Beyond Signal and Noise: Unraveling Scale Invariance in Neuroscience and Financial Networks with Topological Data Analysis

This exploratory study delves into persistent homology, an integral component of TDA that initially aimed at differentiating between signal and noise. We explore two methodologies for this differentiation: the conventional cycle length approach and the novel death-birth ratio method proposed by Bobrowski and Skraba. Analyzing comprehensive rs-fMRI data from the Human Connectome Project and daily S\&P 500 financial networks, our study compares these methods in identifying significant cycles. A pivotal discovery of this paper is a robust relationship between z-score thresholds applied to bar lengths or ratios and, respectively, behavioural traits in brain networks and market volatility in financial networks. In the brain, this is evident in the strong correlation between the number of significant 1-cycles in brain networks, brain volumes, and sex-based differences. In financial markets, a fractal pattern emerges, where market volatility consistently negatively correlates with the number of significant cycles, indicating that more intricate market topologies are associated with increased stability and less susceptibility to rapid shifts. Our findings also imply a fractal nature of 1-cycles at both population levels and across multiple days in the stock market. Notably, the distribution of significant loops, marked by high z-scores, remains consistent across various z-score thresholds, revealing a scale-invariant, fractal structure in both data sets. Given the scale invariance in these fractal structures, the traditional TDA distinction between signal and noise becomes less meaningful. The fractal nature of 1-cycles suggests that all scales of cycle length are relevant, challenging the conventional approach of segregating signal from noise. This realization broadens the scope of TDA, underscoring its potential to reveal intricate, scale-invariant relationships in complex systems

Identifying cardiac syncope based on clinical history : a literature-based model tested in four independent datasets

BACKGROUND: We aimed to develop and test a literature-based model for symptoms that associate with cardiac causes of syncope. METHODS AND RESULTS: Seven studies (the derivation sample) reporting 652 predictors of cardiac syncope were identified (4 Italian, 1 Swiss, 1 Canadian, and 1 from the United States). From these, 10 criteria were identified as diagnostic predictors. The conditional probability of each predictor was calculated by summation of the reported frequencies. A model of conditional probabilities and a priori probabilities of cardiac syncope was constructed. The model was tested in four datasets of patients with syncope (the test sample) from Calgary (n=670; 21% had cardiac syncope), Amsterdam (n=503; 9%), Milan (n=689; 5%) and Rochester (3877; 11%). In the derivation sample ten variables were significantly associated with cardiac syncope: age, gender, structural heart disease, low number of spells, brief or absent prodrome, supine syncope, effort syncope, and absence of nausea, diaphoresis and blurred vision. Fitting the test datasets to the full model gave C-statistics of 0.87 (Calgary), 0.84 (Amsterdam), 0.72 (Milan) and 0.71 (Rochester). Model sensitivity and specificity were 92% and 68% for Calgary, 86% and 67% for Amsterdam, 76% and 59% for Milan, and 73% and 52% for Rochester. A model with 5 variables (age, gender, structural heart disease, low number of spells, and lack of prodromal symptoms) was as accurate as the total set. CONCLUSION: A simple literature-based Bayesian model of historical criteria can distinguish patients with cardiac syncope from other patients with syncope with moderate accuracy

Predictors of injury mortality: Findings from a large national cohort in Thailand

Objective: To present predictors of injury mortality by types of injury and by pre-existing attributes or other individual exposures identified at baseline

Effectiveness of Protease Inhibitor Monotherapy versus Combination Antiretroviral Maintenance Therapy: A Meta-Analysis

The unparalleled success of combination antiretroviral therapy (cART) is based on the combination of three drugs from two classes. There is insufficient evidence whether simplification to ritonavir boosted protease inhibitor (PI/r) monotherapy in virologically suppressed HIV-infected patients is effective and safe to reduce cART side effects and costs

Cerebrospinal fluid HIV-1 RNA, intrathecal immunoactivation, and drug concentrations after treatment with a combination of saquinavir, nelfinavir, and two nucleoside analogues: the M61022 study

BACKGROUND: The way various antiretroviral drugs and drug combinations affect HIV-1 infection in the central nervous system is still largely unknown. The aim of this study was to determine the cerebrospinal fluid (CSF) steady-state concentrations of saquinavir and nelfinavir in relation to plasma concentrations, and to study their effect in combination with two nucleoside reverse transcriptase inhibitors (NRTIs) on CSF viral loads, intrathecal immunoactivation, and blood-brain barrier integrity. METHODS: Paired CSF and plasma samples from 8 antiretroviral-naïve HIV-1 infected patients starting combination therapy with saquinavir, nelfinavir, and two nucleoside analogues were collected prior to treatment, and again after approximately 12 and 48 weeks of antiretroviral therapy. Additional plasma samples were taken at weeks 2, 4, 8, 24, and 36. The concentrations of protease inhibitors were analysed, as were levels of HIV-1 RNA, CD4+ T-cell count, β2-microglobulin, neopterin, albumin ratio, IgG index, and monocytic cell count. RESULTS: None of the patients in the study presented with HIV-1 RNA < 50 copies/mL in CSF or plasma prior to treatment, compared to 5/7 at the end of the study. Signs of cell-mediated intrathecal immunoactivation, measured by neopterin and β2-microglobulin, decreased significantly in both CSF and serum, although only 1/7 reached normal CSF neopterin levels after 48 weeks of treatment. There was no significant reduction of albumin ratio, IgG index or CSF monocytic cell count. Saquinavir median (range) concentrations were < 2.5 (< 2.5–96.0) nM unbound in plasma, and < 2.5 (< 2.5–9.0) nM total in CSF. Nelfinavir median (range) concentrations were 10.0 (< 2.0–31.0) nM unbound in plasma, and < 2.0 (< 2.0–23.0) nM total in CSF. Saquinavir and nelfinavir were detectable in 7/15 and 9/15 CSF samples, respectively. CONCLUSION: Saquinavir and nelfinavir, in combination with two NRTIs, decrease the CSF viral load and, to a lesser extent, intrathecal immunoactivation. We found reasonably high CSF concentrations of nelfinavir, but suboptimal concentrations of saquinavir

A novel application of capnography during controlled human exposure to air pollution

BACKGROUND: The objective was to determine the repeatability and stability of capnography interfaced with human exposure facility. METHODS: Capnographic wave signals were obtained from five healthy volunteers exposed to particle-free, filtered air during two consecutive 5 min intervals, 10 min apart, within the open and then the sealed and operational human exposure facility (HEF). Using a customized setup comprised of the Oridion Microcap(® )portable capnograph, DA converter and AD card, the signal was acquired and saved as an ASCII file for subsequent processing. The minute ventilation (VE), respiratory rate (RR) and expiratory tidal volume (V(TE)) were recorded before and after capnographic recording and then averaged. Each capnographic tracing was analyzed for acceptable waves. From each recorded interval, 8 to 19 acceptable waves were selected and measured. The following wave parameters were obtained: total length and length of phase II and III, slope of phase II and III, area under the curve and area under phase III. In addition, we recorded signal measures including the mean, standard deviation, mode, minimum, maximum – which equals end-tidal CO(2 )(EtCO(2)), zero-corrected maximum and true RMS. RESULTS: Statistical analysis using a paired t-test for means showed no statistically significant changes of any wave parameters and wave signal measures, corrected for RR and V(TE), comparing the measures when the HEF was open vs. sealed and operational. The coefficients of variation of the zero-corrected and uncorrected EtCO(2), phase II absolute difference, signal mean, standard deviation and RMS were less than 10% despite a sub-atmospheric barometric pressure, and slightly higher temperature and relative humidity within the HEF when operational. CONCLUSION: We showed that a customized setup for the acquisition and processing of the capnographic wave signal, interfaced with HEF was stable and repeatable. Thus, we expect that analysis of capnographic waves in controlled human air pollution exposure studies is a feasible tool for characterization of cardio-pulmonary effects of such exposures

Long-term air pollution exposure and self-reported morbidity: A longitudinal analysis from the Thai cohort study (TCS)

[Background] Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. [Methods] This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005–2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM₁₀, O₃, NO₂, SO₂, and CO. [Results] After controlling for potential confounders, we found that an IQR increase in PM₁₀ was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO₂ was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O₃ and NO₂. [Conclusions] Long-term exposure to air pollution, especially for PM₁₀ and SO₂ was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population

The relationship between SF-6D utility scores and lifestyle factors across three life-stages: Evidence from the Australian Longitudinal Study on Women’s Health

Purpose: To investigate how SF-6D utility scores change with age between generations of women, and to quantify the relationship of SF-6D with lifestyle factors across life-stages. Methods: Up to seven waves of self-reported, longitudinal data were drawn for the 1973-78 (young, N=13772), 1946-51 (mid-age, N=12792), 1921-26 (older, N=9972) cohorts from the Australian Longitudinal Study on Women’s Health. Mixed effects models were employed for analysis. Results: Young and mid-age women had similar average SF-6D scores at baseline (0.63-0.64), which remained consistent over 16 year period. However, older women had lower scores at baseline at 0.57 which steadily declined over 15 years. Across cohorts, low education attainment, greater difficulty in managing on income, obesity, physical inactivity, heavy smoking, non-drinking and increasing stress levels were associated with lower SF-6D scores. The magnitude of effect varied between cohorts. SF-6D scores were lower amongst young women with high risk drinking behaviours than low-risk drinkers. Mid-age women who were underweight, never married, or underwent surgical menopause also reported lower SF-6D scores. Older women who lived in remote areas, who were ex-smokers, or were underweight reported lower SF-6D scores. Conclusion: The SF-6D utility score is sensitive to differences in lifestyle factors across adult lifestages. Gradual loss of physical functioning may explain the steady decline in health for older women. Key factors associated with SF-6D include physical activity, body mass index, menopause status, smoking, alcohol use and stress. Factors associated with poorer SF-6D scores vary in type and magnitude at different life stages