Spearman's Coefficient Research Articles

Serotonin and 5-hydroxyindoleacetic acid are involved in the pathogenesis of COVID-19 in children

Background. The new coronavirus infection COVID-19 is a pressing health problem around the world. This disease affects the respiratory, cardiovascular and other systems. The role of serotonin as one of the key factors in COVID-19 is discussed in the literature.
 Aim. Determination of the concentration of serotonin and its metabolite 5-hydroxyindoleacetic acid in the blood serum of children in the acute period of COVID-19 for use as a diagnostic criterion for the severity of the disease.
 
 Material and methods. A study that included 141 children aged 0 to 17 years was conducted: 92 patients hospitalized in a hospital with a diagnosis of COVID-19 without concomitant pathology made up the study group, 49 healthy children were included in the control group. The subjects were divided into two age groups: younger (0–2 years) and older (3–17 years). The groups of patients and children from the control group were comparable in age and gender. A study of the concentration of serotonin and its metabolite — 5-hydroxyindoleacetic acid — in the blood was carried out using high-performance liquid chromatography, and the results of laboratory and instrumental research methods (obtained from medical records) were evaluated. Based on the results of computed tomography, the proportion of involvement of the lung parenchyma in the pathological process was calculated: CT0 — absence of lung damage; CT1 — less than 25%; CT2 — 25–49%; CT3 — 50–74%; CT4 — more than 75%. Quantitative data were described using median (Me) and lower and upper quartiles (Q1–Q3). To analyze the data, the Pearson χ2 test, nonparametric Kruskal–Wallis and Mann–Whitney tests, as well as the ROC curve method were used. A correlation analysis was carried out using the Spearman coefficient and an assessment of the dependence of a quantitative variable on factors using the linear regression method.
 Results. In children with COVID-19 aged 0–2 years, the concentration of serotonin (969.41 pmol/ml) in the blood serum was statistically significantly higher by 49.1 times, in the group of 3–17 years (637.87 pmol/ml) — by 24.5 times compared to age-matched controls (19.74 pmol/ml; p 0.001 and 26.0 pmol/ml; p 0.001, respectively). The concentration of 5-hydroxyindoleacetic acid in patients 0–2 years old (204.90 pmol/ml) was 4.7 times higher relative to healthy children (43.56 pmol/ml; p=0.003), and in the older age group (78.25 pmol/ml) — 2.4 times higher (32.65 pmol/ml; p=0.012), which suggests increased breakdown of serotonin under the influence of monoamine oxidase A. Maximum concentrations of serotonin in blood serum were detected in children aged 0–2 years (1808.79 pmol/ml) with damage to the lung parenchyma from 50 to 74% (grade 3 according to computed tomography). However, in children aged 3–17 years, the maximum concentrations of serotonin (2036.95 pmol/ml) were detected with lung damage ranging from 25 to 49% (grade 2 according to computed tomography). In patients with COVID-19, when the concentration of serotonin in the blood was above 1046.5 pmol/ml, grade 2–4 lung lesions were predicted according to computed tomography, sensitivity 62.5%, specificity 75%.
 Conclusion. With COVID-19, a significant increase in the concentration of serotonin and 5-hydroxyindoleacetic acid in the blood was detected in children.

Continuing bonds in men grieving a loved one.

to examine internalized and externalized continuing bonds in men grieving a loved one. a correlational, descriptive and cross-sectional study. Convenience sample comprised by 170 mourning men. The variables were mediators of mourning, continuing bonds and sociodemographic data. The instrument used was an online questionnaire comprised by mediators of mourning, a continuing bonds scale and sociodemographic data. Descriptive statistics, analysis of variance and Spearman's coefficient were used. The significance level adopted was p<0.05. the participants' mean age was 36.61 years old (SD=13.40), and 80.00% had Higher Education. The mean values corresponding to internalized and externalized continuing bonds were 24.85(SD=7.93) and 7.68(SD=2.33), respectively. Significant differences were established referring to internalized and externalized continuing bonds in terms of kinship with the deceased person(p<0.001), and none with the cause of death or with the time elapsed since the event. No significant correlations were defined between internalized/externalized continuing bonds and mediators of mourning. grieving men express internalized and externalized continuing bonds frequently and occasionally, respectively, with differences according to who the deceased person was. The Nursing discipline might devise specific strategies that strengthen coping with grief in this population group. (1) It was usual to continue the bond with the deceased loved one. (2) The expression of internalized continuing bonds was frequent after the death. (3) When facing the loss, there was occasional expression of externalized continuingbonds. (4) There were differences in internalized and externalized continuing bonds according tokinship. (5) There were no associations between continuing bonds and mediators of mourning.

Розлади харчової поведінки дітей внаслідок стресу, спричиненого війною: загальні результати дослідження

The purpose of the study is to determine eating disorders based on the results of a survey of parents and an analysis of the perception of the behavior of children aged 5-17 in conditions of stress caused by war. Research materials and methods. A large-scale cross-sectional survey of parents of school-age children who were in Ukraine at the time of the start of the war (February 24, 2022) was conducted. A total of 5,165 parents took part in the survey. The survey concerned eating disorders and included information about the gender, age, place and conditions of the child's stay, financial support and the family's access to food, general mental manifestations of stress, eating disorders that arose as a result of military operations, changes in the child's physique, etc. The work uses a specially developed questionnaire based on standardized questionnaires about children's stress and eating disorders. This stage of the work determines the peculiarities of the child's whereabouts in relation to military events (staying in occupied territories, in close proximity to hostilities, in peaceful territory, moving within Ukraine or going abroad) and their impact on the eating behavior of school-aged children. The processing of the results included descriptive statistics, as well as the analysis of the relationships of the variables using conjugation tables by calculating the Spearman's rank coefficient and Pearson's chi-square for qualitative variables. The results. It was established that the absence or decrease of appetite, rapid satiety, change in attitude to food are general stress disorders inherent in the entire studied cohort of children. Statistical analysis revealed that the frequency and duration of eating disorders, appetite, delayed satiety, capriciousness or lack of understanding, somato-vegetative manifestations, the formation of disgust or passion for certain food products in school-age children are related to the intensity and nature of the experienced military stress. Being in occupied territories or near hostilities and subsequent displacement has the greatest impact on the frequency and duration of eating disorders. The formation of long-term eating disorders in all groups is actually a deepening of unhealthy eating habits of schoolchildren, which were demonstrated in previous studies. It is expected that these violations will lead to an increase in the frequency of chronic non-communicable diseases in later life. Conclusions. The obtained results are important for the further interpretation of the results in the framework of the study of children's eating disorders under the conditions of stress caused by the war in Ukraine and providing recommendations for the correction of the detected violations. The research has an important social significance for Ukraine, as it is aimed at solving the psychological and medical consequences of the war.

Whole Genome Deconvolution Unveils Alzheimer’s Resilient Epigenetic Signature.

AbstractBackgroundThe pathological hallmarks of Alzheimer’s disease (AD) are amyloid beta plaques and neurofibrillary tangles that usually progressively affect characteristic brain regions as individuals advance from latent to prodromal to severe AD dementia (ADD). An uncommon exception to coupled progression of disease burden and clinical impairment are resilient individuals who harbor a high pathological load sufficient to cause ADD yet remain cognitively normal. We hypothesize that determining the biological mechanisms of such underlying resilience to AD (RAD) will provide unique insights into therapeutic opportunities.MethodHere, we combined epigenetic sequencing data and an innovative computational algorithm to identify gene regulatory mechanisms and putative mediators distinguishing RAD from normal control and ADD at an unprecedented scale. We developed and validated a novel machine learning method, Cellformer, for deconvoluting bulk ATAC‐seq into cell type‐specific expression across the whole genome, leading to extensive regional and cellular chromatin profiling of RAD.ResultCellformer successfully deconvoluted in silico bulk ATAC‐seq data across cross‐validation iterations, achieving strong performances with a mean Spearman coefficient of 0.82 between deconvoluted and ground truth expressions, outperforming other approaches. Validation was performed using external single nucleus datasets and showed a significant correlation above 0.75 (P‐value&lt;0.05) between deconvoluted cell type‐specific ATAC‐seq and single‐ATAC‐seq expressions for each cell type. Applied on 191 samples from normal control, RAD and ADD’s 3 brain regions, CellFormer predicted cell type‐specific expression of more than 41954 open chromatin regions (OCR), preserving regional and phenotypic variations. Downstream analysis of the derived RAD‐specific epigenetic features pinpointed the hippocampus, a region critical for learning and memory, as the major player in the resilience, modulating synaptic and neuronal process in a cell‐type specific manner.ConclusionCellformer opens new perspectives to advance bulk analysis and understand biological mechanisms using cost effective bulk sequencing. Through this study, we showed that cell type‐resolved data nominated potential epigenetic and transcriptional mediators underlying RAD that may illuminate therapeutic opportunities to limit the cognitive impact of this highly prevalent yet stubbornly incurable disease. Cellformer will be made publicly available to advance analysis of high‐throughput bulk ATAC‐seq in future investigations.

Evaluation of NLRP3 and NLRP1 inflammasome pathways in patients with Alzheimer’s disease: a clinicopathological study

AbstractBackgroundA growing body of evidence has suggested a detrimental role of NLRP1 and NLRP3 inflammasome in experimental AD. However, the characterization of these pathways in AD human brains is still missing. We aimed to characterize the hippocampal expression of the NLRP1 and NLRP3 inflammasomes in individuals with AD neuropathological change (ADNC) compared to age‐ and sex‐matched controls. We also sought to investigate the association of the expression of these proteins with cognitive abilities and AD‐pathology.MethodThe expression of NLRP1, NLRP3, caspase‐1, ASC, and hyperphosphorylated tau (p‐tau) was evaluated in the cornu ammonis (CA), dentate gyrus (DG), and subiculum (SUB) of individuals with pure AD and controls (n = 28 per group), using immunohistochemistry. The percentage of the immunostained area (IA) and the optical density (OD) of the staining were quantified through semiautomatic morphometry. Cognitive abilities were evaluated using the Clinical Dementia Rating – sum of boxes (CDR‐SB) and the AD‐pathology was based on Braak staging and the Consortium to Establish a Registry for AD (CERAD) criteria. We applied the Mann‐Whitney test to compare control with ADNC hippocampi, linear regression to examine the association of inflammasome proteins with cognition and AD‐pathology, and Spearman coefficient to examine the correlation of these proteins with p‐tau.ResultSociodemographic and clinical variables were similar between the groups (Table 1). NLRP1 and caspase‐1 expression was predominant in neurons, while ASC was detected in glial cells. NLRP3 was expressed in neurons and glia. NLRP1 and NLRP3 deposits were observed in neuritic plaques. Except for NLRP1, all the inflammasome proteins were overexpressed in CA and SUB of individuals with ADNC compared to controls (p&lt;0.05) (Figure 1). CDR‐SB and CERAD criteria were associated with increased IA for NLRP3, caspase‐1, and ASC; the Braak stage was associated with higher expression of caspase‐1 and ASC (p&lt;0.05, Table 2). Interestingly, NLRP3 (r = ‐0.52, p = 0.009) and ASC expression (r = ‐0.43, p = 0.004) correlated negatively with OD of p‐tau immunostaining in the CA of individuals with ADNCConclusionNLRP3 inflammasome pathway is up‐regulated in the ADNC hippocampi and was associated with AD‐pathology. Our results suggest that NLRP3 inflammasome contributes to cognitive impairment in AD.

Cognitive Aspects of Prymary Sjögren’s Syndrome

AbstractBackgroundSjögren’s primary syndrome (PSS) is an autoimmune disease that affects the tear line exocrine glands and saliva and may also interfere with the central (CNS) and peripheral nervous systems. PSS patients presenting with the disease can be divided into a profile characterized by the greater intensity of symptoms such as pain, fatigue, and dryness and another with fewer symptoms but a more severe prognosis. Therefore, it was verified the involvement of the CNS through neuropsychological evaluation in the different profiles of PSS.Method24 women, 11 with profile 1 (more intense symptoms, PSS1), and 13 with profile 2 (worse prognosis, PSS2), performed neuropsychological assessment composed by: MoCa, Boston reduced version, FAS. Mann Withney’s nonparametric test compared the groups, and the variables were correlated by Spearman coefficient of SPSS 23.ResultThere was a predominance of women (100%) with a mean age of 49.91 ±10.56 years and schooling of 7,83 ± 2.79 years. The comparison between PSS1 and PSS2 showed no significant difference between age (PSS1 = 52,72±8.83; Pss2 = 47.53±11.64; p = 0.257), schooling (PSS1 = 528.18± 2.67;; Pss2 = 7.53±2.96, p = 0.451) and between the tests for profiles, Moca (p = .636), Boston (p = .194), FAS (p = 1.00). Between the tests, we can verify significant positive correlations between Moca x Boston; Moca x FAS_F; Moca x FAS_A; Moca x FAS_S; Moca x FAS, and the FAS variables among themselves. The correlation between age and schooling was not significant.ConclusionThere was no difference between age and schooling or neuropsychological assessment, considering the techniques used. Then, cognition may be preserved in this sample, reflecting a non‐involvement of the CNS in this disease. However, future studies that are being conducted need to complement these results by expanding the sample or using other instruments.

Examining the Relationship and Prognostic Significance of Cell-Free DNA Levels and the PSMA-Positive Tumor Volume in Men with Prostate Cancer: A Retrospective-Prospective [68Ga]Ga-PSMA-11 PET/CT Study.

Functional imaging with prostate-specific membrane antigen (PSMA) ligands has emerged as the standard imaging method for prostate cancer (PCA). In parallel, the analysis of blood-derived, cell-free DNA (cfDNA) has been shown to be a promising quantitative biomarker of PCA aggressiveness and patient outcome. This study aimed to evaluate the relationship and prognostic value of cfDNA concentrations and the PSMA-positive tumor volume (PSMA-TV) in men with PCA undergoing [68Ga]Ga-PSMA-11 PET/CT imaging. Methods: We recruited 148 men with histologically proven PCA (mean age, 70.7 ± 7.7 y) who underwent [68Ga]Ga-PSMA-11 PET/CT (184.9 ± 18.9 MBq) and blood sampling between March 2019 and August 2021. Among these, 74 (50.0%) had hormone-sensitive PCA and 74 (50.0%) had castration-resistant PCA (CRPC). All patients provided written informed consent before blood sample collection and imaging. The cfDNA was extracted and quantified, and PSMA-expressing tumor lesions were delineated to extract the PSMA-TVs. The Spearman coefficient assessed correlations between PSMA-TV and cfDNA concentrations and cfDNA's relation with clinical parameters. The Kruskal-Wallis test examined the mean cfDNA concentration differences based on PSMA-TV quartiles for significantly correlated patient groups. Log-rank and multivariate Cox regression analyses evaluated the prognostic significance of high and low cfDNA and PSMA-TV levels for overall survival. Results: Weak positive correlations were found between cfDNA concentration and PSMA-TV in the overall group (r = 0.16, P = 0.049) and the CRPC group (r = 0.31, P = 0.007) but not in hormone-sensitive PCA patients (r = -0.024, P = 0.837). In the CRPC cohort, cfDNA concentrations significantly differed between PSMA-TV quartiles 4 and 1 (P = 0.002) and between quartiles 4 and 2 (P = 0.016). Survival outcomes were associated with PSMA-TV (P < 0.0001, P = 0.004) but not cfDNA (P = 0.174, P = 0.12), as per the log-rank and Cox regression analysis. Conclusion: These findings suggest that cfDNA might serve as a biomarker of advanced, aggressive CRPC but does not reliably reflect total tumor burden or prognosis. In comparison, [68Ga]Ga-PSMA-11 PET/CT provides a highly granular and prognostic assessment of tumor burden across the spectrum of PCA disease progression.

Comparison of methods for cardiac interoception self-assessment

Aim. Interoception reflects the perception, integration and modulation of visceral signals. Currently, there is no established universal approach to cardiac interoception assessment allowing its inclusion in the diagnostic protocol for various diseases. The aim was to compare three tests of interoception self-assessment based on heart palpitations within one day in healthy subjects.Material and methods. Eighty healthy volunteers took part in the study. To assess cardiac interoception, a test with button pushes at the moment of palpitations, a feedback test in the form of synchronous and asynchronous sound signals, a heartbeat counting task at specified time intervals were conducted with simultaneous electrocardiographic recording. The obtained data were compared with each other (Wilcoxon test). Its pairwise dependence (Spearman coefficient) and dependence on body parameters (sex, age, body mass index, fat mass, anxiety) were assessed (univariate linear regression).Results. The accuracy of the heartbeat counting task turned out to be significantly higher than in the button- pressing test (p=0,005). However, both estimates correlate with each other (r=0,66, p=0,003). A positive dependence of test accuracy on sex was found for the heartbeat counting task (p=0,021) and a negative dependence on fat mass for button- pressing task (p=0,032).Conclusion. The study found that volunteers' estimates of heartbeat accuracy varied across tests and were also associated with sex and body composition. The heart rate counting task and the button- pressing task are the most suitable for interoception assessment.

Toward AI-Assisted Clinical Assessment for Patients with Multiple Myeloma: Feature Selection for Large Language Models

Large language models (LLM) can potentially revolutionize the healthcare industry. They could reduce the burden on healthcare, increase care accessibility in areas with shortage and provide multilingual support to break down language barriers. Although, these models equipped with vast amounts of medical knowledge and the ability to understand and generate human-like text, require a proper set of feeding data (i.e., prompt engineering) for accurate diagnosis and providing reliable personalized treatment plans for patients. Multiple Myeloma (MM) is a complex hematological malignancy characterized by the uncontrolled proliferation of plasma cells in the bone marrow. Disease management for MM becomes particularly challenging due to its multisystemic nature based on the varying volume of malignant cells within the bone marrow. Implementing LLMs for clinical assessment of patients with MM needs feature selection to develop the most effective prompt for these models. Here, we utilized a machine learning (ML) approach to define salient features in a typical visit day that correlates most significantly with disease volume on the same day. These features could be the best candidate to reflect the multisystemic and dynamic nature of MM in each visit, and they could be candidates to be incorporated into LLMs to develop a system-based assessment in clinic visits. Methods: This study examined 1,472 clinical observations. To select a curated list of features associated with same-day M-spike values, 43 clinical and lab variables were input into an ML model. Random Forest (RF), an ensemble of regression trees suitable for nonlinear multiple regression, was selected as the model. The data were randomly divided into a training set (80%) and a test set (20%) for model validation. Using bootstrapping and generating 500 data sets, a random forest of regression trees was constructed, and results and estimates were aggregated across the trees. To determine the importance of each covariate, their inclusion and exclusion were compared in the models. Results: The residual distribution of the RF model indicated that nearly all M-spike values determined using the 43 variables distributed equally on either side of zero (Fig. 1). The weighted value of each of the 43 independent variables was determined by individually removing a variable from the ML algorithm and measuring its effect on the mean squared error (MSE) (Fig.2). Removal of the first lagged M-spike, serum total protein, second-lagged M-spike, serum IgG, serum IgM, and serum IgA, had the greatest effects on the ML algorithm. M-spike values determined using the ML algorithm correlated highly with M-spike values determined using the laboratory measured SPEP values as indicated by the proximity of the Pearson and Spearman correlation coefficients to +1. Using the 43 variables, the Pearson coefficient was 0.96 and the Spearman coefficient was 0.91. Feature selected modeling was performed to reduce the variables needed to predict the M-spike. Five RF models with different predictors were selected for comparison. Model A included all 43 predictors, Model B included the ten most important variables, Model C the top five variables, Model D included the first and second-lagged M-spike and serum total protein, and Model E the first-lagged M-spike and serum total protein. The Pearson's r and RMSE (root mean square error) values were used to compare the models. Pearson's r values for Model A, B, C, and D were 0.96, 0.96, 0.96, and 0.95 respectively, and the RMSE values were 0.21, 0.19, 0.19, and 0.22. In Model E, feature selection used only two variables and accurately predicted the M-spike value (Pearson's r = 0.95; RMSE 0.22). The Pearson's r values for feature selected models A, B, C, D, and E were 0.95, 0.96, 0.96, 0.95 and 0.91. Conclusion: Accurate prompt engineering to create global assessment of Myeloma clone by LLM requires a curated set of variables that correlated with disease volume. Here, we developed an ML model for feature selection utilizing the same-day available data in the patient chart. Features could be used in order of importance to provide focused, comprehensive prompts that aligned with the patient's context. The quality of AI-assisted disease assessment using these models should be compared with assessments performed by real world providers in future studies to ensure that the LLMs generate a written assessment that accurately reflects the patient's health status.

102. Assessing ChatGPT Performance in the Brazilian Infectious Disease Specialist Certification Examination

Abstract Background Advances in artificial intelligence have the potential to impact medical fields, including the use of natural language processing-based models, such as ChatGPT. The ability of the ChatGPT to provide insightful responses across diverse fields of expertise could assist in medical decision-making and knowledge management processes. ChatGPT has already demonstrated high accuracy in medical examinations such as the USMLE. To explore the potential of this tool in various contexts, our study aimed to evaluate the accuracy of the ChatGPT in the 2022 Brazilian Infectious Disease Specialist Certification Examination. Methods We conducted a test to evaluate the performance of GPT-3.5 and GPT-4 on the 2022 Brazilian Infectious Disease Specialist Certification Exam. A theoretical exam, consisting of 80 multiple-choice questions with five alternatives, was used to test performance. The GPT was given a command containing the question statement and alternatives, and a brief comment on the logic behind the answer was requested. Descriptive statistics were used to analyze the absolute performance of the correct answers in the ChatGPT-3.5 and ChatGPT-4 models. In addition, the degree of correlation between answers and performance throughout the test was estimated using Spearman's coefficient and a logistic regression curve, respectively. Results Of the 80 questions in the exam, four were excluded because they were invalidated in the final answer key. ChatGPT-3.5 had an accuracy of 53.95% (41/76), whereas ChatGPT-4 had an accuracy of 73.68% (56/76). Spearman's correlation coefficient between the two models was 0.585. There was a slight trend towards improvement in ChatGPT-4 performance throughout the test, as observed in the logistic regression curve. Comparison of Accuracy between ChatGPT 3.5 and ChatGPT4 The graph shows the percentage of accuracy for the two GPT models. The performance of ChatGPT-4 was superior to ChatGPT-3.5. Distribution of Correct and Incorrect Responses by ChatGPT-4 in Medical Test Questions The graph displays the distribution of responses generated by ChatGPT-4. The logistic regression curve shows a slight upward trend, indicating a slight improvement in performance as the questions were answered. Conclusion ChatGPT-4 achieved performance above the 60% minimum threshold required for the certification exam. This indicates that it is a promising technology in various fields, including infectious diseases. However, its potential applications and associated ethical dilemmas must be thoroughly assessed. This advancement also highlights the need for medical education to concentrate on developing competence, skills, and critical thinking rather than relying solely on memorization Disclosures All Authors: No reported disclosures

Oral health challenges in patients with chronic kidney disease: A comprehensive clinical assessment

Loss of kidney function causes oral manifestations and multiple complications that have implications for dental treatment and patients’ systemic conditions. We aimed to determine the clinical condition, epidemiological profile, and incidence of dental caries in patients with chronic kidney disease (CKD). This was an observational, cross-sectional, field study using a quantitative and epidemiological approach. The sample consisted of 45 randomly selected patients with CKD from a total of 114 patients. Data were collected through oral clinical examination, anamnesis, and medical records compiled in a clinical file specially developed for this research. Clinical evaluation was performed, including a Decayed, Missing, and Filled Teeth (DMFT) index examination. Data were analyzed using the Shapiro–Wilk test, Mann–Whitney test, and Spearman's rho coefficient. All analyses were performed using IBM SPSS Statistics software version 20.0, with a confidence interval of 95 % and significance level of 5 % (p < 0.05). The results indicated that CKD is more prevalent in the 5th decade of life, with a slight predilection for men. Oral cavity alterations were observed in 77.8 % of patients. The study population had a very high DMFT index, with a high number of missing teeth and a low number of decayed and filled teeth. Poor oral health in patients with CKD indicates a lack of care that supports the necessity of installing a preventive and therapeutic oral program and a regular follow-up aimed at this group of patients.

A simple coronary CT angiography-based jeopardy score for the identification of extensive coronary artery disease: Validation against invasive coronary angiography

PurposeThe invasive British Cardiovascular Intervention Society Jeopardy Score (iBCIS-JS) is a simple angiographic scoring system, enabling quantification of the extent of jeopardized myocardium related to clinically significant coronary artery disease (CAD). The purpose of this study was to develop and validate the coronary CT angiography-based BCIS-JS (CT-BCIS-JS) against the iBCIS-JS in patients with suspected or stable CAD. Materials and methodsPatients who underwent coronary CT angiography followed by invasive coronary angiography, within 90 days were retrospectively included. CT-BCIS-JS and iBCIS-JS were calculated, with a score ≥ 6 indicating extensive CAD. Correlation between the CT-BCIS-JS and iBCIS-JS was searched for using Spearman's coefficient, and agreement with weighted Kappa (κ) analyses. ResultsA total of 122 patients were included. There were 102 men and 20 women with a median age of 62 years (Q1, Q3: 54, 68; age range: 19–83 years). No differences in median CT-BCIS-JS (4; Q1, Q3: 0, 8) and median iBCIS-JS (4; Q1, Q3: 0, 8) were found (P = 0.18). Extensive CAD was identified in 53 (43.4%) and 52 (42.6%) patients using CT-BCIS-JS and iBCIS-JS, respectively (P = 0.88). CT-based and iBCIS-JS showed excellent correlation (r = 0.98; P < 0.001) and almost perfect agreement (κ = 0.93; 95% confidence interval: 0.90–0.97). Agreement for identification of an iBCIS-JS ≥ 6 was almost perfect (κ = 0.94; 95 % confidence interval: 0.87–0.99). ConclusionThe CT-BCIS-JS represents a feasible, and accurate method for quantification of CAD, with capabilities not different from those of iBCIS-JS. It enables simple, non-invasive identification of patients with anatomically extensive CAD.

Does maxillary sinus proximity affect molar root resorption during distalization using Invisalign? a CBCT study

BackgroundThis study aimed to assess the correlation between maxillary sinus proximity to root apices of maxillary molars and root resorption during molar distalization using clear aligner therapy (CAT).Materials and methodsThirty-eight cone beam computed tomography scans (CBCTs) obtained pre- (T0) and post-treatment (T1) from 19 adult patients (36.68 ± 13.50 years), who underwent maxillary molar distalization using Invisalign® aligners (Align Technology, Inc., San José, CA, USA) with a minimum of 2 mm distalization, were evaluated in this study At least 22 h of aligner wear per day was a main inclusion criterion. Sinus proximity and changes in root lengths were measured for 61 molars (183 roots). Spearman coefficient analysis was used for assessing correlation between sinus proximity and root resorption. The level of significance was set at p ≤ 0.05. The reproducibility of measurements was assessed by intraclass correlation coefficient (ICC).ResultsSpearman coefficient revealed no significant correlation between sinus proximity and molar root resorption for mesiobuccal, distobuccal or palatal roots (p = 0.558, p = 0.334, p = 0.931, respectively).ConclusionThere was no correlation between maxillary sinus proximity to root apices of maxillary molars and root resorption.

Prediction of fetal RR intervals from maternal factors using machine learning models

Previous literature has highlighted the importance of maternal behavior during the prenatal period for the upbringing of healthy adults. During pregnancy, fetal health assessments are mainly carried out non-invasively by monitoring fetal growth and heart rate (HR) or RR interval (RRI). Despite this, research entailing prediction of fHRs from mHRs is scarce mainly due to the difficulty in non-invasive measurements of fetal electrocardiogram (fECG). Also, so far, it is unknown how mHRs are associated with fHR over the short term. In this study, we used two machine learning models, support vector regression (SVR) and random forest (RF), for predicting average fetal RRI (fRRI). The predicted fRRI values were compared with actual fRRI values calculated from non-invasive fECG. fRRI was predicted from 13 maternal features that consisted of age, weight, and non-invasive ECG-derived parameters that included HR variability (HRV) and R wave amplitude variability. 156 records were used for training the models and the results showed that the SVR model outperformed the RF model with a root mean square error (RMSE) of 29 ms and an average error percentage (< 5%). Correlation analysis between predicted and actual fRRI values showed that the Spearman coefficient for the SVR and RF models were 0.31 (P < 0.001) and 0.19 (P < 0.05), respectively. The SVR model was further used to predict fRRI of 14 subjects who were not included in the training. The latter prediction results showed that individual error percentages were (≤ 5%) except in 3 subjects. The results of this study show that maternal factors can be potentially used for the assessment of fetal well-being based on fetal HR or RRI.

CTIM-29. FINAL EFFICACY AND CORRELATIVE ANALYSES OF 2-THE-TOP: A PILOT STUDY OF TTFIELDS (OPTUNE) PLUS PEMBROLIZUMAB PLUS MAINTENANCE TEMOZOLOMIDE IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA (NDGBM)

Abstract INTRODUCTION TTFields induce anti-tumor immunity via the STING and AIM2 inflammasomes. Thus, TTFields-treated GBM cells may provide a complete in situ vaccination platform and synergize with immune checkpoint inhibitors to prolong survival in GBM patients. METHODS We enrolled 26 ndGBM patients in a pilot study combining TTFields, pembrolizumab and maintenance temozolomide (TMZ). To distinguish immune effects of TTFields from pembrolizumab, TTFields starts at cycle 1 of TMZ while pembrolizumab (200mg Q3Wks) at cycle 2. The primary endpoint is PFS versus a case-matched cohort of 56 patients from the EF-14 study. Secondary endpoints include OS, toxicity, and mechanism of response by multiomics of PBMCs and tumors. RESULTS The median age was 60.5 years. Fourteen (54%) had biopsy only or partial resection. Nineteen (73%) had unmethylated MGMT and 3 (11.5%) had an IDH mutation. Median PFS was 12.0 months versus 5.8 months in controls (HR = 0.377; 95CI: 0.217-0.653; P = 0.0026). Median OS was 24.8 months versus 14.6 months in controls (HR = 0.522; 95CI: 0.301-0.905; P = 0.047). Importantly, residual tumor size positively correlated with the objective response and survival. Six of 15 (40%) patients with measurable disease achieved partial to complete response. The most common SAEs were thromboses, seizures, and metabolic disturbances in 4 (15%), 3 (11.5%), and 2 (7.7%) patients, respectively. Molecular analyses confirmed robust T cell activation by TTFields via T1IFN-dependent plasmacytoid dendritic cells (Spearman coefficient = -0.8; P = 0.014). Successful clonal replacement of the most expanded T cell clones after pembrolizumab strongly predicted objective responses to the triple combination in a Cox HR fit model (concordance rate = 0.876; P = 0.031). CONCLUSIONS The triple combination was well tolerated and demonstrated promising efficacy in ndGBM. Bulky residual disease was associated with better outcomes, consistent with the in-situ immunizing properties of TTFields, which synergize with pembrolizumab. Additional molecular analysis will be updated

The Chinese version of the brief pain inventory–Facial (BPI-F) among different populations: Factor structure and measurement invariance

ObjectiveThis study aimed to translate and adapt the Brief Pain Inventory-Facial (BPI-F) into Chinese, proposing a validated Chinese version for clinical application. MethodsTo evaluate the applicability of Chinese BPI-F, this study included two groups: clinical sample (406 patients with OFP) and non-clinical sample (514 college students without OFP medical history). Content validity was improved through patient interviews. Cronbach's α was used to evaluate the reliability of BPI-F in both groups. The best-fit factor structure was tested on clinical sample via exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Convergent and discriminant validity of BPI-F was evaluated by Spearman's coefficient. Serial CFA was used to assess measurement invariance between the two groups. ResultsContent validity and reliability of BPI-F were verified. EFA results support a two-factor structure, interference with general activities (1–7 items) and face-specific pain interference (8–14 items). CFA results demonstrated this two-factor structure is appropriate for different populations. Spearman results showed that BPI-F had good convergent and discriminant validity. Full measurement invariance is observed across the two groups. ConclusionThe Chinese BPI-F, with two-factor structure (interference with general / orofacial functions), enables accurate assessment of functional interference caused by OFP. BPI-F has the same significance in different clinical populations, which expands its application. Clinical significanceThis manuscript proposed the Chinese version of the BPI-F and examined its psychometric characteristics for the first time. This validated scale provides a favorable instrument for aiding individual diagnosis and treatment for OFP patients in China.

Utilizing a Machine Learning Approach to Define Racial Difference in Multi-Systemic Impact of Monoclonal Protein in Patient with Multiple Myeloma

Multiple myeloma (MM) is the second common hematologic malignancy characterized by the clonal proliferation of plasma cells. While the clinical outcomes of MM have been improved significantly, there remains an intriguing observation regarding the potential influence of race on disease biology and treatment response. In MM, the malignant plasma cell clone not only disrupts the local bone marrow microenvironment but also exerts a systemic impact on various physiological processes result in significant derangements in immune function, hematopoiesis, renal function, bone metabolism, and electrolyte homeostasis. Understanding the extent of this systemic impact and its potential variation between racial groups is crucial for optimizing patient care and treatment strategies. Here, we hypothesized that the systemic impact of the plasma cell clone does not differ significantly between African American and Caucasian patients. We employed a machine learning approach to capture the full spectrum of systemic effects comprehensively. Our novel model was trained to predict the magnitude of the plasma cell clone, as represented by serum monoclonal protein levels. By systematically comparing model performance with and without the inclusion of race as a variable, we sought to evaluate the potential influence of race on the systemic impact of the plasma cell clone. Method: A total of 171 patients with plasma cell dyscrasias including 1,472 observations were analyzed. where the upper limit of the observed M-spike was 3.5 gr/dL. Forty three clinical and lab variables as predictors of M-spike were fed into the machine learning model. Two lagged variables as the last two preceding M-spike values by the same subject were included. The random forest model was used, where regression forests are an ensemble of different regression trees and are used for nonlinear multiple regression. The goal of using a large number of trees was to train enough that each feature had a chance to appear in several models. The data was randomly split into a training set (80%) and a test set (20%), and a regression tree was built with the training set and then validated using the test set. Bootstrapping was used to generate a collection of data sets (n=500). Importance was measured by leaving a covariate out of models and comparing performance with its inclusion. Result: The training set used to develop the ML algorithm comprised 749 patient-based observations, which represented ~50% of the patient-based observations. The number of observations at each M-Spike value and the distribution of M-Spike values measured by SPEP are shown (Fig. 1). The residual distribution of the RF model indicated that nearly all M-spike values determined using the 43 variables distributed equally on either side of zero. The addition of race as variables did not significantly change the residual plots. The weighted value of each of the 43 independent variables was determined by individually removing a variable from the ML algorithm and measuring its effect on the mean squared error (MSE). As shown, removal of the first lagged M-spike, serum total protein, second-lagged M-spike, serum IgG, serum IgM, and serum IgA, had the greatest effects on the ML algorithm. The effect of race was then added to the ML algorithm. However, patient race had a low weighted value compared to the other variables included in the ML algorithm (Fig-2). M-spike values determined using the ML algorithm correlated highly with M-spike values determined using the laboratory measured SPEP values as indicated by the proximity of the Pearson and Spearman correlation coefficients to +1 . Using the 43 independent variables, the Pearson coefficient was 0.96 and the Spearman coefficient was 0.91, when M-spike values determined using the ML algorithm were compared to laboratory determined M-spike values. When race was added as a variable in the ML algorithm, the Pearson coefficient was 0.95 and the Spearman coefficient was 0.94 which is not significantly different. Conclusion: Here, we present the results of our machine learning analysis, which further supports our hypothesis and sheds light on the potential racial difference in the overall systemic impact of MM. Understanding the factors underlying racial disparities in MM will pave the way for more personalized and equitable treatment strategies, ultimately improving patient outcomes and overall disease management.

HGF Regulation in the Tumor-Supportive Microenvironment Combined with Pan-PIM Kinases Inhibition in Malignant Cells As a Multi-Target Approach for Acute Myeloid Leukemia

Background: In acute myeloid leukemia (AML), persistent clonal proliferation of malignant myeloid cells results in high severity and low cure potential. Resistance to currently available chemotherapeutics and disease relapse remains an important concern worldwide. Several molecular targets play key roles in impairing therapeutic response, including PIM-kinases, a serine/threonine kinase family associated with the progression of hepatocyte growth factor (HGF)-driven cancers through its receptor, MET. We reported that enhanced HGF secretion by bone marrow (BM) mesenchymal stromal cells (MSC) correlated with low levels of the serine protease inhibitor kunitz-type2 (SPINT2) in AML (Roversi et al., 2019), which are affected by immunosuppressive properties of the tumor microenvironment (TME). However, the interplay between SPINT2, HGF, and PIM-kinases in the TME is yet to be elucidated and could represent an important multi-target therapeutic strategy in hematological cancers. Aims: Given the importance of HGF to AML prognosis and progression, we analyzed the interplay between SPINT2, HGF, and pan-PIM kinases by evaluating the gene expression and the effects of a novel pan-PIM kinase inhibitor, PIM447 (Novartis), in leukemia cells and in the TME. Methods: SPINT2, HGF, PIM1, PIM2 and PIM3 mRNA expression data were obtained from OHSU (2018) AML study and TCGA (cBio Portal). Correlation analysis was obtained by Spearman's coefficient (r). A total of 5 healthy donors (HD) and 5 de novo AML patients BMMSC (CD90+CD105+CD73+CD45-CD34-CD31-HLA-DR-) were treated with 5-Azacitidine (Aza), and evaluated for SPINT2 gene expressions. Myeloid (OCI-AML3, MOLM13, U937) and lymphoblastic (RS4;11, Jurkat) leukemia cells were treated with increasing concentrations of PIM447, and the 101nd apoptosis rates were determined. Peripheral blood and BM mononuclear cells (PBMC/BMMC) from HD were tested for cytotoxicity. Leukemia cells were also examined for reactive oxygen species (ROS), nitric oxide (NO) production, and mitochondrial membrane potential (ΔΨm). To verify PIM447 action onto an immunosuppressive TME, cocultures of leukemia cells and monocytes or monocyte-derived macrophages (MDMs) were performed. To understand the interplay between SPINT2 and PIM-kinases, cocultures of SPINT2-overexpressed MSC and leukemia cells, were performed. Statistical analyzes were performed using Kruskal Wallis, ANOVA or Mann-Whitney tests ( P&amp;lt;.05). Results: The analysis of gene expression performed in MC from 188 AML patients (age median: 57.5 years [range: 18-88]) showed that levels of HGF correlated positively with PIM1, PIM2, and PIM3 ((r) =.8727;.9094;.9093, respectively, P&amp;lt;.0001) and negatively with SPINT2 (r=-.06402). We also verified that SPINT2 mRNA expression was upregulated in AML-BMMSC ( P&amp;lt;.05) after Aza treatment when compared to HD-BMMSC, suggesting that this gene is methylated in AML. Our in vitro results showed PIM447 treatment (2-20μM) yielded reduced cell viability and increased apoptosis in leukemia cells [IC50 range: 12.2-22.2μM, P&amp;lt;.01] without affecting HD cells. PIM447 reduced ROS, NO production, and ΔΨm (all P&amp;lt;.0001) in all cell lines. PIM447 treatment of macrophages differentiated from HD-PBMC revealed a shorter population of M2 macrophages (HLA-DR-CD206+) ( P&amp;lt;.001) and an increased population of M1 macrophages (HLA-DR+CD80+) ( P&amp;lt;.05). Moreover, PIM447 promoted apoptosis of leukemia cells co-cultured with MDMs ( P&amp;lt;.0001). Interestingly, co-culture analyses of SPINT2-overexpressed MSC enhanced PIM447 cytotoxic activity towards leukemia cells (P&amp;lt;.05) and reduced cell-cell adhesion by diminishing CD49b, CD49d, and CD49e (P&amp;lt;.05), suggesting an interplay between SPINT2 and pan-PIM kinases Conclusion: Collectively, our data identify a novel pan-PIM kinase inhibitor, PIM447, which effectively induces leukemia cell apoptosis through reducing MET receptor activation as well as acts on their tumor-supportive microenvironment by inducing a phenotypic shift from immunosuppressive M2 to anti-tumor M1 macrophages. PIM447 also interplays with SPINT2/HGF pathway in the TME, reducing AML progression. These findings suggest that a pivotal strategy to treat AML could be a multi-target therapy, acting both on leukemia cells and in the tumor microenvironment. Funding: FAPESP #2017/21801-2, #2019/25247-5, #2021/05320-0; CNPq #303405/2018-0.

A study of macroinvertebrate communities in Bolshiye Koty Bay of Lake Baikal using DNA metabarcoding.

The diversity of macroinvertebrates, the structure of their communities in Bolshiye Koty Bay (Lake Baikal) was studied by a DNA metabarcoding approach using an Illumina MiSeq system. Internal primer mlCOIintF in combination with jgHCO2198 of the Folmer fragment of the COI gene were used for macroinvertebrate metabarcoding. A total of 118009 reads of the COI gene fragment (at least 313 bp in length) were obtained. The correlation of the Spearman coefficient (S = 0.6, p<0.05) with the abundance of macroinvertebrates in the samples before DNA extraction showed that the number of reads can serve as an indirect characteristic of the abundance of a species (operational taxonomic unit, OTU). 115 OTUs belonging to the higher taxa of macroinvertebrates were identified: Porifera, 1; Platyhelminthes, 3; Annelida, 38; Arthropoda, 55; Mollusca, 18. At a high level of resolution (with homology with GenBank reference sequences ≥ 95 %, coverage ≥ 90 %), 46 taxa of macroinvertebrates comprising three communities were registered: one dominated by molluscs (Choanomphalus conf. maacki) and two dominated by chironomids (Orthocladius gregarius Linev., Sergentia baicalensis Tshern.). Communities are characterized by low species diversity according to Shannon (from 0.7 to 1.2 bits), high concentration of dominance according to Simpson (from 0.5 to 0.7) and low evenness according to Pielou (from 0.3 to 0.4). Dominants and subdominants in the communities account for 91 to 96 % of COI gene fragment reads. The spatial distribution of the dominant species identified in the communities is influenced by the geomorphological features of the bottom and the composition of sediments in the area studied. The approach proposed for studying the structure of macroinvertebrate communities based on DNA metabarcoding and next generation sequencing can be recommended for express assessment of the state of aquatic ecosystems in the monitoring.

Otosclerosis online: a critical analysis of quality, reliability, readability and content of otosclerosis information.

Several therapeutic options are usually discussed for otosclerosis management. Patients seek medical advice from an ENT specialist but are also increasingly using the internet for medical issues. This study intends to assess readability and quality of websites with information on otosclerosis. This is a cross-sectional study performed in a tertiary care centre. The results of the first two pages of a Google search with the keyword "otosclerosis" were reviewed by two independent investigators. Readability was assessed with the Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES) and Gunning Fog Index. For quality and reliability assessment, the 16-item DISCERN instrument was used. Spearman's coefficient was used for correlations, and multivariate analyses of variance were used to assess differences. Inter-rater agreement was evaluated with concordance correlation coefficient. 18 websites were included. Two websites (11.0%) were authored by academic institutions, 5/18 (28%) by government agencies, 6/18 (33%) by professional organisations and 5/18 (28%) were medical information websites. The mean DISCERN score of the 18 websites was 40.8 ± 6.7/80 (range 28.7-51.7), corresponding to "fair" quality. The mean FRES score was 43.27 ± 10.6, and the mean FKGL was 11.43 ± 2.30, corresponding to "difficult to read". The mean Gunning Fog index was 12.90 ± 2.19 (range 9.81-18.20), corresponding to a "college freshman" level. This study shows that internet information on otosclerosis has an overall low readability, while the quality is heterogeneous and varies from "poor" to "good". Efforts should be made to improve the readability of otosclerosis websites.