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BackgroundAlthough most current medication error prevention systems are rule-based, these systems may result in alert fatigue because of poor accuracy. Previously, we had developed a machine learning (ML) model based on Taiwan’s local databases (TLD) to address this issue. However, the international transferability of this model is unclear. ObjectiveThis study examines the international transferability of a machine learning model for detecting medication errors and whether the federated learning approach could further improve the accuracy of the model. MethodsThe study cohort included 667,572 outpatient prescriptions from 2 large US academic medical centers. Our ML model was applied to build the original model (O model), the local model (L model), and the hybrid model (H model). The O model was built using the data of 1.34 billion outpatient prescriptions from TLD. A validation set with 8.98% (60,000/667,572) of the prescriptions was first randomly sampled, and the remaining 91.02% (607,572/667,572) of the prescriptions served as the local training set for the L model. With a federated learning approach, the H model used the association values with a higher frequency of co-occurrence among the O and L models. A testing set with 600 prescriptions was classified as substantiated and unsubstantiated by 2 independent physician reviewers and was then used to assess model performance. ResultsThe interrater agreement was significant in terms of classifying prescriptions as substantiated and unsubstantiated (κ=0.91; 95% CI 0.88 to 0.95). With thresholds ranging from 0.5 to 1.5, the alert accuracy ranged from 75%-78% for the O model, 76%-78% for the L model, and 79%-85% for the H model. ConclusionsOur ML model has good international transferability among US hospital data. Using the federated learning approach with local hospital data could further improve the accuracy of the model.

In response to the strong coupling between line-of-sight angular rate and attitude error in the output of the strapdown rotating projectile, a method based on adaptive fading volume covariance Kalman filtering (AFCKF) is proposed. To achieve the decoupling of line-of-sight angular rate, the relative motion characteristics of missile and target are considered. A state model is constructed, which includes an estimation model of line-of-sight angular rate in the terminal guidance phase, and a measurement model including line-of-sight angle and attitude angular is established based on geometric relationships. To solve the problem of filter failure caused by the divergence of the line-of-sight angular rate estimation results in traditional CKF for rotating projectile, a fading factor based on residual sequence is introduced to adjust the predicted state covariance for quick convergence of the estimation results. To verify the effectiveness of AFCKF, typical interferences of attitude angle and measurement angle are considered. Simulation results show that the mean estimation errors of line-of-sight elevation rate and azimuth rate of the proposed method are 30.41% and 42.18% of the traditional EKF, respectively, effectively improving the accuracy of line-of-sight angular rate estimation for rotating projectil

In order to comprehensively and objectively evaluate and analyze the quality of table Chinese olive (Cauarium album L.) fruits from different varieties (lines), a rapid method for the detection of the quality characteristics of table Chinese olive was established. In this study, the fruit quality of 10 different varieties (lines) of Chinese olive was evaluated by fuzzy mathematics sensory evaluation and multi-frequency pulsed electronic tongue and its correlation with physicochemical indicators was analyzed. On this basis, a quality prediction model of table Chinese olive was developed and evaluated in terms of coefficient of determination (R2) and average relative error (δ). Sensory evaluation on a nine-point hedonic scale using the Delphi method showed that the total weight of sweetness and astringency were 76.9%, both of which were the major quality characteristics of table Chinese olive fruit. The correlation analysis indicated that phenol-to-sugar ratio was significantly correlated with aftertaste sweetness and astringency (P < 0.01). According to principal component analysis (PCA), the best electrode combination for multi-frequency pulse electronic tongue to distinguish the fruit quality of different varieties of Chinese olive was palladium (10 Hz) and titanium (10 Hz). Multiple stepwise regression was used to develop a model describing the relationship between sensory evaluation score or physicochemical indicators and electronic tongue signal eigenvalues. It was found that the physicochemical indicators could be effectively predicted from the electronic tongue signal eigenvalues and the prediction performance for phenol-to-sugar ratio (R2 = 0.832, δ = 10.89%) and soluble sugar content (R2 = 0.831, δ = 5.75%) was best, followed by total phenol content (R2 = 0.783, δ = 12.08%). The sensory evaluation score could be effectively predicted by the regression model based on phenol-to-sugar ratio or electronic tongue signal eigenvalues, and the predictive effect of the model based on phenol-to-sugar ratio was better than that of the one based on tongue signal eigenvalues. However, the R2 values of the two models were low, only 0.589 and 0.542, respectively. These results provide a reference for the rapid detection of Chinese olive quality characteristics and the selection of excellent varieties.

Objective: To report the clinical features, gene detection results and treatment results of two patients with familial male limited precocious puberty(FMPP). Methods: Detailed medical history collection and physical examination were carried out in 2 FMPP patients. LHRH challenge test, sex hormone, adrenal cortical hormone and other tests and relevant imaging examinations were performed. At the same time, peripheral blood of related family members was collected for gene detection, and relevant literature was retrieved in the Chinese database and PubMed database for comprehensive discussion. Results: The initial diagnosis age of the two patients was 6 years and 1 month (case 1) and 3 years and 7 months (case 2), respectively. The symptoms were penis and testis enlargement, accelerated growth, and advanced bone age. Case 2 was accompanied by aggressive behavior. Laboratory examination indicated that the peak value of luteinizing hormone was 7.28 mIU/mL and 4.96 mIU/mL respectively, and the basal testosterone level rose to 2.49 ng/mL and 3.58 ng/mL, while no abnormality was found in imaging examination. According to the medical history and various examination results of 2 patients, central precocious puberty was clinically diagnosed. Gene testing showed that there were heterozygous variations in the luteinizing hormone/chorionic gonadotropin receptor (LHCGR) gene boys including c.1756TCTdel (p.Ser586del) variation and c.1723A>C (p.Ile575Leu) variation were identified in case 1 and case 2). It revealed that genetic variation in case 1 resulted from his father, while in case 2 came from his mother. According to the guidelines of The American College of Medical Genetics and Genomics(ACMG), genovariation of LHCGR gene was assessed as possible pathogenic variation, so it was clear that central precocious puberty was caused by LHCGR gene mutation. Conclusions: Two male FMPP caused by LHCGR genetic variation are reported in this paper, and c.1756TCTdel(p.Ser586del) in case 1 which is first reported both in demastic and aboard. For boys with central precocious onseting in low age or with poor treatment effect, test on LHCGR genetic variation may be performed.

Fibromyalgia (FM) is a widespread muscle pain disorder that primarily affects females. Osteoarthritis (OA) is another common chronic condition. This study utilized sequential window acquisition of all theoretical mass spectra (SWATH)‐based proteomic analysis on the urine of patients with FM and OA. The study identified 54 differentially expressed proteins (DEPs) in the FM group compared to the healthy control (HC) group; 17 DEPs in the OA group compared to the HC group; and 47 DEPs in the FM group compared to the OA group, with a p‐value <0.05 and a fold change >1.5 or <0.67. The DEPs in both FM and OA groups were primarily involved in pathways related to coagulation and the complement system, as well as serotonin, dopamine, glutamate pathways, and acute phase reactions. The study suggests that FM and OA induce inflammatory reactions, significantly altering the expression of acute phase proteins and notably decreasing the expression of GNB2. This distinction between health and disease, and the differentiation between FM and OA, is facilitated through the coagulation and complement systems, with SERPING1 and EPCR being key markers. Through these pathways, a better understanding of the impact of FM and OA on the human proteome is achieved. [ABSTRACT FROM AUTHOR]

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics‐based methods) are still in use; however, emerging approaches like mass spectrometry (MS)‐based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS‐based metabolomics, proteomics and other approaches. [ABSTRACT FROM AUTHOR]

Background: Adherence to healthy lifestyles can be beneficial for depression among adults, but the intergenerational impact of maternal healthy lifestyles on offspring depressive symptoms is unknown. Methods: In total, 10 368 mothers in Nurses' Health Study II and 13 478 offspring in the Growing Up Today Study were paired. Maternal and offspring healthy lifestyles were defined as a composite score including a healthy diet, normal body mass index (BMI), never-smoking, light-to-moderate consumption of alcohol, and regular moderate-to-vigorous physical activity. Maternal lifestyles were assessed during their offspring's childhood. Offspring depressive symptoms were repeatedly assessed five times using the Center for Epidemiological Studies Depression Scale-10 (CESD-10); the offspring were between the ages of 14 and 30 when the first CESD-10 was assessed. Covariates included maternal variables (age at baseline, race/ethnicity, antidepressant use, pregnancy complications, etc.) and offspring age and sex. Results: Children of mothers with the healthiest lifestyle had significantly fewer depressive symptoms (a 0.30 lower CESD-10 score, 95% confidence interval (CI) 0.09–0.50) in comparison with children of mothers with the least healthy lifestyle. The association was only found significant in female offspring but not in males. For individual maternal lifestyle factors, a normal BMI, never-smoking, and adherence to regular physical activity were independently associated with fewer depressive symptoms among the offspring. The association between maternal healthy lifestyles and offspring depressive symptoms was mediated by offspring's healthy lifestyles (mediation effect: 53.2%, 95% CI 15.8–87.3). Conclusions: Our finding indicates the potential mechanism of intergenerational transmission of healthy lifestyles to reduce the risk of depressive symptoms in offspring. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A), one of the most prevalent mRNA modifications in eukaryotes, plays a critical role in modulating both biological and pathological processes. However, it is unknown whether mutant p53 neomorphic oncogenic functions exploit dysregulation of m6A epitranscriptomic networks. Here, we investigate Li-Fraumeni syndrome (LFS)-associated neoplastic transformation driven by mutant p53 in iPSC-derived astrocytes, the cell-of-origin of gliomas. We find that mutant p53 but not wild-type (WT) p53 physically interacts with SVIL to recruit the H3K4me3 methyltransferase MLL1 to activate the expression of m6A reader YTHDF2, culminating in an oncogenic phenotype. Aberrant YTHDF2 upregulation markedly hampers expression of multiple m6A-marked tumor-suppressing transcripts, including CDKN2B and SPOCK2, and induces oncogenic reprogramming. Mutant p53 neoplastic behaviors are significantly impaired by genetic depletion of YTHDF2 or by pharmacological inhibition using MLL1 complex inhibitors. Our study reveals how mutant p53 hijacks epigenetic and epitranscriptomic machinery to initiate gliomagenesis and suggests potential treatment strategies for LFS gliomas. The dysregulation of the m6A epitranscriptomic networks have been reported to contribute to the development of gliomas. Here, the authors utilize induced pluripotent stem cell-derived astrocytes with a p53 mutation and demonstrate that mutant p53 upregulates the m6A reader YTHDF2, resulting in the initiation of gliomas. [ABSTRACT FROM AUTHOR]