Physical frailty identification using machine learning to explore the 5-item FRAIL scale, Cardiovascular Health Study index, and Study of Osteoporotic Fractures index.

Background: Physical frailty is an important issue in aging societies. Three models of physical frailty assessment, the 5-Item fatigue, resistance, ambulation, illness and loss of weight (FRAIL); Cardiovascular Health Study (CHS); and Study of Osteoporotic Fractures (SOF) indices, have been regularly used in clinical and research studies. However, no previous studies have investigated the predictive ability of machine learning (ML) for physical frailty assessment. The aim was to use two ML algorithms, random forest (RF) and extreme gradient boosting (XGBoost), to predict these three physical frailty assessment models. Materials and methods: Questionnaires regarding demographic characteristics, lifestyle habits, living environment, and physical frailty assessment were answered by 445 participants aged 60 years and above. The RF and XGBoost algorithms were used to assess their scores for the three physical frailty indices. Furthermore, feature importance and Shapley additive explanations (SHAP) were used to determine the important physical frailty factors. Results: The XGBoost algorithm obtained higher accuracy for predicting the three physical frailty indices; the areas under the curve obtained by the XGBoost algorithm for the 5-Item FRAIL, CHS, and SOF indices were 0.84. 0.79, and 0.69, respectively. The feature importance and SHAP of the XGBoost algorithm revealed that systolic blood pressure, diastolic blood pressure, age, and body mass index play important roles in all three physical frailty models. Conclusion: The XGBoost algorithm has a more accurate predictive rate than RF across all three physical frailty assessments. Thus, ML can be a useful tool for the early detection of physical frailty.

Enhanced Magnetic Order and Reversed Magnetization Induced by Strong Antiferromagnetic Coupling at Hybrid Ferromagnetic-Organic Heterojunctions.

Organic-molecular magnets based on a metal-organic framework with chemically tuned electronic and magnetic properties have been attracting tremendous attention due to their promising applications in molecular magnetic sensors, magnetic particle medicines, molecular spintronics, etc. Here, we investigated the magnetic behavior of a heterojunction comprising a ferromagnetic nickel (Ni) film and an organic semiconductor (OSC) 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4-TCNQ) layer. Through the magneto-optical Kerr effect (MOKE), a photoemission electron microscopy (PEEM), X-ray magnetic circular dichroism (XMCD), and X-ray photoelectron spectroscopy (XPS), we found that the adsorption of F4-TCNQ on Cu(100)/Ni not only reverses the in-plane magnetization direction originally exhibited by the Ni layer but also results in enhanced magnetic ordering. Furthermore, the cyano group (CN) in adsorbed F4-TCNQ was found spin-polarized along with conspicuous charge transfer with Ni. The density functional theory (DFT) calculations suggest that the experimentally found spin polarization originates from hybridization between the CN group's π orbitals and Ni's d band. These findings signify that the hybrid states at the organic-ferromagnet interface play a key role in tailoring the magnetic behavior of interfaces. For the case of the F4-TCNQ and Ni heterojunction reported here, interface coupling is an antiferromagnetic one.

Development of a new predictive model for interactions with human cytochrome P450 2A6 using pharmacophore ensemble/support vector machine (PhE/SVM) approach.

PURPOSE: The objective of this investigation was to yield a generalized in silico model to quantitatively predict CYP2A6-substrates/inhibitors interactions to facilitate drug discovery. METHODS: The newly invented pharmacophore ensemble/support vector machine (PhE/SVM) scheme was employed to generate the prediction model based on the data compiled from the literature. RESULTS: The predictions by the PhE/SVM model are in good agreement with the experimental observations for those molecules in the training set (n = 24, r (2) = 0.94, q (2) = 0.85, RMSE = 0.30) and the test set (n = 9, r (2) = 0.96, RMSE = 0.29). In addition, this in silico model performed equally well for those molecules in the external validation sets, namely one set of benzene and naphthalene derivatives (n = 45, r (2) = 0.81, RMSE = 0.46) and one set of amine neurotransmitters (n = 4, r (2) = 0.98, RMSE = 0.32). Furthermore, when compared with crystal structures, the calculated results are consistent with the published CYP2A6-substrate co-complex structure and the plasticity nature of CYP2A6 is also revealed. CONCLUSIONS: This PhE/SVM model is an accurate and robust model and can be utilized for predicting interactions with CYP2A6, high-throughput screening and data mining to facilitate drug discovery.

Herpes zoster-associated voiding dysfunction: a retrospective study and literature review.

OBJECTIVES: (1) To describe the demographic features of patients with voiding dysfunction associated with herpes zoster; (2) to discuss the pathophysiology of voiding dysfunction associated with herpes zoster; and (3) to suggest the best management policy. DESIGN: A retrospective study. SETTING: A university-affiliated medical center in Taiwan. PARTICIPANTS: Four hundred twenty-three patients (mean age, 55.5y) admitted with the diagnosis of herpes zoster from 1988 to 2000. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Dermatomal distribution of skin eruptions, urologic symptoms, treatment (catheterization, urecholine), clinical course of voiding dysfunction, and outcome. RESULTS: Seventeen (mean age, 61.2+/-14.1y) of 423 patients (4.02%) with voiding dysfunction related to this virus infection were identified. Ten (58.8%) were men, and 7 (41.2%) were women. The incidence of dysfunction was as high as 28.6% if only lumbosacral dermatome-involved patients were considered. We classified urologic manifestations caused by herpes zoster into 3 groups: cystitis-associated (n=12), neuritis-associated (n=4), and myelitis-associated (n=1). Urinalysis revealed pyuria in all patients with cystitis-associated voiding dysfunction and microscopic hematuria in all patients with neuritis-associated voiding dysfunction. All patients, although receiving different treatment regimens for voiding dysfunction, regained a normal or balanced bladder within 8 weeks. No major urologic sequelae were noted. CONCLUSION: Voiding dysfunction, although a transient course, is not uncommon in patients with herpes zoster involving lumbosacral dermatomes. Treatment with intermittent catheterization (our preferred choice) or indwelling catheter placement is recommended if the patients have prolonged difficulty in urination. This disease entity usually has a benign clinical course, and almost every patient will either regain normal voiding or, at least, balanced bladder function.