Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment

The environmental microclimatic characteristics are often subject to fluctuations of considerable importance, which can cause irreparable damage to art works. We explored the applicability of Artificial Intelligence (AI) techniques to the Cultural Heritage area, with the aim of predicting short-term microclimatic values based on data collected at Rosenborg Castle (Copenhagen), housing the Royal Danish Collection. Specifically, this study applied the NAR (Nonlinear Autoregressive) and NARX (Nonlinear Autoregressive with Exogenous) models to the Rosenborg microclimate time series. Even if the two models were applied to small datasets, they have shown a good adaptive capacity predicting short-time future values. This work explores the use of AI in very short forecasting of microclimate variables in museums as a potential tool for decision-support systems to limit the climate-induced damages of artworks within the scope of their preventive conservation. The proposed model could be a useful support tool for the management of the museums.

Machine Learning Algorithms as a Computer-Assisted Decision Tool for Oral Cancer Prognosis and Management Decisions: A Systematic Review

<b><i>Introduction:</i></b> Despite multiple prognostic indicators described for oral cavity squamous cell carcinoma (OCSCC), its management still continues to be a matter of debate. Machine learning is a subset of artificial intelligence that enables computers to learn from historical data, gather insights, and make predictions about new data using the model learned. Therefore, it can be a potential tool in the field of head and neck cancer. <b><i>Methods:</i></b> We conducted a systematic review. <b><i>Results:</i></b> A total of 81 manuscripts were revised, and 46 studies met the inclusion criteria. Of these, 38 were excluded for the following reasons: use of a classical statistical method (<i>N</i> = 16), nonspecific for OCSCC (<i>N</i> = 15), and not being related to OCSCC survival (<i>N</i> = 7). In total, 8 studies were included in the final analysis. <b><i>Conclusions:</i></b> ML has the potential to significantly advance research in the field of OCSCC. Advantages are related to the use and training of ML models because of their capability to continue training continuously when more data become available. Future ML research will allow us to improve and democratize the application of algorithms to improve the prediction of cancer prognosis and its management worldwide.

Automated Breast Volume Scanner (ABVS)-Based Radiomic Nomogram: A Potential Tool for Reducing Unnecessary Biopsies of BI-RADS 4 Lesions

Improving the assessment of breast imaging reporting and data system (BI-RADS) 4 lesions and reducing unnecessary biopsies are urgent clinical issues. In this prospective study, a radiomic nomogram based on the automated breast volume scanner (ABVS) was constructed to identify benign and malignant BI-RADS 4 lesions and evaluate its value in reducing unnecessary biopsies. A total of 223 histologically confirmed BI-RADS 4 lesions were enrolled and assigned to the training and validation cohorts. A radiomic score was generated from the axial, sagittal, and coronal ABVS images. Combining the radiomic score and clinical-ultrasound factors, a radiomic nomogram was developed by multivariate logistic regression analysis. The nomogram integrating the radiomic score, lesion size, and BI-RADS 4 subcategories showed good discrimination between malignant and benign BI-RADS 4 lesions in the training (AUC, 0.959) and validation (AUC, 0.925) cohorts. Moreover, 42.5% of unnecessary biopsies would be reduced by using the nomogram, but nine (4%) malignant BI-RADS 4 lesions were unfortunately missed, of which 4A (77.8%) and small-sized (<10 mm) lesions (66.7%) accounted for the majority. The ABVS radiomics nomogram may be a potential tool to reduce unnecessary biopsies of BI-RADS 4 lesions, but its ability to detect small BI-RADS 4A lesions needs to be improved.

Electrical impedance tomography: a potential tool for intraoperative imaging of the tongue base

The presence of a tumor in the tongue is a pathology that requires surgical intervention from a certain stage. This type of surgery is difficult to perform because of the limited space available around the base of the tongue for the insertion of surgical tools. During the procedure, the surgeon has to stretch and then fix the tongue firmly in order to optimize the available space and prevent tissue movement. As a result, the preoperative images of the inside of the tongue no longer give a reliable indication of the position and shape of the cancerous tissue due to the deformation of the overall tissue in the area. Thus, new images are needed during the operation, but are very difficult to obtain using conventional techniques due to the presence of surgical tools. Electrical Impedance Tomography (EIT) is an imaging technique that maps the resistivity or difference of resistivity of biological tissues from electrical signals. The small size of the electrodes makes it a potentially interesting tool to obtain intraoperative images of the inside of the tongue. In this paper, the possibility of using EIT for this purpose is investigated. A detection method is proposed, including an original configuration of the electrodes, consistent with the anatomical specificities of the tongue. The proposed method is studied in simulation and then a proof of concept is obtained experimentally on a 3D printed test tank filled with saline solution and plant fibres.

Volunteering, Charitable Donation, and Psychological Well-Being of College Students in China

Psychological well-being indicates individuals’ positive psychological functioning and well-being. A growing body of literature, largely based on adults and old people, suggests that volunteering and charitable donations are related to individuals’ psychological well-being. As emerging adulthood is a vital time for lifespan development, the aim of this study is to examine the effects of volunteering and charitable donation on individuals’ psychological well-being on college students. Relying on theories of altruism and the warm-glow theory, this study estimates the relationships among hours of volunteering, amount of charitable donations, and psychological well-being from 1,871 Chinese college students. The linear regression results indicate that students’ hours of volunteering and the amount of charitable donations in the past year were positively associated with their psychological well-being. Volunteering, compared to charitable donations, had a slightly stronger association with psychological well-being. This study provides a rationale for academic institutions to integrate social service activities into the curriculum as a potential tool to promote students’ psychological well-being.

Polyketide Derivatives in the Resistance of Gerbera hybrida to Powdery Mildew

Powdery mildew is a common disease affecting the commercial production of gerbera flowers (Gerbera hybrida, Asteraceae). Some varieties show a certain degree of resistance to it. Our objective was to identify biomarkers of resistance to powdery mildew using an 1H nuclear magnetic resonance spectroscopy and chemometrics approach in a complex, fully factorial experiment to suggest a target for selection and breeding. Resistant varieties were found to differ from those that were susceptible in the metabolites of the polyketide pathway, such as gerberin, parasorboside, and gerberinside. A new compound probably involved in resistance, 5-hydroxyhexanoic acid 3-O-β-D-glucoside, was described for the first time. A decision tree model was built to distinguish resistant varieties, with an accuracy of 57.7%, sensitivity of 72%, and specificity of 44.44% in an independent test. Our results suggest the mechanism of resistance to powdery mildew in gerbera and provide a potential tool for resistance screening in breeding programs.

Ultrasonic Elastography of the Rectus Femoris, a Potential Tool to Predict Sarcopenia in Patients With Chronic Obstructive Pulmonary Disease

Purpose: Skeletal muscle dysfunction is common in patients with chronic obstructive pulmonary disease (COPD) and is associated with a poor prognosis. Abnormal muscle quantity of the lower limbs is a manifestation of skeletal muscle dysfunction in patients with COPD. Shear wave ultrasound elastography (SWE) is a novel and possible tool to evaluate qualitative muscle parameters. This study explores the feasibility of SWE to measure the stiffness of the rectus femoris and evaluates its value in predicting sarcopenia in patients with COPD.Methods: Ultrasound examination of the rectus femoris was performed to determine the mean elasticity index (SWEmean), cross-sectional area (RFcsa), and thickness (RFthick) using grayscale ultrasonography (US) and SWE in 53 patients with COPD and 23 age-matched non-COPD healthy controls. The serum levels of circulating biomarkers (GDF15, resistin, and TNF-α) were measured using ELISA. The definition of sarcopenia followed the guidelines from the Asian Working Group for Sarcopenia. Receiver operating characteristic (ROC) curve analysis of the SWEmean, RFthick, and RFcsa was used to evaluate their predictive ability for sarcopenia.Results: The intraobserver and interobserver repeatability of SWE performance was excellent (all correlation coefficients &gt; 0.95; p &lt; 0.05). The SWEmean of the rectus femoris in patients with COPD (8.98 ± 3.12 kPa) was decreased compared with that in healthy controls (17.00 ± 5.14 kPa) and decreased with advanced global initiative for chronic obstructive lung disease (GOLD) stage. Furthermore, SWEmean was found to be independent of sex, height, and body mass, and a lower SWEmean in patients with COPD was positively associated with reduced pulmonary function, worse physical function, poor exercise tolerance, decreased muscle strength, and worse dyspnea index score. The correlation between physical function [five-repetition sit-to-stand test (5STST)], muscle function, and SWEmean was higher than those of RFthick and RFcsa. In addition, SWEmean was negatively correlated with serum GDF15 levels (r = −0.472, p &lt; 0.001), serum resistin levels (r = −0.291, p = 0.035), and serum TNF-α levels (r = −0.433, p = 0.001). Finally, the predictive power of SWEmean [area under the curve (AUC): 0.863] in the diagnosis of sarcopenia was higher than that of RFthick (AUC: 0.802) and RFcsa (AUC: 0.816).Conclusion: Compared with grayscale US, SWE was not affected by the patient’s height, weight, or BMI and better represented skeletal muscle function and physical function. Furthermore, SWE is a promising potential tool to predict sarcopenia in patients with COPD.

Evaluation of nocturnal vs. morning measures of heart rate indices in young athletes

Purpose The purpose of this study was to compare heart rate (HR) and heart rate variability in young endurance athletes during nocturnal sleep and in the morning; and to assess whether changes in these values are associated with changes in submaximal running (SRT) and counter-movement jump (CMJ) performance. Methods During a three-week period of similar training, eleven athletes (16 ± 1 years) determined daily HR and heart rate variability (RMSSD) during sleep utilizing a ballistocardiographic device (Emfit QS), as well as in the morning with a HR monitor (Polar V800). Aerobic fitness and power production were assessed employing SRT and CMJ test. Results Comparison of the average values for week 1 and week 3 revealed no significant differences with respect to nocturnal RMSSD (6.8%, P = 0.344), morning RMSSD (13.4%, P = 0.151), morning HR (-3.9 bpm, P = 0.063), SRT HR (-0.7 bpm, P = 0.447), SRT blood lactate (4.9%, P = 0.781), CMJ (-4.2%, P = 0.122) or training volume (16%, P = 0.499). There was a strong correlation between morning and nocturnal HRs during week 1 (r = 0.800, P = 0.003) and week 3 (r = 0.815, P = 0.002), as well as between morning and nocturnal RMSSD values (for week 1, r = 0.895, P<0.001 and week 3, r = 0.878, P = 0.001). Conclusion This study concluded that HR and RMSSD obtained during nocturnal sleep and in the morning did not differ significantly. In addition, weekly changes in training and performance were small indicating that fitness was similar throughout the 3-week period of observation. Consequently, daily measurement of HR indices during nocturnal sleep provide a potential tool for long-term monitoring of young endurance athletes.