids, and carbohydrates. It serves to characterize the secondary structure composition of proteins, including intrinsically disordered proteins, by analyzing their recorded spectra. Several computational tools have been developed to interpret protein CD spectra. These methods have been calibrated and tested mostly on globular proteins with well-defined structures, mainly due to the lack of reliable reference structures for disordered proteins...
April 22, 2024: Applied Spectroscopy
#4
JOURNAL ARTICLE
Ahmed M Zayed, Veroniek Saegeman, Nicolas Delvaux
BACKGROUND: This paper presents a data-driven strategy for establishing the reportable interval in clinical laboratory testing. The reportable interval defines the range of laboratory result values beyond which reporting should be withheld. The lack of clear guidelines and methodology for determining the reportable interval has led to potential errors in reporting and patient risk. METHODS: To address this gap, the study developed an integrated strategy that combines statistical analysis, expert review, and hypothetical outlier calculations...
March 26, 2024: Journal of Applied Laboratory Medicine
#5
JOURNAL ARTICLE
Qin-Hua Guo, Feng-Chun Xie, Fang-Min Zhong, Wen Wen, Xue-Ru Zhang, Xia-Jing Yu, Xin-Lu Wang, Bo Huang, Li-Ping Li, Xiao-Zhong Wang
BACKGROUND: Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC. METHODS: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015...
April 2024: Cancer Medicine
#6
JOURNAL ARTICLE
Kelvin Walenta, Simon Genser, Selim Solmaz
In the realm of road safety and the evolution toward automated driving, Advanced Driver Assistance and Automated Driving (ADAS/AD) systems play a pivotal role. As the complexity of these systems grows, comprehensive testing becomes imperative, with virtual test environments becoming crucial, especially for handling diverse and challenging scenarios. Radar sensors are integral to ADAS/AD units and are known for their robust performance even in adverse conditions. However, accurately modeling the radar's perception, particularly the radar cross-section (RCS), proves challenging...
March 28, 2024: Sensors
#7
JOURNAL ARTICLE
Chenbo Shi, Zheng Qin, Xiaowei Hu, Changsheng Zhu, Yuanzheng Mo, Zelong Li, Shaojia Yan, Yue Yu, Xiangteng Zang, Chun Zhang
Fringe projection profilometry (FPP), with benefits such as high precision and a large depth of field, is a popular 3D optical measurement method widely used in precision reconstruction scenarios. However, the pixel brightness at reflective edges does not satisfy the conditions of the ideal pixel-wise phase-shifting model due to the influence of scene texture and system defocus, resulting in severe phase errors. To address this problem, we theoretically analyze the non-pixel-wise phase propagation model for texture edges and propose a reprojection strategy based on scene texture modulation...
March 24, 2024: Sensors
#8
JOURNAL ARTICLE
Levi Matthies, Hendrik Amir-Kabirian, Medhanie T Gebrekidan, Andreas S Braeuer, Ulrike S Speth, Ralf Smeets, Christian Hagel, Martin Gosau, Christian Knipfer, Reinhard E Friedrich
In Neurofibromatosis type 1 (NF1), peripheral nerve sheaths tumors are common, with cutaneous neurofibromas resulting in significant aesthetic, painful and functional problems requiring surgical removal. To date, determination of adequate surgical resection margins-complete tumor removal while attempting to preserve viable tissue-remains largely subjective. Thus, residual tumor extension beyond surgical margins or recurrence of the disease may frequently be observed. Here, we introduce Shifted-Excitation Raman Spectroscopy in combination with deep neural networks for the future perspective of objective, real-time diagnosis, and guided surgical ablation...
2024: PloS One
#9
JOURNAL ARTICLE
Dorit Hadar-Shoval, Kfir Asraf, Yonathan Mizrachi, Yuval Haber, Zohar Elyoseph
BACKGROUND: Large language models (LLMs) hold potential for mental health applications. However, their opaque alignment processes may embed biases that shape problematic perspectives. Evaluating the values embedded within LLMs that guide their decision-making have ethical importance. Schwartz's theory of basic values (STBV) provides a framework for quantifying cultural value orientations and has shown utility for examining values in mental health contexts, including cultural, diagnostic, and therapist-client dynamics...
April 9, 2024: JMIR Mental Health
#10
JOURNAL ARTICLE
Xiao Liu, Stephen J Read
INTRODUCTION: Individuals with depression who do not respond to two or more courses of serotonergic antidepressants tend to have greater deficits in reward processing and greater internalizing symptoms, yet there is no validated self-report method to determine the likelihood of treatment resistance based on these symptom dimensions. METHODS: This online case-control study leverages machine learning techniques to identify differences in self-reported anhedonia and internalizing symptom profiles of antidepressant non-responders compared to responders and healthy controls, as an initial proof-of-concept for relating these indicators to medication responsiveness...
2024: Frontiers in Psychiatry
#11
Marvin Petersen, Mirthe Coenen, Charles DeCarli, Alberto De Luca, Ewoud van der Lelij, Frederik Barkhof, Thomas Benke, Christopher P L H Chen, Peter Dal-Bianco, Anna Dewenter, Marco Duering, Christian Enzinger, Michael Ewers, Lieza G Exalto, Evan F Fletcher, Nicolai Franzmeier, Saima Hilal, Edith Hofer, Huiberdina L Koek, Andrea B Maier, Pauline M Maillard, Cheryl R McCreary, Janne M Papma, Yolande A L Pijnenburg, Anna Rubinski, Reinhold Schmidt, Eric E Smith, Rebecca M E Steketee, Esther van den Berg, Wiesje M van der Flier, Vikram Venkatraghavan, Narayanaswamy Venketasubramanian, Meike W Vernooij, Frank J Wolters, Xu Xin, Andreas Horn, Kaustubh R Patil, Simon B Eickhoff, Götz Thomalla, J Matthijs Biesbroek, Geert Jan Biessels, Bastian Cheng
INTRODUCTION: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enabling the inference of brain networks disconnected by lesions, represents a promising technique for enhancing our understanding of the role of WMH in cognitive disorders...
March 28, 2024: medRxiv
#12
JOURNAL ARTICLE
Zejun Liang, Qian Wang, Chunchao Xia, Zengtong Chen, Miao Xu, Guilun Liang, Yu Zhang, Chao Ye, Yiteng Zhang, Xiaocheng Yu, Hairong Wang, Han Zheng, Jing Du, Zhenlin Li, Jing Tang
BACKGROUND CONTEXT: Adolescent idiopathic scoliosis (AIS) necessitates accurate spinal curvature assessment for effective clinical management. Traditional two-dimensional (2D) Cobb angle measurements have been the standard, but the emergence of three-dimensional (3D) automatic measurement techniques, such as those using weight-bearing 3D imaging (WR3D), presents an opportunity to enhance the accuracy and comprehensiveness of AIS evaluation. PURPOSE: This study aimed to compare traditional 2D Cobb angle measurements with 3D automatic measurements utilizing the WR3D imaging technique in patients with AIS...
April 5, 2024: Spine Journal: Official Journal of the North American Spine Society
#13
RANDOMIZED CONTROLLED TRIAL
Yalin Zhang, Huiling Liu, Cheng Chang, Yong Yin, Ruozheng Wang
Noninvasive differentiation between the squamous cell carcinoma (SCC) and adenocarcinoma (ADC) subtypes of non-small cell lung cancer (NSCLC) could benefit patients who are unsuitable for invasive diagnostic procedures. Therefore, this study evaluates the predictive performance of a PET/CT-based radiomics model. It aims to distinguish between the histological subtypes of lung adenocarcinoma and squamous cell carcinoma, employing four different machine learning techniques. A total of 255 Non-Small Cell Lung Cancer (NSCLC) patients were retrospectively analyzed and randomly divided into the training (n = 177) and validation (n = 78) sets, respectively...
2024: PloS One
#14
REVIEW
Arnab Mukherjee, Suzanna Abraham, Akshita Singh, S Balaji, K S Mukunthan
In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers...
April 2, 2024: Molecular Biotechnology
#15
JOURNAL ARTICLE
Clara S Kim, Nathalie A Reisbig, James L Carmalt
BACKGROUND: Disorders of the equine temporomandibular joint (TMJ) cause clinical problems and detailed investigations of this joint are becoming more common. Specialist radiographic projections have the potential to highlight osseous abnormalities; however, the ability to assess the intra-articular soft tissue structures is currently limited to computed tomography (with, or without contrast enhancement) or magnetic resonance imaging. Both modalities are expensive and not readily accessible...
2024: Frontiers in Veterinary Science
#16
JOURNAL ARTICLE
Hua Wang, Jichong Ying, Jianlei Liu, Tianming Yu, Dichao Huang
BACKGROUND: Ankle fractures are prevalent injuries that necessitate precise diagnostic tools. Traditional diagnostic methods have limitations that can be addressed using machine learning techniques, with the potential to improve accuracy and expedite diagnoses. METHODS: We trained various deep learning architectures, notably the Adapted ResNet50 with SENet capabilities, to identify ankle fractures using a curated dataset of radiographic images. Model performance was evaluated using common metrics like accuracy, precision, and recall...
April 1, 2024: BMC Musculoskeletal Disorders
#17
JOURNAL ARTICLE
Sudip Kumar Sengupta, Rohit Aggarwal, Manish Kumar Singh
There are proponents of decompressive craniectomy (DC) and its various modifications who claim reasonable clinical outcomes for each of them. Clinical outcome in cases of traumatic brain injury, managed conservatively or aided by different surgical techniques, depends on multiple factors, which vary widely among patients and have complex interplay, making it difficult to compare one case with another in absolute terms. This forms the basis of the perceived necessity to have a standard model to study, compare, and strategize in this field...
2024: Neurotrauma reports
#18
JOURNAL ARTICLE
Li Li, Weiwei Zhang, Yanjun Sun, Weiling Zhang, Mengmeng Lu, Jiaqian Wang, Yunfeng Jin, Qinghua Xi
BACKGROUND: According to statistics, ovarian cancer (OV) is the most prevalent type of gynecologic malignancy and has the highest mortality rate of all gynecologic tumors. Although several studies have shown that oxidative stress (OS) contributes significantly to the onset and progression of cancer, the role of OS in OV needs to be investigated further. Thus, it is critical to comprehend the function of OS-related genes in OV. METHODS: In this study, all data related to the transcriptome and clinical status of the patients were retrieved from "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) databases...
April 15, 2024: Heliyon
#19
JOURNAL ARTICLE
Jiahong Fu, Qi Xie, Deyu Meng, Zongben Xu
The deep unfolding approach has attracted significant attention in computer vision tasks, which well connects conventional image processing modeling manners with more recent deep learning techniques. Specifically, by establishing a direct correspondence between algorithm operators at each implementation step and network modules within each layer, one can rationally construct an almost "white box" network architecture with high interpretability. In this architecture, only the predefined component of the proximal operator, known as a proximal network, needs manual configuration, enabling the network to automatically extract intrinsic image priors in a data-driven manner...
April 1, 2024: IEEE Transactions on Pattern Analysis and Machine Intelligence
#20
JOURNAL ARTICLE
Santiago Martínez, Loïs Morineau, Joana Fernandes, Fabien Chainet
BACKGROUND: Chlorine concentrations above 1 mg kg-1 in lipid feedstocks for biofuel production can generate corrosion issues in the different refining units as well as catalyst deactivation by clogging or fouling. To reach accurate analyses by inductively coupled plasma (ICP) techniques at low concentration levels, dilution in organic solvents rises as a simpler and more straightforward sample preparation methodology than conventional sample decomposition procedures (e.g., microwave-assisted acid digestion)...
May 1, 2024: Analytica Chimica Acta
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