Miracle-dz/UniFAR-FTUs huggingface dataset:
A Unified Probabilistic Framework for Cancer Risk Management

Cancer risk assessments in the regulatory realm are often deterministic. Probabilistic approaches that allow characterizing and propagating uncertainty and variability are better suited to predict the socioeconomic impacts of regulating carcinogens. In this article, I present a unified framework for cancer risk management consisting of (i) a probabilistic exposure model that takes into account variability in individual exposure to the substance of concern; (ii) a probabilistic dose–response model that accounts for differences in individual cancer susceptibility; (iii) an impact assessment model that quantifies individuals’ excess lifetime cancer risk; and (iv) a welfare model that values changes in disability‐adjusted life expectancy based on workers’ willingness‐to‐pay and aggregates individual valuations across the population at risk. I illustrate the framework with data on occupational exposure to hexavalent chromium in France. In a cohort of 10,000 synthetic workers, about one third of the exposed benefit from the introduction of a binding occupational exposure limit (BOEL). Limiting hexavalent chromium exposure to the BOEL reduces the statistical worker's excess lifetime risk of fatal and nonfatal lung cancer by 4.7E‐3 and 1.5E‐3, respectively. At cohort level, the risk reduction corresponds to 738.4 full and 30.7 disability‐adjusted life years saved. The expected welfare gain of introducing the BOEL is close to €30 million. A major advantage of the framework is its ability to visualize uncertainty and variability inherent to cancer risk assessment. Notwithstanding some implementation challenges, the framework provides a transparent characterization of regulatory impacts that supports informed risk management decisions.
Obesity and Cancer Metastasis: Molecular and Translational Perspectives

Simple Summary A major challenge in treating cancer is when the cancer spreads from its original site to other parts of the body, a process also known as metastasis. In order to survive, the cancer cells must communicate with their environment for survival. It is increasingly recognized that fat tissue supports the survival of metastatic cancer cells allowing tumors to form at distant sites. Obese patients therefore have a worse prognosis due to accelerated tumor spread. Preventing cancer cells from communicating with fat tissue could therefore lead to new treatments aimed at stopping this spread. In this review we discuss how dysfunctional fat tissue supports the metastatic process and evaluate new therapies and lifestyle interventions that aim to prevent the communication between cancer cells and fat tissue. Abstract Obesity is a modern health problem that has reached pandemic proportions. It is an established risk factor for carcinogenesis, however, evidence for the contribution of adipose tissue to the metastatic behavior of tumors is also mounting. Over 90% of cancer mortality is attributed to metastasis and metastatic tumor cells must communicate with their microenvironment for survival. Many of the characteristics observed in obese adipose tissue strongly mirror the tumor microenvironment. Thus in the case of prostate, pancreatic and breast cancer and esophageal adenocarcinoma, which are all located in close anatomical proximity to an adipose tissue depot, the adjacent fat provides an ideal microenvironment to enhance tumor growth, progression and metastasis. Adipocytes provide adipokines, fatty acids and other soluble factors to tumor cells whilst immune cells infiltrate the tumor microenvironment. In addition, there are emerging studies on the role of the extracellular vesicles secreted from adipose tissue, and the extracellular matrix itself, as drivers of obesity-induced metastasis. In the present review, we discuss the major mechanisms responsible for the obesity–metastatic link. Furthermore, understanding these complex mechanisms will provide novel therapies to halt the tumor–adipose tissue crosstalk with the ultimate aim of inhibiting tumor progression and metastatic growth.
Promises and Perils of Artificial Intelligence in Dentistry.

Artificial intelligence (AI) is a subdiscipline of computer science that has made substantial progress in medicine and there is a growing body of AI research in dentistry. Dentists should have an understanding of the foundational concepts and the ability to critically evaluate dental research in AI. Machine learning (ML) is a subfield of AI that most dental AI research is dedicated to. The most prolific area of ML research is automated interpretation of dental imaging. Other areas include providing treatment recommendations, predicting future disease and treatment outcomes. The research impact is limited by small datasets that do not harness the positive correlation between very large datasets and ML performance. There is also a need to standardise research methodologies and utilise performance metrics that are appropriate for the clinical context. In addition to research challenges, this article discusses the ethical, legal and logistical considerations associated with implementation in clinical practice. This includes explainable AI, model bias, data privacy and security. The future implications of AI in dentistry involve a promise for a novel form of practicing dentistry however, the effect of AI on patient outcomes is yet to be determined.
Effects of Different Loading Conditions During Resisted Sprint Training on Sprint Performance

Abstract Rodríguez-Rosell, D, Sáez de Villarreal, E, Mora-Custodio, R, Asián-Clemente, JA, Bachero-Mena, B, Loturco, I, and Pareja-Blanco, F. Effects of different loading conditions during resisted sprint training on sprint performance. J Strength Cond Res 36(10): 2725–2732, 2022—The aim of this study was to compare the effects of 5 loading conditions (0, 20, 40, 60, and 80% of body mass [BM]) during weighted sled sprint training on unresisted and resisted sprint performance and jump ability. Sixty physically active men were randomly assigned into 5 groups according to the overload used during sled sprint training: 0% (G0%, n = 12), 20% (G20%, n = 12), 40% (G40%, n = 12), 60% (G60%, n = 12), and 80% BM (G80%, n = 12). Pretraining and post-training assessments included: countermovement jump (CMJ), 30-m sprint without extra load, and 20-m sprint with 20, 40, 60, and 80% BM. All 5 experimental groups trained once a week for a period of 8 weeks completing the same training program (number of sessions, number of bouts, running distance in each sprint, rest intervals between repetitions, and total running distance), but with different sled loads (0, 20, 40, 60, and 80% BM). There was a significant “time × group” interaction for resisted sprint performance at 80% BM condition, where the G40% group attained improvements in performance and G80% worsened. Moreover, G40% increased performance in unresisted and the rest of loading conditions. In addition, G0% and G60% showed statistically significant increases in unresisted sprint performance. No relevant changes were observed in the other experimental groups. All groups showed significant improvements (p < 0.05–0.001) in CMJ height. Therefore, our findings suggest that resisted sprint training with moderate loads (i.e., 40% BM) may have a positive effect on unresisted and resisted sprint performance.
Adiposity‐related insulin resistance and thickness of the cerebral cortex in middle‐aged adults

The thickness of the cerebral cortex decreases with ageing. Recent research suggests that obesity and type 2 diabetes mellitus may accelerate this cortical thinning, and that obesity‐related insulin resistance may be a shared mechanistic pathway. Ageing of the cerebral cortex demonstrates sex‐specific trajectories, with a gradual shift towards accelerated thinning beginning in midlife. Here, we investigated whether adiposity‐related insulin resistance is associated with lower thickness of the human cerebral cortex in a community‐based sample of middle‐aged adults. We studied 533 adult participants (36‐65 years) from the Saguenay Youth Study. Adiposity was assessed with bioimpedance, and insulin resistance was evaluated from a fasting blood sample with the homeostatic model assessment of insulin resistance (HOMA‐IR). Associations between adiposity‐related insulin resistance (adiposity/IR) and cortical thickness were assessed with linear models, separately in males and females younger or older than 50 years. Potential biological underpinnings were investigated with virtual histology. Adiposity/IR was associated with lower cortical thickness in females older than 50 years but not in males or younger females. The strength of the association varied across the cerebral cortex, with regions of the lateral frontal and parietal cortices and the superior temporal cortex demonstrating most pronounced thinning. Based on virtual histology, adiposity/IR‐related cortical thinning may involve neurones, astrocytes, oligodendrocytes and ependymal cells acting so that they lower the cortical potential for synaptogenesis, formation of dendritic spines, production of extracellular matrix and myelination. Adiposity‐related insulin resistance is associated with lower cortical thickness in middle‐aged women older than 50 years. This aspect of thinning may involve neuronal and glial cells in a way that lowers the capacity of the cerebral cortex for neuronal plasticity and maintenance of myelination.
Effect of Bariatric Surgery on Natriuretic Peptide Levels

Supplemental Digital Content is available in the text. The effect of bariatric surgery on natriuretic peptide levels in patients with obesity is unclear. The purpose of this study was to conduct a systematic review and meta-analysis to determine the effect of bariatric surgery on B-type natriuretic peptide (BNP) and aminoterminal BNP (NT-proBNP) levels. MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials were searched to February 2020. Primary outcomes included change in NT-proBNP or BNP levels following bariatric surgery and change in weight and body mass index. Secondary outcomes included change in blood pressure, echocardiographic findings, and heart failure symptoms. MINORS tool was used to assess quality of evidence. Twelve studies with 622 patients were included. Most patients underwent Roux-en-Y gastric bypass (RYGB) (70.5%). Mean absolute reduction in body mass index was 23%. NT-proBNP levels increased significantly from baseline at 6 months (mean difference [MD] 53.67 pg/mL; 95% confidence interval [CI], 28.72–78.61; P ≤ 0.001, I2 = 99%; 8 studies) and 12 months (MD 51.16 pg/mL; 95% CI, 20.46–81.86; P = 0.001, I2 = 99%; 8 studies) postbariatric surgery. BNP levels also increased significantly at 6 months (MD 17.57 pg/mL; 95% CI, 7.62–27.51; P < 0.001, I2 = 95%; 4 studies). Systolic and diastolic blood pressure decreased significantly 12 months after surgery. Studies measuring echocardiographic findings saw improvement in left ventricle mass and the E/A ratio, but no significant change in ejection fraction. Bariatric surgery is associated with increased natriuretic peptide levels in the absence of deteriorating cardiac function, and may be associated with improved cardiac and metabolic function after the procedure.
Cervical lymph node metastasis in squamous cell carcinoma of the buccal mucosa: a retrospective study on pattern of involvement and clinical analysis

Background The study was performed with an aim to map the pattern of metastasis of squamous cell carcinomas of buccal mucosa to various cervical lymph node levels and analyze its correlation with primary tumor size and histo-pathological grading. Material and Methods 254 patients with squamous cell carcinoma of the buccal mucosa treated with surgery first approach were analyzed retrospectively. The tumor size was noted from pre-operative CT Scans and were divided into early and advanced tumors. The resected specimen was studied to note the histo-pathological grading of the squamous cell carcinoma and the metastatic deposits at various lymph node levels. Results Out of 254 patients (149 females, 105 males), 145 patients showed histo-pathologically proven metastatic deposits in one or more lymph nodes out of which there were 56 patients showing occult metastasis. 78/145 patients showed metastatic involvement of level IB and/or IA lymph nodes, 31 showed involvement of level II and/or I lymph nodes, 27 showed involvement of level III with or without involvement of level I and II and 9 showed metastasis to level IV and V lymph nodes with or without level I, II or III lymph nodes. Cervical lymph node metastasis had statistically significant association with tumor size with advanced tumors showing worse pattern of metastatic spread beyond level I and II lymph nodes. As the degree of differentiation of squamous cell carcinoma reduced, they were more prone for cervical metastasis with moderately and poorly differentiated squamous cell carcinoma showing higher involvement of level III, IV and V lymph nodes. Conclusions The majority of buccal mucosa cases showed metastasis to level I, II and III lymph nodes out of which level IB and/or IA was most frequently involved. Metastasis to level IV and V lymph nodes was rare and was seen especially in patients with advanced primary tumor and poor histo-pathologic differentiation. Key words:Oral squamous cell carcinoma (OSCC), cervical lymph node metastasis, histologic differentiation, locally advanced disease.
Beta-Cell Mass in Obesity and Type 2 Diabetes, and Its Relation to Pancreas Fat: A Mini-Review

Type 2 diabetes (T2DM) is characterized by insulin resistance and beta-cell dysfunction. Although insulin resistance is assumed to be a main pathophysiological feature of the development of T2DM, recent studies have revealed that a deficit of functional beta-cell mass is an essential factor for the pathophysiology of T2DM. Pancreatic fat contents increase with obesity and are suggested to cause beta-cell dysfunction. Since the beta-cell dysfunction induced by obesity or progressive decline with disease duration results in a worsening glycemic control, and treatment failure, preserving beta-cell mass is an important treatment strategy for T2DM. In this mini-review, we summarize the current knowledge on beta-cell mass, beta-cell function, and pancreas fat in obesity and T2DM, and we discuss treatment strategies for T2DM in relation to beta-cell preservation.
In Situ Preparation of Novel Porous Nanocomposite Hydrogel as Effective Adsorbent for the Removal of Cationic Dyes from Polluted Water

The use of some hydrogels as adsorbents for pollutants removal from wastewater is limited due to their high swelling properties and the difficulty in recovering them after the adsorption process. To overcome these problems, a new hydrogel nanocomposite based on chitosan-grafted-polyacrylic acid/oxidized electrospun carbon nanofibers (CT-g-PAA/O-ECNFs) was prepared by an in situ grafting polymerization process. The prepared hydrogel nanocomposite was used as a novel effective and highly reusable adsorbent for the removal of methylene blue (MB) from polluted water with low cost. The morphology and the structure of CT-g-PAA/O-ECNFs were investigated by numerous techniques. The effect of incorporating O-ECNFs on the swelling capability of the prepared hydrogel was explored in distillated water and MB solution at normal pH. The effect of parameters including ratio of O-ECNFs, contact time, pH, initial concentration, and temperature on adsorption process were explored. The adsorption isotherm and kinetic were studied by numerous non-linear models. The obtained results confirmed that the incorporation of O-ECNFs into the hydrogel network decreased the swelling capacity and improved its ability towards MB dye removal. The adsorption process depended on the pH value of the dye solution. Additionally, the adsorption and kinetic results were fitted using the Freundlich isotherm model and pseudo second order model (PSO), respectively. Moreover, the new adsorbents can be recycled for at least five cycles keeping its adsorption capacity and can be easily recovered without loss in its initial weight.
Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry‐based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.
Potentially Severe Traumatic Brain Injury: Let Us Consider Patient Context.

1. Arcoverde de Sousa D, Spessoto SB: Peripherally Inserted Central Catheter Versus Central Venous Catheter: It Is Time to Use Different Approaches and Metrics for a More Useful Comparison. Crit Care Med 2020; 48:e109–e110 2. Patel N, Petersen TL, Simpson PM, et al: Rates of venous thromboembolism and central line-associated bloodstream infections among types of central venous access devices in critically ill children. Crit Care Med 2020; 48:1340– 1348 3. Yamaguchi RS, Noritomi DT, Degaspere NV, et al: Peripherally inserted central catheters are associated with lower risk of bloodstream infection compared with central venous catheters in pediatric intensive care patients: A propensity adjusted analysis. Intensive Care Med 2017; 43:1097–1104 4. Hanson SJ, Mahajerin A, Petty JP, et al: Risks of venous thrombosis and bleeding in critically ill adolescents after trauma or major surgery. J Ped Surgery 2020 Jun 30. [online ahead of print]
Relationships between Plant Defense Inducer Activities and Molecular Structure of Gallomolecules.

Plant defense inducers (PDIs) are booming and attractive protection agents designed to immunostimulate the plant to reduce subsequent pathogen colonization. The structure-PDI activity relationship of epicatechin (EC) and four flavan-3-ols, epigallocatechin (EGC), epicatechin gallate (ECG), epigallocatechin gallate (EGCG), and gallotannic acid (GTA), was investigated in both whole plant and suspension cell systems. ECG, EGCG, and GTA displayed elicitor activities. Their infiltration into tobacco leaves induced hypersensitive reaction-like lesions with topical scopoletin and PR-target transcript accumulations. On the contrary, EC and EGC infiltrations fail to trigger the biochemical changes in tobacco tissues. The tobacco BY-2 cells challenged with ECG, EGCG, or GTA led to alkalinization of the BY-2 extracellular medium while EC and EGC did not trigger any pH variation. This work provides evidence that the esterified gallate pattern is as an essential flavonoid entity to induce plant defense reactions in tobacco. The phytoprotective properties of the esterified gallate-free EC and the esterified gallate-rich GTA were evaluated on the tobacco/Phytophthora parasitica var. nicotianae (Ppn) pathosystem. Tobacco treatment with EC did not induce significant protection against Ppn compared to GTA which shows antimicrobial properties on Ppn and decreases the infection on GTA-infiltrated and -sprayed wild-type leaves. GTA protection was impaired in the transgenic NahG tobacco plants, suggesting that protection was mediated by salicylic acid.
SAP-cGAN: Adversarial Learning for Breast Mass Segmentation in Digital Mammogram Based on Superpixel Average Pooling.

PURPOSE Breast mass segmentation is a prerequisite step in the use of computer-aided tools designed for breast cancer diagnosis and treatment planning. However, mass segmentation remains challenging due to the low contrast, irregular shapes, and fuzzy boundaries of masses. In this work, we propose a mammography mass segmentation model for improving segmentation performance. METHODS We propose a mammography mass segmentation model called SAP-cGAN, which is based on an improved conditional Generative Adversarial Network (cGAN). We introduce a superpixel average pooling layer into the cGAN decoder, which utilizes superpixels as a pooling layout to improve boundary segmentation. In addition, we adopt a multiscale input strategy to enable the network to learn scale-invariant features with increased robustness. The performance of the model is evaluated with two public datasets: CBIS-DDSM and INbreast. Moreover, ablation analysis is conducted to evaluate further the individual contribution of each block to the performance of the network. RESULTS Dice and Jaccard scores of 93.37% and 87.57%, respectively, are obtained for the CBIS-DDSM dataset. The Dice and Jaccard scores for the INbreast dataset are 91.54% and 84.40%, respectively. These results indicate that our proposed model outperforms current state-of-the-art breast mass segmentation methods. The super-pixel average pooling layer and multiscale input strategy has improved the Dice and Jaccard scores of the original cGAN by 7.8% and 12.79%, respectively. CONCLUSIONS Adversarial learning with the addition of a superpixel average pooling layer and multiscale input strategy can encourage the Generator network to generate masks with increased realism and improve breast mass segmentation performance through the minimax game between the Generator network and Discriminator network.
Quantitative Analysis on Risk Influencing Factors in the Jiangsu Segment of the Yangtze River

Quantitative risk influencing factors (RIFs) are proposed, using the Conjugate Bayesian update approach to analyze 945 collision accidents and incidents cases from the Jiangsu Segment of the Yangtze River over five years from 2012 to 2016. The accident probability is compared under a pairwise comparison mode in order to reflect the relative risk between accidental situations. The Bayesian update mode is constructed to quantitatively evaluate the relative importance of different RIFs. The riskiest segment of Jiangsu Waterways as well the main causations of collisions are identified based on the distributions of collision risk in the six segments of the waterways. The results can support managers to develop the most effective policies to mitigate the collision risk.