Article
Biology
Jinlian Ma, Dexing Kong, Fa Wu, Lingyun Bao, Jing Yuan, Yusheng Liu
Summary: In this study, a new method based on MDenseNet is proposed for automatic segmentation of nodular lesions from ultrasound images. Experimental results demonstrate that the proposed method can accurately extract multiple nodules from thyroid and breast ultrasound images, with good accuracy and reproducibility, and it shows great potential in other clinical segmentation tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai
Summary: Omics fusion is an important preprocessing approach in medical image processing that assists in various studies. This study aims to develop a fusion methodology for predicting distant metastasis in nasopharyngeal carcinoma by mitigating the disparities in omics data and utilizing a label-softening technique and a multi-kernel-based neural network.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Shaherin Basith, Balachandran Manavalan, Gwang Lee
Summary: This study combined microsecond-scale unbiased molecular dynamics simulation with network analysis to elucidate the local and global conformational changes and allosteric communications in SOD1 systems. Structural analyses revealed significant variations in catalytic sites and stability due to unmetallated SOD1 systems and cysteine mutations. Dynamic motion analysis showed balanced atomic displacement and highly correlated motions in the Holo system.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Amirreza Khalili Golmankhaneh, Suemeyye Tunc, Agnieszka Matylda Schlichtinger, Dachel Martinez Asanza, Alireza Khalili Golmankhaneh
Summary: This article introduces important concepts such as fractal calculus and fractal analysis, the calculation of squared residuals, and the determination of Aikaike's information criterion for fitting cancer-related data. The study also investigates the double-size cancer in the fractal temporal dimension with respect to various mathematical models.
Article
Biology
Christophe Noel, Nicla Settembre
Summary: This study investigates the vascular disorders caused by sustained exposure to high-level hand-transmitted vibrations. The researchers found that the diameter of the digital arteries, wall shear stress, and wall shear stress temporal gradient were the most relevant hemodynamic descriptors. Furthermore, vibration-induced wall shear stress decreased and was proportional to the acceleration level. Vibration also caused a decrease in wall shear stress power for the frequency band associated with the sympathetic nervous system's activity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Xiaoyu Wang, Nitin Patil, Fuyi Li, Zhikang Wang, Haolan Zhan, Daniel Schmidt, Philip Thompson, Yuming Guo, Cornelia B. Landersdorfer, Hsin-Hui Shen, Anton Y. Peleg, Jian Li, Jiangning Song
Summary: In this study, we developed a machine learning framework called PmxPred for predicting polymyxin analogues with high antimicrobial activity against Gram-negative bacteria. The framework achieved good performance on multiple datasets, outperforming traditional transfer learning methods.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jorg Schilcher, Alva Nilsson, Oliver Andlid, Anders Eklund
Summary: Atypical femur fractures (AFF) are rare fractures associated with drugs used to prevent fractures in the elderly. Current radiological identification is limited, but deep learning models can improve accuracy. Data fusion using both image and tabular data can further enhance identification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Xin Zeng, Fan-Fang Meng, Xin Li, Kai -Yang Zhong, Bei Jiang, Yi Li
Summary: Accurately pinpointing protein-protein interaction site is crucial for understanding protein function and disease mechanisms. In this study, a groundbreaking graph-based computational model called GHGPR-PPIS was proposed, which utilized graph convolutional network and generalized PageRank techniques to predict PPIS. Experimental findings demonstrated the superiority of GHGPR-PPIS compared to other models, with excellent generalization performance and practical applicability.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qianqian Wang, Mingyu Zhang, Aohan Li, Xiaojun Yao, Yingqing Chen
Summary: The development of PARP-1 inhibitors is crucial for the treatment of various cancers. This study investigates the structural regulation of PARP-1 by different allosteric inhibitors, revealing the basis of allosteric inhibition and providing guidance for the discovery of more innovative PARP-1 inhibitors.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Ramin Ranjbarzadeh, Payam Zarbakhsh, Annalina Caputo, Erfan Babaee Tirkolaee, Malika Bendechache
Summary: This study proposes an automatic and robust brain tumor segmentation framework using four MRI sequence images. The weight and bias values of the CNN model are adjusted using an Improved Chimp Optimization Algorithm (IChOA), and the best features are selected using a Support Vector Machine (SVM) classifier. The proposed framework achieves superior performance compared to existing frameworks on the BRATS 2018 dataset.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng
Summary: This study proposes a deep unrolled neural network, pFISTA-DR, for radial MRI image reconstruction, which successfully preserves image details using a preprocessing module, learnable convolution filters, and adaptive threshold.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhenxiang Xiao, Liang He, Boyu Zhao, Mingxin Jiang, Wei Mao, Yuzhong Chen, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang
Summary: This study systematically investigates the functional connectivity characteristics between gyri and sulci in the human brain under naturalistic stimulus, and identifies unique features in these connections. This research provides novel insights into the functional brain mechanism under naturalistic stimulus and lays a solid foundation for accurately mapping the brain anatomy-function relationship.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Aref Maddahi, Adel Saberivand, Hossein Hamali, Farnoosh Jafarpour, Maryam Saberivand
Summary: Heat stress affects the fertility of dairy cattle, but supplementing vitamins E and coenzyme Q10 can alleviate its adverse effects on oocyte maturation and embryo development. Vitamin E was found to be more effective than vitamin C and coenzyme Q10 in improving maturation and cleavage rates, as well as increasing the count of blastocyst cells.
JOURNAL OF THERMAL BIOLOGY
(2024)
Article
Biology
Seyyed Bahram Borgheai, Alyssa Hillary Zisk, John McLinden, James Mcintyre, Reza Sadjadi, Yalda Shahriari
Summary: This study proposed a novel personalized scheme using fNIRS and EEG as the main tools to predict and compensate for the variability in BCI systems, especially for individuals with severe motor deficits. By establishing predictive models, it was found that there were significant associations between the predicted performances and the actual performances.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jingfei Hu, Linwei Qiu, Hua Wang, Jicong Zhang
Summary: This study proposes a novel semi-supervised point consistency network (SPC-Net) for retinal artery/vein (A/V) classification, addressing the challenges of specific tubular structures and limited well-labeled data in CNN-based approaches. The SPC-Net combines an AVC module and an MPC module, and introduces point set representations and consistency regularization to improve the accuracy of A/V classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Theodoros Kyriazos, Mary Poga
Summary: This paper explores the innovative intersection of quantum mechanics and psychology, examining the potential impact of quantum principles on human emotions, cognition, and consciousness. By drawing parallels between quantum phenomena and psychological counterparts, a quantum-psychological model is proposed, reimagining the characteristics of emotional states, cognitive breakthroughs, interpersonal relationships, and the nature of consciousness. Computational models and simulations are used to explore the implications and applications of this interdisciplinary fusion, highlighting its potential benefits and inherent challenges. Approaching this emerging framework with both enthusiasm and skepticism is crucial, and rigorous empirical validation is necessary to fully realize its potential in research and therapeutic contexts.
Article
Biology
Arturo Avendano-Estrada, Miguel Angel Olarte-Casas, Miguel Angel Avila-Rodriguez
Summary: The diagnosis of neurological diseases is complicated, but PET molecular imaging can help with early and accurate diagnosis and staging. This study proposed a novel method to combine PET data of two radiopharmaceuticals and obtain new quantitative metrics. The results showed that this method can effectively differentiate healthy controls from Parkinson's disease patients and detect slight changes in patients undergoing treatment.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Antonio Picornell, Sandro Hurtado, Maria Luisa Antequera-Gomez, Cristobal Barba-Gonzalez, Rocio Ruiz-Mata, Enrique de Galvez-Montanez, Marta Recio, Maria del Mar Trigo, Jose F. Aldana-Montes, Ismael Navas-Delgado
Summary: Airborne pollen can cause allergic rhinitis and other respiratory diseases, making accurate pollen forecast systems crucial for public health. This study applied LSTM algorithms to forecast monthly pollen integrals in Malaga and found that the CNN-LSTM model was the most accurate. Traditional forecast methods were outperformed by all LSTM variants.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
P. Michaux, B. Gaume, Y. Cong, O. Quemener
Summary: This article presents the development of a digital twin model for the thigh portion undergoing various thermal treatments. Two scenarios, cold water immersion (CWI) and whole body cryotherapy (WBC), are investigated and the numerical results are validated against experimental measurements. The use of real geometry on a first subject demonstrates the heterogeneity of the temperature field and the importance of accurate geometry. A second subject with thicker adipose tissue highlights the impact of the subject's actual morphology on treatment validity and the need for real geometry to optimize cold modalities and develop personalized treatments.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhixin Xu, Seohoon Lim, Yucheng Lu, Seung-Won Jung
Summary: Despite the new paradigm brought by digital pathology in modern medicine, the lack of annotations for training poses a significant challenge. This research focuses on enhancing the model's generalization ability through domain adaptation, using only source domain labels to train the model and improving prediction ability for target domain data. Additionally, nuclei segmentation is introduced to provide more diagnostically valuable information for classification, and a reversed domain adaptation strategy is proposed to generate target-like results in the source domain, making the classification model more robust to inaccurate segmentation. Extensive experiments demonstrate that the proposed method effectively reduces disparities in nuclei segmentation between the source and target domains, leading to improved image classification performance in the target domain.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
