Identification Of Individuals Research Articles

Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning.

Early identification of high-risk individuals for weight problems in children and adolescents is crucial for implementing timely preventive measures. While machine learning (ML) techniques have shown promise in addressing this complex challenge with high-dimensional data, feature selection is vital for identifying the key predictors that can facilitate effective and targeted interventions. This study aims to utilize feature selection process to identify a robust and minimal set of predictors that can aid in the early prediction of short- and long-term weight problems in children and adolescents. We utilized demographic, physical, and psychological wellbeing predictors to model weight status (normal, underweight, overweight, and obese) for 1-, 3-, and 5-year periods. To select the most influential features, we employed four feature selection methods: (1) Chi-Square test; (2) Information Gain; (3) Random Forest; (4) eXtreme Gradient Boosting (XGBoost) with six ML approaches. The stability of the feature selection methods was assessed by Jaccard's index, Spearman's rank correlation and Pearson's correlation. Model evaluation was performed by various accuracy metrics. With 3,862,820 million student-visits were included in this population-based study, the mean age of 11.6 (SD = 3.64) for the training set and 10.8 years (SD = 3.50) for the temporal test set. From the initial set of 38 predictors, we identified 6, 9, and 13 features for 1-, 3-, and 5-year predictions, respectively, by the best performed feature selection method of Chi-Square test in XGBoost models. These feature sets demonstrated excellent stability and achieved prediction accuracies of 0.82, 0.73, and 0.70; macro-AUCs of 0.94, 0.86, and 0.83; micro-AUCs of 0.96, 0.93, and 0.92 for different prediction windows, respectively. Weight, height, sex, total score of self-esteem, and age were consistently the most influential predictors across all prediction windows. Additionally, several psychological and social wellbeing predictors showed relatively high importance in long-term weight status prediction. We demonstrate the potential of ML in identifying key predictors of weight status in children and adolescents. While traditional anthropometric measures remain important, psychological and social wellbeing factors also emerge as crucial predictors, potentially informing targeted interventions to address childhood and adolescence weight problems.

The relationship between remnant cholesterol and the risk of testosterone deficiency in US adults: a cross-sectional study based on the NHANES database.

Testosterone deficiency (TD) is an urgent health issue that requires attention, associated with various adverse health outcomes including cardiovascular diseases (CVD) and metabolic syndrome. Remnant cholesterol (RC) has emerged as a potential biomarker for cardiovascular risk, but its relationship with testosterone levels and TD has not been thoroughly investigated. This study aims to explore the association between RC and TD in adult American males using data from the National Health and Nutrition Examination Survey (NHANES). This cross-sectional study utilized data from three NHANES cycles (2011-2016), including 2,848 adult male participants. RC was calculated as total cholesterol minus high-density lipoprotein cholesterol (HDL) and low-density lipoprotein cholesterol (LDL). TD was defined as total testosterone levels below 300 ng/dL. Multivariable linear and logistic regression analyses, as well as smooth curve fitting and generalized additive models, were performed to assess the associations between RC and total testosterone levels and TD, adjusting for potential confounders. Subgroup analyses were conducted based on age, BMI, smoking status, diabetes, hypertension, CVD, and chronic kidney disease (CKD). Higher RC levels were significantly associated with lower total testosterone levels (β = -53.87, 95% CI: -77.69 to -30.06, p<0.001) and an increased risk of TD (OR = 1.85, 95% CI: 1.29 to 2.66, p=0.002) in fully adjusted models. When RC was analyzed as quartiles, participants in the highest quartile (Q4) had significantly lower total testosterone levels (β = -62.19, 95% CI: -93.62 to -30.76, p<0.001) and higher odds of TD (OR = 2.15, 95% CI: 1.21 to 3.84, p=0.01) compared to those in the lowest quartile (Q1). Subgroup analyses revealed consistent associations across different age groups, particularly strong in participants over 60 years, and in never smokers. The associations remained significant in both hypertensive and non-hypertensive groups, as well as in those with and without CKD. No significant interactions were found across subgroups. This study demonstrates a significant inverse association between RC levels and total testosterone levels, along with a positive association with the risk of TD. These findings suggest that RC could serve as a valuable biomarker for early identification of individuals at risk for TD. Future longitudinal studies are needed to confirm these findings and explore the underlying mechanisms.

A Soul Laid Bare by Trauma

During treatment, most patients share their traumatic experiences, which can be a precipitating factor in the development of various psychiatric disorders. In numerous studies, traumatic experience has been highlighted as a possible etiological factor in the development of different personality disorders. Traumatic experiences in developmental stages of personality can result in disturbances in the ability to maintain feelings of security and individual identity in adulthood. Therefore, it is not difficult to imagine the dimension of trauma's impact on overall personality sensitivity and the inability to achieve individuation, separation, and overall personality cohesion. The most prevalent studies on the traumatic impact on personality development are related to borderline personality disorder (BPD). They point to the existence of a combination of genetic and environmental factors in the development of BPD, particularly the combination of biological vulnerability and exposure to traumatic experiences during childhood. Developing preventive programs and initiating psychotherapy in a timely manner, along with the use of contemporary pharmacotherapeutic treatment algorithms, can protect individuals at high risk of developing disorders or minimize disorder symptoms later in the lives of those affected.

Abstract C150: Evaluating breast cancer risk by race and ethnicity using the Tyrer Cuzick and Gail models in the Komen Tissue Bank cohort

Abstract Introduction: Breast cancer is the second leading cause of cancer death in women after lung cancer in the United States. While early detection is critical to reducing morbidity and mortality, predication of individualized risk is important in prevention and could also reduce unnecessary costs related to screening. The Susan G. Komen Tissue Bank (KTB) at Indiana University is the only tissue bank in the world that provides breast tissue specimens donated by healthy individuals to further to breast cancer research; however, as donors are volunteers, it is not clear how representative they are with respect to breast cancer risk compared to the general population. Methods: In this study, we calculated Breast Cancer Risk Assessment scores using Tyrer Cuzick (TCZ) and the Breast Cancer Risk Assessment Tool (The Gail Model, GM) in the KTB cohort by race and ethnicity. Recruited between 2007 and 2023, the participants completed a questionnaire encompassing their demographics, personal health and reproductive history, family history, and modifiable risk factors like smoking and alcohol use. In both models, participants with a lifetime risk of breast cancer of more than 15% were classified as having higher than average risk, while those with a risk of less than 15% were classified as having an average risk. Data analysis was performed using SAS v.9.4 software. Statistical significance was determined by p-values &amp;lt;0.05. Results: Out of 5118 participants, 206 with prior breast cancer and 37 male donors were excluded, resulting in a final sample of 4875 participants (aged 18–90) for analysis. The cohort was predominantly non-Hispanic white (NHW, 69.73%), followed by non-Hispanic black (NHB, 16.7%), Hispanic (8. 6%), and Asian individuals (3.3%), with 1.8% reporting multiracial or other race. The GM consistently categorized fewer women as having higher than average risk compared to the TZM. Across both TCZ and GM, the percentages of individuals classified as higher than average risk was greatest for NHW women, with 29.2% being categorized as higher than average risk in the TCZ, compared to 21.0% in the GM. The greatest discordance between the models was seen in NHB women, with the TCZ estimating 25.2% were at greater than average risk, and the GM only reporting 3.7% to be at greater than average risk. Overall, risk assessment scores varied across racial and ethnic groups (p- value&amp;lt;0.001). Factors driving these differences will be presented in additional analyses. Conclusion: There are known limitations in breast cancer risk assessment models by race and ethnicity that were confirmed in the women who comprise the KTB cohort. Donors to the KTB are generally representative of the US population with respect to breast cancer risk. As the KTB cohort continues to grow and mature, it can be utilized to assess breast cancer risk models for various racial and ethnic groups to assist in the identification of high-risk individuals that may benefit from prevention strategies and targeted screening. Citation Format: Vidya Patil, Michele L. Cote, Jenny Cui. Evaluating breast cancer risk by race and ethnicity using the Tyrer Cuzick and Gail models in the Komen Tissue Bank cohort [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C150.

Abstract A138: Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system

Abstract Three percent of cancers are due to inherited cancer-predisposing syndromes, the most common ones being Hereditary Breast and Ovarian cancer syndrome and Lynch syndrome. Surveillance and preventive measures among diagnosed individuals lead to early detection, prevention of future cancers, and appropriate treatment modalities ultimately resulting in lower cancer mortality. Thus, identifying these individuals through genetic testing is of most importance. While guidelines have been drafted to identify people who need to be ruled out based on personal and family history of cancer, less than 30% of qualifying individuals are currently tested and these numbers are much worse among underserved communities. Lack of awareness, largely due to guideline complexity, has been documented as a critical factor for the low testing rates while clinician’s unconscious bias contributes to disparities. The objective of this project was to increase the identification of individuals at risk, especially among the underserved groups. We hypothesized that this could be accomplished by establishing a mechanism of automatic identification of candidates leveraging the electronic health records (EHR), the ARCAGEN-ID (At-Risk Cancer Genetic Syndrome Identification) system. Methods: An inclusion logic was designed based on 218 rules that evaluate personal and family history of specific cancers and age at diagnosis, relevant to NCCN/ACMG guidelines for genetic testing. Structured data was pulled from discrete fields in the EHR. External data was accessed by enabling the standard interoperability exchange of information system. The system was applied to the wellness registry, a cohort of 1,357,337 patients with an active EHR in our healthcare system. Results: The ARCAGEN-ID system identified 57,628 individuals at-risk (4.25%). Of those, 45,646 (79.2%) had no evidence of prior genetic test, cancer genetics evaluation, or referral. A manual chart review of 559 cases showed an identification accuracy rate of 96.2%. The ARCAGEN-ID identified a lower proportion of self-reported African Americans, Hispanics and Medicaid insured patients than the overall wellness registry (likely reflecting less complete relevant information in the EHR). However, patients in those categories were significantly overrepresented among the ones who were not previously referred for genetic testing. Thus, ARCAGEN-ID significantly increased the identification of individuals from minority groups by 12.7 to 23% in each category. Regarding criteria for inclusion, individuals identified only through ARCAGEN-ID were more likely identified because of family history of cancer only, representing 80.69%. In conclusion, a fully automated system that leverages the EHR was able to multiply by 5 the number of individuals who need to be ruled out for an inherited cancer syndrome while addressing the bias against underserved communities seen under current routine care. Citation Format: Rosa Munoz Xicola, Vinit Singh, Thomas Rafter, Jing Liu, Quiana Brown, Nitu Kashyap, Xavier Llor. Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A138.

Nuclear magnetic resonance-based metabolomics with machine learning for predicting progression from prediabetes to diabetes.

Identification of individuals with prediabetes who are at high risk of developing diabetes allows for precise interventions. We aimed to determine the role of nuclear magnetic resonance (NMR)-based metabolomic signature in predicting the progression from prediabetes to diabetes. This prospective study included 13,489 participants with prediabetes who had metabolomic data from the UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models were performed to estimate the associations between metabolites and diabetes risk. Supporting vector machine, random forest, and extreme gradient boosting were used to select the optimal metabolite panel for prediction. CPH and random survival forest (RSF) models were utilized to validate the predictive ability of the metabolites. During a median follow-up of 13.6 years, 2525 participants developed diabetes. After adjusting for covariates, 94 of 168 metabolites were associated with risk of progression to diabetes. A panel of nine metabolites, selected by all three machine-learning algorithms, was found to significantly improve diabetes risk prediction beyond conventional risk factors in the CPH model (area under the receiver-operating characteristic curve, 1 year: 0.823 for risk factors + metabolites vs 0.759 for risk factors, 5 years: 0.830 vs 0.798, 10 years: 0.801 vs 0.776, all p < 0.05). Similar results were observed from the RSF model. Categorization of participants according to the predicted value thresholds revealed distinct cumulative risk of diabetes. Our study lends support for use of the metabolite markers to help determine individuals with prediabetes who are at high risk of progressing to diabetes and inform targeted and efficient interventions. Shanghai Municipal Health Commission (2022XD017). Innovative Research Team of High-level Local Universities in Shanghai (SHSMU-ZDCX20212501). Shanghai Municipal Human Resources and Social Security Bureau (2020074). Clinical Research Plan of Shanghai Hospital Development Center (SHDC2020CR4006). Science and Technology Commission of Shanghai Municipality (22015810500).

Cerebrospinal fluid lactate levels as a prognostic indicator in HIV-negative patients with cryptococcal meningitis: a retrospective cohort study

Abstract Background Cryptococcal meningitis (CM) is a severe central nervous system infection. In patients with human immunodeficiency virus (HIV) infections and coexisting CM, elevated baseline cerebrospinal fluid (CSF) lactate levels can predict increased mortality. However, the CSF lactate level’s significance in HIV-negative patients with CM remains unclear, necessitating further investigation to elucidate the potential distinctions and enhance patient management. This study investigated the CSF lactate level significance in HIV-negative patients with CM. Methods This retrospective study utilized data from the clinical databases of patients who underwent lumbar punctures at a medical center in Kaohsiung City, Southern Taiwan. Demographic data, CSF lactate levels, routine CSF analyses, and hematological and neurological findings were evaluated. The optimal CSF lactate threshold value was determined using the Youden index. Results This retrospective study included 70 patients with CM, among whom 44 (63%) and 26 (37%) tested negative and positive for HIV, respectively. The group without HIV exhibited higher CSF lactate levels, with an optimal CSF lactate cut-off point for predicting 90-day mortality of 7.935 mmol/L, resulting in significant predictive accuracies (area under the curve, 0.755; sensitivity, 57.1%; specificity, 100%); this value was an independent mortality predictor in HIV-negative patients. In HIV-negative patients with CM, CSF lactate levels ≥7.935 mmol/L correlated with higher mortality rates but without statistical significance. All HIV-negative patients with CM and CSF lactate levels ≥7.935 mmol/L died within 3 months of admission. Conclusions HIV-negative patients with CM had elevated CSF lactate levels that correlated with adverse outcomes, enabling early identification of high-risk individuals.

THE PHENOMENON OF RESENTMENT IN CULTURE: NIETZSCHE, SCHELER, FUKUYAMA

The article delves into the concept of ressentiment within the context of phenomenology and its profound impact on the formation of moral values and socio-cultural dynamics. Drawing on the ideas of Max Scheler, which are partially rooted in Friedrich Nietzsche's philosophy and extended through Francis Fukuyama’s works, the paper explores how ressentiment serves as a critical factor in transforming various spheres of human social activity. The article identifies ressentiment as a driving force behind the crisis of humanistic ideals and examineі its pervasive effect on contemporary values. It emphasizes the importance of understanding this phenomenon in shaping socio-cultural dynamics, particularly in relation to moral-legal perceptions and the collective shifts in society’s values. By examining the internal conflict experienced by individuals influenced by ressentiment, the article sheds light on its role in moral conflicts and social tensions. Furthermore, the work underscores the relevance of Scheler’s phenomenology and Fukuyama’s exploration of identity politics in addressing the challenges posed by ressentiment. It highlights the need to grasp ressentiment not merely as a sociological phenomenon but as a complex psychological experience with deep social implications. The study also opens avenues for future research into how ressentiment influences modern political ideologies and cultural narratives, impacting both individual identities and collective consciousness. Additionally, the article discusses the implications of ressentiment in the digital age, where social media amplifies these sentiments, further polarizing societies and intensifying identity-based conflicts. By providing a focused and nuanced analysis of ressentiment, the article emphasizes its significance in the evolution and transformation of cultural and moral values in the modern world, making it a crucial topic for ongoing philosophical inquiry. This exploration is essential for understanding the roots of contemporary societal divisions and offers insights into potential pathways for addressing these deep-seated issues.

Association between estimated glucose disposal rate and cardiovascular mortality across the spectrum of glucose tolerance in the US population.

To determine if estimated glucose disposal rate (eGDR) can predict cardiovascular disease mortality risk at different levels of glycaemic tolerance. The eGDR levels of 11 656 individuals aged 45-79 years from the National Health and Nutrition Examination Survey cycles 1999 to 2010 were analysed. Associations between eGDR levels and all-cause and cardiovascular mortality were examined using Cox proportional hazards and Fine and Gray models, respectively. After a median follow-up of 12.8 years, a total of 2852 participants died, with 777 of those deaths attributed to cardiovascular causes. When comparing participants with eGDR values of ≤4 mg/kg/min to those with eGDR values falling within the ranges of 4-6, 6-8 and >8 mg/kg/min, it was found that the latter groups exhibited lower hazard ratios for both all-cause mortality (0.61 [0.52-0.72], 0.61 [0.52-0.72] and 0.46 [0.39-0.55]) and cardiovascular mortality (0.44 [0.33-0.57], 0.45 [0.34-0.59] and 0.30 [0.23-0.40]). A U-shaped relationship between eGDR and all-cause mortality was observed, with an inflection point at an eGDR of 9.54 mg/kg/min. In the general population, the association between reduced eGDR and all-cause and cardiovascular mortality was independently significant, contributing to the identification of individuals at high risk for different levels of glucose tolerances.

Analysing the pedigree to identify undesirable losses of genetic diversity and to prioritize management decisions in captive breeding: a case study.

When prevention of species extinction is the priority, captive breeding is a key component in conservation programmes, allowing the recording of pedigree information in studbooks. The genealogical information registered in Cuvier's gazelle studbook between 1975 and 2023 was analysed to (a) assess if the implemented mating policy was successful in preserving the genetic background of the founders (1 male:3 females) in the present population, and b) improve future management and breeding decisions. Although the maternal contribution of one founder female was lost and the mean inbreeding of the total live population was high (0.305 ± 0.095), the breeding policy applied produced better results than expected from a population starting from four founders. It was successful in keeping the individual increase in inbreeding low (0.047 ± 0.021), and, notably, the inbreeding tended to decrease during the last three decades of the breeding programme, ensuring the viability of this highly inbred population. Historical dissemination of individuals among the zoos of Europe and North America caused population structuring and genetic differentiation of the live North American population. However, it did not risk the viability of the captive population. The average relatedness coefficients allowed the identification of individuals with underrepresented genotypes, which is relevant to plan future mating guidelines to keep the founders' representation balanced in the next generations. This study highlights the importance of keeping long-term pedigree information to monitor changes in the genetic diversity of captive populations, which is crucial to implement optimal mating decisions and assuring their long-term viability within an ex situ conservation programme.

Agama dan Identitas Sosial Dalam Praktek Pembelajaran Hadis di Langgar di Kabupaten Malang Jawa Timur

Abstract: This study examines the role of religion in shaping social identity through Hadith learning in the violations of Malang Regency, East Java. This study analyses how the teaching of Hadith in these places of worship affects individuals' perceptions of themselves and their communities. The research methodology involves in-depth interviews with teachers and pilgrims and content analysis of the learning materials used. The results of this study revealed that the practice of Hadith learning in Malang Regency has a significant role in shaping individual social identity. This manifests itself in the influence of religion on social norms, values, and community solidarity. The research also highlights the critical role of teachers in conveying religious messages and how these messages influence individual understanding and identity. This research provides in-depth insights into the complexity of the relationship between religion and social identity in the context of local communities. These findings may contribute to a better understanding of the role of religion in shaping social identity and guide learning efforts, as well as a better understanding of religion in diverse societies. Keywords: Religion, Social Identity, Hadith Learning, Langgar, East Java

The Dangers of (Masculine) Storytelling: Gender and Memory in Puig’s Sangre de amor correspondido

Drawing from the field of Cultural Memory Studies, this article examines the process of recollection as depicted in Sangre de amor correspondido (Seix Barral, 1982) by Manuel Puig (1932–1990). Within this novel, we witness the portrayal of memory processes through the eyes of Josemar, a marginalized construction worker from a small rural town in Brazil. The protagonist endeavors to narrate his life experiences through the lens of idealized hegemonic masculinity. Some scholars think that gender represents a fundamental facet of identity. Furthermore, identity emerges from introspective processes driven by memory. Consequently, this paper asserts that the integration and signifying of masculine prostheses hinge upon the articulation and solidification of a self-narrative rooted in “masculinity’s social frameworks of memory.” Through narration, hegemonic masculinity assumes a foundational role within individual identity; simultaneously, it disseminates the patterns—these social frameworks of memory—used for the interpretation and organization of life experiences as recollections.

Dynamic visualization level 3 details of latent fingerprints by fluorescence imaging and photoluminescent macromolecules functionalized with spiropyran photoswitch

Detecting latent fingerprints (LFPs) poses a considerable challenge for individual identification in the case of the criminal scene because detecting more details about three levels of identification patterns at a fast rate and by conventional instruments is very important for investigators. This research involved creating nanoparticles made of a copolymer containing tertiary amine-functionalized methacrylate through emulsion copolymerization, and then modifying them with a spiropyran derivative. The concentration of tertiary amine groups significantly influenced the optical properties, with samples containing more than 10 wt% exhibiting negative photochromism, leading to the absence of dynamic emission and reversible photochromism. The study of the kinetics of isomerization from spiropyran to merocyanine using solid-state fluorescence spectroscopy highlighted the important role of negative photochromism in the photoswitching of spiropyran. The resulting dynamic photoluminescent polymer powders were effectively utilized for LFP visualization through powder dusting, fluorescence imaging, optical security tag production, and the development of innovative OLEDs. The study confirmed the efficiency of these polymer powders in visualizing LFPs, enabling the identification of intricate details and patterns at three distinct levels. The observed LFPs emitted fluorescence in a range of colors, displaying high contrast, resolution, maximum intensity, and brightness. Three levels of identification details were detected for an unknown LFP that remained on the surface of the glass bottle as a real sample in the criminal scene. Successful identification of the unknown offender indicates the potential application of samples for time-dependent visualization of LFPs in criminal scenes.

The Pangolin Universal Notching System: a scale-marking methodology for pangolins

Abstract Despite thousands of individuals entering the illegal wildlife trade each year, assessments of pangolin populations are largely non-existent, even in areas with high exploitation and limited personnel and field equipment. Although pangolins have unique keratin-based scales, there is no universal scale-marking method for individuals despite some pangolin conservation programmes utilizing marking for reference and cataloguing. Each programme currently establishes and manages its own system, resulting in inconsistencies and limiting data sharing. To facilitate pangolin monitoring and research, we developed a standardized method for assigning individual identification numbers, which we call the Pangolin Universal Notching System. This system is neither resource nor training intensive, which could facilitate its adoption and implementation globally. Its application could help to address knowledge gaps in pangolin ageing, reproduction, survivorship, migration and local trafficking patterns, and could be used in combination with other tagging techniques for research on pangolin biology.

CREATION OF A SKIN MODEL FOR CALCULATING OPTICAL RADIATION PROPAGATION IN BIOMETRIC IDENTIFICATION SYSTEMS BASED ON THE VENOUS PATTERN OF THE PALM

Introduction. Palm vein biometric identification systems are important for establishments that require accurate identification of individuals. These systems differ in their operation and structure, and developing and setting up a prototype to test the visibility of the venous pattern is time-consuming and resource-intensive, so it is advisable to conduct computer simulations of the passage of infrared radiation through the skin of the palm.

Analysis of non-metric dental traits for ethnicity identification in a mixed population of Uttar Pradesh

BackgroundForensic odontology involves the identification of individuals through dental records, making it a crucial tool in legal investigations. Non-metric dental traits (NMDT), which are variations in dental morphology play a key role as these traits are inherited characteristics that can help establish biological relationships or ancestry. Thus, we aim to assess the frequency and variability of NMDT in the human dentition of four ethnically mixed populations in Uttar Pradesh. This study can aid in the future by maintaining records of ethnic groups and their variability, which can be crucial for disaster victim management and forensic odontology. MethodsThe study was conducted on a total of 100 patients coming to the OPD of Oral Medicine and Oral Pathology and Microbiology of King George's Medical University from January 2022 to July 2023. Impressions of both arches were made for participants using irreversible hydrocolloid (alginate), and casts were examined under a stereomicroscope to assess 15 different morphological characteristics. ResultsNMDTs such as winging, shoveling, double-shoveling interruption groove, canine mesial ridge, hypocone, metacone, carabelli's trait, peg-shaped incisors, peg-shaped molar, premolar lingual cusp variation, deflecting wrinkle, protostylid, metaconulid, entoconulid was evaluated. The NMDTS were evaluated in four different ethnics Nordics, Mediterranean, Oriental Mediterranean, and Protoaustraloid amongst which various traits showed a statistically significant variation among the population of Uttar Pradesh. ConclusionThe sample studied presented confirmed supernumerary traits like metacone, protostylid, carabellis trait, metaconulid, premolar lingual cusp variation, and deflecting wrinkle were seen highest in Nordic, Mediterranean, Oriental Mediterranean, and Protoaustraloid ethnicity have a significant association with the Uttar Pradesh population.

Predicting prognosis for epithelial ovarian cancer patients receiving bevacizumab treatment with CT-based deep learning

Epithelial ovarian cancer (EOC) presents considerable difficulties in prognostication and treatment strategy development. Bevacizumab, an anti-angiogenic medication, has demonstrated potential in enhancing progression-free survival (PFS) in EOC patients. Nevertheless, the identification of individuals at elevated risk of disease progression following treatment remains a challenging task. This study was to develop and validate a deep learning (DL) model using retrospectively collected computed tomography (CT) plain scans of inoperable and recurrent EOC patients receiving bevacizumab treatment diagnosed between January 2013 and January 2024. A total of 525 patients from three different institutions were retrospectively included in the study and divided into training set (N = 400), internal test set (N = 97) and external test set (N = 28). The model’s performance was evaluated using Harrell’s C-index. Patients were categorized into high-risk and low-risk group based on a predetermined cutoff in the training set. Additionally, a multimodal model was evaluated, incorporating the risk score generated by the DL model and the pretreatment level of carbohydrate antigen 125 as input variables. The Net Reclassification Improvement (NRI) metric quantified the reclassification performance of our optimal model in comparison to the International Federation of Gynecology and Obstetrics (FIGO) staging model. The results indicated that DL model achieved a PFS predictive C-index of 0.73 in the internal test set and a C-index of 0.61 in the external test set, along with hazard ratios of 34.24 in the training set (95% CI: 21.7, 54.1; P < 0.001) and 8.16 in the internal test set (95% CI: 2.5, 26.8; P < 0.001). The multimodal model demonstrated a C-index of 0.76 in the internal test set and a C-index of 0.64 in the external test set. Comparative analysis against FIGO staging revealed an NRI of 0.06 (P < 0.001) for the multimodal model. The model presents opportunities for prognostic assessment, treatment strategizing, and ongoing patient monitoring.

Causal relationship between circulating glutamine levels and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive and debilitating respiratory disease with a median survival of less than 5 years. In recent years, glutamine has been reported to be involved in the regulation of collagen deposition and cell proliferation in fibroblasts, thereby influencing the progression of IPF. However, the relationships between glutamine and the incidence, progression, and treatment response of IPF remain unclear. Our study aimed to investigate the relationship between circulating glutamine levels and IPF, as well as its potential as a therapeutic target.MethodsWe performed a comprehensive Mendelian Randomization (MR) analysis using the most recent genome-wide association study summary-level data. A total of 32 single nucleotide polymorphisms significantly correlated to glutamine levels were identified as instrumental variables. Eight MR analysis methods, including inverse variance weighted, MR-Egger, weighted median, weighted mode, constrained maximum likelihood, contamination mixture, robust adjusted profile score, and debiased inverse-variance weighted method, were used to assess the relationship between glutamine levels with IPF.ResultsThe inverse variance weighted analysis revealed a significant inverse correlation between glutamine levels and IPF risk (Odds Ratio = 0.750; 95% Confidence Interval : 0.592–0.951; P = 0.017). Sensitivity analyses, including MR-Egger regression and MR-PRESSO global test, confirmed the robustness of our findings, with no evidence of horizontal pleiotropy or heterogeneity.ConclusionOur study provides novel evidence for a causal relationship between lower circulating glutamine levels and increased risk of IPF. This finding may contribute to the early identification of high-risk individuals for IPF, disease monitoring, and development of targeted therapeutic strategies.

Prospects of Artificial Intelligence in the Annihilation of Caste

The masquerading effect of caste has engulfed the social structure in such a way that the myth associated with it has perked up in the ideas of existence, making it a reality regulating day-to-day affairs of interaction. Most of the time, it is considered a functional prerequisite. The stratification associated with it has conformity emanating from the acceptance of the identity, which is not evading even after migrating to foreign countries to participate and be part of the capitalist mode of production. Artificial Intelligence (AI) is a creation of the human mind. Caste is also a creation of the human mind. Technology has always paved the way for the betterment of society if used properly. Caste practices have always divided society and contaminated the public sphere with divisive manifestations of their stronghold in influencing social processes and policies. Annihilation of caste was the published work of Dr B. R. Ambedkar in the year 1936, and still the content and the context are seen in society. In the backdrop of this, the article engages with the role (if any) of AI in mitigating the divisions in society. The readers are already aware of the repercussions of the caste system since time immemorial. The diffusion of technology has always been trying to be inclusive, depending on the socio-economic aspect of any society. Industrialization along with the Information and Communication Technology (ICT) revolution has rendered several avenues and opportunities for the so-called lower caste people to come forward and amalgamate themselves with the so-called upper caste people in the socio- economic process. The article discusses the prospect of the annihilation of caste by the influence of AI. It also engages in discussing caste as a main component of individual and community identity, which has become immune to any form of change in society. The article is based on available secondary sources.

Psychodrama as group intervention on minority stress, identity and psychosocial well-being of LGBTQ+ Italian young adults: A qualitative case study

ABSTRACT Background Growing attention is given to LGBTQ+ well-being, mainly using the minority stress model, although it’s seldom applied in group therapy research. This study aims to investigate individual experiences and identity processes related to minority stress while exploring the effectiveness of group psychodrama on LGBTQ+ well-being and stress levels. Methods Seven LGBTQ+ participants aged 19 to 27 years attended 10 weekly sessions of group psychodrama. The study utilized a qualitative exploratory case study design, where interview data underwent inductive thematic analysis and were triangulated with quantitative data concerning well-being, alexithymia, and LGBT Minority Stress. Results Participants manage their minority-contextualized identity and stigma within their narratives, indicating that group psychodrama may benefit young LGBTQ+ adults by raising awareness and resolving stressors. Conclusions The study validates the minority stress model but suggests broader theoretical integration, emphasizing the role of social identity and therapeutic impact of psychodrama in managing minority stress.