Correlation Patterns Research Articles

A comparison of antibiotic resistance genes and mobile genetic elements in wild and captive Himalayan vultures.

As the most widely distributed scavenger birds on the Qinghai-Tibetan Plateau, Himalayan vultures (Gyps himalayensis) feed on the carcasses of various wild and domestic animals, facing the dual selection pressure of pathogens and antibiotics and are suitable biological sentinel species for monitoring antibiotic resistance genes (ARGs). This study used metagenomic sequencing to comparatively investigate the ARGs and mobile genetic elements (MGEs) of wild and captive Himalayan vultures. Overall, the resistome of Himalayan vultures contained 414 ARG subtypes resistant to 20 ARG types, with abundances ranging from 0.01 to 1,493.60 ppm. The most abundant resistance type was beta-lactam (175 subtypes), followed by multidrug resistance genes with 68 subtypes. Decreases in the abundance of macrolide-lincosamide-streptogramin (MLS) resistance genes were observed in the wild group compared with the zoo group. A total of 75 genera (five phyla) of bacteria were predicted to be the hosts of ARGs in Himalayan vultures, and the clinical (102 ARGs) and high-risk ARGs (35 Rank I and 56 Rank II ARGs) were also analyzed. Among these ARGs, twenty-two clinical ARGs, nine Rank I ARG subtypes, sixteen Rank II ARG subtypes were found to differ significantly between the two groups. Five types of MGEs (128 subtypes) were found in Himalayan vultures. Plasmids (62 subtypes) and transposases (44 subtypes) were found to be the main MGE types. Efflux pump and antibiotic deactivation were the main resistance mechanisms of ARGs in Himalayan vultures. Decreases in the abundance of cellular protection were identified in wild Himalayan vultures compared with the captive Himalayan vultures. Procrustes analysis and the co-occurrence networks analysis revealed different patterns of correlations among gut microbes, ARGs, and MGEs in wild and captive Himalayan vultures. This study is the first step in describing the characterization of the ARGs in the gut of Himalayan vultures and highlights the need to pay more attention to scavenging birds.

Assessing the Language Abilities of Preterm-Born Children: An Examination of Standardized Testing and Language Sample Analysis.

To understand how best to assess the language abilities of preterm-born children, this study: (a) compared preterm- and term-born children's language skills using standardized testing and language sample analysis (LSA), (b) investigated how executive function skills and the language sampling context respectively affect standardized test and LSA scores, and (c) examined the pattern of associations between standardized test and LSA scores among preterm-/term-born groups. Twenty-five term-born and 23 preterm-born 2-year-old singletons were administered the language scales of the Bayley Scales of Infant and Toddler Development-Third Edition (receptive communication, expressive communication, language composite scores). Parent-child free-play recordings were used to quantify the (para)linguistic features of the children's speech. Executive function was measured via parent report. The preterm-born group obtained significantly lower scores than the term-born group on all Bayley language measures (though differences were not consistently observed when using cutoff scores). Few preterm-term differences in LSA measures were found. The preterm-term differences in Bayley scores were not explained by between-group differences in executive function. Some preterm-term differences in LSA scores were moderated by the language sampling context. The preterm- and term-born groups exhibited different patterns of Bayley-LSA correlations. Preterm language difficulties were more apparent on standardized test than LSA scores. Nonetheless, the Bayley-LSA correlations indicate that poor test performance (linked with preterm birth) is associated with functional communication difficulties. The discussion outlines the complementary utility of standardized tests and LSA while acknowledging the limited utility of cutoff scores and the confounding influence of the language sampling context. https://doi.org/10.23641/asha.26142661.

Interpretable multi-graph convolution network integrating spatio-temporal attention and dynamic combination for wind power forecasting

Graph neural networks (GNN) can effectively improve wind power forecasting accuracy due to their ability to capture spatial correlations between wind farms. However, conventional GNN-based forecasting models constructing the graphs from only one specific perspective fail to characterize the spatial correlation patterns comprehensively and accurately. Furthermore, their black-box structure leads to deficient interpretability of the forecasting results, which hampers the quantification of forecasting uncertainty and reduces the credibility of applying these forecasting models in practice. To address the above problems, an interpretable ultra-short-term wind power forecasting method is proposed based on multi-graph convolution network integrating spatio-temporal attention and dynamic graph combination. Four undirected weight graphs are constructed to form a multi-graph scheme by considering various geographical and statistical aspects, and then graph convolution network (GCN) and temporal convolution network (TCN) are used to enhance the forecasting performance by leveraging information in both space and time dimensions. Meanwhile, it consists of temporal attention that deeply mines the temporal dependencies and spatial attention that interprets the influence of wind farms on the forecasts. Additionally, to boost the adaptability and generalization capability of the proposed method, an improved reinforcement learning is elaborately designed to combine the results of different graphs by dynamically optimizing their weights to obtain the final forecasts. Experiment results suggest that the proposed method exhibits superior forecasting accuracy and reasonable interpretability compared with other benchmark methods.

The effect of the Solar System Ephemeris on the search for the nano-Hz gravitational wave background

ABSTRACT The detection of the nano-Hz gravitational-wave background (GWB) is one of the main targets of Pulsar timing arrays (PTAs). The detection can be achieved via searching for a common signal with quadrapolar correlation between pulsar pairs. Errors in the Solar-System ephemeris (SSE) can induce dipolar correlations in PTA data, which may affect the results of GWB searches, especially when the data quality is not high enough to constrain the correlation pattern. We investigate the effect of unmodelled SSE errors on GWB searches with PTAs, using simulations with properties based on the European Pulsar Timing Array data set. When the GWB signal is strong, SSE errors have little effect on the GWB search results, including parameter inference and model selection. When the GWB signal is weak, SSE errors can lead to overestimation of the GWB amplitude. However, model comparison would show strong support for dipolar correction, which implies the source of the common signal to be SSE-related and helps avoid its misidentification as a GWB signal. This indicates that SSE error is unlikely to be the main source of the common signal detected recently with real PTA data. We also use simulations to test the ability of the SSE model LINIMOSS in absorbing SSE-error signals and leaving the GWB signal intact. We show that marginalizing LINIMOSS planetary parameters with infinite priors is good at absorbing SSE errors, but may also lead to improper absorption of a GWB signal. Caution is therefore required when setting appropriate limits on the priors of SSE parameters.

P-707 Discovery of novel serum biomarkers for premature ovarian insufficiency through machine-learning bioinformatic analysis

Abstract Study question Can we develop predictive, practical biomarkers for premature ovarian insufficiency (POI) from normal ovaries and human blood, tested and validated by machine-learning (ML) algorithm? Summary answer Applying random forest and XGBoost algorithms, we pinpointed 60 significant genes from ovarian tissues; transcriptome analysis identified RPM1 as the most significant biomarker. What is known already Accelerated ovarian aging has been suggested as one of the possible underlying mechanisms of POI; previous literature has focused on identifying its cause in genetic realm, commonly adopting first-generation sequencing (Sanger) and next-generation sequencing (NGS). However, such powerful tools are still limited in accurately depicting the complete transcript information of ovarian tissue. Moreover, theoretical value of such disease-predictive gene candidates needs to be validated using human tissues and blood, and finally, underlying mechanisms should be confirmed with ideal animal model and cell line. Study design, size, duration To overcome the existing limitations and maximize clinical relevance of disease-predictive gene analysis and theoretical biomarker exploration, the current study incorporated the transcriptome expression data from both young and old ovaries obtained from the Genotype-Tissue Expression (GTEx) database. Using supervised machine learning techniques, potential marker genes were identified, and a meaningful predictive index was subsequently developed using human plasma samples of control and POI women with and without pregnancy history. Participants/materials, setting, methods The performance evaluation of two ML models were achieved using the area under receiver operating characteristic curve (AUROC), accuracy, kappa, and F1 score, among various age groups. The expression profiles of final candidate marker genes were analyzed within the GTEx datasets, in relation to their correlation pattern with age. Finally, the potential transcriptome biomarkers were quantitatively evaluated using human blood samples from 92 controls and 108 POI women visiting a tertiary center in 2023. Main results and the role of chance We found 41 significant genes using the random forest algorithm and 19 significant genes using the XGboost algorithm. We then tested the ML-characterized 7 final candidate biomarkers in human blood samples (all p < 0.05). The AUROC and interventional predictive index results demonstrated the potential of RPM1 as a predictive marker with AUROC of 0.784, comparable to the AUROC of anti-mullerian hormone (AMH) as 0.659 and inhibin B (INHB) as 0.646. Limitations, reasons for caution To avoid potential biases, RPMs should be tested in a larger, multinational cohort with different genetic and geographic backgrounds, possibly incorporating Mendelian randomization method to estimate the causal effect of RPMs on POI. Finally, to ultimately confirm their therapeutic potential, preclinical studies should be considered using RPM recombinant proteins. Wider implications of the findings Our results proposed that predictive biomarkers for POI could be associated with premature, accelerated ovarian aging of the disease mechanism, and these biomarkers can be developed as evaluation metrics for the efficacy, progress, and prognosis of interventions and treatment modalities assigned to POI women seeking fertility. Trial registration number 202302240001

Genetic parameters of feeding behaviour traits in ducks bred for foie gras production

The mule duck accounts for over 90% of French foie gras production, a sector where feed represents two-thirds of production costs. This study focuses on analysing the feeding behaviours of the mule duck and its parental populations (Pekin and Muscovy) using automated feeders. To assess feed efficiency, feed conversion ratio and residual feed intake were analysed, along with six traits derived at the daily and meal levels. Genetic parameters were estimated separately in purebred populations, as well as with a joint crossbred model that estimated the parental contributions to the hybrid crossbred performances. In relation to higher feed intakes and much−reduced feeding times (P < 0.001), the feeding rate in the Pekin population was twice as high as in the Muscovy population (19 g/min vs 9 g/min), while the mule duck exhibited a large heterosis for this trait (29 g/min). Feeding traits exhibited moderate (0.38 ± 0.11) to high (0.65 ± 0.11) heritabilities. Similar correlation patterns were observed between feeding traits in the two parental populations. In the Pekin line, the feed conversion ratio did not significantly correlate with feeding traits except for daily feed intake. However, in the Muscovy population, it was negatively correlated with the number of meals (−0.51 ± 0.21) and positively with meal feed intake and meal duration (+0.79 ± 0.17 and + 0.71 ± 0.26, respectively). The contributions of the two parental species to the hybrid’s performance differed, with the Pekin contributing more to feeding and meat traits compared to the Muscovy. They were similar only for liver weight. Additionally, unfavourable correlations between meat traits and liver traits were estimated in both pathways. Genetic relationships between feeding traits and slaughter traits varied by parental origin, suggesting different strategies for improving hybrid performance in the two parental species. However, in both pathways, genetic correlations between feed conversion ratio and meat traits (breast muscle and thigh weights) were favourable (<−0.42 ± 0.18), whereas they were unfavourable (>0.41 ± 0.20) for fatty liver weight. Altogether, improving liver traits and feed efficiency in the hybrid through selection in the parental populations could be enhanced by considering feeding traits recorded with electronic feeders, provided that adverse correlations are properly accounted for in a multitrait index.

Exploration of the biochemical composition of Citrus L. seeds for industrial applications

This study aimed to assess the biochemical profiles of Citrus L. seeds and elucidate the correlation patterns among varieties based on their biochemical compositions. Samples of Citrus L. seeds were subjected to extraction, and the resulting oils were analyzed for their biochemical levels. Principal Component Analysis (PCA) was usedto unveil the relationship patterns among Citrus L. The research findings revealed that several citrus seeds, including C. Paradise, C. limon (L.) Burm.f., Citrus reticulate, C. maxima (Burm.) Merr., and Citrus sinensis, exhibited similarities in their compositions of flavonoid compounds, phenolic acids, and carotenoids. However, aromatic volatile compounds displayed variations among varieties without discernible patterns of similarity. The N-serotonin compound exhibited significant variations among varieties; whereas fatty acid compounds demonstrated similarities between Citrus latifolia and C. limon (L.) Burm.f. The eight samples showed no similarity in their biochemical variation patterns.

Estimation of the lateral mis-registrations of the GRAVITY+ adaptive optics system

Context. The GRAVITY+ upgrade implies a complete renewal of its adaptive optics (AO) systems. Its complex design, featuring moving components between the deformable mirrors and the wavefront sensors, requires the monitoring and auto-calibrating of the lateral mis-registrations of the system while in operation. Aims. For preset and target acquisition, large lateral registration errors must be assessed in open loop to bring the system to a state where the AO loop closes. In closed loop, these errors must be monitored and corrected, without impacting the science. Methods. With respect to the first requirement, our method is perturbative, with two-dimensional modes intentionally applied to the system and correlated to a reference interaction matrix. For the second requirement, we applied a non-perturbative approach that searches for specific patterns in temporal correlations in the closed loop telemetry. This signal is produced by the noise propagation through the AO loop. Results. Our methods were validated through simulations and on the GRAVITY+ development bench. The first method robustly estimates the lateral mis-registrations, in a single fit and with a sub-subaperture resolution while in an open loop. The second method is not absolute, but it does successfully bring the system towards a negligible mis-registration error, with a limited turbulence bias. Both methods proved to robustly work on a system still under development and not fully characterised. Conclusions. Tested with Shack-Hartmann wavefront sensors, the proposed methods are versatile and easily adaptable to other AO instruments, such as the pyramid, which stands as a baseline for all future AO systems. The non-perturbative method, not relying on an interaction matrix model and being sparse in the Fourier domain, is particularly suitable to the next generation of AO systems for extremely large telescopes that will present an unprecedented level of complexity and numbers of actuators.

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma.

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response. RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types. Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8. TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.

Multi-Height and Heterogeneous Sensor Fusion Discriminant with LSTM for Weak Fire Signal Detection in Large Spaces with High Ceilings

Fire is a significant cause of fatalities and property loss. In tall spaces, early smoke dispersion is hindered by thermal barriers, and initial flames with limited smoke production may be obscured by ground-level structures. Consequently, smoke, temperature, and other fire sensor signals are weakened, leading to delays in fire detection by sensor networks. This paper proposes a multi-height and heterogeneous fusion discriminant model with a multilayered LSTM structure for the robust detection of weak fire signals in such challenging situations. The model employs three LSTM structures with cross inputs in the first layer and an input-weighted LSTM structure in the second layer to capture the temporal and cross-correlation features of smoke concentration, temperature, and plume velocity sensor data. The third LSTM layer further aggregates these features to extract the spatial correlation patterns among different heights. The experimental results demonstrate that the proposed algorithm can effectively expedite alarm response during sparse smoke conditions and mitigate false alarms caused by weak signals.

Study on Pricing and Replenishment of Vegetable Commodities based on TOPSIS and ARIMA Models

This study focuses on sales forecasting and pricing optimization of vegetable categories in fresh produce supermarkets. By analyzing the sales data, correlation analysis and clustering methods were used to reveal the correlation patterns among different vegetable categories. The ARIMA model was used to predict the daily replenishment quantity, and TOPSIS and entropy weighting methods were combined to screen out 27 high-quality individual products with high sales volume and stable price to achieve the maximum profit target. The study provides effective sales strategies and operational decision support for fresh food supermarkets, which has practical significance and reference value.

Testing an integrated model of climate change anxiety

Emerging studies have reported that people may experience anxiety when thinking about climate change. Although such an anxiety experience can be a rational response to climate change threats, it can still be a psychological burden to people's daily lives. In this research, we proposed an integrated model of climate change anxiety as a guiding framework to identify relevant psychological factors that predict climate change anxiety. According to this model, anxiety about climate change is related to experience, perception, and appraisal of climate change, processes that are underpinned by experiential, cognitive, and sociocultural factors. Furthermore, previous studies have operationalized climate change anxiety either by affect-based responses (i.e., anxiety-related feelings) or symptom-based responses (i.e., anxiety-related impairments), but it is unclear whether the two types of responses are conceptually and empirically similar or distinct. We thus examined how the three sets of factors relate to these responses and how they relate to outcome correlates simultaneously. We tested our framework in two pre-registered studies conducted in the US (Study 1) and China (Study 2). Both studies involved representative samples of US and Chinese adults regarding gender and age. Results of the partial least square-structural equation modeling revealed supporting evidence for the role of experiential, cognitive, and sociocultural factors, although some patterns were inconsistent with our pre-registered hypotheses. Importantly, we observed that the two types of climate change anxiety showed both similar and different correlation patterns with the predictors (e.g., efficacy beliefs, values) and outcome variables (e.g., pro-environmental behavior, life satisfaction). Our findings provide initial evidence for the usefulness of the integrated model as a guiding framework for understanding climate change anxiety and the need to differentiate different types of climate change anxiety responses.

Unified stress–strain calculation model for UHPC-filled stainless-steel tubular columns with various cross-sectional shapes under axial compression

Different cross-sectional shapes of ultrahigh-performance concrete (UHPC)-filled stainless-steel tubular (UHPCFSST) columns result in their stress-strain curves exhibiting softening or hardening stages, and currently, there is no unified calculation model available that can effectively simulate these variations. Based on experimental data, models for predicting peak stress, peak strain, ultimate stress, and ultimate strain of UHPCFSSTs with high accuracy has been provided. Comparative analysis reveals that the stress transfer capability and stability of UHPCFSSTs with the different cross-sectional shapes from highest to lowest are as follows: circular, square, and rectangular. Building upon Wei et al.'s general stress-strain calculation model, a high correlation pattern between parameter b and hoop confinement coefficient (ξs) has been obtained through correlation analysis, elucidating the post-peak behavior of stress-strain curves of UHPCFSSTs. By modeling parameter b, Wei et al.'s model has been extended to accommodate the stress-strain relationship under axial compression for UHPCFSSTs with different cross-sectional shapes. This establishes a unified stress-strain calculation model for UHPCFSSTs with different cross-sectional shapes under axial compression. Comparative analysis indicates that the proposed unified calculation model for axial compression stress-strain behavior of UHPCFSSTs can effectively quantify the influence of cross-sectional shape on stress-strain curves, demonstrating high predictive accuracy and generality.

Distinct patterns of electrophysiologic-neuroimaging correlations between Parkinson's disease and multiple system atrophy

Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the "on medication" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease.

Barriers to Seek Professional Help for Mental Health Scale: Development and Psychometric Validation

Background: Mental health conditions are highly prevalent, and both supply- and demand-side factors drive a high treatment gap. There is a dearth of socio-culturally appropriate measures to assess barriers to professional help-seeking in distressed non-treatment seekers. This study aimed to develop and validate the Barriers to Seek Professional Help for Mental Health Scale for distressed, non-treatment-seeking young adults experiencing common mental health concerns in the Indian context. Methods: The study was conducted in three phases: Phase I: development of initial measure; Phase II: scale try-out ( N = 190); and Phase III: validating the factor structure ( N = 172). Distressed, non-treatment-seeking young adults (20–35 years old) were recruited for the present study. Exploratory factor analysis (EFA) was used to identify the factor structure, and confirmatory factor analysis (CFA) was conducted to validate it. Results: EFA showed that a five-factor structure best fits the data, namely, stigma and minimization, instrumental barriers, problem perception, self-efficacy in service utilization, and negative service expectancies. CFA revealed that the model was a reasonably good fit. The scale was finalized into a 24-item measure. Internal consistency reliabilities of the scale and subscales were satisfactory. Correlation patterns of barriers subscales with help negation, help-seeking inclination, and distress support its convergent validity. Conclusion: The Barriers to Seek Professional Help for Mental Health Scale was developed, and preliminary evidence supports its reliability, construct, and convergent validity. The scale could prove valuable for assessing barriers to seeking professional help for mental health in the Indian context, developing help-seeking interventions, and examining their effectiveness in increasing the uptake of mental health services.

Cognitive Correlates of Risky Decision-Making in Individuals with and without ADHD: A Meta-analysis.

This meta-analytic study aims to investigate the cognitive correlates of risky decision-making in individuals with attention-deficit/hyperactivity disorder (ADHD) and typically developing (TD) individuals. A systematic analysis of existing literature was conducted, encompassing 38 studies (496 ADHD and 1493 TD). Findings revealed a consistent propensity for riskier decision-making in individuals with ADHD, supported by significant correlations with attention, cognitive flexibility, inhibitory control, time perception, and working memory. The study underscores the relevance of these cognitive functions in shaping decision-making tendencies, with nuanced patterns observed within the ADHD and TD subgroups. Individuals with ADHD often demonstrate altered patterns of correlation, reflecting the specific cognitive challenges characteristic of the disorder.

Comparative analyses of SARS-CoV-2 RNA concentrations in Detroit wastewater quantified with CDC N1, N2, and SC2 assays reveal optimal target for predicting COVID-19 cases

To monitor COVID-19 through wastewater surveillance, global researchers dedicated significant endeavors and resources to develop and implement diverse RT-qPCR or RT-ddPCR assays targeting different genes of SARS-CoV-2. Effective wastewater surveillance hinges on the appropriate selection of the most suitable assay, especially for resource-constrained regions where scant technical and socioeconomic resources restrict the options for testing with multiple assays. Further research is imperative to evaluate the existing assays through comprehensive comparative analyses. Such analyses are crucial for health agencies and wastewater surveillance practitioners in the selection of appropriate methods for monitoring COVID-19. In this study, untreated wastewater samples were collected weekly from the Detroit wastewater treatment plant, Michigan, USA, between January and December 2023. Polyethylene glycol precipitation (PEG) was applied to concentrate the samples followed by RNA extraction and RT-ddPCR. Three assays including N1, N2 (US CDC Real-Time Reverse Transcription PCR Panel for Detection of SARS-CoV-2), and SC2 assay (US CDC Influenza SARS-CoV-2 Multiplex Assay) were implemented to detect SARS-CoV-2 in wastewater. The limit of blank and limit of detection for the three assays were experimentally determined. SARS-CoV-2 RNA concentrations were evaluated and compared through three statistical approaches, including Pearson and Spearman's rank correlations, Dynamic Time Warping, and vector autoregressive models. N1 and N2 demonstrated the highest correlation and most similar time series patterns. Conversely, N2 and SC2 assay demonstrated the lowest correlation and least similar time series patterns. N2 was identified as the optimal target to predict COVID-19 cases. This study presents a rigorous effort in evaluating and comparing SARS-CoV-2 RNA concentrations quantified with N1, N2, and SC2 assays and their interrelations and correlations with clinical cases. This study provides valuable insights into identifying the optimal target for monitoring COVID-19 through wastewater surveillance.

(088) CONTRALATERAL SYMMETRY IN THE TOPOGRAPHY OF SELF-REPORTED VULVAR PAIN

Abstract Introduction Vulvar pain is a transdiagnostic symptom that is associated with diverse end organs, neurological, and musculoskeletal mechanisms. A better understanding of the neural mechanisms behind the spreading/worsening of vulvar pain across different sites on the vulva, could guide future research, classification, and treatment of vulvar pain-related conditions. Objective Examine the topographic correlations of vulvar pain and provide insights regarding the involvement of neural pathways underlying the topographic distribution of such pain. Methods Self-reports of sexual and genital health were collected from 2199 women through online questionnaires, as part of a larger study. Efforts were made to recruit a heterogenous sample, oversampling for women with genito-pelvic pain. Participants were asked about the presence and location of vulvar and/or vaginal pain. In addition, participants were asked about history and types of non-genital injuries. If a participant reported chronic vulvar pain, they were then presented with a drawing of a vulva divided into 24 areas, asking them to indicate the location(s) of their pain (localization of vaginal pain not included). Correlations were conducted on the presence of pain across vulvar areas that were contralaterally distributed (horizontal) vs spatially close but ipsilaterally distributed (vertical and radial), and distinguishing between women with vs without a history of back and/or pelvic injury. Results 911 women reported experiencing chronic vulvar or vulvar-vaginal pain. Results from correlations across vulvar areas are reported in Figure 1, 2 and 3, distinguishing between women with and without a history of back/pelvic injury. In both groups, horizontal correlations across left and right sides of the same tissue/structure were the strongest (Figure 1), whereas areas that were spatially close on the ipsilateral side (vertical and radial) showed weaker correlations (Figures 2 &amp; 3). Statistical tests confirmed differences in correlations both between-groups and within-groups, across different spatial relations (horizontal, vertical, radial). Conclusions The observed pattern of topographic correlations suggests specific constraints on the mechanisms involved in the spreading of vulvar pain, showing a horizontally symmetrical distribution of correlations (within tissue/structure), as opposed to a proximity-based distribution of correlations. This appears to reflect symmetrically contralateral sensitization within the same structure, even if the areas were relatively distant (e.g., right and left labia minora). According to our results, this applies more to women without a history of back/pelvic injury, compared to women with a history back/pelvic injury. Consistent with past research showing that a temporary nociceptive stimulus induces hyperalgesia and allodynia in the ipsilateral and symmetrically contralateral site of noxious stimulation (Shenker et al.,2008), our results suggest that similar neural mechanism(s) might be involved in chronic vulvar pain. The pattern of correlations found could be mediated by chronic pain-induced activation of the commissural fibers that connect, and perhaps sprout into, the symmetrically contralateral sides at the level of the dorsal horn. This would constitute a form of central sensitization (Latremoliere &amp; Woolf, 2007). Whether a comparable central sensitization process also occurs at the level of the sensory cortex (or other brain regions), or whether different forms of synaptic potentiation at the neural level are involved, must also be considered. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Adamo Bioscience.

Markers of Bone Mineral Metabolism in Thyroid Disorders

Abstract Background and Aim: Thyroid hormones are essential for normal skeletal development and bone metabolism. Despite various studies, the effect of thyroid hormone on bone metabolism has not been clearly understood. We studied the bone formation markers (procollagen type 1 N-propeptide [P1NP] and osteocalcin [OC]) and bone resorption markers (C-terminal cross-linking telopeptide of type 1 collagen [CTX] and tartrate-resistant acid phosphatase [TRAP]) in patients with thyroid disorders and the effect of treatment on them. Furthermore, a study correlating these markers with thyroid-stimulating hormone (TSH) levels was done. Materials and Methods: This cross-sectional study recruited 60 cases (40 – hypothyroid and 20 – hyperthyroid) and 20 controls based on inclusion and exclusion criteria. To evaluate the effect of treatment, cases were further subdivided based on the duration of treatment received into 0-month (newly diagnosed), 1–6-month, and &gt;6-month treatment subgroups. Both the cases and control underwent a thorough history, clinical examination, and detailed investigation based on a predesigned proforma. Results: In hyperthyroidism with 0-month treatment subgroup, both formation (OC, P1NP) and resorption (CTX) markers were significantly increased compared to control (P &lt; 0.05), which became insignificant on treatment (1–6 months) with antithyroid medication despite low TSH value. Contrarily, in hypothyroidism, a statistically significant (P &lt; 0.05) lower mean value of markers (OC, P1NP, and CTX) was observed only in the subgroup with levothyroxine supplementation. In hyperthyroidism, both the formation (OC and P1NP) and resorption markers (CTX and TRAP) showed a strong negative (P &lt; 0.001) correlation with TSH, the strength of correlation decreased, and became insignificant on treatment. In hypothyroidism, only P1NP and CTX showed an overall significant positive (P &lt; 0.05) correlation with TSH. Conclusion: Hyperthyroidism has high bone turnover markers, which showed early reversibility of markers on treatment with antithyroid medication despite low TSH, whereas in hypothyroidism, significantly lower mean value of markers is seen only in the subgroup with levothyroxine supplementation, probably owing to the suppressive effect of TSH. P1NP and CTX showed high sensitivity in both hypothyroidism and hyperthyroidism. The pattern of correlation between TSH and bone metabolism markers in hyperthyroidism suggests a direct negative effect of TSH on bone turnover, whereas in hypothyroidism, it either suggests TSH showing a positive correlation at a very high level which becomes negative as the TSH value decreases or TSH is not a dominant hormone regulating bone metabolism in hypothyroidism.

Implications of accounting for marker-based population structure in the quantitative genetic evaluation of genetic parameters related to growth and wood properties in Norway spruce

BackgroundForest geneticists typically use provenances to account for population differences in their improvement schemes; however, the historical records of the imported materials might not be very precise or well-aligned with the genetic clusters derived from advanced molecular techniques. The main objective of this study was to assess the impact of marker-based population structure on genetic parameter estimates related to growth and wood properties and their trade-offs in Norway spruce, by either incorporating it as a fixed effect (model-B) or excluding it entirely from the analysis (model-A).ResultsOur results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions.ConclusionWe conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.