Artificial Intelligence and Machine Learning in Cancer Research: A Systematic and Thematic Analysis of the Top 100 Cited Articles Indexed in Scopus Database.

INTRODUCTION: Cancer is a major public health problem and a global leading cause of death where the screening, diagnosis, prediction, survival estimation, and treatment of cancer and control measures are still a major challenge. The rise of Artificial Intelligence (AI) and Machine Learning (ML) techniques and their applications in various fields have brought immense value in providing insights into advancement in support of cancer control. METHODS: A systematic and thematic analysis was performed on the Scopus database to identify the top 100 cited articles in cancer research. Data were analyzed using RStudio and VOSviewer.Var1.6.6. RESULTS: The top 100 articles in AI and ML in cancer received a 33 920 citation score with a range of 108 to 5758 times. Doi Kunio from the USA was the most cited author with total number of citations (TNC = 663). Out of 43 contributed countries, 30% of the top 100 cited articles originated from the USA, and 10% originated from China. Among the 57 peer-reviewed journals, the "Expert Systems with Application" published 8% of the total articles. The results were presented in highlight technological advancement through AI and ML via the widespread use of Artificial Neural Network (ANNs), Deep Learning or machine learning techniques, Mammography-based Model, Convolutional Neural Networks (SC-CNN), and text mining techniques in the prediction, diagnosis, and prevention of various types of cancers towards cancer control. CONCLUSIONS: This bibliometric study provides detailed overview of the most cited empirical evidence in AI and ML adoption in cancer research that could efficiently help in designing future research. The innovations guarantee greater speed by using AI and ML in the detection and control of cancer to improve patient experience.

Ubiquitin E3 ligase Atrogin-1 protein is regulated via the rapamycin-sensitive mTOR-S6K1 signaling pathway in C2C12 muscle cells.

Atrogin-1 and Muscle-specific RING finger protein 1 (MuRF1) are highly expressed in multiple conditions of skeletal muscle atrophy. The phosphoinositide 3-kinase (PI3K)/Akt/forkhead box (FoxO) signaling pathway is well known to regulate Atrogin-1 and MuRF1 gene expressions. However, Akt activation also activates the mechanistic target of rapamycin complex 1 (mTORC1), which induces skeletal muscle hypertrophy. Whether mTORC1-dependent signaling has a role in regulating Atrogin-1 and/or MuRF1 gene and protein expression is currently unclear. In this study, we showed that activation of insulin-mediated Akt signaling suppresses both Atrogin-1 and MuRF1 protein contents and that inhibition of Akt increases both Atrogin-1 and MuRF1 protein contents in C2C12 myotubes. Interestingly, inhibition of mTORC1 with a specific mTORC1 inhibitor, rapamycin, increased Atrogin-1, but not MuRF1, protein content. Furthermore, activation of AMP-activated protein kinase (AMPK), a negative regulator of the mTORC1 signaling pathway, also showed distinct time-dependent changes between Atrogin-1 and MuRF1 protein contents, suggesting differential regulatory mechanisms between Atrogin-1 and MuRF1 protein content. To further explore the downstream of mTORC1 signaling, we employed a specific S6K1 inhibitor, PF-4708671. We found that Atrogin-1 protein content was dose-dependently increased with PF-4708671 treatment, whereas MuRF1 protein content was decreased at 50 µM of PF-4708671 treatment. However, MuRF1 protein content was unexpectedly increased by PF-4708671 treatment for a longer period. Overall, our results indicate that Atrogin-1 and MuRF1 protein contents are regulated by different mechanisms, the downstream of Akt, and that Atrogin-1 protein content can be regulated by the rapamycin-sensitive mTOR-S6K1-dependent signaling pathway.

Cytochrome P450 3A4 suppression by epimedium and active compound kaempferol leads to synergistic anti-inflammatory effect with corticosteroid.

Introduction: Cytochrome P450 (CYP) 3A4 is a major drug metabolizing enzyme for corticosteroids (CS). Epimedium has been used for asthma and variety of inflammatory conditions with or without CS. It is unknown whether epimedium has an effect on CYP 3A4 and how it interacts with CS. We sought to determine the effects of epimedium on CYP3A4 and whether it affects the anti-inflammatory function of CS and identify the active compound responsible for this effect. Methods: The effect of epimedium on CYP3A4 activity was evaluated using the Vivid CYP high-throughput screening kit. CYP3A4 mRNA expression was determined in human hepatocyte carcinoma (HepG2) cells with or without epimedium, dexamethasone, rifampin, and ketoconazole. TNF-α levels were determined following co-culture of epimedium with dexamethasone in a murine macrophage cell line (Raw 264.7). Active compound (s) derived from epimedium were tested on IL-8 and TNF-α production with or without corticosteroid, on CYP3A4 function and binding affinity. Results: Epimedium inhibited CYP3A4 activity in a dose-dependent manner. Dexamethasone enhanced the expression of CYP3A4 mRNA, while epimedium inhibited the expression of CYP3A4 mRNA and further suppressed dexamethasone enhancement of CYP3A4 mRNA expression in HepG2 cells (p < 0.05). Epimedium and dexamethasone synergistically suppressed TNF-α production by RAW cells (p < 0.001). Eleven epimedium compounds were screened by TCMSP. Among the compounds identified and tested only kaempferol significantly inhibited IL-8 production in a dose dependent manner without any cell cytotoxicity (p < 0.01). Kaempferol in combination with dexamethasone showed complete elimination of TNF-α production (p < 0.001). Furthermore, kaempferol showed a dose dependent inhibition of CYP3A4 activity. Computer docking analysis showed that kaempferol significantly inhibited the catalytic activity of CYP3A4 with a binding affinity of -44.73kJ/mol. Discussion: Inhibition of CYP3A4 function by epimedium and its active compound kaempferol leads to enhancement of CS anti-inflammatory effect.

AMPK activation induces mitophagy and promotes mitochondrial fission while activating TBK1 in a PINK1-Parkin independent manner.

Mitophagy is a key process regulating mitochondrial quality control. Several mechanisms have been proposed to regulate mitophagy, but these have mostly been studied using stably expressed non-native proteins in immortalized cell lines. In skeletal muscle, mitophagy and its molecular mechanisms require more thorough investigation. To measure mitophagy directly, we generated a stable skeletal muscle C2C12 cell line, expressing a mitophagy reporter construct (mCherry-green fluorescence protein-mtFIS1101-152 ). Here, we report that both carbonyl cyanide m-chlorophenyl hydrazone (CCCP) treatment and adenosine monophosphate activated protein kinase (AMPK) activation by 991 promote mitochondrial fission via phosphorylation of MFF and induce mitophagy by ~20%. Upon CCCP treatment, but not 991, ubiquitin phosphorylation, a read-out of PTEN-induced kinase 1 (PINK1) activity, and Parkin E3 ligase activity toward CDGSH iron sulfur domain 1 (CISD1) were increased. Although the PINK1-Parkin signaling pathway is active in response to CCCP treatment, we observed no change in markers of mitochondrial protein content. Interestingly, our data shows that TANK-binding kinase 1 (TBK1) phosphorylation is increased after both CCCP and 991 treatments, suggesting TBK1 activation to be independent of both PINK1 and Parkin. Finally, we confirmed in non-muscle cell lines that TBK1 phosphorylation occurs in the absence of PINK1 and is regulated by AMPK-dependent signaling. Thus, AMPK activation promotes mitophagy by enhancing mitochondrial fission (via MFF phosphorylation) and autophagosomal engulfment (via TBK1 activation) in a PINK1-Parkin independent manner.

Electrophysiologic identification and monitoring of the external branch of superior laryngeal nerve during thyroidectomy.

OBJECTIVE: The aim of the study is to examine the correlation between weight, gender, and race with external branch of superior laryngeal nerve (EBSLN) visualization. Furthermore, we compared normative EBSLN neural-monitoring values to those of the recurrent laryngeal nerve (RLN). STUDY DESIGN: Retrospective study. SETTING: North American tertiary academic hospital. SUBJECTS AND METHODS: A retrospective, institutional review board-approved review was carried out on patients undergoing thyroid surgery by a single surgeon over 3.5 years. Preoperative and postoperative laryngoscopy was done on all patients in accordance with recently published American Academy of Otolaryngology voice optimization at thyroidectomy guidelines, and patients' clinical and operative relevant data were collected. RESULTS: A total of 447 nerves were at risk in 371 thyroidectomy patients. Of these nerves at risk, 237 (53.02%) were visualized and stimulated. The average amplitude and latency for the EBSLN were significantly lower when compared to the amplitude and the latency of RLN stimulation (P < 0.0001, P < 0.0001, respectively). There was no gender or racial disparity. Out of our study population, the EBSLN was identified in 64.56% in nonobese patients, whereas it was only 40.00% in obese patients (P < 0.001). Additionally, of the 56 patients in whom the EBSLN was visualized on one side and who further underwent bilateral neck exploration, 41 (73%) had visualization of the nerve on the contralateral side as well. CONCLUSION: EBSLN is less likely to be visualized in obese patients; however, there was no gender or racial disparity. Stimulation of EBSLN was felt to be a useful adjunct during superior pole dissection to assure the nerve integrity. LEVEL OF EVIDENCE: 4.

Splitting strategy for simulating genetic regulatory networks.

The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions.