Allostatic Load in Childhood, Adolescence, and Young Adulthood: Are Assumptions of Measurement Invariance Warranted?

OVERVIEW: Allostatic load represents the cumulative toll of chronic mobilization of the body's stress response systems, as indexed by biomarkers. Higher levels of stress and disadvantage predict higher levels of allostatic load, which, in turn, predict poorer physical and mental health outcomes. To maximize the efficacy of prevention efforts, screening for stress- and disadvantage-associated health conditions must occur before middle age-that is, during childhood, adolescence, and young adulthood. However, this requires that models of allostatic load display properties of measurement invariance across age groups. Because most research on allostatic load has featured older adults, it is unclear if these requirements can be met. METHODS: To address this question, we fit a series of exploratory and confirmatory analytic models to data on eight biomarkers using a nationally representative sample of N = 4260 children, adolescents, and young adults drawn from the National Health and Nutrition Examination Survey dataset. RESULTS: Exploratory and confirmatory models indicated that, consistent with allostatic load theory, a unidimensional model was a good fit to the data. However, this model did not display properties of measurement invariance; post-hoc analyses suggested that the biomarkers included in the final confirmatory model were most strongly intercorrelated among young adults and most weakly intercorrelated among adolescents. CONCLUSIONS: These results underscore the importance of testing assumptions about measurement invariance in allostatic load before drawing substantive conclusions about stress, disadvantage, and health by directly comparing levels of allostatic load across different stages of development, while underscoring the need to expand investigations of measurement invariance to samples of longitudinal data.

Local origin of excitatory-inhibitory tuning equivalence in a cortical network.

The interplay between excitation and inhibition determines the fidelity of cortical representations. The receptive fields of excitatory neurons are often finely tuned to encoded features, but the principles governing the tuning of inhibitory neurons remain elusive. In this study, we recorded populations of neurons in the mouse postsubiculum (PoSub), where the majority of excitatory neurons are head-direction (HD) cells. We show that the tuning of fast-spiking (FS) cells, the largest class of cortical inhibitory neurons, was broad and frequently radially symmetrical. By decomposing tuning curves using the Fourier transform, we identified an equivalence in tuning between PoSub-FS and PoSub-HD cell populations. Furthermore, recordings, optogenetic manipulations of upstream thalamic populations and computational modeling provide evidence that the tuning of PoSub-FS cells has a local origin. These findings support the notion that the equivalence of neuronal tuning between excitatory and inhibitory cell populations is an intrinsic property of local cortical networks.

Development of a reference interval for urinary ammonia-to-creatinine ratio in feline patients.

BACKGROUND: Disruption of acid-base homeostasis can lead to many clinical problems. Ammonia excretion by the kidneys is critical to maintaining acid-base homeostasis through bicarbonate production. Measurement of ammonia excretion may help determine if the kidneys are properly functioning in maintaining acid-base balance. Reference intervals are essential tools for clinical decision-making but do not currently exist for urinary ammonia-to-creatinine ratio (UACR) in feline patients. OBJECTIVE: This study aimed to generate a reference interval (RI) for UACR in healthy adult cats. METHODS: The study used samples from client-owned adult healthy cats that presented to the University of Florida Primary Care and Dentistry service (n = 92). Physical examination, serum biochemistry, urinalysis, urine ammonia, and creatinine concentrations were measured. Cats were excluded if there were significant abnormalities in their urinalysis or biochemistry panel. The RI for UACR was calculated according to the recommendation of the American Society for Veterinary Clinical Pathology. The UACR was evaluated for correlation with serum bicarbonate, weight, age, and sex. RESULTS: The RI for UACR was 3.4-20.7 with 90% confidence intervals for the lower and upper limits of (3.0-3.7) and (16.0-23.7), respectively. No significant correlation with age, sex, or weight was found. There was no discernable relationship between serum bicarbonate and UACR. CONCLUSIONS: Establishing an RI for UACR in healthy adult cats will allow further studies to determine if changes in UACR are observed during specific disease states.

Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior.

Neural population dynamics relevant to behavior vary over multiple spatial and temporal scales across three-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice, enabling the investigation of cell-type- and neurotransmitter-specific signals over arbitrary 3D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum, revealing distinct, modality-specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and the spatial localization of behavioral function across large circuits.

Personalized Accelerated ChEmoRadiation (PACER) for Lung Cancer: Protocol for a Bayesian Optimal Phase I/II Trial.

INTRODUCTION: Prior attempts to escalate radiation dose for non-small cell lung cancer (NSCLC) have not improved survival. Given the high risk for cardiopulmonary toxicity with treatment and heterogenous presentation of locally advanced NSCLC, it is unlikely that a single dose regimen is optimal for all patients. This phase I/II trial aims to evaluate a novel treatment approach where the level of accelerated hypofractionation is determined by the predicted toxicity from dose to organs at risk (OARs). METHODS: Patients ≥ 18 years old with lung cancer planned for fractionated radiotherapy to the lung with concurrent chemotherapy will be eligible. Radiation therapy (RT) will be delivered to a total dose of 60 to 66 Gy in 30, 25, or 20 fractions depending on the ability to meet constraints to key organs at risk including the lungs, heart, and esophagus. The primary endpoint is high grade pulmonary, esophageal, or cardiac toxicity. A Bayesian optimized design is used to determine stopping boundaries and evaluate the primary endpoint. CONCLUSION: PACER will evaluate the safety and feasibility of personalized accelerated chemoradiotherapy for lung cancer.

Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior.

Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.

Individualized Stereotactic Ablative Radiotherapy for Lung Tumors: The iSABR Phase 2 Nonrandomized Controlled Trial.

Importance: Stereotactic ablative radiotherapy (SABR) is used for treating lung tumors but can cause toxic effects, including life-threatening damage to central structures. Retrospective data suggested that small tumors up to 10 cm3 in volume can be well controlled with a biologically effective dose less than 100 Gy. Objective: To assess whether individualizing lung SABR dose and fractionation by tumor size, location, and histological characteristics may be associated with local tumor control. Design, Setting, and Participants: This nonrandomized controlled trial (the iSABR trial, so named for individualized SABR) was a phase 2 multicenter trial enrolling participants from November 15, 2011, to December 5, 2018, at academic medical centers in the US and Japan. Data were analyzed from December 9, 2020, to May 10, 2023. Patients were enrolled in 3 groups according to cancer type: initial diagnosis of non-small cell lung cancer (NSCLC) with an American Joint Committee on Cancer 7th edition T1-3N0M0 tumor (group 1), a T1-3N0M0 new primary NSCLC with a history of prior NSCLC or multiple NSCLCs (group 2), or lung metastases from NSCLC or another solid tumor (group 3). Intervention: Up to 4 tumors were treated with once-daily SABR. The dose ranged from 25 Gy in 1 fraction for peripheral tumors with a volume of 0 to 10 cm3 to 60 Gy in 8 fractions for central tumors with a volume greater than 30 cm3. Main outcome: Per-group freedom from local recurrence (same-lobe recurrence) at 1 year, with censoring at time of distant recurrence, death, or loss to follow-up. Results: In total, 217 unique patients (median [IQR] age, 72 [64-80] years; 129 [59%] male; 150 [69%] current or former smokers) were enrolled (some multiple times). There were 240 treatment courses: 79 in group 1, 82 in group 2, and 79 in group 3. A total of 285 tumors (211 [74%] peripheral and 74 [26%] central) were treated. The most common dose was 25 Gy in 1 fraction (158 tumors). The median (range) follow-up period was 33 (2-109) months, and the median overall survival was 59 (95% CI, 49-82) months. Freedom from local recurrence at 1 year was 97% (90% CI, 91%-99%) for group 1, 94% (90% CI, 87%-97%) for group 2, and 96% (90% CI, 89%-98%) for group 3. Freedom from local recurrence at 5 years ranged from 83% to 93% in the 3 groups. The proportion of patients with grade 3 to 5 toxic effects was low, at 5% (including a single patient [1%] with grade 5 toxic effects). Conclusions and Relevance: The results of this nonrandomized controlled trial suggest that individualized SABR (iSABR) used to treat lung tumors may allow minimization of treatment dose and is associated with excellent local control. Individualized dosing should be considered for use in future trials. Trial Registration: ClinicalTrials.gov Identifier: NCT01463423.

Four conservation challenges and a synthesis.

Conservation and management of biological systems involves decision-making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue-specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences.

Effect of Radiation Schedule on Transportation-Related Carbon Emissions: A Case Study in Rectal Cancer.

Purpose: The health care sector is a major contributor of worldwide greenhouse gas (GHG) emissions. Indirect emissions, including those associated with transportation, make up 82% of the US health care sector's environmental footprint. Radiation therapy (RT) treatment regimens present an opportunity for environmental health care-based stewardship owing to the high incidence of cancer diagnosis, significant utilization of RT, and myriad treatment days required for curative regimens. Because the use of short-course RT (SCRT) in the treatment of rectal cancer has demonstrated noninferior clinical outcomes compared with conventional, long-course RT (LCRT), we investigate the environmental and health equity-related outcomes. Methods and Materials: Patients treated with curative, preoperative RT for newly diagnosed rectal cancer at our institution between 2004 and 2022 and living in-state were included. Travel distance was estimated using patients' reported home address. Associated GHG emissions were calculated and reported in carbon dioxide equivalents (CO2e). Results: Of 334 patients included, the total distance traveled for the treatment course was significantly greater in patients treated with LCRT versus SCRT (median, 1417 vs 319 miles; P < .001). Total CO2e emissions for those undergoing LCRT (n = 261) and SCRT (n = 73) were 665.3 kg CO2e and 149.9 kg CO2e, respectively, per treatment course (P < .001), with a net difference of 515.4 kg CO2e. Relatively, this suggests that LCRT is associated with 4.5 times greater GHG emissions from patient transportation. Conclusions: Using treatment of rectal cancer as proof-of-principle, we advocate for the inclusion of environmental considerations in the creation of climate-resilient oncologic RT practices, especially in the context of equivocal clinical outcomes between RT fractionation schedules.

Partial observability and management of ecological systems.

The actual state of ecological systems is rarely known with certainty, but management actions must often be taken regardless of imperfect measurement (partial observability). Because of the difficulties in accounting for partial observability, it is usually treated in an ad hoc fashion, or simply ignored altogether. Yet incorporating partial observability into decision processes lends a realism that has the potential to improve ecological outcomes significantly. We review frameworks for dealing with partial observability, focusing specifically on dynamic ecological systems with Markovian transitions, i.e., transitions among system states that are influenced by the current system state and management action over time. Fully observable states are represented in an observable Markov decision process (MDP), whereas obscure or hidden states are represented in a partially observable process (POMDP). POMDPs can be seen as a natural extension of observable MDPs. Management under partial observability generalizes the situation for complete observability, by recognizing uncertainty about the system's state and incorporating sequential observations associated with, but not the same as, the states themselves. Decisions that otherwise would depend on the actual state must be based instead on state probability distributions ("belief states"). Partial observability requires adaptation of the entire decision process, including the use of belief states and Bayesian updates, valuation that includes expectations over observations, and optimal strategy that identifies actions for belief states over a continuous belief space. We compare MDPs and POMDPs and highlight POMDP applications to some common ecological problems. We clarify the structure and operations, approaches for finding solutions, and analytic challenges of POMDPs for practicing ecologists. Both observable and partially observable MDPs can use an inductive approach to identify optimal strategies and values, with a considerable increase in mathematical complexity with POMDPs. Better understanding of POMDPs can help decision makers manage imperfectly measured ecological systems more effectively.

Enhancing Human-Centered Design With Youth-Led Participatory Action Research Approaches for Adolescent Sexual and Reproductive Health Programming.

Existing participatory research approaches have failed to identify innovative methods that overcome the persistent barriers to adolescent sexual and reproductive health service demand and access. Increasingly, programmers have turned to human-centered design (HCD), a problem-solving process that centers the needs, perspectives, and experiences of people, when developing solutions to complex SRH challenges. This article describes the application of a youth-engaged version of HCD as part of Adolescents 360, a transdisciplinary initiative to increase 15- to 19-year-old girls' use of modern contraception in Nigeria, Ethiopia, and Tanzania. Youth-adult design teams (including 111 "youth designers" trained in HCD methods) undertook formative research to inform the design and implementation of interventions. We reflect on the practical implications of using instrumental strategies of HCD with a youth-led participatory approach. Our experience indicates that (1) engaging youth as project partners in transdisciplinary teams requires planned and dedicated financial and human resources; (2) involving youth as action researchers can help identify opportunities to improve program empathy and responsiveness; (3) it is difficult to recruit "extreme users" as project partners because of the high competencies needed in HCD; (4) centering empathy and employing design standards during prototyping can drive decision-making and resolve questions raised by conflicting evidence claims in existing bodies of literature; and (5) testing tangible services and products in real-world settings continues long after the intervention design phase. Youth-adult partnership should continue throughout this iterative and adaptive phase to ensure that the adolescent experience of the intervention remains at the core of intervention delivery.

Identification of Suicidal Ideation in the Canadian Community Health Survey-Mental Health Component Using Deep Learning.

Introduction: Suicidal ideation (SI) is prevalent in the general population, and is a risk factor for suicide. Predicting which patients are likely to have SI remains challenging. Deep Learning (DL) may be a useful tool in this context, as it can be used to find patterns in complex, heterogeneous, and incomplete datasets. An automated screening system for SI could help prompt clinicians to be more attentive to patients at risk for suicide. Methods: Using the Canadian Community Health Survey-Mental Health Component, we trained a DL model based on 23,859 survey responses to classify patients with and without SI. Models were created to classify both lifetime SI and SI over the last 12 months. From 582 possible parameters we produced 96- and 21-feature versions of the models. Models were trained using an undersampling procedure that balanced the training set between SI and non-SI; validation was done on held-out data. Results: For lifetime SI, the 96 feature model had an Area under the receiver operating curve (AUC) of 0.79 and the 21 feature model had an AUC of 0.77. For SI in the last 12 months the 96 feature model had an AUC of 0.71 and the 21 feature model had an AUC of 0.68. In addition, sensitivity analyses demonstrated feature relationships in line with existing literature. Discussion: Although further study is required to ensure clinical relevance and sample generalizability, this study is an initial proof of concept for the use of DL to improve identification of SI. Sensitivity analyses can help improve the interpretability of DL models. This kind of model would help start conversations with patients which could lead to improved care and a reduction in suicidal behavior.

Deconstructing Cumulative Risk: Poverty and Aspects of Instability Relate Uniquely to Young Children's Basal Cortisol.

This study deconstructs cumulative risk to probe unique relations to basal cortisol for family income and four distinct aspects of poverty-related instability. Participants were 288 children aged 3-5 years who attended Head Start preschool. Parents reported on poverty risks. Children provided samples of salivary cortisol at four times of day on 6 days. Results of hierarchical linear modeling with piecewise latent growth curves representing basal cortisol indicated unique relations for family income, household chaos, neighborhood risk, attachment-disruptive residential changes, and non-attachment changes. The findings support an equifinality implied by cumulative risk models in demonstrating that multiple risks relate to cortisol dysregulation yet also suggest the utility of considering unique effects of different risks for neurophysiological stress response functioning.

What are the Physiological Benefits of Increased Daily Number of Steps in Middle-Aged Women?

BACKGROUND: Physical activity plays an important role in the prevention of cardio-metabolic diseases. The present study evaluated the effect of habitual physical activity on body composition, peak oxygen consumption, cardiac and metabolic function. METHODS: This was a retrospective study. Data was collected between February 2014 and November 2015. Thirty-six healthy women (age 50±16 years) were stratified according to daily number of steps into low- (<7500 steps/day, n=17) or high-active group (>12500 steps/day, n=19). All participants underwent body composition assessment, oral glucose tolerance test and non-invasive gas-exchange and haemodynamic (bioreactance) measurements at rest and in response to maximal graded cardiopulmonary exercise test. RESULTS: The high active group averaged 16280±3205 steps/day and the low active group averaged 6285±943 steps/day (difference p=0.00). High-active women (vs. low active) demonstrated significantly lower body weight (62.1±12.3 vs. 71.2±9.1 kg, p=0.02), body fat (27.2±9.1 vs 37.7±6.4 %, p=0.00), but increased lean body mass (72.8±9.1 vs. 62.3±6.4 %, p=0.00). Peak oxygen consumption was significantly higher in high- versus low active women (2.0±0.5 vs. 1.5±0.2 l/min, p=0.00). There were no significant differences between the groups in fasting- and 2-hour glucose levels (4.9±0.6 vs. 4.8±0.5, p=0.45 and 4.8±1.3 vs. 5.5±1.4 mmol/L, p=0.16) haemodynamic measures of cardiac function including cardiac power output, cardiac output, stroke volume and arterial blood pressure at rest and in response to exercise stress test (p>0.05). CONCLUSIONS: Increased levels of habitual physical activity improve body composition and peak oxygen consumption but appears to have limited effect cardio-metabolic function in middle-aged women.

Planting the Seeds: Orchestral Music Education as a Context for Fostering Growth Mindsets.

Growth mindset is an important aspect of children's socioemotional development and is subject to change due to environmental influence. Orchestral music education may function as a fertile context in which to promote growth mindset; however, this education is not widely available to children facing economic hardship. This study examined whether participation in a program of orchestral music education was associated with higher levels of overall growth mindset and greater change in levels of musical growth mindset among children placed at risk by poverty. After at least 2 years of orchestral participation, students reported significantly higher levels of overall growth mindset than their peers; participating students also reported statistically significant increases in musical growth mindset regardless of the number of years that they were enrolled in orchestral music education. These findings have implications for future research into specific pedagogical practices that may promote growth mindset in the context of orchestral music education and more generally for future studies of the extra-musical benefits of high-quality music education.

Incidence of necrotising enterocolitis before and after introducing routine prophylactic Lactobacillus and Bifidobacterium probiotics.

OBJECTIVE: To compare rates of necrotising enterocolitis (NEC), late-onset sepsis, and mortality in 5-year epochs before and after implementation of routine daily multistrain probiotics administration in high-risk neonates. DESIGN: Single-centre retrospective observational study over the 10-year period from 1 January 2008 to 31 December 2017. SETTING: Level 3 neonatal intensive care unit (NICU) of the Norfolk and Norwich University Hospital, UK. PATIENTS: Preterm neonates at high risk of NEC: admitted to NICU within 3 days of birth at <32 weeks' gestation or at 32-36 weeks' gestation and of birth weight <1500 g. INTERVENTION: Prior to 1 January 2013 probiotics were not used. Thereafter, dual-species Lactobacillus acidophilus and Bifidobacterium bifidum combination probiotics were routinely administered daily to high-risk neonates; from April 2016 triple-species probiotics (L. acidophilus, B. bifidum, and B. longum subspecies infantis) were used. MAIN OUTCOME MEASURES: Incidence of NEC (modified Bell's stage 2a or greater), late-onset sepsis, and mortality. RESULTS: Rates of NEC fell from 7.5% (35/469 neonates) in the pre-implementation epoch to 3.1% (16/513 neonates) in the routine probiotics epoch (adjusted sub-hazard ratio=0.44, 95% CI 0.23 to 0.85, p=0.014). The more than halving of NEC rates after probiotics introduction was independent of any measured covariates, including breast milk feeding rates. Cases of late-onset sepsis fell from 106/469 (22.6%) to 59/513 (11.5%) (p<0.0001), and there was no episode of sepsis due to Lactobacillus or Bifidobacterium. All-cause mortality also fell in the routine probiotics epoch, from 67/469 (14.3%) to 47/513 (9.2%), although this was not statistically significant after multivariable adjustment (adjusted sub-hazard ratio=0.74, 95% CI 0.49 to 1.12, p=0.155). CONCLUSIONS: Administration of multispecies Lactobacillus and Bifidobacterium probiotics has been associated with a significantly decreased risk of NEC and late-onset sepsis in our neonatal unit, and no safety issues. Our data are consistent with routine use of Lactobacillus and Bifidobacterium combination probiotics having a beneficial effect on NEC prevention in very preterm neonates.

Economic instability and household chaos relate to cortisol for children in poverty.

The present study investigated relations among various aspects of economic adversity and cortisol levels for young children facing economic hardship. Specifically, the study examined relations to cortisol for variables representing family income, material hardship, financial strain, economic instability, and household chaos. Participants were 374 children, ages 3-5 years, who attended a Head Start preschool, as well as their primary caregivers. Nearly all children lived in households classified as poor or low-income, defined as less than two times the federal poverty threshold. Caregivers completed interviews about family demographics and economic adversity at the beginning of the school year. Child salivary cortisol was sampled in duplicate on two weekday mornings at the end of the school year. We hypothesized that economic instability would show direct statistical effects on child cortisol as well as indirect effects via household chaos. A structural equation model that corresponded to this hypothesis showed adequate fit for the sample data and revealed a statistically significant indirect effect of economic adversity on child cortisol via economic instability and household chaos, as well as statistically significant direct effects of economic instability and chaos on child cortisol, and a significant indirect effect of economic instability on cortisol via household chaos. Implications concern understanding mechanisms of poverty risk, including the impact of instability and chaos on stress physiology, and promoting physiological regulation for children facing economic hardship. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder.

INTRODUCTION: The heterogeneity of symptoms and complex etiology of depression pose a significant challenge to the personalization of treatment. Meanwhile, the current application of generic treatment approaches to patients with vastly differing biological and clinical profiles is far from optimal. Here, we conduct a meta-review to identify predictors of response to antidepressant therapy in order to select robust input features for machine learning models of treatment response. These machine learning models will allow us to learn associations between patient features and treatment response which have predictive value at the individual patient level; this learning can be optimized by selecting high-quality input features for the model. While current research is difficult to directly apply to the clinic, machine learning models built using knowledge gleaned from current research may become useful clinical tools. METHODS: The EMBASE and MEDLINE/PubMed online databases were searched from January 1996 to August 2017, using a combination of MeSH terms and keywords to identify relevant literature reviews. We identified a total of 1909 articles, wherein 199 articles met our inclusion criteria. RESULTS: An array of genetic, immune, endocrine, neuroimaging, sociodemographic, and symptom-based predictors of treatment response were extracted, varying widely in clinical utility. LIMITATIONS: Due to heterogeneous sample sizes, effect sizes, publication biases, and methodological disparities across reviews, we could not accurately assess the strength and directionality of every predictor. CONCLUSION: Notwithstanding our cautious interpretation of the results, we have identified a multitude of predictors that can be used to formulate a priori hypotheses regarding the input features for a computational model. We highlight the importance of large-scale research initiatives and clinically accessible biomarkers, as well as the need for replication studies of current findings. In addition, we provide recommendations for future improvement and standardization of research efforts in this field.

The potential for citizen science to produce reliable and useful information in ecology.

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Potencial de la Ciencia Ciudadana para Producir Información Útil y Confiable en la Ecología Resumen Examinamos las características de la ciencia ciudadana que influyen sobre la calidad de datos, el poder inferencial, y la utilidad en la ecología. Consideramos temas como el muestreo ecológico (basado en probabilidad, deliberado, oportunista), la conexión entre la técnica de muestreo y la inferencia estadística (basada en diseño, basada en modelo) y los paradigmas científicos (confirmatorio, exploratorio) como trasfondo contextual para nuestra evaluación. Distinguimos varios tipos de investigación de ciencia ciudadana, desde investigación intensiva con protocolos rigurosos enfocados en preguntas claramente articuladas hasta proyectos de participación masiva en plataformas de internet con recolección de datos oportunistas carentes de un diseño de muestreo, y examinamos los objetivos generales, el diseño, el análisis, y la preparación de los voluntarios y el desempeño. Identificamos características clave que influyen sobre la calidad de los datos: los objetivos del proyecto, el diseño y el análisis, y la preparación y el desempeño de los voluntarios. Los proyectos con buenos diseños, voluntarios preparados, y supervisión profesional pueden cumplir con criterios estadísticos para producir datos de alta calidad con un fuerte poder inferencial, y por lo tanto son muy adecuados para los objetivos de investigación ecológica. Los proyectos con una recolección oportunista de datos, un diseño de muestreo ínfimo o nulo, y una preparación mínima de los voluntarios son más adecuados para los objetivos generales relacionados con la educación pública o la exploración de datos ya que la estimación estadística confiable puede ser complicada o imposible. En algunos casos los métodos analíticos estadísticamente sólidos, los datos externos, o ambos, pueden incrementar el poder inferencial de ciertos datos recolectados de manera oportunista. El manejo ecológico, en especial el que realizan las agencias gubernamentales, requiere frecuentemente de datos apropiados para una inferencia confiable. Con protocolos estandarizados, métodos analíticos modernos, y programas supervisados correctamente, la ciencia ciudadana puede contribuir de forma valiosa a la conservación al incrementar el alcance de los esfuerzos de monitoreo para una especie. La calidad de datos puede mejorarse si se adhiere a los principios básicos de la recolección y análisis de datos, se diseñan los estudios para que proporcionen la calidad requerida de datos, y si se incluye una pericia estadística adecuada, fortaleciendo así el aspecto científico de la ciencia ciudadana y aumentando su aceptación dentro de la comunidad científica y con quienes toman las decisiones.