Autoregressive Modeling and Prediction of the Activity of Antihypertensive Peptides

Naturally derived bioactive peptides with antihypertensive activities serve as promising alternatives to pharmaceutical drugs. There are few relevant reports on the mapping relationship between the EC50 value of antihypertensive peptide activity (AHTPA-EC50) and its corresponding amino acid sequence (AAS) at present. In this paper, we have constructed two group series based on sorting natural logarithm of AHTPA-EC50 or sorting its corresponding AAS encoding number. One group possesses two series, and we find that there must be a random number series in any group series. The random number series manifests fractal characteristics, and the constructed series of sorting natural logarithm of AHTPA-EC50 shows good autocorrelation characteristics. Therefore, two non-linear autoregressive models with exogenous input (NARXs) were established to describe the two series. A prediction method is further designed for AHTPA-EC50 prediction based on the proposed model. Two dynamic neural networks for NARXs (NARXNNs) are designed to verify the two series characteristics. Dipeptides and tripeptides are used to verify the proposed prediction method. The results show that the mean square error (MSE) of prediction is about 0.5589 for AHTPA-EC50 prediction when the classification of AAS is correct. The proposed method provides a solution for AHTPA-EC50 prediction.

Evolutionary Synthesis of Failure-Resilient Analog Circuits

Analog circuit design requires large amounts of human knowledge. A special case of circuit design is the synthesis of robust and failure-resilient electronics. Evolutionary algorithms can aid designers in exploring topologies with new properties. Here, we show how to encode a circuit topology with an upper-triangular incident matrix and use the NSGA-II algorithm to find computational circuits that are robust to component failure. Techniques for robustness evaluation and evolutionary algorithm guidances are described. As a result, we evolve square root and natural logarithm computational circuits that are robust to high-impedance or short-circuit malfunction of an arbitrary rectifying diode. We confirm the simulation results by hardware circuit implementation and measurements. We think that our research will inspire further searches for failure-resilient topologies.

A Simple Predictive Score to Distinguish between Disseminated Histoplasmosis and Tuberculosis in Patients with HIV

Disseminated histoplasmosis is a common differential diagnosis of tuberculosis in disease-endemic areas. We aimed to find a predictive score to orient clinicians towards disseminated histoplasmosis or tuberculosis when facing a non-specific infectious syndrome in patients with advanced HIV disease. We reanalyzed data from a retrospective study in Cayenne Hospital between January 1997–December 2008 comparing disseminated histoplasmosis and tuberculosis: 100 confirmed disseminated histoplasmosis cases and 88 confirmed tuberculosis cases were included. A simple logit regression model was constructed to predict whether a case was tuberculosis or disseminated histoplasmosis. From this model, a score may be obtained, where the natural logarithm of the probability of disseminated histoplasmosis/tuberculosis = +3.917962 × WHO performance score (1 if >2, 0 if ≤2) −1.624642 × Pulmonary presentation (1 yes, 0 no) +2.245819 × Adenopathies > 2 cm (1 yes, 0 no) −0.015898 × CD4 count − 0.001851 × ASAT − 0.000871 × Neutrophil count − 0.000018 × Platelet count + 6.053793. The area under the curve was 98.55%. The sensitivity of the model to distinguish between disseminated histoplasmosis and tuberculosis was 95% (95% CI = 88.7–98.3%), and the specificity was 93% (95% CI = 85.7.3–97.4%). In conclusion, we here present a clinical-biological predictive score, using simple variables available on admission, that seemed to perform very well to discriminate disseminated histoplasmosis from tuberculosis in French Guiana in well characterized patients.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11340 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (bias 0.20 ms, p < 0.001) and nocturnal recordings (bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

Modification Model of Soil Fertility Evaluation FAO-UNESCO on the Slopes of Merapi Volcano, Indonesia

One of the mountains known as active volcanoes in the world was Merapi volcano. From the very active impact of Merapi activity, there was a continuous addition of volcanic material associated with soil fertility, which can be evaluated using the Soil Fertility Evaluation (SFE) system. This study aims to obtain a more adaptive SFE system to the southern slopes of Merapi volcano by modifying the FAO- UNESCO version of SFE system that still uses linear equations. In this research used system of quadratic equation, use of natural logarithm (ln), and modification of new parameter. From the evaluation of soil fertility is then connected with the production component of paddy rice (dry grains crop). There were several indicators that used to see the quality of the model or test the goodness of fit of the model we make, for example from its R2. In this study the quality of a model was seen from: Akaike Info Criterion (AIC) and Schwarz Criterion (SC), and the data was done by using EViews 9. The results showed the parameters that influence big in the model can be seen from the correlation and influence the parameters in single. Quadratic equations can improve the quality of a model over a linear equation. The standard SFE model which is modified by using the nat

The Determinants of Income Smoothing: Study of Indonesian Manufacturing Companies

The purpose of this research is to obtain empirical evidence about the effect of profitability, financial, dividend payout ratio and firm size towards income smoothing. The dependent variable of this research is income smoothing measured by Eckel Index. The independent variables of this research are profitability measured by Net Profit Margin (NPM), financial leverage measured by Debt to Assets Ratio (DAR), Dividend Payout Ratio (DPR), and firm size measured by natural logarithm assets. The samples were determined based on purposive sampling method. The sample of this research are 11 manufacture companies that listed in Indonesian Stock Exchange (IDX) in 2016-2018. Secondary data used in this research was analyzed by using logistic regression method. The result of this research are (1) profitability (NPM) has no positive effect towards income smoothing, (2) financial leverage (DAR) has no positive effect towards income smoothing, (3) Dividend Payout Ratio (DPR) has no positive effect towards income smoothing, (4) firm size has significant negative effect towards income smoothing, (5) profitability, financial leverage, Dividend Payout Ratio, and firm size has significant effect towards income smoothing.

Are age-related biomarkers of dementia risk accelerated by low educational attainment?

Background: Low education significantly elevates dementia risk but it is not clear whether this is through chronic systemic inflammation, early-onset dementia pathology, or other factors. This project compares biomarkers of inflammation and dementia pathology in a young-old and older cohort. Due to significantly lower education in the young-old cohort, we hypothesized evidence of similar or higher biomarker levels in the young-old cohort compared to the older cohort. Methods: Blood samples were used to measure pro-inflammatory cytokines (C-reactive protein (CRP), tumor necrosis factor (TNF interleukin (IL)-6, and IL-1 anti-inflammatory cytokines (IL-10 and IL-1RA), and the brain biomarkers phosphorylated tau (p-tau) and neurofilament light (NfL). Inflammatory markers were measured at the Considine Lab at the Indiana University School of Medicine using ELISA assays while p-tau and NfL were measured with Simoa assays at the Quanterix lab in Massachusetts. We used the natural logarithm of all biomarker variables to address skewed data. Linear regression was used to investigate race- and gender-adjusted differences in the biomarkers. Results: The young-old cohort (N=42) has a mean age of 62.4, 69.1% are female, and 78.6% are non-Hispanic black (NHB), while the older cohort (N=60) has a mean age of 80.3, 60% are female, and 20% are NHB. Median education in the young-old cohort is 12 vs 16 in the older cohort. Adjusted models showed higher mean CRP (p=0.004) and lower mean IL-10 (p<0.001) in the young-old cohort. TNF- (p <0.001), IL-6 (p=0.021), and IL-1(p=0.017), P-tau (p=0.003), and NfL (p<0.001) were all higher in the older cohort. Conclusion: We found partial support of our hypothesis in that the younger, low education cohort had higher mean CRP and lower mean IL-10 (anti-inflammatory). However, brain biomarkers were higher in the older cohort. More research will be needed to determine if and how low education elevates ADRD risk through systemic inflammation.

Similar Supine Heart Rate Variability Changes During 24-h Exposure to Normobaric vs. Hypobaric Hypoxia

Purpose: This study aimed to investigate the differences between normobaric (NH) and hypobaric hypoxia (HH) on supine heart rate variability (HRV) during a 24-h exposure. We hypothesized a greater decrease in parasympathetic-related parameters in HH than in NH.Methods: A pooling of original data from forty-one healthy lowland trained men was analyzed. They were exposed to altitude either in NH (FIO2 = 15.7 ± 2.0%; PB = 698 ± 25 mmHg) or HH (FIO2 = 20.9%; PB = 534 ± 42 mmHg) in a randomized order. Pulse oximeter oxygen saturation (SpO2), heart rate (HR), and supine HRV were measured during a 7-min rest period three times: before (in normobaric normoxia, NN), after 12 (H12), and 24 h (H24) of either NH or HH exposure. HRV parameters were analyzed for time- and frequency-domains.Results: SpO2 was lower in both hypoxic conditions than in NN and was higher in NH than HH at H24. Subjects showed similarly higher HR during both hypoxic conditions than in NN. No difference in HRV parameters was found between NH and HH at any time. The natural logarithm of root mean square of the successive differences (LnRMSSD) and the high frequency spectral power (HF), which reflect parasympathetic activity, decreased similarly in NH and HH when compared to NN.Conclusion: Despite SpO2 differences, changes in supine HRV parameters during 24-h exposure were similar between NH and HH conditions indicating a similar decrease in parasympathetic activity. Therefore, HRV can be analyzed similarly in NH and HH conditions.

Ascorbic Acid Deficiency Prevalence and Associated Cognitive Impairment in Alcohol Detoxification Inpatients: A Pilot Study

Malnutrition has been reported in alcohol use disorder patients as having a possible influence on cognitive function. The aim of this study was to analyse the prevalence of ascorbic acid (AA) deficiency in inpatients admitted for alcohol detoxification and the associated factors, including cognitive impairment in the early period of abstinence. A retrospective chart review was conducted. The AA level was categorised into three groups: deficiency (AAD) (<2 mg/L), insufficiency (AAI) (2–5 mg/L) and normal level. The cognitive impairment was screened using the Montreal Cognitive Assessment (MoCA). Ninety-six patients were included (74 men; mean age 49.1 years (±11.5)). Twenty-seven AAD (28.1%) and twenty-two AAI (22.9%) were observed. In multivariate analysis, risk factors for AAD versus normal AA level were men (OR 17.8, 95%CI (1.63–194)), compensated cirrhosis (OR 9.35, 95%CI (1.60–54.6)) and street homelessness (OR 5.76, 95%CI (1.24–26.8) versus personal housing). The MoCA score was available for 53 patients (mean MoCA score: 25.7 (±3.3)). In multivariate analysis, the natural logarithm of AA (β = 1.18, p = 0.037) and sedative use disorder (β = −2.77, p = 0.046) were associated with the MoCA score. AAD and AAI are frequent in inpatients admitted for alcohol detoxification. A low level of AA was associated with cognitive impairment in the early period of abstinence.

A GNSS-based method to define athlete manoeuvrability in field-based team sports

This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Australian Football League [AFL]; n = 36, 17 matches, National Rugby League [NRL]; n = 26, 21 matches). To quantify manoeuvrability, tortuosity was calculated from the X and Y coordinates from match GNSS files (converted from latitude and longitude). Tortuosity was calculated as 100 x natural logarithm of the chord distance (distance travelled between X and Y coordinates), divided by the straight-line distance. The maximal tortuosity was then quantified for each 0.5 m∙s-1 speed increment, ranging from 0 to the highest value for each game file. A quadratic model was fitted for each match file, controlling for the curvilinear relationship between tortuosity and velocity. A comparison of the quadratic coefficients between sports, and within sport between positions was investigated using linear mixed models. Resulting standard deviations (SDs) and mean differences were then assessed to establish standardized effect sizes (ES) and 90% confidence intervals (CI). A curvilinear relationship exists between maximal tortuosity and running speed, reflecting that as speed increases, athletes’ ability to deviate from a linear path is compromised (i.e., run in a more linear path). Compared to AFL, NRL had a greater negative quadratic coefficient (a) (ES = 0.70; 0.47 to 0.93) for the 5 second analysis, meaning that as speed increased, NRL athletes’ manoeuvrability reduced at a faster rate than when compared to AFL. There were no positional differences within each sport. GNSS derived information can be used to provide a measure of manoeuvrability tortuosity during NRL and AFL matches. The curvilinear relationship between tortuosity and speed demonstrated that as speed increased, manoeuvrability was compromised.