Background: Various combinations of ultrasonographic (US) characteristics are increasingly utilized to classify thyroid nodules. But they lack theories, and heavily depend on radiologists’ experience, and cannot correctly classify thyroid nodules. Hence, our main purpose of this manuscript is to select the US characteristics significantly associated with malignancy and to develop an efficient scoring system for facilitating ultrasonic clinicians to correctly identify thyroid malignancy.Methods: A logistic regression (LR) model is utilized to identify the potential thyroid malignancy, and the least absolute shrinkage and selection operator (LASSO) method is adopted to simultaneously select US characteristics significantly associated with malignancy and estimate parameters in LR model. Based on the selected US characteristics, we calculate the probability for each of thyroid nodules via random forest (RF) and extreme learning machine (ELM), and develop a scoring system to classify thyroid nodules. For comparison, we also consider eight state-of-the-art methods such as support vector machine (SVM), neural network (NET), etc. The area under the receiver operating characteristic curve (AUC) is employed to measure the accuracy of various classifiers.Results: The US characteristics: nodule size, AP/T≥1, solid component, micro-calcifications, hackly border, hypoechogenicity, presence of halo, unclear border, irregular margin, and central vascularity are selected as the significant predictors associated with thyroid malignancy via the LASSO LR (LLR). Using the developed scoring system, thyroid nodules are classified into the following four categories: benign, low suspicion, intermediate suspicion, and high suspicion, whose rates of malignancy correctly identified for RF (ELM) method on the testing dataset are 0.0% (4.3%), 14.3% (50.0%), 58.1% (59.1%) and 96.1% (97.7%), respectively.Conclusion: LLR together with RF performs better than other methods in identifying malignancy, especially for abnormal nodules, in terms of risk scores. The developed scoring system can well predict the risk of malignancy and guide medical doctors to make management decisions for reducing the number of unnecessary biopsies for benign nodules.

Introduction: Methamphetamine is currently one of the most commonly used addictive substances with strong addiction and a high relapse rate. This systematic review aims to examine the effectiveness of physical activity in improving negative emotions, cognitive impairment, and drug craving in people with methamphetamine use disorder (MUD).Methods: A total of 17 studies out of 133 found from Embase and PubMed were identified, reporting results from 1836 participants from MUD populations. Original research using clearly described physical activity as interventions and reporting quantifiable outcomes of negative mood, cognitive function and drug craving level in people with MUD were eligible for inclusion. We included prospective studies, randomized controlled trials, or intervention studies, focusing on the neurological effects of physical activity on MUD.Results: Taken together, the available clinical evidence showed that physical activity-based interventions may be effective in managing MUD-related withdrawal symptoms.Discussion: Physical exercise may improve drug rehabilitation efficiency by improving negative emotions, cognitive behaviors, and drug cravings.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024530359.

Substance use disorders (SUD) can lead to serious health problems, and there is a great interest in developing new treatment methods to alleviate the impact of substance abuse. In recent years, the ketogenic diet (KD) has shown therapeutic benefits as a dietary therapy in a variety of neurological disorders. Recent studies suggest that KD can compensate for the glucose metabolism disorders caused by alcohol use disorder by increasing ketone metabolism, thereby reducing withdrawal symptoms and indicating the therapeutic potential of KD in SUD. Additionally, SUD often accompanies increased sugar intake, involving neural circuits and altered neuroplasticity similar to substance addiction, which may induce cross-sensitization and increased use of other abused substances. Reducing carbohydrate intake through KD may have a positive effect on this. Finally, SUD is often associated with mitochondrial damage, oxidative stress, inflammation, glia dysfunction, and gut microbial disorders, while KD may potentially reverse these abnormalities and serve a therapeutic role. Although there is much indirect evidence that KD has a positive effect on SUD, the small number of relevant studies and the fact that KD leads to side effects such as metabolic abnormalities, increased risk of malnutrition and gastrointestinal symptoms have led to the limitation of KD in the treatment of SUD. Here, we described the organismal disorders caused by SUD and the possible positive effects of KD, aiming to provide potential therapeutic directions for SUD.