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When interest lies in causal analysis of the effects of multiple exposures on an outcome, one may be interested in investigating the interaction between the exposures. In such settings, causal analysis requires modeling the joint distribution of exposures given pertinent confounding variables. In the most general setting, this may require modeling the effect of confounding variables on the association between exposures via a second-order regression model. We consider joint modeling of exposures for causal analysis via regression adjustment and inverse weighting. In both frameworks, we also investigate the asymptotic bias of estimators when the dependence model for the generalized propensity score incorrectly assumes conditional independence of exposures or is based on a naive dependence model which does not accommodate the effect of confounders on the conditional association of exposures. We also consider the problem of a semi-continuous bivariate exposure and propose a two-stage estimation technique to study the effects of prenatal alcohol exposure, and the effects of drinking frequency and intensity on childhood cognition. [ABSTRACT FROM AUTHOR]

Hakea decurrens subsp. physocarpa is an invasive fire-adapted shrub of Australian origin that is quickly expanding in Portugal with potential impacts on fire behavior and fire regime. In this study we examined the effects of H. decurrens on fire hazard by assessing fire behavior indicators at the landscape scale, using a modeling and simulation approach. Six fuel models for H. decurrens were developed through fuel characterization and experimental fires. The fuel models correspond to combinations of developmental stages of H. decurrens populations (Early, Intermediate and Mature) and management (Standing and Slashed fuels). These combinations were used with three levels of H. decurrens invasion, corresponding to 25%, 50% and 75% of cover of the landscape, applied to five real landscapes in northern Portugal (replicates) under three fuel moisture conditions (Low, Medium and High), used as surrogates of weather severity. Fire behavior simulations were conducted with FlamMap software. The relationships between fire behavior indicators (flame length, rate of spread and burn probability) at the landscape level and the four factors tested were analyzed using Generalized Linear Mixed Models. Standing fuels were found to be more hazardous than slashed fuels. Fire-hazard increased with H. decurrens stand maturity and slash, regardless of moisture conditions. The results of this study indicate that H. decurrens expansion might negatively affect the fire regime in the north of Portugal. Our findings add to other known negative impacts of the species on native ecosystems, calling for the need to reinforce its control. [ABSTRACT FROM AUTHOR]

Agroforestry practices (AFPs) play a critical role in enhancing income and reducing poverty. This study assessed the effect of AFPs on income and poverty status of farmers in Lay Armachiho (LA), Bahir Dar Zuria (BDR), and Banja districts of Northwestern Ethiopia. 387 households, and 63 key informants were interviewed. Data were analyzed using descriptive statistics, FGT index, Gini coefficient, and multiple linear regression. About 49.35% of the respondents are categorized poor with a poverty gap of 18.93 and a poverty severity level of 9.7. Banja was the greatest with persons below poverty level (59.2%), followed by BDR (49.72%). Agroforestry practices contribute 28.43% to household income. Income from AFPs lowered the poverty ratio, poverty gap index, and poverty severity level of households by 13%, 9%, and 7%, respectively. Income from AFPs lowered the area between the line of equality and the Lorenz curve, as well as the Gini coefficient, by 7.97%. AFPs also lowered the income disparity of households in all districts. Age, AFPs land size, road accessibility, irrigation, AFPs experience, and AFPs types affect households AFPs income positively. Family size and membership to credit institutions had a negative effect. Thus, in order to lower poverty and raise household income, labor productivity, the credit service system, the road and irrigation infrastructure, and AFPs all need to be improved and scaled up. [ABSTRACT FROM AUTHOR]

Introduction Fine-needle aspiration cytology (FNAC) is an effective tool in the diagnostic work-up of patients with thyroid nodules. The aim of our study was to assess the diagnostic sensitivity of FNAC in thyroid cancer (TC) in Sweden by correlating the findings of preoperative FNAC with those obtained through final histology of the surgical specimen. Methods A Swedish nationwide cohort of patients having surgery for TC (n = 2519) from the Scandinavian Quality Register for Thyroid, Parathyroid and Adrenal surgery between 2004 and 2013 was obtained. Data was validated through scrutinizing patient FNAC and histology reports. Results Among the 2519 cases operated with a final diagnosis of TC, the diagnosis was substantiated and validated through the histology report in 2332 cases (92.6%), included in the present study. Among these, 1679 patients (72%) were female and the median age at TC diagnosis was 52.3 years (range 18-94.6). In 353 cases (15.1%) FNAC was not performed at all; whereas in the remaining 1965 cases, the diagnostic sensitivity of FNAC was 81.6%. In lesions > 1 cm, FNAC diagnostic sensitivity reached 86.5%, whereas in lesions < 1 cm, FNAC yielded a sensitivity of 61.5%. Approximately 85% of FNACs (n = 1981/2332) were performed using ultra-sonographic (US) guidance. In TC lesions > 1 cm, the diagnostic sensitivity of US-guided FNAC (n = 1504) was 86.9% as compared to 76.9% in clinically applied FNAC without US utilization (n = 118). Conclusions FNAC is performed in most patients operated for TC in Sweden (85%) and retains its value as a tool in TC diagnostic work-up with an overall sensitivity of 82%, reaching 87% in lesions > 1 cm, that harbor clinically relevant TC. [ABSTRACT FROM AUTHOR]

Background: Many radiology programs utilize a night-float system to mitigate the effects of fatigue, improve patient care, and provide faster report turnaround times. Prior studies have demonstrated an increase in discrepancy rates during night-float shifts. Objectives: This study was performed to examine the effects of night-float shift work on radiology resident cognition. We hypothesized that there would be diminished cognitive function on testing following night-float shifts when compared to testing following day shifts. Methods: Diagnostic radiology residents in their second to fifth years of residency at a single institution were recruited to participate in this pilot study. Cognitive function was evaluated using the Lumosity Neurocognitive Performance Tests (NCPT), standardized performance tests that provide real-time, objective measurements of cognitive function. Study participants completed the NCPT in 5 sessions following 5 consecutive day shifts to evaluate their baseline cognitive function. The tests were re-administered at the end of consecutive night-float shifts to assess for any changes. Sleep was objectively monitored using actigraphy devices worn around the wrist during all study weeks. Descriptive and summary statistics were performed. Results: 23 prospectively recruited diagnostic radiology residents working night-float shifts took a mean 13.6 (± 5.1) neurocognitive performance tests during the study period. There was a statistically significant decline in 2 of the 6 cognitive tests administered, signifying a decrease in attention, speed, and complex reasoning ability. Night-float shifts were significantly longer than the day shifts and associated with a significantly higher study volume and cross-sectional study volume. Fitbit data demonstrated that there were no significant differences in level of activity while awake. However, participants slept significantly longer during day shifts. Conclusions: A sample of 23 radiology residents working night-float shifts demonstrated declines in attention, speed, and complex reasoning ability following sequential administration of standardized neurocognitive performance tests. While the sample size is small, these findings demonstrate the potential deleterious effects of night-float shift work and provide evidence to support further inquiry into this phenomenon. [ABSTRACT FROM AUTHOR]

Rationale: Motivation and inhibitory control are dominantly regulated by the dopaminergic (DA) and noradrenergic (NA) systems, respectively. Hypothalamic hypocretin (orexin) neurons provide afferent inputs to DA and NA nuclei and hypocretin-1 receptors (HcrtR1) are implicated in reward and addiction. However, the role of the HcrtR1 in inhibitory control is not well understood. Objectives: To determine the effects of HcrtR1 antagonism and motivational state in inhibitory control using the go/no-go task in mice. Methods: n = 23 male C57Bl/6JArc mice were trained in a go/no-go task. Decision tree dendrogram analysis of training data identified more and less impulsive clusters of animals. A HcrtR1 antagonist (BI001, 12.5 mg/kg, per os) or vehicle were then administered 30 min before go/no-go testing, once daily for 5 days, under high (food-restricted) and low (free-feeding) motivational states in a latin-square crossover design. Compound exposure levels were assessed in a satellite group of animals. Results: HcrtR1 antagonism increased go accuracy and decreased no-go accuracy in free-feeding animals overall, whereas it decreased go accuracy and increased no-go accuracy only in more impulsive, food restricted mice. HcrtR1 antagonism also showed differential effects in premature responding, which was increased in response to the antagonist in free-feeding, less impulsive animals, and decreased in food restricted, more impulsive animals. HcrtR1 receptor occupancy by BI001 was estimated at ~ 66% during the task. Conclusions: These data indicate that hypocretin signalling plays roles in goal-directed behaviour and inhibitory control in a motivational state-dependant manner. While likely not useful in all settings, HcrtR1 antagonism may be beneficial in improving inhibitory control in impulsive subpopulations. [ABSTRACT FROM AUTHOR]

The A3 adenosine receptor (AR) is an important inflammatory and immunological target. However, the underlying mechanisms are not fully understood. Here, we report the gene regulation in HL-60 cells treated acutely with highly selective A3AR agonist MRS5698, positive allosteric modulator (PAM) LUF6000, or both. Both pro- and anti-inflammatory genes, such as IL-1a, IL-1β, and NFκBIZ, are significantly upregulated. During our observations, LUF6000 alone produced a lesser effect, while the MRS5698 + LUF6000 group demonstrated generally greater effects than MRS5698 alone, consistent with allosteric enhancement. The number of genes up- and down-regulated are similar. Pathway analysis highlighted the critical involvement of signaling molecules, including IL-6 and IL-17. Important upstream regulators include IL-1a, IL-1β, TNF-α, NF-κB, etc. PPAR, which modulates eicosanoid metabolism, was highly downregulated by the A3AR agonist. Considering previous pharmacological results and mathematical modeling, LUF6000's small enhancement of genetic upregulation suggested that MRS5698 is a nearly full agonist, which we demonstrated in both cAMP and calcium assays. The smaller effect of LUF6000 on MRS5698 in comparison to its effect on Cl-IB-MECA was shown in both HL-60 cells endogenously expressing the human (h) A3AR and in recombinant hA3AR-expressing CHO cells, consistent with its HL-60 cell genetic regulation patterns. In summary, by using both selective agonists and PAM, we identified genes that are closely relevant to immunity and inflammation to be regulated by A3AR in differentiated HL-60 cells, a cell model of neutrophil function. In addition, we demonstrated the previously uncharacterized allosteric signaling-enhancing effect of LUF6000 in cells endogenously expressing the hA3AR. [ABSTRACT FROM AUTHOR]

Copyright of AIDS & Behavior is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Understanding the principles of colonization resistance of the gut microbiome to the pathogen Clostridioides difficile will enable the design of defined bacterial therapeutics. We investigate the ecological principles of community resistance to C. difficile using a synthetic human gut microbiome. Using a dynamic computational model, we demonstrate that C. difficile receives the largest number and magnitude of incoming negative interactions. Our results show that C. difficile is in a unique class of species that display a strong negative dependence between growth and species richness. We identify molecular mechanisms of inhibition including acidification of the environment and competition over resources. We demonstrate that Clostridium hiranonis strongly inhibits C. difficile partially via resource competition. Increasing the initial density of C. difficile can increase its abundance in the assembled community, but community context determines the maximum achievable C. difficile abundance. Our work suggests that the C. difficile inhibitory potential of defined bacterial therapeutics can be optimized by designing communities featuring a combination of mechanisms including species richness, environment acidification, and resource competition.

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures. [ABSTRACT FROM AUTHOR]

Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervasive online, STB risk detection may be improved through development of uniquely insightful digital markers. Focusing on Sanctioned Suicide, an online pro-choice suicide forum, this work derived 17 egocentric network features to capture dynamics of social interaction and engagement within this uniquely uncensored community. Using network data generated from over 3.2 million unique interactions of N = 192 individuals, n = 48 of which were determined to be highest risk users (HRUs), a machine learning classification model was trained, validated, and tested to predict HRU status. Model prediction dynamics were analyzed using introspection techniques to uncover patterns in feature influence and highlight social phenomena. The model achieved a test AUC = 0.73 ([0.61, 0.85], 95% CI), suggesting that network-based socio-behavioral patterns of online interaction can signal for heightened suicide risk. Transitivity, density, and in-degree centrality were among the most important features driving this performance. Moreover, predicted HRUs tended to be targets of social exchanges with lesser frequency and possessed egocentric networks with "small world" network properties. Through the implementation of an underutilized method on an unlikely data source, findings support future incorporation of network-based social interaction features in descriptive, predictive, and preventative STB research. [ABSTRACT FROM AUTHOR]

The neurotransmitter dopamine has central roles in mood, appetite, arousal and movement1. Despite its importance in brain physiology and function, and as a target for illicit and therapeutic drugs, the human dopamine transporter (hDAT) and mechanisms by which it is inhibited by small molecules and Zn2+ are without a high-resolution structural context. Here we determine the structure of hDAT in a tripartite complex with the competitive inhibitor and cocaine analogue, (–)-2-β-carbomethoxy-3-β-(4-fluorophenyl)tropane2 (β-CFT), the non-competitive inhibitor MRS72923 and Zn2+ (ref. 4). We show how β-CFT occupies the central site, approximately halfway across the membrane, stabilizing the transporter in an outward-open conformation. MRS7292 binds to a structurally uncharacterized allosteric site, adjacent to the extracellular vestibule, sequestered underneath the extracellular loop 4 (EL4) and adjacent to transmembrane helix 1b (TM1b), acting as a wedge, precluding movement of TM1b and closure of the extracellular gate. A Zn2+ ion further stabilizes the outward-facing conformation by coupling EL4 to EL2, TM7 and TM8, thus providing specific insights into how Zn2+ restrains the movement of EL4 relative to EL2 and inhibits transport activity.Cryo-electron microscopy structure of the human dopamine transporter in complex with multiple inhibitors illuminates mechanisms of allosteric inhibition. [ABSTRACT FROM AUTHOR]

Repulsive guidance molecule A (RGMa) is an inhibitor of neuronal growth and survival which is upregulated in the damaged central nervous system following acute spinal cord injury (SCI), traumatic brain injury, acute ischemic stroke (AIS), and other neuropathological conditions. Neutralization of RGMa is neuroprotective and promotes neuroplasticity in several preclinical models of neurodegeneration and injury including multiple sclerosis, AIS, and SCI. Given the limitations of current treatments for AIS due to narrow time windows to intervention (TTI), and restrictive patient selection criteria, there is significant unmet need for therapeutic agents that enable tissue survival and repair following acute ischemic damage for a broader population of stroke patients. In this preclinical study, we evaluated whether elezanumab, a human anti-RGMa monoclonal antibody, could improve neuromotor function and modulate neuroinflammatory cell activation following AIS with delayed intervention times up to 24 h using a rabbit embolic permanent middle cerebral artery occlusion model (pMCAO). In two replicate 28-day pMCAO studies, weekly intravenous infusions of elezanumab, over a range of doses and TTIs of 6 and 24 h after stroke, significantly improved neuromotor function in both pMCAO studies when first administered 6 h after stroke. All elezanumab treatment groups, including the 24 h TTI group, had significantly less neuroinflammation as assessed by microglial and astrocyte activation. The novel mechanism of action and potential for expanding TTI in human AIS make elezanumab distinct from current acute reperfusion therapies, and support evaluation in clinical trials of acute CNS damage to determine optimal dose and TTI in humans. A: Ramified/resting astrocytes and microglia in a normal, uninjured rabbit brain. B: Rabbit pMCAO brain illustrating lesion on right side of brain (red), surrounded by penumbra (pink) during acute phase post stroke, with minimal injury to left brain hemisphere. Penumbra characterized by activated astrocytes and microglia (region in crosshair within circle), with upregulation of free and bound RGMa. C: Elezanumab binds to both free and bound RGMa, preventing full activation of astrocytes and microglia. D: Elezanumab is efficacious in rabbit pMCAO with a 4 × larger TTI window vs. tPA (6 vs. 1.5 h, respectively). In human AIS, tPA is approved for a TTI of 3-4.5 h. Elezanumab is currently being evaluated in a clinical Ph2 study of AIS to determine the optimal dose and TTI (NCT04309474). [ABSTRACT FROM AUTHOR]

Copyright of AIDS & Behavior is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Convolutional neural networks (CNNs) have achieved impressive results on imbalanced image data, but they still have difficulty generalizing to minority classes and their decisions are difficult to interpret. These problems are related because the method by which CNNs generalize to minority classes, which requires improvement, is wrapped in a black-box. To demystify CNN decisions on imbalanced data, we focus on their latent features. Although CNNs embed the pattern knowledge learned from a training set in model parameters, the effect of this knowledge is contained in feature and classification embeddings (FE and CE). These embeddings can be extracted from a trained model and their global, class properties (e.g., frequency, magnitude and identity) can be analyzed. We find that important information regarding the ability of a neural network to generalize to minority classes resides in the class top-K CE and FE. We show that a CNN learns a limited number of class top-K CE per category, and that their magnitudes vary based on whether the same class is balanced or imbalanced. We hypothesize that latent class diversity is as important as the number of class examples, which has important implications for re-sampling and cost-sensitive methods. These methods generally focus on rebalancing model weights, class numbers and margins; instead of diversifying class latent features. We also demonstrate that a CNN has difficulty generalizing to test data if the magnitude of its top-K latent features do not match the training set. We use three popular image datasets and two cost-sensitive algorithms commonly employed in imbalanced learning for our experiments. [ABSTRACT FROM AUTHOR]

Human T-cell leukemia virus type 1 (HTLV-1) infection is linked to the development of adult T-cell leukemia/lymphoma (ATLL) and the neuroinflammatory disease, HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). The HTLV-1 Tax oncoprotein regulates viral gene expression and persistently activates NF-κB to maintain the viability of HTLV-1-infected T cells. Here, we utilize a kinome-wide shRNA screen to identify the tyrosine kinase KDR as an essential survival factor of HTLV-1-transformed cells. Inhibition of KDR specifically induces apoptosis of Tax expressing HTLV-1-transformed cell lines and CD4 + T cells from HAM/TSP patients. Furthermore, inhibition of KDR triggers the autophagic degradation of Tax resulting in impaired NF-κB activation and diminished viral transmission in co-culture assays. Tax induces the expression of KDR, forms a complex with KDR, and is phosphorylated by KDR. These findings suggest that Tax stability is dependent on KDR activity which could be exploited as a strategy to target Tax in HTLV-1-associated diseases. The human T-cell leukemia virus type 1 Tax oncoprotein plays essential roles in regulating viral gene expression and cell survival. Here, the authors show that Tax requires the tyrosine kinase KDR to prevent its degradation by autophagy. [ABSTRACT FROM AUTHOR]

Angiogenin, an RNase-A-family protein, promotes angiogenesis and has been implicated in cancer, neurodegenerative diseases and epigenetic inheritance1–10. After activation during cellular stress, angiogenin cleaves tRNAs at the anticodon loop, resulting in translation repression11–15. However, the catalytic activity of isolated angiogenin is very low, and the mechanisms of the enzyme activation and tRNA specificity have remained a puzzle3,16–23. Here we identify these mechanisms using biochemical assays and cryogenic electron microscopy (cryo-EM). Our study reveals that the cytosolic ribosome is the activator of angiogenin. A cryo-EM structure features angiogenin bound in the A site of the 80S ribosome. The C-terminal tail of angiogenin is rearranged by interactions with the ribosome to activate the RNase catalytic centre, making the enzyme several orders of magnitude more efficient in tRNA cleavage. Additional 80S–angiogenin structures capture how tRNA substrate is directed by the ribosome into angiogenin’s active site, demonstrating that the ribosome acts as the specificity factor. Our findings therefore suggest that angiogenin is activated by ribosomes with a vacant A site, the abundance of which increases during cellular stress24–27. These results may facilitate the development of therapeutics to treat cancer and neurodegenerative diseases.Angiogenin binds to the ribosomal A site to cleave tRNA. [ABSTRACT FROM AUTHOR]

We study a 2+1D lattice gauge theory with fundamental representation scalar fields which has both Higgs and confining regimes with a spontaneously-broken U(1) 0-form symmetry. We show that the Higgs and confining regimes may be distinguished by a natural gauge invariant observable: the phase Ω of a correlation function of a vortex line operator linking with an electric Wilson line. We employ dualities and strong coupling expansions to analytically explore parameter regimes which were inaccessible in previous continuum calculations, and discuss possible implications for the phase diagram. [ABSTRACT FROM AUTHOR]

Pistia stratiotes L. (water lettuce) is a floating tropical macrophyte long identified and managed as a non-native species within the State of Florida and other areas of the southern United States. Macrofossil seeds from Lake Annie, Florida, however, indicate abundant presence of P. stratiotes intermixed with other locally native macrophytes from ~13,500 to ~12,000 calibrated years before present (cal yr BP). This was soon after the lake depression first began filling with water as the piezometric groundwater surface of the Florida peninsula rose in response to rising seas during the transition (~18,000 to ~11,000 cal yr BP) from the Last Glacial Maximum (LGM) to the Holocene interglacial. These macrofossil records join several other lines of evidence supporting native status of P. stratiotes in the Florida peninsula. While recent cryptic invasion of non-native Pistia genotypes into some of Florida's freshwater ecosystems also appears likely, confirmed paleo-presence and contemporary persistence of native P. stratiotes subpopulations may have especially important management and conservation implications for Florida's spring-fed streams. Palaeobotanical evidence of this type may be useful in further resolving the global biogeography of P. stratiotes and other cryptic aquatic plant species. [ABSTRACT FROM AUTHOR]

Complete eradication of invasive plants is often infeasible but in some cases it is possible to reduce the invader to low levels with reduced ongoing management costs, referred to as functional eradication. Non-native Phragmites australis has challenged land managers across North America but functional eradication may yet be possible in some scenarios. Here we present data from Chesapeake Bay brackish tidal wetlands where two approaches to Phragmites management (long-term, continuous management and short-term, non-continuous management) were used. We demonstrate that the application of herbicides will lead to the establishment of native species, but long-term, continuous management is required to facilitate functional eradication of Phragmites by keeping it at low levels of occurrence and restoring native plant communities. Ultimately, historical data from sites that were sampled as part of this study indicate that if management is successful and results in functional eradication of Phragmites, then the recovering vegetation will include native species that were present before the sites were invaded by Phragmites. [ABSTRACT FROM AUTHOR]

Purpose of Review: Critically assess and evaluate existing measures of sexual function developed for and validated in gender minority individuals (e.g., transgender, non-binary, Two-Spirit, intersex individuals). Provide recommendations for the development of gender minority inclusive measures of sexual function. Recent Findings: The present review describes the measurement development processes and psychometric properties of sexual function assessment tools that have been developed for and validated in gender minority individuals. Two measures of sexual function were recently developed with the intention of being used specifically in gender diverse groups. The Transmasculine Sexual Function Index (TM-SFI) for sexually active transmasculine individuals with cervixes was adapted from the six-item Female Sexual Function Index (FSFI). The Operated Male-to-Female Sexual Function Index (oMtFSFI) is for individuals who have received gender-affirming surgery (GAS), specifically penile skin inversion vaginoplasty. Although the TM-SFI is validated for use in English, the oMtFSFI is currently validated for use only in Italian. Psychometric properties of both measures are discussed, and recommendations for equity-informed measurement applicable to gender minority individuals are provided. Summary: We present a critical review focused on the psychometric properties of two measures of sexual function for gender minority adults. Existing gaps with current measurement tools for this population are discussed, and recommendations are made using best practices in equity-informed measure development relevant to this population. [ABSTRACT FROM AUTHOR]

Nocturia has been increasingly recognized as a manifestation of various non-urological conditions including hypertension. In adults, blood pressure (BP) elevation has been identified as a robust correlate of nocturia, but such a relationship has not been studied in pediatric populations where nocturia is often attributed to hormonal, sleep, physiological or psychological disorders. Accordingly, this study aimed to determine the relationship between nocturia and BP elevation in adolescents. We prospectively studied 100 patients, aged 10–18 years, recruited from pediatric clinics at our institution. Nocturia (defined as ≥ 1 voids on voiding diary analysis) was present in 45% of the study sample (range: 1–4 voids/night). 37% of subjects self-reported awakening to urinate, and 34% of subjects had BP elevation according to age-dependent thresholds from current Pediatrics guidelines. On multivariate analyses, BP elevation was strongly associated with nocturia determined by both voiding diary (OR 26.2, 95% CI: 6.5, 106.0) and self-report. Conversely, nocturia was associated with increased odds of elevated BP by diary (26.3, 95% CI: 6.5, 106.4) and self-report (OR 8.1, 95% CI: 3.2, 20.5). In conclusion, nocturia appears to be common and is strongly associated with BP elevation in adolescents. These findings suggest that eliciting a history of nocturia holds promise as a simple method of identifying adolescents at risk for hypertension. [ABSTRACT FROM AUTHOR]

Studies show that interpersonal relations impact behavior change. Yet, a comprehensive review of their efficacy remains unclear. This systematic review examines the efficacy of dyadic and group-based studies that intervened on primary endpoints: diet, PA, and weight loss in adults and their networks. We searched five databases for eligible articles published from 1980 to present. Final inclusion and risk of bias were independently determined and agreed upon by two of the paper's co-authors. Nine dyads and twelve group-based studies were eligible. Of the studies, 36% (4/11) of PA studies, 60% (3/5) of diet studies and 57% (8/14) of studies with weight loss as primary outcomes, reported significant findings. Compared to dyadic interventions, a greater proportion of group-based interventions demonstrated efficacy in PA gain and weight loss as outcomes. Approximately 43% of studies demonstrated low to moderate methodological quality. This systematic review synthesized the evidence of dyadic and group studies that intervened on PA, diet, and weight in adults from the same network. Moderately-high risk of bias and lack of diverse representation restricts inferences around efficacy. High-quality rigorous research is needed to understand the efficacy of dyadic and group-based interventions in addressing these co-occurring endpoints of interest. [ABSTRACT FROM AUTHOR]

Alcohol consumption during pregnancy can result in a range of adverse postnatal outcomes among exposed children. However, identifying at-risk children is challenging given the difficulty to confirm prenatal alcohol exposure and the lack of early diagnostic tools. Placental surveys present an important opportunity to uncover early biomarkers to identify those at risk. Here, we report the first transcriptome-wide evaluation to comprehensively evaluate human placental pathways altered by fetal alcohol exposure. In a prospective longitudinal birth cohort in Cape Town, South Africa, we performed bulk tissue RNAseq in placenta samples from 32 women reporting heavy drinking during pregnancy and 30 abstainers/light drinkers. Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis were performed to assess associations between fetal alcohol exposure and placental gene expression patterns at a network-wide and single gene level, respectively. The results revealed altered expression in genes related to erythropoiesis and angiogenesis, which are implicated in established postnatal phenotypes related to alcohol exposure, including disruptions in iron homeostasis, growth, and neurodevelopment. The reported findings provide insights into the molecular pathways affected by prenatal alcohol exposure and highlight the potential of placental biomarkers for detecting and understanding the effects of alcohol on fetal development. [ABSTRACT FROM AUTHOR]

Proficient reading requires critical phonological processing skill that interacts with both genetic and environmental factors. However, the precise nature of the relationships between phonological processing and genetic and environmental factors are poorly understood. We analyzed data from the Genes, Reading and Dyslexia (GRaD) Study on 1419 children ages 8–15 years from African-American and Hispanic-American family backgrounds living in North America. The analyses showed that phonological awareness mediated the relationship between DCDC2-READ1 and reading outcomes when parental education and socioeconomic status was low. The association between READ1 and reading performance is complex, whereby mediation by phonological awareness was significantly moderated by both parental education and socioeconomic status. These results show the importance of home environment and phonological skills when determining associations between READ1 and reading outcomes. This will be an important consideration in the development of genetic screening for risk of reading disability. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to examine the effects of intravenous (IV) fluid restriction on time to resolution of hyperlactatemia in septic shock. Hyperlactatemia in sepsis is associated with worse outcome. Sepsis guidelines suggest targeting lactate clearance to guide fluid therapy despite the complexity of hyperlactatemia and the potential harm of fluid overload. Methods: We conducted a post hoc analysis of serial plasma lactate concentrations in a sub-cohort of 777 patients from the international multicenter clinical CLASSIC trial (restriction of intravenous fluids in intensive care unit (ICU) patients with septic shock). Adult ICU patients with septic shock had been randomized to restrictive (n = 385) or standard (n = 392) intravenous fluid therapy. The primary outcome, time to resolution of hyperlactatemia, was analyzed with a competing-risks regression model. Death and discharge were competing outcomes, and administrative censoring was imposed 72 h after randomization if hyperlactatemia persisted. The regression analysis was adjusted for the same stratification variables and covariates as in the original CLASSIC trial analysis. Results: The hazard ratios (HRs) for the cumulative probability of resolution of hyperlactatemia, in the restrictive vs the standard group, in the unadjusted analysis, with time split, were 0.94 (confidence interval (CI) 0.78–1.14) at day 1 and 1.21 (0.89–1.65) at day 2–3. The adjusted analyses were consistent with the unadjusted results. Conclusion: In this post hoc retrospective analysis of a multicenter randomized controlled trial (RCT), a restrictive intravenous fluid strategy did not seem to affect the time to resolution of hyperlactatemia in adult ICU patients with septic shock. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) is a chronic condition affecting up to 1 billion people, globally. Despite this spread, OSA is still thought to be underdiagnosed. Lack of diagnosis is largely attributed to the high cost, resource-intensive, and time-consuming nature of existing diagnostic technologies during sleep. As individuals with OSA do not show many symptoms other than daytime sleepiness, predicting OSA while the individual is awake (wakefulness) is quite challenging. However, research especially in the last decade has shown promising results for quick and accurate methodologies to predict OSA during wakefulness. Furthermore, advances in machine learning algorithms offer new ways to analyze the measured data with more precision. With a widening research outlook, the present review compares methodologies for OSA screening during wakefulness, and recommendations are made for avenues of future research and study designs. [ABSTRACT FROM AUTHOR]

Alcohol use was associated with elevated COVID-19 risk in the general population. People with HIV (PWH) have high prevalences of alcohol use. To evaluate the effect of alcohol use on COVID-19 risks among PWH, we estimated the risk of COVID-19 diagnosis and COVID-19-related hospitalization among PWH in routine care at 8 HIV primary care centers that contributed data to the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort according to their alcohol use just prior to the COVID-19 pandemic. The CNICS data repository includes demographic characteristics, clinical diagnoses, and laboratory test results from electronic medical records and other sources. Alcohol use, substance use, and mental health symptoms were self-reported on tablet-based standardized surveys. Alcohol use was categorized according to standard, sex-specific Alcohol Use Disorder Identification Test-Consumption instrument cut-offs. We followed 5,496 PWH (79% male, 48% Black race, median age = 53 years) from March 1, 2020 to December 31, 2020. Relative to PWH with no baseline alcohol use, the adjusted hazard ratio (aHR) of COVID-19 diagnosis was 1.09 (95% confidence interval [CI]: 0.78, 1.51) for lower-risk drinking and 1.19 (95%CI: 0.81, 1.73) for unhealthy drinking. The aHR of COVID-19-related hospitalization was 0.82 (95%CI: 0.33, 1.99) for lower-risk drinking and 1.25 (95%CI: 0.50, 3.09) for unhealthy drinking. Results were not modified by recent cocaine or non-prescribed opioid use, depressive symptoms, or diagnoses of alcohol use disorder. The study suggested a slightly increased, but not statistically significant risk of COVID-19 diagnosis and hospitalization associated with unhealthy alcohol use. [ABSTRACT FROM AUTHOR]

Understanding the amount of space required by animals to fulfill their biological needs is essential for comprehending their behavior, their ecological role within their community, and for effective conservation planning and resource management. The space-use patterns of habituated primates often are studied by using handheld GPS devices, which provide detailed movement information that can link patterns of ranging and space-use to the behavioral decisions that generate these patterns. However, these data may not accurately represent an animal's total movements, posing challenges when the desired inference is at the home range scale. To address this problem, we used a 13-year dataset from 11 groups of white-faced capuchins (Cebus capucinus imitator) to examine the impact of sampling elements, such as sample size, regularity, and temporal coverage, on home range estimation accuracy. We found that accurate home range estimation is feasible with relatively small absolute sample sizes and irregular sampling, as long as the data are collected over extended time periods. Also, concentrated sampling can lead to bias and overconfidence due to uncaptured variations in space use and underlying movement behaviors. Sampling protocols relying on handheld GPS for home range estimation are improved by maximizing independent location data distributed across time periods much longer than the target species' home range crossing timescale. [ABSTRACT FROM AUTHOR]

Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa. Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences. [ABSTRACT FROM AUTHOR]

Positive psychology (PP) interventions utilize short tasks (e.g., using personal strengths,) to cultivate well-being, and they may increase cardiac health behaviors. Text message interventions (TMIs) may represent a novel, accessible means to deliver a personalized, PP-based program to promote health behavior engagement. Accordingly, we developed Text4Health, a 12-week, adaptive, PP-based TMI, which delivers specific text messages to individuals in response to their ratings of prior messages, to promote health in persons at elevated cardiac risk. In this manuscript, we describe the design, conduct, and process-related results of a controlled pilot trial of the Text4Health program, compared to enhanced usual care, among 60 patients with multiple cardiac risk conditions and suboptimal adherence to diet and exercise. The primary aim of this study is to assess the feasibility and acceptability of the adaptive TMI. As a key secondary analysis, we are comparing between-group differences in health-related outcomes at 12 and 24 weeks. Study procedures have been successfully completed for all 60 participants. Study participants reported the intervention as useful (mean rating 7.5 [SD 1.7] out of 10) and low burden (mean rating of burden 1.5/10 [SD 2.1]). In exit interviews, they reported enjoying the different types of text messages and provided suggestions for further intervention refinement. If subsequent analysis of the intervention shows potential benefit on clinically relevant outcomes, the next step will be to test it in a larger randomized trial powered to detect changes in health behaviors and other patient-centered outcomes. Trial registration: The study was registered at ClinicalTrials.gov, on May 11, 2020, after IRB approval but prior to the initiation of recruitment. The registration number is NCT04382521, https://clinicaltrials.gov/ct2/show/NCT04382521 [ABSTRACT FROM AUTHOR]

Purpose: This study aims to understand parents' experiences of school integration support for their child's transition to K-12 schooling during or after cancer treatment.Methods: This integrative literature review used PubMed, CINAHL, PsycINFO, and Embase databases and included articles from January 2000 to July 2022 describing parent experiences with support from healthcare providers, school faculty/systems, and school integration programs. This review was guided by an adapted School Re-Entry Model and used constant comparison to identify common themes and guide synthesis. The Johns Hopkins Evidence and Quality Guide was used to appraise article quality and level of evidence.Results: Thirty-five articles were included in the final review: seventeen qualitative, fourteen quantitative, and four mixed or multi-method designs. Parents reported experiences receiving support from healthcare providers, school faculty/systems, school integration programs, and "other" sources. Parents reported both facilitators and barriers to communication, knowledge, and the process of receiving school integration support.Conclusions: Parents found neuro/psychologists highly supportive but reported limited support from other healthcare providers. Most parents reported mixed experiences with school faculty and reported many barriers to school system support. Parents reported positive experiences with school integration programs; however, limited programs were available.Implications For Cancer Survivors: Future programs and research should focus on addressing identified barriers and facilitators of school integration support. Further work is also needed to understand a wider range of parent experiences during school integration. [ABSTRACT FROM AUTHOR]

Central to the Research Domain Criteria (RDoC) framework is the idea that RDoC constructs, which vary dimensionally by individual, are heavily influenced by contextual factors. Perhaps chief among these contextual factors is structural opportunity – the quality of resources available to a child as they grow. The aim of this study is to understand the impact of access to opportunity during childhood on three central RDoC cognitive systems constructs: language, visual perception, and attention. These constructs were measured using clinical data from psychological evaluations of youth ages 4–18 years (N = 16,523; Mage = 10.57, 62.3% male, 55.3% White). Structural opportunity was measured using the geocoded Child Opportunity Index 2.0 (COI), a composite score reflecting 29 weighted indicators of access to the types of neighborhood conditions that help children thrive. Findings indicate that, controlling for demographic and socioeconomic factors, greater access to opportunity is associated with significantly stronger cognitive skills across all three constructs. However, opportunity uniquely explains the largest proportion of the variance in language skills (8.4%), compared to 5.8% of the variance in visual processing skills and less than 2% of the variance in attention. Further, a moderating effect of age was found on the relation between COI and language skills, suggesting that the longer children remain exposed to lower levels of opportunity, the lower their language skills tend to be. Understanding how opportunity impacts cognitive development allows clinicians to offer better tailored recommendations to support children with cognitive systems deficits, and will support policy recommendations around access to opportunity. [ABSTRACT FROM AUTHOR]

Cattle herders and agricultural workers have been identified has key high-risk populations for malaria in northern Namibia. Population size estimates for these groups are lacking but are important for planning, monitoring and evaluating the effectiveness of targeted strategies towards malaria elimination in the region. In this analysis, we extend population size estimation methods routinely used in HIV research, specifically social mapping and multiple source capture-recapture, to the context of malaria to estimate how many cattle herders and agricultural workers lived in two regions of northern Namibia over the course of the 2019–2020 malaria season. Both methods estimated two to three times more agricultural workers than cattle herders but size estimates based on the multiple source capture-recapture method were two to three times greater than the mapping-based, highlighting important methodological considerations to apply such methods to these highly mobile populations. In particular, we compared open versus closed populations assumptions for the capture-recapture method and assessed the impact of sensitivity analyses on the procedure to link records across multiple data sources on population size estimates. Our results are important for national control programs to target their resources and consider integrating routine population size estimation of high risk populations in their surveillance activities. [ABSTRACT FROM AUTHOR]

SiGe heteroepitaxial growth yields pristine host material for quantum dot qubits, but residual interface disorder can lead to qubit-to-qubit variability that might pose an obstacle to reliable SiGe-based quantum computing. By convolving data from scanning tunneling microscopy and high-angle annular dark field scanning transmission electron microscopy, we reconstruct 3D interfacial atomic structure and employ an atomistic multi-valley effective mass theory to quantify qubit spectral variability. The results indicate (1) appreciable valley splitting (VS) variability of ~50% owing to alloy disorder and (2) roughness-induced double-dot detuning bias energy variability of order 1–10 meV depending on well thickness. For measured intermixing, atomic steps have negligible influence on VS, and uncorrelated roughness causes spatially fluctuating energy biases in double-dot detunings potentially incorrectly attributed to charge disorder. Our approach yields atomic structure spanning orders of magnitude larger areas than post-growth microscopy or tomography alone, enabling more holistic predictions of disorder-induced qubit variability. [ABSTRACT FROM AUTHOR]

Protein synthesis terminates when a stop codon enters the ribosome’s A-site. Although termination is efficient, stop codon readthrough can occur when a near-cognate tRNA outcompetes release factors during decoding. Seeking to understand readthrough regulation we used a machine learning approach to analyze readthrough efficiency data from published HEK293T ribosome profiling experiments and compared it to comparable yeast experiments. We obtained evidence for the conservation of identities of the stop codon, its context, and 3’-UTR length (when termination is compromised), but not the P-site codon, suggesting a P-site tRNA role in readthrough regulation. Models trained on data from cells treated with the readthrough-promoting drug, G418, accurately predicted readthrough of premature termination codons arising from CFTR nonsense alleles that cause cystic fibrosis. This predictive ability has the potential to aid development of nonsense suppression therapies by predicting a patient’s likelihood of improvement in response to drugs given their nonsense mutation sequence context.Stop codon readthrough, the ribosomal bypass of mRNA nonsense codons, has therapeutic potential for diseases caused by nonsense mutations. Here, the authors used machine learning to define readthrough-conducive mRNA sequences and predict specific CFTR alleles likely amenable to readthrough therapy. [ABSTRACT FROM AUTHOR]

Introduction: Strong evidence suggests that olfactory dysfunction (OD) can predict additional neurocognitive decline in neurodegenerative conditions such as Alzheimer's and Parkinson's diseases. However, research exploring olfaction and cognition in younger populations is limited. The aim of this review is to evaluate cognitive changes among non-elderly adults with non-COVID-19-related OD. Methods: We performed a structured comprehensive literature search of PubMed, Ovid Embase, Web of Science, and Cochrane Library in developing this scoping review. The primary outcome of interest was the association between OD and cognitive functioning in adults less than 60 years of age. Results: We identified 2878 studies for title and abstract review, with 167 undergoing full text review, and 54 selected for data extraction. Of these, 34 studies reported on populations of individuals restricted to the ages of 18–60, whereas the remaining 20 studies included a more heterogeneous population with the majority of individuals in this target age range in addition to some above the age of 60. The etiologies for smell loss among the included studies were neuropsychiatric disorders (37%), idiopathic cause (25%), type 2 diabetes (7%), trauma (5%), infection (4%), intellectual disability (4%), and other (18%). Some studies reported numerous associations and at times mixed, resulting in a total number of associations greater than the included number of 54 studies. Overall, 21/54 studies demonstrated a positive association between olfaction and cognition, 7/54 demonstrated no association, 25/54 reported mixed results, and only 1/54 demonstrated a negative association. Conclusion: Most studies demonstrate a positive correlation between OD and cognition, but the data are mixed with associations less robust in this young adult population compared to elderly adults. Despite the heterogeneity in study populations and outcomes, this scoping review serves as a starting point for further investigation on this topic. Notably, as many studies in this review involved disorders that may have confounding effects on both olfaction and cognition, future research should control for these confounders and incorporate non-elderly individuals with non-psychiatric causes of smell loss. [ABSTRACT FROM AUTHOR]

The Paris Agreement has seen the adoption of a 1.5° to 2 °C climate target, based on the belief that climate change becomes 'dangerous' above this level. Since then, the scientific community and the countries most affected by global warming have reiterated that the maximum limit to be reached should be 1.5 °C. This paper goes one step further by questioning the reasoning behind the adoption of these targets, arguing that the fossil fuel-dependent political context in which they were adopted has undermined justice concerns. We highlight the political influence of the fossil fuels industry within target-setting negotiations, analyzing the evolution of climate targets and fossil fuel lobbying. We then harness published scientific evidence and the Earth System Justice framework to analyze the impacts of the 1.5 °C target, and the injustices that have so far been implicitly deemed acceptable. We argue that 1 °C would have been a far more just target and was undermined by vested interests and status quo maintenance. Finally, we propose just supply-side policies to ensure an adequate placement of responsibility on the fossil fuel industry. This way we (a) identify political influences and scientific blind spots that have and could continue to hinder climate action, (b) reveal how these influences delayed more ambitious climate objectives, contributing to the adoption of an unjust climate target, and (c) promote a focus on supply-side measures and polluting industries in order to break free from the impasse in the energy transition and foster more just outcomes. [ABSTRACT FROM AUTHOR]

Abstract The beta‐site amyloid precursor protein cleaving enzyme‐1 (BACE‐1) initiates the generation of amyloid‐β (Aβ), and the amyloid cascade leading to amyloid plaque deposition, neurodegeneration, and dementia in Alzheimer's disease (AD). Clinical failures of anti‐Aβ therapies in dementia stages suggest that treatment has to start in the early, asymptomatic disease states. The BACE‐1 inhibitor CNP520 has a selectivity, pharmacodynamics, and distribution profile suitable for AD prevention studies. CNP520 reduced brain and cerebrospinal fluid (CSF) Aβ in rats and dogs, and Aβ plaque deposition in APP‐transgenic mice. Animal toxicology studies of CNP520 demonstrated sufficient safety margins, with no signs of hair depigmentation, retina degeneration, liver toxicity, or cardiovascular effects. In healthy adults ≥ 60 years old, treatment with CNP520 was safe and well tolerated and resulted in robust and dose‐dependent Aβ reduction in the cerebrospinal fluid. Thus, long‐term, pivotal studies with CNP520 have been initiated in the Generation Program.

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention. Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined and the pathophysiology unknown. Here, the authors conduct deep phenotyping of a cohort of PI-ME/CFS patients. [ABSTRACT FROM AUTHOR]

Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public health and economic challenges in tropical and sub-tropical regions worldwide. Predicting infectious disease outbreaks on a countrywide scale is complex due to spatiotemporal variations in dengue incidence across administrative areas. To address this, we propose a machine learning ensemble model for forecasting the dengue incidence rate (DIR) in Brazil, with a focus on the population under 19 years old. The model integrates spatial and temporal information, providing one-month-ahead DIR estimates at the state level. Comparative analyses with a dummy model and ablation studies demonstrate the ensemble model's qualitative and quantitative efficacy across the 27 Brazilian Federal Units. Furthermore, we showcase the transferability of this approach to Peru, another Latin American country with differing epidemiological characteristics. This timely forecast system can aid local governments in implementing targeted control measures. The study advances climate services for health by identifying factors triggering dengue outbreaks in Brazil and Peru, emphasizing collaborative efforts with intergovernmental organizations and public health institutions. The innovation lies not only in the algorithms themselves but in their application to a domain marked by data scarcity and operational scalability challenges. We bridge the gap by integrating well-curated ground data with advanced analytical methods, addressing a significant deficiency in current practices. The successful transfer of the model to Peru and its consistent performance during the 2019 outbreak in Brazil showcase its scalability and practical application. While acknowledging limitations in handling extreme values, especially in regions with low DIR, our approach excels where accurate predictions are critical. The study not only contributes to advancing DIR forecasting but also represents a paradigm shift in integrating advanced analytics into public health operational frameworks. This work, driven by a collaborative spirit involving intergovernmental organizations and public health institutions, sets a precedent for interdisciplinary collaboration in addressing global health challenges. It not only enhances our understanding of factors triggering dengue outbreaks but also serves as a template for the effective implementation of advanced analytical methods in public health. [ABSTRACT FROM AUTHOR]