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A laboratory-free test for assessing recovery from pulmonary tuberculosis (TB) would be extremely beneficial in regions of the world where laboratory facilities are lacking. Our hypothesis is that analysis of cough sound recordings may provide such a test. In the current paper, we present validation of a cough analysis tool. Cough data was collected from a cohort of TB patients in Lima, Peru and 25.5 hours of recordings were manually annotated by clinical staff. Analysis software was developed and validated by comparison to manual scoring. Because many patients cough in bursts, coughing was characterized in terms of cough epochs. Our software correctly detects 75.5% of cough episodes with a specificity of 99.6% (comparable to past results using the same definition) and a median false positive rate of 4 false positives/hour, due to the noisy, real-world nature of our dataset. We then manually review detected coughs to eliminate false positives, in effect using the algorithm as a pre-screening tool that reduces reviewing time to roughly 5% of the recording length. This cough analysis approach provides a foundation to support larger-scale studies of coughing rates over time for TB patients undergoing treatment.

While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are regarded as uninterpretable. Here we explore correlations between MFCC coefficients and more interpretable speech biomarkers. In particular we quantify the MFCC2 endpoint, which can be interpreted as a weighted ratio of low- to high-frequency energy, a concept which has been previously linked to disease-induced voice changes. By exploring MFCC2 in several datasets, we show how its sensitivity to disease can be increased by adjusting computation parameters.

Background. Cough is the major determinant of tuberculosis transmission. Despite this, there is a paucity of information regarding characteristics of cough frequency throughout the day and in response to tuberculosis therapy. Here we evaluate the circadian cycle of cough, cough frequency risk factors, and the impact of appropriate treatment on cough and bacillary load. Methods. We prospectively evaluated human immunodeficiency virus–negative adults (n = 64) with a new diagnosis of culture-proven, drug-susceptible pulmonary tuberculosis immediately prior to treatment and repeatedly until treatment day 62. At each time point, participant cough was recorded (n = 670) and analyzed using the Cayetano Cough Monitor. Consecutive coughs at least 2 seconds apart were counted as separate cough episodes. Sputum samples (n = 426) were tested with microscopic-observation drug susceptibility broth culture, and in culture-positive samples (n = 252), the time to culture positivity was used to estimate bacillary load. Results. The highest cough frequency occurred from 1 PM to 2 PM, and the lowest from 1 AM to 2 AM (2.4 vs 1.1 cough episodes/hour, respectively). Cough frequency was higher among participants who had higher sputum bacillary load (P < .01). Pretreatment median cough episodes/hour was 2.3 (interquartile range [IQR], 1.2–4.1), which at 14 treatment days decreased to 0.48 (IQR, 0.0–1.4) and at the end of the study decreased to 0.18 (IQR, 0.0–0.59) (both reductions P < .001). By 14 treatment days, the probability of culture conversion was 29% (95% confidence interval, 19%–41%). Conclusions. Coughs were most frequent during daytime. Two weeks of appropriate treatment significantly reduced cough frequency and resulted in one-third of participants achieving culture conversion. Thus, treatment by 2 weeks considerably diminishes, but does not eliminate, the potential for airborne tuberculosis transmission.

Digital measures may provide objective, sensitive, real-world measures of disease progression in Parkinson’s disease (PD). However, multicenter longitudinal assessments of such measures are few. We recently demonstrated that baseline assessments of gait, tremor, finger tapping, and speech from a commercially available smartwatch, smartphone, and research-grade wearable sensors differed significantly between 82 individuals with early, untreated PD and 50 age-matched controls. Here, we evaluated the longitudinal change in these assessments over 12 months in a multicenter observational study using a generalized additive model, which permitted flexible modeling of at-home data. All measurements were included until participants started medications for PD. Over one year, individuals with early PD experienced significant declines in several measures of gait, an increase in the proportion of day with tremor, modest changes in speech, and few changes in psychomotor function. As measured by the smartwatch, the average (SD) arm swing in-clinic decreased from 25.9 (15.3) degrees at baseline to 19.9 degrees (13.7) at month 12 ( P  = 0.004). The proportion of awake time an individual with early PD had tremor increased from 19.3% (18.0%) to 25.6% (21.4%; P  < 0.001). Activity, as measured by the number of steps taken per day, decreased from 3052 (1306) steps per day to 2331 (2010; P  = 0.16), but this analysis was restricted to 10 participants due to the exclusion of those that had started PD medications and lost the data. The change of these digital measures over 12 months was generally larger than the corresponding change in individual items on the Movement Disorder Society—Unified Parkinson’s Disease Rating Scale but not greater than the change in the overall scale. Successful implementation of digital measures in future clinical trials will require improvements in study conduct, especially data capture. Nonetheless, gait and tremor measures derived from a commercially available smartwatch and smartphone hold promise for assessing the efficacy of therapeutics in early PD.

Abstract The Maintenance of Wakefulness Test (MWT) is a widely accepted objective test used to evaluate daytime somnolence and is commonly used in clinical studies evaluating novel therapeutics for excessive daytime sleepiness. In the latter, sleep onset latency (SOL) is typically the sole MWT endpoint. Here, we explored microsleeps, sleep probability measures derived from automated sleep scoring, and quantitative electroencephalography (qEEG) features as additional MWT biomarkers of daytime sleepiness, using data from a phase 1B trial of the selective orexin receptor 2 agonist danavorexton (TAK-925) in people with narcolepsy type 1 (NT1) or type 2 (NT2). Danavorexton treatment reduced the rate and duration of microsleeps during the MWT in NT1 (days 1 and 7; p ≤ .005) and microsleep rate in NT2 (days 1 and 7; p < .0001). The use of an EEG-sleep-staging − derived measure to determine the probability of wakefulness for each minute revealed a novel metric to track changes in daytime sleepiness, which were consistent with the θ/α ratio, a known biomarker of drowsiness. The slopes of line-fits to both the log-transformed sleepiness score or log-transformed θ/α ratio correlated well to (inverse) MWT SOL for NT1 (R = 0.93 and R = 0.83, respectively) and NT2 (R = 0.97 and R = 0.84, respectively), suggesting that individuals with narcolepsy have increased sleepiness immediately after lights-off. These analyses demonstrate that novel EEG-based biomarkers can augment SOL as predictors of sleepiness and its response to treatment and provide a novel framework for the analysis of wake EEG in hypersomnia disorders. Graphical Abstract Graphical Abstract

The Philippines is home to the second largest known population of whale sharks in the world. The species is listed as endangered due to continued population declines in the Indo-Pacific. Knowledge about the connectivity within Southeast Asia remains poor, and thus international management is difficult. Here, we employed pop-up archival tags, data mining and dedicated effort to understand an aggregation of whale sharks at Honda Bay, Palawan, Philippines, and its role in the species' conservation. Between Apr and Oct 2018, we conducted 159 surveys identifying 117 individual whale sharks through their unique spot patterns (96.5% male, mean 4.5 m). A further 66 individual whale sharks were identified from local operators, and data mined on social media platforms. The satellite telemetry data showed that the whale sharks moved broadly, with one individual moving to Sabah, Malaysia, before returning to the site <1 year later. Similarly, another tagged whale shark returned to the site at a similar periodicity after reaching the Malay-Filipino border. One individual whale shark first identified in East Kalimantan, Indonesia by a citizen scientist was resighted in Honda Bay ~3.5 years later. Honda Bay is a globally important site for the endangered whale shark with connectivity to two neighbouring countries, highlighting the need for international cooperation to manage the species.

IntroductionCough is a key symptom of tuberculosis (TB) as well as the main cause of transmission. However, a recent literature review found that cough frequency (number of coughs per hour) in patients with TB has only been studied once, in 1969. The main aim of this study is to describe cough frequency patterns before and after the start of TB treatment and to determine baseline factors that affect cough frequency in these patients. Secondarily, we will evaluate the correlation between cough frequency and TB microbiological resolution.MethodsThis study will select participants with culture confirmed TB from 2 tertiary hospitals in Lima, Peru. We estimated that a sample size of 107 patients was sufficient to detect clinically significant changes in cough frequency. Participants will initially be evaluated through questionnaires, radiology, microscopic observation drug susceptibility broth TB-culture, auramine smear microscopy and cough recordings. This cohort will be followed for the initial 60 days of anti-TB treatment, and throughout the study several microbiological samples as well as 24 h recordings will be collected. We will describe the variability of cough episodes and determine its association with baseline laboratory parameters of pulmonary TB. In addition, we will analyse the reduction of cough frequency in predicting TB cure, adjusted for potential confounders.Ethics and disseminationEthical approval has been obtained from the ethics committees at each participating hospital in Lima, Peru, Asociación Benéfica PRISMA in Lima, Peru, the Universidad Peruana Cayetano Heredia in Lima, Peru and Johns Hopkins University in Baltimore, USA. We aim to publish and disseminate our findings in peer-reviewed journals. We also expect to create and maintain an online repository for TB cough sounds as well as the statistical analysis employed.

Background Environmental low frequency noise (LFN < 125 Hz), ubiquitous in urban areas, is an understudied area of exposure science and an overlooked threat to population health. Environmental noise has historically been measured and regulated by A-weighted decibel (dBA) metrics, which more heavily weight frequencies between 2000 and 5000 Hz. Limited research has been conducted to measure and characterize the LFN components of urban environmental noise. Objectives We characterized LFN noise at two urban sites in Greater Boston, Massachusetts (USA) using dBA and full spectrum noise measurements with aims to (1.) analyze spatio-temporal differences in the two datasets; (2.) compare and contrast LFN metrics with dBA noise metrics in the two sites; and (3.) assess meteorological covariate contributions to LFN in the dataset. Methods We measured A- and C-weighted, and flat, unweighted noise levels and 1/3-octave band continuously for 5 months using sound level meters sampling at f  = 1 Hz and we recorded sound samples at 44.1 kHz. Our measurement sites were located in two urban, densely populated communities, burdened by close proximity to bus, rail, and aircraft routes. Results We found that (1.) LFN does not follow the same seasonal trends as A-weighted dBA loudness; there are spatial differences in LFN and its very low frequency noise components (VLFN) between two urban sites; (2.) VLFN and LFN are statistically significant drivers of LCeq (nearly independent of frequency) minus LAeq, (LCeq-LAeq) >10 dB, an accepted LFN metric; and (3.) LFN was minimally affected by high wind speeds at either Site. Impact Statement Environmental low-frequency noise (LFN < 125 Hz), ubiquitous in urban areas, is an understudied area of exposure science and an overlooked risk to population health. We measured environmental noise across the full spectrum of frequencies continuously for five months at two urban sites located in Environmental Justice communities. We found that LFN did not follow the same seasonal trends as A-weighted (dBA) loudness, and we observed spatial differences in LFN and very low frequency noise (VLFN < 20 Hz) at the two sites. Not characterizing LFN and basing noise regulations only on A-weightings, a poor predictor of LFN, may expose populations to LFN levels of concern.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson’s disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.

As the economy continues to struggle, job growth remains the Holy Grail in any recovery. Consider the current landscape. Overall growth remains dampened by the housing sector, with a recent Federal Reserve housing white paper stating that \"continued weakness in the housing market poses a significant barrier to a more vigorous economic recovery.\" With no end to the housing crisis in sight and many markets saddled by stubbornly high unemployment, private investment remains a critical need in areas hardest hit by foreclosure and job losses. The Low-Income Housing Tax Credit program is administered by the states and regulated by the IRS, with rules set by the Department of Housing and Urban Development. Credits are allocated to the states on a per capita basis, and state housing agencies award the credits to developers in a competitive process. The New Markets Tax Credit program encourages investment in businesses and commercial real estate projects in low-income communities. Adapted from the source document.