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Nutrients Aug 2023The aim of this investigation was to determine whether, after Ramadan, pre-exercise caffeine intake can reduce any possible negative effects of this month on short-term... (Randomized Controlled Trial)
Randomized Controlled Trial
Pre-Exercise Caffeine Intake Attenuates the Negative Effects of Ramadan Fasting on Several Aspects of High-Intensity Short-Term Maximal Performances in Adolescent Female Handball Players.
The aim of this investigation was to determine whether, after Ramadan, pre-exercise caffeine intake can reduce any possible negative effects of this month on short-term maximal performances in young female handball players. A randomized study involved thirteen young female handball players. Participants performed a squat jump (SJ), Illinois agility test (AG), and 5 m run shuttles test (total (TD) and peak (PD) distances) at 08:00 AM and 06:00 PM on three different occasions: one week before Ramadan (Pre-R), the last week of Ramadan (R), and the week after Ramadan (Post-R). A placebo (Pla) or caffeine (Caff) (6 mg·kg) was administered 60 min before exercise test sessions at two distinct times of day (08:00 AM and 06:00 PM) during the two periods: Pre and Post-R. The PSQI and dietary intake were assessed during all testing periods. The results revealed that Pre-R, (SJ, AG, TD, and PD) test performances were greater in the evening (PM) than in the morning (AM) (all < 0.001). However, compared with Pre-R, PM performances declined significantly during R (all < 0.001) and Post-R ( < 0.05, < 0.01, < 0.01 and < 0.001, respectively). In addition, Pre-R, AM Caff produced moderate significant improvements compared with AM Pla, with small-to-no beneficial effects observed with PM Caff in SJ (4.8% vs. 1%), AG (1.8% vs. 0.8%), TD (2.8% vs. 0.3%), and PD (6% vs. 0.9%). Nevertheless, Caff produced moderate ergogenic effects during both AM and PM sessions during Post-R in SJ (4.4% vs. 2.4%), AG (1.7% vs. 1.5%), TD (2.9% vs. 1.3%), and PD (5.8% vs. 3%) with values approaching those of Pre-R Pla within the same time of day ( > 0.05, > 0.05, < 0.05, and < 0.05, respectively). In summary, pre-exercise Caff intake with a dose equivalent to 6 mg·kg reduced the negative effects of Ramadan fasting in several aspects of short-term maximal performances in young female handball players at both times of the day.
Topics: Adolescent; Female; Humans; Athletic Performance; Caffeine; Eating; Fasting; Sports; Time
PubMed: 37571369
DOI: 10.3390/nu15153432 -
Cancer Imaging : the Official... Nov 2023This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central...
BACKGROUND
This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters.
METHODS
A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δ = 7.1 ms) and conventional pulsed gradient (Δ = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC and ADC), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95 percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices.
RESULTS
In enhancing regions, the mean and fifth and 95 percentile values of ADC and ADC in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95 percentile of ADC, p = 0.04 for ADC, and p < 0.01 for others). Furthermore, the mean and fifth and 95 percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC was significantly lower than that for ADC (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC, ADC, cADC, and rcADC was observed between PCNSLs and GBMs.
CONCLUSIONS
Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.
Topics: Humans; Glioblastoma; Brain Neoplasms; Retrospective Studies; Diffusion Magnetic Resonance Imaging; Diagnosis, Differential; Lymphoma; Central Nervous System
PubMed: 38037172
DOI: 10.1186/s40644-023-00639-7 -
Computers in Biology and Medicine Sep 2023Deep learning (DL) has become one of the major approaches in computational dermatopathology, evidenced by a significant increase in this topic in the current literature....
Deep learning (DL) has become one of the major approaches in computational dermatopathology, evidenced by a significant increase in this topic in the current literature. We aim to provide a structured and comprehensive overview of peer-reviewed publications on DL applied to dermatopathology focused on melanoma. In comparison to well-published DL methods on non-medical images (e.g., classification on ImageNet), this field of application comprises a specific set of challenges, such as staining artifacts, large gigapixel images, and various magnification levels. Thus, we are particularly interested in the pathology-specific technical state-of-the-art. We also aim to summarize the best performances achieved thus far with respect to accuracy, along with an overview of self-reported limitations. Accordingly, we conducted a systematic literature review of peer-reviewed journal and conference articles published between 2012 and 2022 in the databases ACM Digital Library, Embase, IEEE Xplore, PubMed, and Scopus, expanded by forward and backward searches to identify 495 potentially eligible studies. After screening for relevance and quality, a total of 54 studies were included. We qualitatively summarized and analyzed these studies from technical, problem-oriented, and task-oriented perspectives. Our findings suggest that the technical aspects of DL for histopathology in melanoma can be further improved. The DL methodology was adopted later in this field, and still lacks the wider adoption of DL methods already shown to be effective for other applications. We also discuss upcoming trends toward ImageNet-based feature extraction and larger models. While DL has achieved human-competitive accuracy in routine pathological tasks, its performance on advanced tasks is still inferior to wet-lab testing (for example). Finally, we discuss the challenges impeding the translation of DL methods to clinical practice and provide insight into future research directions.
Topics: Humans; Deep Learning; Melanoma
PubMed: 37315382
DOI: 10.1016/j.compbiomed.2023.107083 -
Scientific Reports Aug 2023Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges,...
Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they provide a wealth of information about gene expression at the cell level, but they are expensive, hindering their use in large-scale clinical oncology studies. Predicting gene expression from hematoxylin and eosin stained histology images provides a more affordable alternative for such studies. Here we present BrST-Net, a deep learning framework for predicting gene expression from histopathology images using spatial transcriptomics data. Using this framework, we trained and evaluated four distinct state-of-the-art deep learning architectures, which include ResNet101, Inception-v3, EfficientNet (with six different variants), and vision transformer (with two different variants), all without utilizing pretrained weights for the prediction of 250 genes. To enhance the generalisation performance of the main network, we introduce an auxiliary network into the framework. Our methodology outperforms previous studies, with 237 genes identified with positive correlation, including 24 genes with a median correlation coefficient greater than 0.50. This is a notable improvement over previous studies, which could predict only 102 genes with positive correlation, with the highest correlation values ranging from 0.29 to 0.34.
Topics: Animals; Deep Learning; Transcriptome; Gene Expression Profiling; Mammary Neoplasms, Animal; Electric Power Supplies
PubMed: 37604916
DOI: 10.1038/s41598-023-40219-0 -
Biomolecules Jul 2023Humankind is witnessing a gradual increase in cancer incidence, emphasizing the importance of early diagnosis and treatment, and follow-up clinical protocols. Oral or...
Humankind is witnessing a gradual increase in cancer incidence, emphasizing the importance of early diagnosis and treatment, and follow-up clinical protocols. Oral or mouth cancer, categorized under head and neck cancers, requires effective screening for timely detection. This study proposes a framework, OralNet, for oral cancer detection using histopathology images. The research encompasses four stages: (i) Image collection and preprocessing, gathering and preparing histopathology images for analysis; (ii) feature extraction using deep and handcrafted scheme, extracting relevant features from images using deep learning techniques and traditional methods; (iii) feature reduction artificial hummingbird algorithm (AHA) and concatenation: Reducing feature dimensionality using AHA and concatenating them serially and (iv) binary classification and performance validation with three-fold cross-validation: Classifying images as healthy or oral squamous cell carcinoma and evaluating the framework's performance using three-fold cross-validation. The current study examined whole slide biopsy images at 100× and 400× magnifications. To establish OralNet's validity, 3000 cropped and resized images were reviewed, comprising 1500 healthy and 1500 oral squamous cell carcinoma images. Experimental results using OralNet achieved an oral cancer detection accuracy exceeding 99.5%. These findings confirm the clinical significance of the proposed technique in detecting oral cancer presence in histology slides.
Topics: Humans; Carcinoma, Squamous Cell; Squamous Cell Carcinoma of Head and Neck; Mouth Neoplasms; Algorithms; Head and Neck Neoplasms
PubMed: 37509126
DOI: 10.3390/biom13071090 -
The Journal of Pathology Aug 2023Computational pathology is currently witnessing a surge in the development of AI techniques, offering promise for achieving breakthroughs and significantly impacting the... (Review)
Review
Computational pathology is currently witnessing a surge in the development of AI techniques, offering promise for achieving breakthroughs and significantly impacting the practices of pathology and oncology. These AI methods bring with them the potential to revolutionize diagnostic pipelines as well as treatment planning and overall patient care. Numerous peer-reviewed studies reporting remarkable performance across diverse tasks serve as a testimony to the potential of AI in the field. However, widespread adoption of these methods in clinical and pre-clinical settings still remains a challenge. In this review article, we present a detailed analysis of the major obstacles encountered during the development of effective models and their deployment in practice. We aim to provide readers with an overview of the latest developments, assist them with insights into identifying some specific challenges that may require resolution, and suggest recommendations and potential future research directions. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Topics: Humans; Artificial Intelligence; United Kingdom
PubMed: 37550878
DOI: 10.1002/path.6168 -
Acta Neuropathologica Communications Aug 2023Cerebrovascular pathologies other than frank infarctions are commonly seen in aged brains. Here, we focus on multi-lumen vascular profiles (MVPs), which are...
Cerebrovascular pathologies other than frank infarctions are commonly seen in aged brains. Here, we focus on multi-lumen vascular profiles (MVPs), which are characterized by multiple vessel lumens enclosed in a single vascular channel. Little information exists on the prevalence, risk factors, and co-pathologies of MVPs. Therefore, we used samples and data from the University of Kentucky Alzheimer's Disease Research Center (n = 91), the University of Kentucky Pathology Department (n = 31), and the University of Pittsburgh Pathology Department (n = 4) to study MVPs. Age at death was correlated with MVP density in the frontal neocortex, Brodmann Area 9 (r = 0.51; p < 0.0001). Exploratory analyses were performed to evaluate the association between conventional vascular risk factors (e.g., hypertension, diabetes), cardiovascular diseases (e.g., heart attack, arrhythmia), and cerebrovascular disease (e.g., stroke); the only nominal association with MVP density was a self-reported history of brain trauma (Prevalence Ratio = 2.1; 95 CI 1.1-3.9, before correcting for multiple comparisons). No specific associations were detected between neuropathological (e.g., brain arteriolosclerosis) or genetic (e.g., APOE) variables and MVP density. Using a tissue clearing method called SeeDB, we provide 3-dimensional images of MVPs in brain tissue. We conclude that MVPs are an age-related brain pathology and more work is required to identify their clinical-pathological correlation and associated risk factors.
Topics: Humans; Aged; Brain; Neuropathology; Stroke; Brain Injuries, Traumatic; Aging
PubMed: 37641147
DOI: 10.1186/s40478-023-01638-2 -
Cancer Science Aug 2023Most multigene mutation tests require tissue specimens. However, cytological specimens are easily obtained in the clinical practice and provide high-quality DNA and RNA....
Most multigene mutation tests require tissue specimens. However, cytological specimens are easily obtained in the clinical practice and provide high-quality DNA and RNA. We aimed to establish a test that utilizes cytological specimens and performed a multi-institutional study to investigate the performance of MINtS, a test based on next-generation sequencing. A standard procedure for specimen isolation was defined. The specimens were considered suitable for the test if >100 ng DNA and >50 ng RNA could be extracted from them. In total, 500 specimens from 19 institutions were investigated. MINtS detected druggable mutations in 63% (136 of 222) of adenocarcinomas. Discordant results between MINtS and the companion diagnostics were observed in 14 of 310 specimens for the EGFR gene, and 6 of 339 specimens for the ALK fusion genes. Confirmation by other companion diagnostics for the EGFR mutations or the clinical response to an ALK inhibitor all supported the results obtained by MINtS. MINtS along with the isolation procedure presented in the current study will be a platform to establish multigene mutation tests that utilize cytological specimens. UMIN000040415.
Topics: Humans; Cytology; Lung Neoplasms; Mutation; Receptor Protein-Tyrosine Kinases; RNA
PubMed: 37139543
DOI: 10.1111/cas.15831 -
Medical Image Analysis Feb 2024Artificial intelligence (AI) has a multitude of applications in cancer research and oncology. However, the training of AI systems is impeded by the limited availability...
Artificial intelligence (AI) has a multitude of applications in cancer research and oncology. However, the training of AI systems is impeded by the limited availability of large datasets due to data protection requirements and other regulatory obstacles. Federated and swarm learning represent possible solutions to this problem by collaboratively training AI models while avoiding data transfer. However, in these decentralized methods, weight updates are still transferred to the aggregation server for merging the models. This leaves the possibility for a breach of data privacy, for example by model inversion or membership inference attacks by untrusted servers. Somewhat-homomorphically-encrypted federated learning (SHEFL) is a solution to this problem because only encrypted weights are transferred, and model updates are performed in the encrypted space. Here, we demonstrate the first successful implementation of SHEFL in a range of clinically relevant tasks in cancer image analysis on multicentric datasets in radiology and histopathology. We show that SHEFL enables the training of AI models which outperform locally trained models and perform on par with models which are centrally trained. In the future, SHEFL can enable multiple institutions to co-train AI models without forsaking data governance and without ever transmitting any decryptable data to untrusted servers.
Topics: Humans; Artificial Intelligence; Learning; Neoplasms; Image Processing, Computer-Assisted; Radiology
PubMed: 38104402
DOI: 10.1016/j.media.2023.103059 -
Journal of Cellular and Molecular... Oct 2023Endometrial cancer (EC) is a common gynaecological malignant tumour with unclear pathogenesis. Small nucleolar RNA (snoRNA) is involved in many biological processes,...
Endometrial cancer (EC) is a common gynaecological malignant tumour with unclear pathogenesis. Small nucleolar RNA (snoRNA) is involved in many biological processes, including those of cancers. Using the Cancer Genome Atlas (TCGA) database, the expression pattern of a snoRNA, SNORA73B, was analysed. The biological functions of SNORA73B were assessed by in vitro proliferation, apoptosis, migration, and invasion assays and in vivo by the xenograft model. RNA sequencing (RNA-seq) and RNA immunoprecipitation assays were performed to determine the relationship between SNORA73B and its target genes. High-performance liquid chromatography (HPLC) was performed to detect the pseudouridine content of the mindbomb E3 ubiquitin protein ligase 1 gene (MIB1). The stability of MIB1 mRNA was evaluated using a transcription inhibitor, actinomycin D. By performing co-immunoprecipitation assays, the change in the ubiquitin levels of the Jagged canonical Notch ligand 1 (Jag 1), caused by SNORA73B and MIB1, was identified. RNA-seq and qRT-PCR were performed to detect the alternative splicing of the regulator of the chromosome condensation 1 gene (RCC1). The TCGA database analysis showed that SNORA73B was highly expressed in EC. SNORA73B promoted cell proliferation, migration, and invasion and inhibited apoptosis. SNORA73B modified the pseudouridine content in MIB1 and increased the stability of MIB1 mRNA and protein; thus, it affected Jag 1 ubiquitination and further activated the Notch pathway. SNORA73B also affected the alternative splicing of RCC1, increasing the number of transcripts, RCC1-T2 and RCC1-T3, which promoted cell proliferation, migration, and invasion. SNORA73B can be a potential target for EC.
Topics: Female; Humans; Ubiquitin-Protein Ligases; Alternative Splicing; Pseudouridine; RNA, Small Nucleolar; Endometrial Neoplasms; RNA, Messenger; Cell Proliferation; Cell Line, Tumor; Gene Expression Regulation, Neoplastic; Nuclear Proteins; Cell Cycle Proteins; Guanine Nucleotide Exchange Factors
PubMed: 37488742
DOI: 10.1111/jcmm.17850