Health Indicators Research Articles

State of health estimation embedded with hardware accelerator based on long short-term memory combined with Bayesian optimization considering extracted health indicator in charging conditions

Recently, the importance of renewable energy has increased as fossil fuel use is regulated worldwide to protect the environment. Accordingly, the use of electric vehicles (EVs) that use a battery as a power source is increasing and estimating the battery state for an efficient and safe operation of EV is a very significant task. This study proposes a method to estimate the state-of-health (SOH) in which batteries are a major state indicator. A health indicator (HI) capable of determining the state of the battery is derived from the charging part by considering the stopping situation in which there is a slight variation in the battery characteristics of the EV. As an integrity indicator, the partial capacity according to the voltage range set by the user can be considered, and the correlation between the SOH and HI is analyzed for validity verification. To learn the derived HI, a long short-term memory (LSTM) model, a type of deep-neural network, is designed, and model tuning was performed through Bayesian optimization. The absolute error of SOH estimation for the proposed LSTM model is 1.1 %, compared and validated against recurrent neural network (RNN) (1.7 %) and gated recurrent unit (GRU) (1.85 %). After validating the performance of the LSTM algorithm, an analysis of SOH estimation error (1 %) based on LSTM was conducted following pack-level experiments to assess scalability. Finally, for evaluation of operation within a hardware accelerator (HA) for integration into EVs, NVIDIA Jetson Nano was utilized. Upon mounting the algorithm on Jetson Nano, the mean absolute error (MAE) was 0.6581, mean absolute percentage error (MAPE) was 0.7209, and root mean square error (RMSE) was 0.7133, demonstrating excellent estimation performance.

Laser-Induced Graphene-Based Fabry-Pérot Cavity Label-Free Immunosensors for the Quantification of Cortisol

There is a strong and growing need to monitor stress biomarkers in human beings and animals for real-time wellness assessment, which is a key indicator of health. Toward this, we report an optical fiber immunosensor based on laser-induced graphene (LIG) for the potential quantification and monitoring of cortisol hormone. The developed sensors were created using the Fabry-Pérot cavity principle. The cavities were filled with polyimide (PI) and, in some cases, PI mixed with gold nanoparticles. The interferometers were tested for temperature and refractive index, and an increase of two times in the sensitivity to the refractive index was observed due to the addition of the gold nanoparticles. In addition, the PI cavity was partially transformed into LIG using a CO2 20 kHz pulsed laser. The resulting LIG morphology was quite porous and presented a leafy texture. The presence of LIG creates a second cavity within the interferometer, and as a consequence, the spectral response of the interferometers resembled the Vernier effect. The refractive index behavior of the LIG-modified interferometers shows improvements in sensitivity up to 15.3 times due to the creation of the LIG cavity. The interferometers were then functionalized with anti-cortisol to promote an affinity for cortisol. Excellent sensitivities of up to -34.7±0.7 nm/log(ng/mL) were achieved within few ng/mL concentration ranges (within the 0.5 to 3 ng/mL). The results obtained show an increase of up to 50 times in sensitivity when compared with other cortisol sensors. The achieved limit of detection was 0.1 ng/mL for the proposed sensors. The sensors’ responses were also shown to be immune to the interference from substances such as glucose, sucrose, fructose, and ascorbic acid. This study lays the foundation for new cortisol biosensors demonstrating a great potential for detection in a simple and highly sensitive way, opening its path for relevant biomedical and environmental monitoring applications in real samples. As a future outline, selectivity studies employing the detection of cortisol in the presence of interfering agents, both using synthetic and real samples, will be accomplished in order to fully investigate the potential of these sensing tools in real-life scenarios.

Low Body Fat Percentage and Menstrual Cycle Disorders in Female Elite Adolescent Dancers.

Introduction: The menstrual cycle is an important indicator of health in female athletes. Female elite adolescent dancers are expected to control their weight while also training intensely, which can lead to menstrual disorders. This study aimed to investigate the relationship between body composition and menstrual status in female elite adolescent dancers. Methods: In total, 131 female elite adolescent dancers (age: 15.9 ± 1.5 years) were enrolled in this study. We measured the height, weight, and body fat percentage (BFP) for each participant and calculated their body mass index (BMI). We gathered information on individual menstruation patterns and the participants' menstrual cycles over the previous year using recall methods. We then compared the differences between dancers with menstrual cycle disorders and those without. Primary amenorrhea was defined as menarche occurring after the age of 15, while secondary amenorrhe was defined as experiencing fewer than 5 or no menstrual periods for at least 3 of the previous 12 months. We conducted a reliability test using the same questionnaire 2 weeks later. Statistical significance was defined as P < .05, and we calculated the effect sizes (d) and 95% confidence intervals (95% CI). Results: The average BMI and BFP were 22.6 ± 3.0% and 19.4 ± 2.2 kg/m2, respectively. Low BFP and low BMI were observed in 51 (38.6%) and 47 (35.6%) participants, respectively. Primary amenorrhea in 3 participants (2.3%) and 29 (22.1%) reported experiencing secondary amenorrhea; they had lower BFP than the dancers who did not experience amenorrhea (P = .041, 95% CI, -2.51 to -0.05). Conclusion: Female elite adolescent dancers in China may have lower BFP and menstrual problems. Given that lower BFP may contribute to the occurrence of menstruation disorders, it is essential to pay an attention to both BFP and the menstruation status in female elite adolescent dancers.

Monkeypox Virus (MPXV) Infection: A Review.

Monkeypox is a viral disease; its outbreak was recently declared a global emergency by the World Health Organization. For the first time, a monkeypox virus (MPXV)-infected patient was found in India. Various researchers back-to-back tried to find the solution to this health emergency just after COVID-19. In this review, we discuss the current outbreak status of India, its transmission, virulence factors, symptoms, treatment, and the preventive guidelines generated by the Indian Health Ministry. We found that monkeypox virus (MPXV) disease is different from smallpox, and the age group between 30-40 years old is more prone to MPXV disease. We also found that, besides homosexuals, gays, bisexuals, and non-vegetarians, it also affects normal straight men and women who have no history of travel. Close contact should be avoided from rats, monkeys and sick people who are affected by monkeypox. To date, there are no monkeypox drugs, but Tecovirimat is more effective than other drugs that are used for other viral diseases like smallpox. Therefore, we need to develop an effective antiviral agent against the virulence factor of MXPV.

Friedreich Ataxia Caregiver-Reported Health Index: Development of a Novel, Disease-Specific Caregiver-Reported Outcome Measure.

The Friedreich ataxia (FRDA) scientific community needs access to patient-centered outcome measures that satisfy regulatory guidelines and are capable of tracking clinically meaningful changes in FRDA disease burden. The objective of this research was to develop a novel, disease-specific caregiver-reported outcome measure for use in FRDA research and clinical care. In prior work, we conducted qualitative interviews and a cross-sectional study of FRDA caregivers and patients to determine the symptoms of greatest importance to individuals with FRDA. We designed the Friedreich Ataxia Caregiver-Reported Health Index (FACR-HI) to serially measure the symptoms of greatest importance to patients and utilized factor analysis, beta testing, reliability testing, and cross-sectional subgroup analysis to further evaluate and optimize this disease-specific outcome measure. The FACR-HI was designed to measure total disease burden and disease burden in 18 symptomatic domains. The FACR-HI total score demonstrated high internal consistency (Cronbach's α = 0.98) and test-retest reliability (intraclass correlation coefficient = 0.96). Beta interview participants found the FACR-HI to be highly relevant, comprehensive, and easy to use. FACR-HI total and subscale scores were associated with functional staging for ataxia scores and speech impairment. Initial evaluation of the FACR-HI supports its content validity, test-retest reliability, and construct validity as a caregiver-reported outcome measure for assessing how pediatric individuals with FRDA feel and function. The FACR-HI provides a potential mechanism to quantify changes in multifactorial FRDA disease burden during future clinical trials.

A cohort study of the multipollutant effects of PM2.5, NO2, and O3 on C-reactive protein levels during pregnancy.

PM2.5, NO2, and O3 contribute to the development of adverse pregnancy complications. While studies have investigated the independent effects of these exposures, literature on their combined effects is limited. Our objective was to study the multipollutant effects of PM2.5, NO2, and O3 on maternal systemic C-reactive protein (CRP) levels. We used data from 1170 pregnant women enrolled in the Maternal-Infant Research on Environmental Chemicals Study (MIREC) study in Canada. Air pollution exposures were assigned to each participant based on residential location. CRP was measured in third-trimester blood samples. We fit multipollutant linear regression models and evaluated the effects of air pollutant mixtures (14-day averages) using repeated-holdout Weighted Quantile Sum (WQS) regression and by calculating the Air Quality Health Index (AQHI). In multipollutant models adjusting for NO2, O3, and green space, each interquartile range (IQR) increase in 14-day average PM2.5 (IQR: 6.9 µg/m3) was associated with 27.1% (95% confidence interval [CI] = 6.2, 50.7) higher CRP. In air pollution mixture models adjusting for green space, each IQR increase in AQHI was associated with 37.7% (95% CI = 13.9, 66.5) higher CRP; and an IQR increase in the WQS index was associated with 78.6% (95% CI = 29.7, 146.0) higher CRP. PM2.5 has the strongest relationship of the individual pollutants examined with maternal blood CRP concentrations. Mixtures incorporating all three pollutants, assessed using the AQHI and WQS index, showed stronger relationships with CRP compared with individual pollutants and illustrate the importance of conducting multipollutant analyses.

Global maternal mortality projections by urban/rural location and education level: a simulation-based analysis

Maternal mortality remains a challenge in global health, with well-known disparities across countries. However, less is known about disparities in maternal health by subgroups within countries. The aim of this study is to estimate maternal health indicators for subgroups of women within each country. In this simulation-based analysis, we used the empirically calibrated Global Maternal Health (GMatH) microsimulation model to estimate a range of maternal health indicators by subgroup (urban/rural location and level of education) for 200 countries/territories from 1990 to 2050. Education levels were defined as low (less than primary), middle (less than secondary), and high (completed secondary or higher). The model simulates the reproductive lifecycle of each woman, accounting for individual-level factors such as family planning preferences, biological factors (e.g., anemia), and history of maternal complications, and how these factors vary by subgroup. We also estimated the impact of scaling up women's education on projected maternal health outcomes compared to clinical and health system-focused interventions. We find large subgroup differences in maternal health outcomes, with an estimated global maternal mortality ratio (MMR) in 2022 of 292 (95% UI 250-341) for rural women and 100 (95% UI 84-116) for urban women, and 536 (95% UI 450-594), 143 (95% UI 117-174), and 85 (95% UI 67-108) for low, middle, and high education levels, respectively. Ensuring all women complete secondary school is associated with a large impact on the projected global MMR in 2030 (97 [95% UI 76-120]) compared to current trends (167 [95% UI 142-188]), with especially large improvements in countries such as Afghanistan, Chad, Madagascar, Niger, and Yemen. Substantial subgroup disparities present a challenge for global maternal health and health equity. Outcomes are especially poor for rural women with low education, highlighting the need to ensure that policy interventions adequately address barriers to care in rural areas, and the importance of investing in social determinants of health, such as women's education, in addition to health system interventions to improve maternal health for all women. John D. and Catherine T. MacArthur Foundation, 10-97002-000-INP.

Unraveling the Determinants of Maternal Well-Being Among Tribal Populations of Kerala: A Systematic Review.

Despite Kerala's noteworthy achievements in health indices, the tribal population in the state continues to face significant challenges in achieving optimal health outcomes. This is particularly evident in the realm of maternal health, where tribal communities struggle. In light of this paradox, a systematic review was conducted to identify the factors influencing the quality of tribal maternal health and their determinants. A comprehensive search strategy was employed, utilizing computer-backed searches of eminent bibliographic databases, along with the exploration of additional cited references and hand-searching of relevant journals. The methodological quality of the selected studies was rigorously assessed through a transparent cataloguing system and analysis by reviewers, resulting in the inclusion of thirty studies following the filtering process. The selected studies were subjected to detailed analysis to identify the determinants of maternal health among tribal populations. Thematic analysis of thirty studies that met the inclusion criteria resulted in four sets of determinants that contribute to maternal health among tribal women; biological/demographic determinants, psychological determinants, social determinants, and cultural determinants. This review provides a comprehensive picture of tribal maternal health in Kerala, shedding light on their multifaceted challenges. The study provides a basis for the formulation of initiatives by addressing the broader determinants of health and accounting unique socio-cultural factors influencing well-being of tribal communities.

Whole Genome Linkage and Association Analyses Identify DLG Associated Protein-1 as a Novel Positional and Biological Candidate Gene for Muscle Strength: The Long Life Family Study.

Grip strength is a robust indicator of overall health, is moderately heritable, and predicts longevity in older adults. Using genome-wide linkage analysis, we identified a novel locus on chromosome 18p (mega-basepair region: 3.4 - 4.0) linked to grip strength in 3755 individuals from 582 families aged 64 ± 12 years (range 30-110 years; 55% women). There were 26 families that contributed to the linkage peak (cumulative logarithm of the odds [LOD] score = 10.94), with six families (119 individuals) accounting for most of the linkage signal (LOD = 6.4). In these 6 families, using whole genome sequencing data, we performed association analyses between the 7312 single nucleotide (SNVs) and insertion deletion (INDELs) variants in the linkage region and grip strength. Models were adjusted for age, age2, sex, height, field center, and population substructure. We found significant associations between genetic variants (8 SNVs and 4 INDELs, p<5*10-5) in the Disks Large-associated Protein 1 (DLGAP1) gene and grip strength. Haplotypes constructed using these variants explained up to 98.1% of the LOD score. Finally, RNAseq data showed that these variants were significantly associated with the expression of nearby Myosin Light Chain 12A (MYL12A), Structural Maintenance of Chromosomes Flexible Hinge Domain Containing 1 (SMCHD1), Erythrocyte Membrane Protein Band 4.1 Like 3 (EPB41L3) genes (p< .0004). The DLGAP1 gene plays an important role in the post-synaptic density of neurons; thus, it is both a novel positional and biological candidate gene for follow-up studies aimed at uncovering genetic determinants of muscle strength.

Effect of COVID-19 pandemic on bioimpedance health indicators in young adults.

Herein, we investigate the relationships between the COVID-19 pandemic and overcoming the virus, and its effects on body composition parameters in young adults from Slovakia. We assessed 773 adults aged 18 to 30 years in pandemic-status sub-groups. Individual lifestyles and overcoming the COVID-19 effects were evaluated by a detailed questionnaire, and body composition parameters were analyzed using the InBody 770 bioimpedance analyzer. Statistically significant lower values were observed in the male group during the pandemic for the following parameters; proteins and minerals, fat free mass (FFM), skeletal muscle mass (SMM), lean body mass (LBM) and its values in the right and left arm and trunk, total body water (TBW) and its values in the right and left arm and trunk, body cell mass (BCM), basal metabolic rate (BMR) and phase angle (PA). The regression analysis confirmed the negative pandemic effect and the negative impact of COVID-19 on men in the following parameters: proteins (p = .027 for pandemic and p = .005 for COVID-19), FFM (p = .023 for pandemic and p = .005 for COVID-19), LBM (p = .022 for pandemic and p = .004 for COVID-19), SMM (p = .028 for pandemic and p = .005 for COVID-19), TBW (p = .020 for pandemic and p = .004 for COVID-19), BMR (p = .024 for pandemic and p = .005 for COVID-19) and PA (p = .009 for pandemic). Physical activity was a further significant predictor in men for all the above parameters. We observed significantly lower body composition parameters associated with fat free mass in young adult men during the pandemic than before it. However, future research is warranted to determine if these effects have long-term significance.

Exploring Catalase Activity as A Biological Indicator in Degraded Soils

This study examines the relationship between catalase activity in degraded soils and soil properties, and addresses its potential as an indicator of soil health and productivity. Catalase, a key enzyme reflecting microbial activity and soil aeration, has been analyzed in 30 soil samples collected from the disturbed surface layer (0-15 cm depth) of erosion-prone areas characterized by rubble accumulation on hill slopes and soil compaction in foot slopes. The soil in the study area is classified as Typic Xerortent. Catalase enzyme activity in the soil samples varied between 10.4 and 48 µl O2 g-1 dry soil. In addition to catalase, the physicochemical properties of the soil were also assessed, including pH, electrical conductivity, organic matter content, and texture. Nutrient contents, including nitrogen (0.046-0.239 g N 100 g-1), phosphorus (1.77-20.05 µg P g-1), and potassium (0.01-3.31 meq K 100 g-1), were also measured. A positive correlation was observed between catalase activity and potassium and phosphorus levels, but the relationship with nitrogen was statistically insignificant. These findings suggest that catalase activity can serve as a biological indicator for the early detection of degradation in soils at risk of erosion. The study provides valuable insights into the impact of erosion on soil biochemistry and highlights the role of catalase in assessing soil health and guiding sustainable land management practices.

A Systematic Review of Global Marine Mammal Rehabilitation and Refloating, 2000–2023

Rehabilitation of marine mammals is performed throughout the world, yet the impact of rehabilitation on individuals and populations is questionable given the lack of robust information on the rehabilitation process and post-release monitoring in most cases. The goals of this study were to perform a systematic review of existing literature on marine mammal rehabilitation between 2000–2023 to determine the current state of rehabilitation and to evaluate the rehabilitation and conservation factors that could be used to build a framework to assess the health of rehabilitation programs worldwide. A total of 418 publications encompassing 52 species of marine mammal were included in the systematic review. Rehabilitation efforts focused mostly on pinnipeds, and North America was the most represented region. Data are scarce for both short- and long-term post-release survival across species. Reports about species threatened with extinction were significantly more likely to include information about conservation parameters than those species of least concern. A meta-analysis demonstrated a fairly strong fit of the dimensions of the proposed framework for a rehabilitation health index. Further refinement would strengthen the utility of this tool for both rehabilitation and conservation programs.

Monitoring Land Management Practices Using Vis–NIR Spectroscopy Provides Insights into Predicting Soil Organic Carbon and Limestone Levels in Agricultural Plots

This study aimed to establish sound relationships between soil properties of agricultural land in central Spain and their spectral attributes to contribute to deriving an indicator for sustainable farm management. Sixteen plots, managed under various conditions, eight with traditional tillage and eight with other alternative managements, were selected to gather soil samples representing three predominant soil orders (Leptosols, Cambisols, and Luvisols). Soil sampling was conducted from depths ranging from 0 to 30 cm (0–50; 5–10, 10–20, and 20–30 cm), ensuring a broad spectrum of sample variability across different times and locations. The reflectance of soil 64 soil samples was measured within the range of 400 to 900 nm, and the corresponding concentrations of soil organic carbon and majoritarian minerals, calcium carbonate, quartz, phyllosilicates, K-Feldspar, and plagioclase were determined for each sample. Partial least squares analysis was employed to construct prediction models using a calibration dataset comprising 66% of randomly selected samples. The remaining 33% of samples were utilized for model validation. The prediction models for the measured soil chemical properties yielded R2 values ranging from 0.14 to 0.79. Only SOC and limestone provided accurate prediction models. These findings hold promise for developing a soil health indicator tailored for site-specific crop management. However, the complex composition of soil organic carbon and calcium carbonate in certain soils underscores the importance of careful interpretation and validation of remote sensing data, as well as the need for advanced modeling approaches that can account for the interactions between multiple soil constituents.

Evaluating Frequency Domain Reflectometry as a Tool for Lithium-Ion Battery Health Prognosis

Monitoring battery aging is crucial for maintaining reliability and performance. This study investigates Frequency Domain Reflectometry (FDR) as a tool for monitoring lithium-ion battery State-of-Health (SoH). While FDR has been applied in battery research, the existing literature fails to address SoH assessment and lacks studies on larger battery samples to provide more meaningful results. In this work, nineteen cells initially underwent Electrochemical Impedance Spectroscopy (EIS) to assess their degradation levels during cyclic aging. This work evaluates FDR’s effectiveness in monitoring battery health indicators, such as capacity and equivalent series resistance (ESR), by correlating these with FDR-measured impedance between 300 kHz and 1 GHz. Analytical comparison between impedance measured before and after de-embedding processes were presented. The results show FDR reactance within 300 kHz–40 MHz correlates with EIS-measured ESR, suggesting its potential as a SoH indicator. However, reduced sensitivity and accuracy, particularly after de-embedding, may limit practical applicability. Additionally, resonance-based analysis was conducted to explore the relationship between changes in circuit resonance and cell dielectric permittivity. Despite having the lowest sensitivity, the method showed that the resonance frequencies of cells remain relatively constant, mirroring behaviours associated with changes in resistive properties. Overall, this study provides insights into FDR’s potential for battery diagnostics while highlighting avenues for future research to enhance effectiveness in real-world scenarios.

Vital health indicator based state of health estimation of lithium-ion battery by adaptive neuro-fuzzy inference system

ABSTRACT The battery management system (BMS) in electric vehicles (EVs) relies on State of Health (SOH) assessment to monitor battery health and ensure performance. BMS can detect and prevent cell balance, thermal runaway, and extend its lifespan. Methodical charging and discharging under different circumstances reduce battery degradation. Grid Partitioning (GP), Subtractive Clustering (SC), and Fuzzy C-Means (FCM) from the Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to predict battery SOH in this work. This study examines charge-discharge cycles of 8 lithium-ion pouch cells from the Oxford Battery Degradation Dataset. Charging cycle data extracts the five vital health indicators (VHIs), whereas discharging cycle data calculates cell capacity. For analyzing the effects of VHIs on SOH, a correlation matrix is formed. Three instances are defined depending on the individual VHIs impacts. Instance 1 utilizes VHI 1, VHI 2, and VHI 5, instance 2 utilizes VHI 3 and VHI 4, and instance 3 uses all VHIs as inputs. Due to enormous data points, only even-numbered cell data is utilized for training the ANFIS model, while odd-numbered cell data is used for validation and testing. In the best-case scenario, instance 1 gives the lowest root mean square error (RMSE) from all the methods.

A Sociocultural Exploration of the Impact Body Image Has on Black College-Aged Women’s Mental Health

This study aimed to explore the relationship between Black cultural identity body image and mental well-being among Black Americans and Black immigrant women who attend predominately white universities (PWIs). As part of the Multi-Site University Study of Identity and Culture (MUSIC) survey, participants completed the Brief Inventory of Body Image, which included questions such as “I’m proud of my body,” “I often feel ugly,” ‘I have a good figure,” “I’m ashamed of my body,” and “I am anxious about the way I look.” The results showed that there were several similarities between the subgroups in the correlations between body image and mental health indices, such as social anxiety, depression, psychological well-being, and self-esteem. Both Black American and Black immigrant college-aged women had a positive association between body image and indicators of Black women’s sense of self, like self-esteem and psychological well-being. They also had a negative association between body image and mental health, such as social anxiety and depression. However, there was one key difference in that Black American women had a stronger association between their sense of self and self-esteem and psychological well-being compared to Black immigrant women. These findings support other studies that suggest Black women tend to have a stronger positive body satisfaction relative to their overall mental well-being. The study has important implications for the understanding of Black women, ethnic identity, body image, and mental health, which are discussed in the paper.

Serum (-2)proPSA/freePSAratio, (-2)proPSA/freePSA density, prostate health index, and prostate health index density as clues to reveal postoperative clinically significant prostate cancer in men with prostate-specific antigen 2-10 ng/mL.

There is a strong clinical need to fill the gap of identifying clinically significant prostate cancer (csPCa) in men with prostate-specific antigen(PSA) gray zone values. Promising, but not definitive results have been obtained using PSA derivatives such as prostate health index (PHI) and PHI density (PHID) and the percentage (-2)proPSA/free PSA(%p2PSA/fPSA). Thus, this study aimed to compare the diagnostic value of PHI, PHID, %proPSA/fPSA, and (-2)proPSA/freePSA density (-2pPSA/fPSAD) for csPCa in the patients with PSAwithin 2-10 ng/mL. Serum samples and clinicopathological features were prospectively collected from 142 patients who underwent robot-assisted radical prostatectomy between September 2021 and December 2023. According to the inclusion criteria, the patients with total PSA within 2 and 10 ng/mL and negative or suspicious digital rectal examination were enrolled. We used two different classifications for csPCa: 1) patients with Gleason score (GS) ≥ 7(4 + 3) and 2) patients with GS ≥ 7(3 + 4). The receiver operating characteristic curves and the area under the curve (AUC)values were used to assess the diagnostic performance. Of the 142 men included, 116 (82%) patients were diagnosed with csPCa as GS ≥ 3 + 4 and 107 (75%) defined as csPCa as GS ≥ 7(4 + 3), respectively. We found that p2PSA/fPSA, p2PSA/fPSAD, PHI, and PHID were significantly higher in csPCa classified as GS ≥ 7(3 + 4) as well as GS ≥ 7(4 + 3), with p-values 0.027, 0.054, 0.0016, and 0.0027, respectively. AUCs of the analyzed variables were higher when used to predict csPCa as GS ≥ 6 compared to csPCa as GS ≥7(4 + 3), with an AUC equal, respectively, to 0.679 (95% CI: 0.571-0.786), 0.685 (95% CI: 0.571-0.799), 0.737 (95% CI: 0.639-0.836), and 0.736 (95% CI: 0.630-0.841) in the first subgroup and with an AUC equal, respectively, to 0.653 (95% CI: 0.552-0.754), 0.665 (95% CI: 0.560-0.770), 0.668 (95% CI: 0.568-0.769), and 0.670 (95% CI: 0.567-0.773) in the second, respectively. Both PHID and p2PSA/fPSADallowed improvement in the diagnostic accuracy with respect to PHI and p2PSA/fPSA ratio, however the differences were not statistically significant (p = 0.409, 0.180 for csPCa as G ≥ Gleason grade (GG) 2 and 0.558 and 0.087 for csPCa as G ≥ GG3, respectively). We found that PHI, PHID, p2PSA/fPSA ratio, and p2PSA/fPSADshowed higher sensitivity, specificity, and positive predictive valuewhen used to predict csPCa as GG ≥ 2, whereas negative predictive valueof all four parameters was higher when used to predict GG ≥ 3. In men with a PSA level between 2 and 10 ng/mL, PHI and PHID, p2PSA/fPSA, and p2PSA/fPSAD showed good diagnostic performance for postoperative csPCa. However, PHID and p2PSA/fPSAD had a small advantage over PHI which needs to be further investigated for the reduction of unnecessary surgical interventions. This finding suggests that it could be a promising biomarker for making the treatment-decision strategy.

Self-rated health, epigenetic ageing, and long-term mortality in older Australians.

Self-rated health (SRH) is a subjective indicator of overall health based on a single questionnaire item. Previous evidence found that it is a strong predictor of mortality, although the underlying mechanism is poorly understood. Epigenetic age is an objective, emerging biomarker of health, estimated using DNA methylation data at hundreds of sites across the genome. This study aimed to assess the overlap and interaction between SRH and epigenetic ageing in predicting mortality risk. We used DNA methylation data from 1059 participants in the Melbourne Collaborative Cohort Study (mean age: 69years) to calculate three age-adjusted measures of epigenetic ageing: GrimAge, PhenoAge, and DunedinPACE. SRH was assessed using a five-category questionnaire item ("excellent, very good, good, fair, poor"). Cox models were used to assess the associations of SRH, epigenetic ageing, and their interaction, with all-cause mortality over up to 17years of follow-up (Ndeaths = 345). The association of SRH with mortality per category increase was HR = 1.29; 95%CI: 1.14-1.46. The association was slightly attenuated after adjusting for all three epigenetic ageing measures (HR = 1.25, 95%CI: 1.10-1.41). A strong gradient was observed in the association of GrimAge (Pinteraction = 0.006) and DunedinPACE (Pinteraction = 0.002) with mortality across worsening SRH strata. For example, the association between DunedinPACE and mortality in participants with "excellent" SRH was HR = 1.02, 95%CI: 0.73-1.43 and for "fair/poor" HR = 1.72, 95%CI: 1.35-2.20. SRH and epigenetic ageing were synergistic risk factors of mortality in our study. These findings suggest that consideration of subjective and objective factors may improve general health assessment, which has implications for the ongoing development of molecular markers of ageing.

Associations between Adolescent Preoperative Mental Health, Psychosocial Factors, and Body Mass Index.

There is little research on adolescent bariatric surgery and mental health (depression, anxiety, etc.) with racial/ethnic minority adolescents. The objective of this study is to determine associations between adolescents' preoperative reports of depression, anxiety, and self-esteem and caregiver's' reports of the caregiver-adolescent relationship and interpersonal relationships with adolescents' BMI and differences based on race/ethnicity. Adolescents (ages 12-21) who underwent metabolic and bariatric surgery from June 2020 to November 2022 had their responses to specific items on the BASC-3 (anxiety, depression, and self-esteem) analyzed for associations with their body mass index (BMI) and with caregiver responses to the BASC-3 for adolescents' interpersonal skills and relationship with caregiver. Demographic differences on the BASC-3 were assessed. Pearson's correlations, independent t-tests, and ANOVA were used. Caregivers who had higher t-scores for relationship with their adolescents had adolescents who had lower depression t-scores, lower anxiety t-scores, and higher self-esteem t-scores. Parents who had higher t-scores for their adolescents' interpersonal relations had adolescents who had lower depression t-scores, lower anxiety t-scores, and higher self-esteem t-scores. White adolescents had higher depression t-scores than Black and Hispanic adolescents. Black and Hispanic adolescents had higher self-esteem t-scores compared to White adolescents. Some of the findings within the study regarding adolescents' race and ethnicity and mental health are not consistent with prior research, affirming the need for additional research of these sub-populations.

On the design of Optimal Health Indicators for early fault detection and their statistical thresholds

This research presents a method for developing optimal health indicators for early fault detection in machine condition monitoring. The devised health indicators are optimal in the Neyman–Pearson sense, as they maximize the probability of detection while maintaining a constant false alarm rate. They are generated through a generalized likelihood ratio test that involves the probability density functions representing the healthy and faulty states. The essence of the approach lies in establishing a framework that defines optimal health indicators as functions of the partial derivatives of the healthy probability density function and a modulation function, representing the distortion of the probability density function in the faulty state. Specific modulation functions lead to the recovery of several traditional health indicators, including kurtosis, skewness, the crest factor, the clearance factor, the smoothness factor, the shape factor, the impulse factor, ℓp/ℓq-norms, the negentropy, among others. New health indicators are also derived. As the proposed optimal health indicators asymptotically follow a chi-squared distribution, they come with a statistical threshold. The study comprehensively outlines the methodology, with its performance assessed through simulated and experimental signals. The results reveal that the early transition from healthy to faulty can be well detected via the established optimal health indicators and their thresholds.