Addressing mechanism bias in model-based impact forecasts of new tuberculosis vaccines

In tuberculosis (TB) vaccine development, multiple factors hinder the design and interpretation of the clinical trials used to estimate vaccine efficacy. The complex transmission chain of TB includes multiple routes to disease, making it hard to link the vaccine efficacy observed in a trial to specific protective mechanisms. Here, we present a Bayesian framework to evaluate the compatibility of different vaccine descriptions with clinical trial outcomes, unlocking impact forecasting from vaccines whose specific mechanisms of action are unknown. Applying our method to the analysis of the M72/AS01E vaccine trial -conducted on IGRA+ individuals- as a case study, we found that most plausible models for this vaccine needed to include protection against, at least, two over the three possible routes to active TB classically considered in the literature: namely, primary TB, latent TB reactivation and TB upon re-infection. Gathering new data regarding the impact of TB vaccines in various epidemiological settings would be instrumental to improve our model estimates of the underlying mechanisms.

Development of a peripheral blood transcriptomic gene signature to predict bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) is the most common lung disease of extreme prematurity, yet mechanisms that associate with or identify neonates with increased susceptibility for BPD are largely unknown. Combining artificial intelligence with gene expression data is a novel approach that may assist in better understanding mechanisms underpinning chronic lung disease and in stratifying patients at greater risk for BPD. The objective of this study is to develop an early peripheral blood transcriptomic signature that can predict preterm neonates at risk for developing BPD. Secondary analysis of whole blood microarray data from 97 very low birth weight neonates on day of life 5 was performed. BPD was defined as positive pressure ventilation or oxygen requirement at 28 days of age. Participants were randomly assigned to a training (70%) and testing cohort (30%). Four gene-centric machine learning models were built, and their discriminatory abilities were compared with gestational age or birth weight. This study adheres to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement. Neonates with BPD (n = 62 subjects) exhibited a lower median gestational age (26.0 wk vs. 30.0 wk, P < 0.01) and birth weight (800 g vs. 1,280 g, P < 0.01) compared with non-BPD neonates. From an initial pool (33,252 genes/patient), 4,523 genes exhibited a false discovery rate (FDR) <1%. The area under the receiver operating characteristic curve (AUC) for predicting BPD utilizing gestational age or birth weight was 87.8% and 87.2%, respectively. The machine learning models, using a combination of five genes, revealed AUCs ranging between 85.8% and 96.1%. Pathways integral to T cell development and differentiation were associated with BPD. A derived five-gene whole blood signature can accurately predict BPD in the first week of life.

Using digital chatbots to close gaps in healthcare access during the COVID-19 pandemic

INTRODUCTION

Chatbots have emerged as a first link to care in recent years. The COVID-19 pandemic, and consequent health system disruptions, expanded their use. Socios En Salud (SES) introduced chatbots in Peru, which experienced one of the highest excess COVID mortalities in the world.

METHODS

SES and the government identified unmet population health needs, which could be amenable to virtual interventions. Chatbots were developed to screen individuals for these conditions; we describe the period of deployment, number of screenings, and number of people who received services.

RESULTS

Between April 2020 and May 2021, SES deployed nine ChatBots: four for mental health, two for maternal and child health, and three for chronic diseases: breast cancer, hypertension, diabetes mellitus, and obesity. Mental health services were provided to 42,932 people, 99.99% of those offered services. The other ChatBots reached fewer people. Overall, more than 50% of eligible people accepted chatbot-based services.

DISCUSSION

ChatBot use was highest for mental health. Chatbots may increase connections between a vulnerable population and health services; this is likely dependent on several factors, including condition, population, and penetration of smart phones. Future research will be critical to understand user experience and preferences and to ensure that chatbots link vulnerable populations to appropriate, high-quality care.

Big Data for Tiny Patients: A Precision Medicine Approach to Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is the most common chronic lung disease of extreme prematurity. Despite more than 50 years of research, current treatments are ineffective, and clinicians are largely unable to accurately predict which neonates the condition will develop in. A deeper understanding of the molecular mechanisms underlying the characteristic arrest in lung development are warranted. Integrating high-fidelity technology from precision medicine approaches may fill this gap and provide the tools necessary to identify biomarkers and targetable pathways. In this review, we describe insights garnered from current studies using omics for BPD prediction and stratification. We conclude by describing novel programs that will integrate multi-omics in efforts to better understand and treat the pathogenesis of BPD. [Pediatr Ann. 2022;51(10):e396-e404.].

Mental and physical health in service member and veteran students who identify as American Indians and Alaskan natives

OBJECTIVE

The purpose of this study was to explore (a) current utilization rates of university mental health services among American Indian/Alaskan Native/Native Hawaiian (AI/AN/NH) student veterans and (b) predictors of mental health service utilization among AI/AN student veterans. Participants: Data for this cross-sectional study were obtained from the American College Health Association (ACHA)'s 2011-2014 National College Health Assessment II (n = 103). Methods: University mental health service utilization rates were calculated as a percentage for AI/AN/NH student veterans. Multivariable logistic regression was used to determine predictors of mental health service utilization. Results: Results showed that 14% of AI/AN/NH student veterans have used university mental health services. Predictors of mental health service utilization in this population included financial stress, lack of deployment during service, suicidal ideation, and a diagnosis of depression, model χ 2 (13) = 162. 128, p < 0.001, Nagelkerke R2 = 0.130. Conclusion: This research identified gaps in service provision for AI/AN service member and veteran students on college campuses and provided possible models for intervention development.

Uncovering reasons for treatment initiation delays among children with TB in Lima, Peru

BACKGROUND: Timely diagnosis and treatment of pediatric tuberculosis (TB) is critical to reducing mortality but remains challenging in the absence of adequate diagnostic tools. Even once a TB diagnosis is made, delays in treatment initiation are common, but for reasons that are not well understood.METHODS: To examine reasons for delay post-diagnosis, we conducted semi-structured interviews with Ministry of Health (MoH) physicians and field workers affiliated with a pediatric TB diagnostic study, and caregivers of children aged 0-14 years who were diagnosed with pulmonary TB in Lima, Peru. Interviews were analyzed using systematic comparative and descriptive content analysis.RESULTS: We interviewed five physicians, five field workers and 26 caregivers with children who initiated TB treatment < 7 days after diagnosis (n = 15) or who experienced a delay of ≥7 days (n = 11). Median time in delay from diagnosis to treatment initiation was 26 days (range 7-117). Reasons for delay included: health systems challenges (administrative hurdles, medication stock, clinic hours), burden of care on families and caregiver perceptions of disease severity.CONCLUSION: Reasons for delay in treatment initiation are complex. Interventions to streamline administrative processes and tools to identify and support families at risk for delays in treatment initiation are urgently needed.

Optofluidic detection setup for multi-parametric analysis of microbiological samples in droplets

High-throughput microbiological experimentation using droplet microfluidics is limited due to the complexity and restricted versatility of the available detection techniques. Current detection setups are bulky, complicated, expensive, and require tedious optical alignment procedures while still mostly limited to fluorescence. In this work, we demonstrate an optofluidic detection setup for multi-parametric analyses of droplet samples by easily integrating micro-lenses and embedding optical fibers for guiding light in and out of the microfluidic chip. The optofluidic setup was validated for detection of absorbance, fluorescence, and scattered light. The developed platform was used for simultaneous detection of multiple parameters in different microbiological applications like cell density determination, growth kinetics, and antibiotic inhibition assays. Combining the high-throughput potential of droplet microfluidics with the ease, flexibility, and simplicity of optical fibers results in a powerful platform for microbiological experiments.

Vasoinhibin comprises a three-helix bundle and its antiangiogenic domain is located within the first 79 residues

Vasoinhibin belongs to a family of angiogenesis inhibitors generated when the fourth α-helix (H4) of the hormone prolactin (PRL) is removed by specific proteolytic cleavage. The antiangiogenic properties are absent in uncleaved PRL, indicating that conformational changes create a new bioactive domain. However, the solution structure of vasoinhibin and the location of its bioactive domain are unknown. Molecular dynamic simulation (MD) showed that the loss of H4 exposes the hydrophobic nucleus of PRL and leads to the compression of the molecule into a three-helix bundle that buries the hydrophobic nucleus again. Compression occurs by the movement of loop 1 (L1) and its interaction with α-helix 1 (H1) generating a new L1 conformation with electrostatic and hydrophobic surfaces distinct from those of PRL, that may correspond to a bioactive domain. Consistent with this model, a recombinant protein containing the first 79 amino acids comprising H1 and L1 of human PRL inhibited the proliferation and migration of endothelial cells and upregulated the vasoinhibin target genes, IL1A and ICAM1. This bioactivity was comparable to that of a conventional vasoinhibin having the 123 residues encompassing H1, L1, Η2, L2, and Η3 of human PRL. These findings extend the vasoinhibin family to smaller proteins and provide important structural information, which will aid in antiangiogenic drug development.

Novel multiferroic state and ME enhancement by breaking the AFM frustration in LuMn1-xO3

This study provides a comprehensive insight into the effects of controlled off-stoichiometry on the structural and multiferroic properties of the hexagonal manganite LuMn_1-xO_3+δ (x = 0.02; δ ∼ 0), supported by neutron powder diffraction measurements confirming single phase P6₃cm symmetry and evidencing a relevant ferromagnetic component, below T_N ∼ 90 K, which breaks the archetypal geometrically frustrated antiferromagnetic state typically ascribed to LuMnO₃. The perturbations in the triangular disposition of spins prompt an additional electric polarization contribution and a clear enhancement of the magnetoelectric coupling which are in good agreement with the results of first principles calculations. In addition, Raman spectroscopy, dielectric permittivity, pyroelectric current and magnetic measurements as a function of temperature point out the precursor effects of the magnetic phase transitions involving a strong coupling between spins, lattice and electric order, even above the Néel temperature.

Delocalized and localized states of eg electrons in half-doped manganites

We have studied the magnetic behaviour of half-doped manganite Y0.5Ca0.5MnO3 in an extended range of temperatures by means of magnetic susceptibility, χ(T), and electron spin resonance (ESR) experiments. At high temperature the system crystallizes in an orthorhombic structure. The resistivity value, ρ ≃ 0.05 Ω cm at 500 K, indicates a metallic behaviour, while the Curie-Weiss dependence of χ(T) and the thermal evolution of the ESR parameters are very well described by a model that considers a system conformed by localized Mn(4+) cores, [Formula: see text], and itinerant, eg, electrons. The strong coupling between t2g and eg electrons results in an enhanced Curie constant and an FM Curie-Weiss temperature that overcomes the AFM interactions between the [Formula: see text] cores. A transition to a more distorted phase is observed at T ≈ 500 K and signatures of localization of the eg electrons appear in the χ(T) behaviour below 300 K. A new Curie-Weiss regime is observed, where the Curie-constant value is consistent with dimer formation. Based on mean-field calculations, the dimer formation is predicted as a function of the interaction strength between the t2g and eg electrons.

Phase coexistence in manganites: doping and structural dependence

We present a study on the phase coexistence (PC) of paramagnetic insulating (PM-I) and ferromagnetic metallic (FM-M) phases in the La(1- y)(Ca(1-x)Sr(x))(y)MnO(3) system with 0.23 ≤ y ≤ 0.45. The study was performed by means of magnetization and electron spin resonance (ESR) measurements. At high temperatures the ESR spectrum consists of a single symmetric PM line. At T(C), a FM asymmetric line is observed shifted to low fields. In a ΔT temperature range both lines are visible, defining a range of PC. For x = 0, we obtained ΔT as a function of the carrier concentration y, finding that the largest ΔT corresponds to y = 0.25. For this y value, the extreme compounds are orthorhombic and rhombohedral for x = 0 and 1, respectively. The rhombohedral to orthorhombic temperature transition (T(RO)) was determined as a function of x. We found that [Formula: see text] only if T(C) < T(RO). The PM-I/FM-M phase coexistence was only observed in the orthorhombic phase while seems to be incompatible with the more symmetric rhombohedral phase.

High MMP-9 activity characterises pleural tuberculosis correlating with granuloma formation

Tuberculosis (TB) pleural disease is complicated by extensive tissue destruction. Matrix metalloproteinase (MMP)-1 and -9 are implicated in immunopathology of pulmonary and central nervous system TB. There are few data on MMP activity in TB pleurisy. The present study investigated MMP-1, -2 and -9 and their specific inhibitors (tissue inhibitor of metalloproteinase (TIMP)-1 and -2) in tuberculous effusions, and correlated these with clinical and histopathological features. Clinical data, routine blood tests, and pleural fluid/biopsy material were obtained from 89 patients presenting with pleural effusions in a TB-endemic area. MMP-1, -2 and -9 were measured by zymography or western blot, and TIMP-1 and -2 by ELISA. Pleural biopsies were examined microscopically, cultured for acid-alcohol fast bacilli and immunostained for MMP-9. Tuberculous pleural effusions contained the highest concentrations of MMP-9 compared with malignant effusions or heart failure transudates. MMP-9 concentrations were highest in effusions from patients with granulomatous biopsies: median (interquartile range) 108 (61-218) pg x mL(-1) versus 43 (12-83) pg x mL(-1) in those with nongranulomatous pleural biopsies. MMP-1 and -2 were not upregulated in tuberculous pleural fluid. The ratio of MMP-9:TIMP-1 was significantly higher in TB effusions. Tuberculous pleurisy is characterised by a specific pattern of matrix metalloproteinase-9 upregulation, correlating with the presence of granulomas and suggesting a specific role for matrix metalloproteinase-9 in inflammatory responses in tuberculous pleural disease.

Risk factors for burns in children: crowding, poverty, and poor maternal education

OBJECTIVE

To characterize the presentation of burns in children and risk factors associated with their occurrence in a developing country as a basis for future prevention programs.

DESIGN

Case-control study.

SETTING

Burn unit of the National Institute of Child Health (Instituto Nacional de Salud del Niño) in Lima, Peru.

METHODS

A questionnaire was administered to all consenting guardians of children admitted to the burns (cases) and general medicine (controls) units during a period of 14 months. Guardians of patients were questioned regarding etiology of the injury, demographic and socioeconomic data.

RESULTS

740 cases and controls were enrolled. Altogether 77.5% of the cases burns occurred in the patient's home, with 67.8% in the kitchen; 74% were due to scalding. Most involved children younger than 5 years. Lack of water supply (odds ratio (OR) 5.2, 95% confidence interval (CI) 2.1 to 1 2.3), low income (OR 2.8, 95% CI 2.0 to 3.9), and crowding (OR 2.5, 95%CI 1.7 to 3.6) were associated with an increased risk. The presence of a living room (OR 0.6, 95% CI 0.4 to 0.8) and better maternal education (OR 0.6, 95% CI 0.5 to 0.9) were protective factors.

CONCLUSIONS

To prevent burns interventions should be directed to low socioeconomic status groups; these interventions should be designed accordingly to local risk factors.

Automated linkage of free-text descriptions of patients with a practice guideline

The process of applying a practice guideline to a patient requires a great deal of clinical data. AAPT (Appropriateness-Assessment Processing from Text) is an experimental computer program that can assess the appropriateness of coronary-artery bypass grafting surgery (CABG) in patients with coronary-artery disease (CAD) and chronic stable angina from the admission summaries of those patients. The AAPT architecture combines natural-language processing (NLP) and probabilistic inference. The NLP module identifies single clinical concepts of interest in the free-text document. The probabilistic inference module, a Bayesian belief network, estimates values for variables not specifically mentioned. AAPT produces a patient's summary of CAD that is similar to a manually generated clinical summary. Work is ongoing to improve AAPT and evaluate it as a tool to assist in the dissemination of guidelines and as a tool to encourage adherence to practice guidelines.

Enterobacter cloacae bacteremia in children: a review of 30 cases in 12 years

A review was performed of the 30 cases of pediatric Enterobacter cloacae (EBC) bacteremia which occurred at our institution during a 12-year period. These 30 cases represented 88% of all cases in which EBC was isolated by blood culture (four other instances were considered contaminants); the rate of isolation of this organism relative to all positive blood cultures was 0.6%. There were 14 patients less than 12 months of age, with 10 less than 2 months of age. Infection was nosocomially-acquired in 17 cases. At the time the positive blood culture was obtained, 5 patients were afebrile, and 8 patients (five immunocompromised) had been receiving parenteral antibiotic therapy to which the organism exhibited in-vitro sensitivity for at least 24 hours. EBC was a constituent of polymicrobial bacteremia in 6 cases; in 5 instances the associated organisms were also gram-negative bacteria. There were a total of 33 underlying medical conditions or foci of infection associated with EBC bacteremia identified in 27 patients, the most common of which were immune-deficiency state (17) and gastrointestinal tract lesions (6). There were 3 patients who died. EBC bacteremia is a relatively rare pediatric infection. It is commonly nosocomially-acquired, and afflicts children who are younger-aged or compromised by underlying medical problems.

VentPlan: a ventilator-management advisor

VentPlan assists physicians, nurses, and respiratory therapists in the management of artificial respiration for critically ill patients in the intensive-care unit (ICU). VentPlan interprets clinical observations, monitored data, and arterial-blood-gas analyses to make recommendations for setting the ventilator. The VentPlan interface allows users to examine the physiologic model, to inspect details of the data on which the model is based, and to exercise the model to try out different ventilator settings before they implement a new setting. We also report here a preliminary evaluation of VentPlan's ability to predict the arterial oxygen and carbon-dioxide tensions following adjustments to the ventilator. We conclude that VentPlan's physiologic models are acceptably accurate for predicting the effects of small adjustments of the ventilator.