Martinussenanderson7686

Objective We aimed to develop a machine learning algorithm to screen for depression and assess severity based on data from wearable devices. Methods We used a wearable device that calculates steps, energy expenditure, body movement, sleep time, heart rate, skin temperature, and ultraviolet light exposure. Depressed patients and healthy volunteers wore the device continuously for the study period. The modalities were compared hourly between patients and healthy volunteers. XGBoost was used to build machine learning models and 10-fold cross-validation was applied for the validation. Results Forty-five depressed patients and 41 healthy controls participated, creating a combined 5,250 days' worth of data. Heart rate, steps, and sleep were significantly different between patients and healthy volunteers in some comparisons. Similar differences were also observed longitudinally when patients' symptoms improved. Based on seven days' data, the model identified symptomatic patients with 0.76 accuracy and predicted Hamilton Depression Rating Scale-17 scores with a 0.61 correlation coefficient. Skin temperature, sleep time-related features, and the correlation of those modalities were the most significant features in machine learning. Limitations The small number of subjects who participated in this study may have weakened the statistical significance of the study. There are differences in the demographic data among groups although we performed a correction for multiple comparisons. Validation in independent datasets was not performed, although 10-fold cross validation with the internal data was conducted. Conclusion The results indicated that utilizing wearable devices and machine learning may be useful in identifying depression as well as assessing severity. © 2020 The Authors. Published by Elsevier Ltd.Biological evaluation of exopolysaccharides (EPS) produced by wild type and mutant Lactobacillus delbureckii (EPSWLD and EPSMLD) was investigated. Varying degrees of functional groups associated with polysaccharides were present thus confirming the EPS. The EPSs had strong antioxidant potential in a dose dependent (0.5-10 mg/mL) manner. EPSWLD and EPSMLD exhibited the highest 1,1-diphemy 1-2-picryl-hydrazyl (DPPH) activity (73.4 % and 65.6 %), total antioxidant activity (1.80 % and 1.42 %), H2O2 scavenging activity (88.5 % and 78.6 %) and Ferric Reducing Antioxidant Power (FRAP) (1.89 % and1.81 %) at 10 mg/mL respectively. WLD and MLD were highly susceptible to chloramphenicol, cotrimoxazole, tetracycline, erythromycin and ceftazidine and resistant to cefuroxime, gentamicin and cloxacillin. The EPSs had antibacterial activity against the test pathogens. B. subtilis and S. aureus had the highest susceptibility (26.0 mm and 23.0 mm). EPSMLD modulate the highest IgG, IgA and IgM production (68-126 mg/dL and 67-98 mg/dL and 64-97 mg/dL) in the treated tumor induced mice (TTIM). EPSWLD and EPSMLD exhibited reduction capability on the CEA level (3.99-4.35 ng/L and 4.12-4.23 ng/L) of the TTIM. EPSWLD TTIM had the highest amount of RBC, WBC and PCV (5.6 × 1012%, 68000% and 42%). The EPS increased the lifespan of TTIM. In conclusion EPSWLD and EPSMLD had strong biological potential with pharmacological and neutraceutical activity. © 2020 Published by Elsevier Ltd.To develop bio-nanocomposites using natural biopolymers, nanocomposite films were prepared based on sodium alginate and kapok nanofibrils (CNFs). CNFs when subjected to TEMPO-mediated oxidation gave rise to cellulose nanocrystals (TOCNCs), with carboxyl groups at the surface ( K a / K b = 3.64). The differences between the two types of nanocelluloses (nanofibrils and nanocrystals) and their impact in the preparation of bio-nanocomposites, were studied. When incorporated in the matrix, the CNFs particles have the tendency to form surface aggregation ( K a / K b = 2.37), distorting the alginate network, creating heterogeneous films, with high surface roughness (S a = 29.37 nm), porosity (D p = 0.087 cm2/min) and vulnerability to heat. The TOCNCs present good dispersion creating a 3D network, which forms uniform (D p = 0.122 cm2/min) and homogeneous films, with smooth surface (S a = 16.83 nm). The ultrasonication treatment facilitated the dispersion improving the interfacial interaction between the reinforcing phase and the matrix. The results show the reinforcement potential of kapok nanocellulose in an industrially and medically important biopolymer, sodium alginate, especially when TOCNCs and ultrasonication were used. © 2020 The Authors.Qualitative elemental analysis was determined in various parts of potential anti-asthmatic medicinal plants using Energy Dispersive X-ray Fluorescence (EDXRF) spectrometer. X-ray beam was used to excite each sample and spectra were recorded with a high resolution Si(Li) detector. The data analysis was carried out by the nEXT software. Trace elements P, S, Cl, K, Ca, Mn, Fe, Cu, Zn, Se, Br, Rb and Sr were estimated and elemental concentrations were determined. The results of the present study compared with standard reference material NIST1515 apple leaves for accuracy. The elements K, Ca, Cl, S and P are major constituents and besides Cu, Zn, Fe, Mn, Se, Br, Rb and Sr were present at low level. selleck chemicals llc The presence of Cu, Zn, Mn and Se in medicinal plants plays a vital role on management and control of asthma disease. © 2020 Published by Elsevier Ltd.Medicinal plants may be effective against helminthic infestation in animals, but to date few studies have investigated the real impact of anthelminthic medicinal plants in veterinary ethnopharmacology. The aim of this study was to assess the geographical use of anthelminthic medicinal plants in livestock in European Union (EU), and to quantify the anthelminthic efficacy of medicinal plants in comparison with anthelminthic drugs. Surveys on the use of anthelminthic traditional medicinal plants in livestock in the EU were included in the qualitative synthesis. Studies that investigated the efficacy of anthelminthic traditional medicinal plants in animals, compared with negative control and/or anthelminthic drugs, were included in the quantitative synthesis (network meta-analysis). Twelve surveys (9 in Italy, 2 in Spain, 1 in Austria) reported the use of anthelminthic medicinal plants in livestock living in EU Countries. Data obtained from 256 animals and extracted from 6 studies were included in the network meta-analysis.