netANOVA: novel graph clustering technique with significance assessment via hierarchical ANOVA.

Many problems in life sciences can be brought back to a comparison of graphs. Even though a multitude of such techniques exist, often, these assume prior knowledge about the partitioning or the number of clusters and fail to provide statistical significance of observed between-network heterogeneity. Addressing these issues, we developed an unsupervised workflow to identify groups of graphs from reliable network-based statistics. In particular, we first compute the similarity between networks via appropriate distance measures between graphs and use them in an unsupervised hierarchical algorithm to identify classes of similar networks. Then, to determine the optimal number of clusters, we recursively test for distances between two groups of networks. The test itself finds its inspiration in distance-wise ANOVA algorithms. Finally, we assess significance via the permutation of between-object distance matrices. Notably, the approach, which we will call netANOVA, is flexible since users can choose multiple options to adapt to specific contexts and network types. We demonstrate the benefits and pitfalls of our approach via extensive simulations and an application to two real-life datasets. NetANOVA achieved high performance in many simulation scenarios while controlling type I error. On non-synthetic data, comparison against state-of-the-art methods showed that netANOVA is often among the top performers. There are many application fields, including precision medicine, for which identifying disease subtypes via individual-level biological networks improves prevention programs, diagnosis and disease monitoring.

Sex-biased genetic regulation of inflammatory proteins in the Dutch population.

BACKGROUND: Significant differences in immune responses, prevalence or susceptibility of diseases and treatment responses have been described between males and females. Despite this, sex-differentiation analysis of the genetic architecture of inflammatory proteins is largely unexplored. We performed sex-stratified meta-analysis after protein quantitative trait loci (pQTL) mapping using inflammatory biomarkers profiled using targeted proteomics (Olink inflammatory panel) of two population-based cohorts of Europeans. RESULTS: Even though, around 67% of the pQTLs demonstrated shared effect between sexes, colocalization analysis identified two loci in the males (LINC01135 and ITGAV) and three loci (CNOT10, SRD5A2, and LILRB5) in the females with evidence of sex-dependent modulation by pQTL variants. Furthermore, we identified pathways with relevant functions in the sex-biased pQTL variants. We also showed through cross-validation that the sex-specific pQTLs are linked with sex-specific phenotypic traits. CONCLUSION: Our study demonstrates the relevance of genetic sex-stratified analysis in the context of genetic dissection of protein abundances among individuals and reveals that, sex-specific pQTLs might mediate sex-linked phenotypes. Identification of sex-specific pQTLs associated with sex-biased diseases can help realize the promise of individualized treatment.

Cost-effectiveness of risk-based low-dose computed tomography screening for lung cancer in Switzerland.

Throughout Europe, computed tomography (CT) screening for lung cancer is in a phase of clinical implementation or reimbursement evaluation. To efficiently select individuals for screening, the use of lung cancer risk models has been suggested, but their incremental (cost-)effectiveness relative to eligibility based on pack-year criteria has not been thoroughly evaluated for a European setting. We evaluate the cost-effectiveness of pack-year and risk-based screening (PLCOm2012 model-based) strategies for Switzerland, which aided in informing the recommendations of the Swiss Cancer Screening Committee (CSC). We use the MISCAN (MIcrosimulation SCreening ANalysis)-Lung model to estimate benefits and harms of screening among individuals born 1940 to 1979 in Switzerland. We evaluate 1512 strategies, differing in the age ranges employed for screening, the screening interval and the strictness of the smoking requirements. We estimate risk-based strategies to be more cost-effective than pack-year-based screening strategies. The most efficient strategy compliant with CSC recommendations is biennial screening for ever-smokers aged 55 to 80 with a 1.6% PLCOm2012 risk. Relative to no screening this strategy is estimated to reduce lung cancer mortality by 11.0%, with estimated costs per Quality-Adjusted Life-Year (QALY) gained of €19 341, and a €1.990 billion 15-year budget impact. Biennial screening ages 55 to 80 for those with 20 pack-years shows a lower mortality reduction (10.5%) and higher cost per QALY gained (€20 869). Despite model uncertainties, our estimates suggest there may be cost-effective screening policies for Switzerland. Risk-based biennial screening ages 55 to 80 for those with ≥1.6% PLCOm2012 risk conforms to CSC recommendations and is estimated to be more efficient than pack-year-based alternatives.

Nationwide registry-based trial of risk-stratified cervical screening.

In well-screened populations, most cervical cancers arise from small groups of women with inadequate screening. The present study aims to assess whether registry-based cancer risk assessment could be used to increase screening intensity among high-risk women. The National Cervical Screening Registry identified the 28,689 women residents in Sweden who had either no previous cervical screening or a screening history indicating high risk. We invited these women by SMS and/or physical letter to order a free human papillomavirus (HPV) self-sampling kit. The Swedish national HPV reference laboratory performed extended HPV genotyping and referred high-risk HPV-positive women to their regional gynecologist. A total of 3691/28,689 (12.9%) women ordered a self-sampling kit and 10.0% (2853/28,689) returned a sample for testing. Participation among women who had never attended screening was low, albeit improved. Up to 22.5% of women in other high-risk groups attended. High-risk HPV types were detected in 8.3% of samples. High-risk HPV-positive women (238/2853) were referred without further triaging and severe cervical precancer or cancer (HSIL+) in histopathology were detected in 36/158 (23%) of biopsied women. Repeat invitations gave modest additional participation. Nationwide contacting of women with high risk for cervical cancer with personal invitations to order HPV self-sampling kits resulted in high yield of detected CIN2+. Further efforts to improve risk-stratified screening strategies should be directed to improving (i) the precision of the risk-stratification algorithm, (ii) the convenience for the women to participate and, (iii) ensuring that screen-positive women are followed-up.

Using context-specific evidence to inform resource-stratified cancer guidelines: A call for a new approach.

Clinical practice guidelines are widely used in oncology to guide clinical decision making and inform health policy and planning. In recent years, the National Comprehensive Cancer Network and the American Society of Clinical Oncology, as well as other international groups, have developed resource-stratified guidelines to guide clinicians and policymakers on cancer diagnosis and management in settings with various levels of resource constraints. Current methods for developing resource-stratified guidelines rely heavily on supporting evidence originating from high-income countries. In this commentary, the authors discuss limitations of the existing methods to develop resource-stratified guidelines and offer perspective on ways to strengthen the guidelines and their evidence base. Pulling from conceptual frameworks in the health policy domain, the authors outline a more inclusive approach to evidence synthesis that seeks to integrate the growing volume of cancer research emerging from low- and middle-income countries. The authors also introduce a revised evidence framework that provides transparency into the generalizability of evidence within the guidelines. These changes have the potential to enhance resource-stratified guidelines and bring us one step closer to the goal of evidence-based guidelines that are appropriate for diverse settings and unique patient populations across the world.

Alterations in gene expression and microbiome composition upon calcium-sensing receptor deletion in the mouse esophagus.

The calcium-sensing receptor (CaSR), a G protein-coupled receptor, regulates Ca2+ concentration in plasma by regulating parathyroid hormone secretion. In other tissues, it is reported to play roles in cellular differentiation and migration and in secretion and absorption. We reported previously that CaSR can be conditionally deleted in the mouse esophagus. This conditional knockout (KO) (EsoCaSR-/-) model showed a significant reduction in the levels of adherens and tight junction proteins and had a marked buildup of bacteria on the luminal esophageal surface. To further examine the role of CaSR, we used RNA sequencing to determine gene expression profiles in esophageal epithelia of control and EsoCaSR-/-mice RNA Seq data indicated upregulation of gene sets involved in DNA replication and cell cycle in EsoCaSR-/-. This is accompanied by the downregulation of gene sets involved in the innate immune response and protein homeostasis including peptide elongation and protein trafficking. Ingenuity pathway analysis (IPA) demonstrated that these genes are mapped to important biological networks including calcium and Ras homologus A (RhoA) signaling pathways. To further explore the bacterial buildup in EsoCaSR-/- esophageal tissue, 16S sequencing of the mucosal-associated bacterial microbiome was performed. Three bacterial species, g_Rodentibacter, s_Rodentibacter_unclassified, and s_Lactobacillus_hilgardi were significantly increased in EsoCaSR-/-. Furthermore, metagenomic analysis of 16S sequences indicated that pathways related to oxidative phosphorylation and metabolism were downregulated in EsoCaSR-/- tissues. These data demonstrate that CaSR impacts major pathways of cell proliferation, differentiation, cell cycle, and innate immune response in esophageal epithelium. The disruption of these pathways causes inflammation and significant modifications of the microbiome.NEW & NOTEWORTHY Calcium-sensing receptor (CaSR) plays a significant role in maintaining the barrier function of esophageal epithelium. Using RNA sequencing, we show that conditional deletion of CaSR from mouse esophagus causes upregulation of genes involved in DNA replication and cell cycle and downregulation of genes involved in the innate immune response, protein translation, and cellular protein synthesis. Pathway analysis shows disruption of signaling pathways of calcium and actin cytoskeleton. These changes caused inflammation and esophageal dysbiosis.

Diagnosis and initial treatment of transplant-eligible high-risk myeloma patients: A British Society for Haematology/UK Myeloma Society Good Practice Paper.

This Good Practice Paper provides recommendations for the diagnosis and initial management of transplant-eligible high-risk myeloma patients. It describes recent updates to the genetic diagnostics of high-risk myeloma and provides recommendations for treatment on the basis of recent prospective clinical trial evidence.

The Epstein-Barr Virus Glycoprotein BDLF2 Is Essential for Efficient Viral Spread in Stratified Epithelium.

Epstein-Barr virus (EBV) is a ubiquitous human pathogen that infects the majority of the adult population regardless of socioeconomic status or geographical location. EBV primarily infects B and epithelial cells and is associated with different cancers of these cell types, such as Burkitt lymphoma and nasopharyngeal carcinoma. While the life cycle of EBV in B cells is well understood, EBV infection within epithelium is not, largely due to the inability to model productive replication in epithelium in vitro. Organotypic cultures generated from primary human keratinocytes can model many aspects of EBV infection, including productive replication in the suprabasal layers. The EBV glycoprotein BDLF2 is a positional homologue of the murine gammaherpesvirus-68 protein gp48, which plays a role in intercellular spread of viral infection, though sequence homology is limited. To determine the role that BDLF2 plays in EBV infection, we generated a recombinant EBV in which the BDLF2 gene has been replaced with a puromycin resistance gene. The ΔBDLF2 recombinant virus infected both B cell and HEK293 cell lines and was able to immortalize primary B cells. However, the loss of BDLF2 resulted in substantially fewer infected cells in organotypic cultures compared to wild-type virus. While numerous clusters of infected cells representing a focus of infection are observed in wild-type-infected organotypic cultures, the majority of cells observed in the absence of BDLF2 were isolated cells, suggesting that the EBV glycoprotein BDLF2 plays a major role in intercellular viral spread in stratified epithelium. IMPORTANCE The ubiquitous herpesvirus Epstein-Barr virus (EBV) is associated with cancers of B lymphocytes and epithelial cells and is primarily transmitted in saliva. While several models exist for analyzing the life cycle of EBV in B lymphocytes, models of EBV infection in the epithelium have more recently been established. Using an organotypic culture model of epithelium that we previously determined accurately reflects EBV infection in situ, we have ascertained that the loss of the viral envelope protein BDLF2 had little effect on the EBV life cycle in B cells but severely restricted the number of infected cells in organotypic cultures. Loss of BDLF2 has a substantial impact on the size of infected areas, suggesting that BDLF2 plays a specific role in the spread of infection in stratified epithelium.

Collaborative model of care between orthopaedics and allied healthcare professionals (CONNACT) in knee osteoarthritis: Effectiveness-implementation hybrid randomized controlled trial of a community-based, multidisciplinary, stratified intervention.

OBJECTIVE: To compare the clinical and cost effectiveness of the Collaborative Model of Care between Orthopaedics and Allied Healthcare Professionals (CONNACT), a community-based, stratified, multidisciplinary intervention consisting of exercise, education, psychological and nutrition delivered through a chronic care model to usual hospital care in adults with knee osteoarthritis (OA). METHODS: Pragmatic, parallel-arm, single-blinded superiority RCT trial. Community-dwelling, ambulant adults with knee OA (Kellgren-Lawrence grade > 1; Knee Injury and OA Outcome Score (KOOS4) ≤75) were enrolled. Primary outcome was KOOS4 at 12-months; secondary outcomes included: quality of life, physical performance measures, symptom satisfaction, psychological outcomes, dietary habits, and global perceived effect. Intention-to-treat analysis using generalized linear model (GLM) and regression modeling were conducted. Economic evaluation through a societal approach was embedded. RESULTS: 110 participants (55 control, 55 intervention) were randomized. No between-group difference found for the primary outcome (MD [95%CI]: -1.86 [-9.11. 5.38]), although both groups demonstrated within-group improvement over 12-months. Among the secondary outcomes, the CONNACT group demonstrated superior dietary change (12 months) and physical performance measures (3 months), and global perceived effect (6 months). While there was no between-group difference in total cost, significant productivity gains (reduced indirect cost) were seen in the CONNACT group. CONCLUSION: CONNACT was not superior to usual care at 1 year. Further efforts are needed to understand the underlying contextual and implementation factors in order to further improve and refine such community-based, stratified care models moving forward. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT03809975. Registered January 18, 2019. https://clinicaltrials.gov/ct2/show/NCT03809975.

Invasive stratified mucin-producing carcinoma (ISMC) of the cervix: a clinicopathological and molecular analysis of 59 cases with special emphasis on histogenesis and potential therapeutic targets.

AIMS: This study aimed to better characterize the clinical and molecular features in invasive stratified mucin-producing carcinoma (ISMC), an uncommon aggressive subtype of endocervical adenocarcinoma (EAC). METHODS AND RESULTS: We recruited 59 ISMC for clinicopathological analysis, immunohistochemistry (n = 56), and targeted next-generation sequencing (n = 17). Our cases contained 29 pure and 30 mixed-type ISMC. Five patients developed local recurrence at 6-32 months (median: 13 months), and died of disease at 16-55 months (median: 16 months). Pure and mixed-type ISMC showed no significant difference in overall survival and tumour relapse (P > 0.05) except larger tumour size in the pure-type (P = 0.009). Compared to the usual-type EAC (n = 217), ISMsC were more frequently associated with large tumour size (P = 0.003), advanced FIGO stage (P = 0.017), lymph node metastasis (P = 0.022), Silva pattern C (P < 0.001), and poor overall survival and short tumour recurrence. SOX2 expression was observed in 82.1% (46/56) ISMC, substantially higher than p63 expression (P < 0.001), while positive SOX17 was present in 3.6% (2/56) cases. PD-L1 was positive in 41/56 ISMC (73.21%) (combined positive score: range: 1-92, median: 22). Three ISMC patients (17.65%) had PIK3CA mutations, while one each (5.88%) patient harboured an ERBB2, TP53, STK11, and PTEN mutation, respectively. CONCLUSION: We conclude that ISMC is clinically more aggressive than the usual-type EAC. ISMC may originate from cervical reserve cells with bidirectional differentiation. PD-L1 overexpression and the molecular profiles raise the possibility that a subset of ISMC patients may benefit from anti-PD-L1 immunotherapy and other targeted therapy, such as mTOR inhibitor and T-DM1.

Efficient estimation for left-truncated competing risks regression for case-cohort studies.

The case-cohort study design provides a cost-effective study design for a large cohort study with competing risk outcomes. The proportional subdistribution hazards model is widely used to estimate direct covariate effects on the cumulative incidence function for competing risk data. In biomedical studies, left truncation often occurs and brings extra challenges to the analysis. Existing inverse probability weighting methods for case-cohort studies with competing risk data not only have not addressed left truncation, but also are inefficient in regression parameter estimation for fully observed covariates. We propose an augmented inverse probability-weighted estimating equation for left-truncated competing risk data to address these limitations of the current literature. We further propose a more efficient estimator when extra information from the other causes is available. The proposed estimators are consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is unbiased and leads to estimation efficiency gain in the regression parameter estimation. We analyze the Atherosclerosis Risk in Communities study data using the proposed methods.

Efficient testing of the biomarker positive and negative subgroups in a biomarker-stratified trial.

In many randomized placebo-controlled trials with a biomarker defined subgroup, it is believed that this subgroup has the same or higher treatment effect compared with its complement. These subgroups are often referred to as the biomarker positive and negative subgroups. Most biomarker-stratified pivotal trials are aimed at demonstrating a significant treatment effect either in the biomarker positive subgroup or in the overall population. A major shortcoming of this approach is that the treatment can be declared effective in the overall population even though it has no effect in the biomarker negative subgroup. We use the isotonic assumption about the treatment effects in the two subgroups to construct an efficient way to test for a treatment effect in both the biomarker positive and negative subgroups. A substantial reduction in the required sample size for such a trial compared with existing methods makes evaluating the treatment effect in both the biomarker positive and negative subgroups feasible in pivotal trials especially when the prevalence of the biomarker positive subgroup is less than 0.5.

Addressing age measurement errors in fish growth estimation from length-stratified samples.

Fish growth models are crucial for fisheries stock assessments and are commonly estimated using fish length-at-age data. This data is widely collected using length-stratified age sampling (LSAS), a cost-effective two-phase response-selective sampling method. The data may contain age measurement errors (MEs). We propose a methodology that accounts for both LSAS and age MEs to accurately estimate fish growth. The proposed methods use empirical proportion likelihood methodology for LSAS and the structural errors in variables methodology for age MEs. We provide a measure of uncertainty for parameter estimates and standardized residuals for model validation. To model the age distribution, we employ a continuation ratio-logit model that is consistent with the random nature of the true age distribution. We also apply a discretization approach for age and length distributions, which significantly improves computational efficiency and is consistent with the discrete age and length data typically encountered in practice. Our simulation study shows that neglecting age MEs can lead to significant bias in growth estimation, even with small but non-negligible age MEs. However, our new approach performs well regardless of the magnitude of age MEs and accurately estimates SEs of parameter estimators. Real data analysis demonstrates the effectiveness of the proposed model validation device. Computer codes to implement the methodology are provided.

Sex- and time-specific associations of obesity with glycaemic traits: A two-step multivariate Mendelian randomization study.

AIM: To assess the sex- and time-specific causal effects of obesity-related anthropometric traits on glycaemic traits. MATERIALS AND METHODS: We used univariate and multivariate Mendelian randomization to assess the causal associations of anthropometric traits (gestational variables, birth weight, childhood body mass index [BMI], BMI, waist-to-hip ratio [WHR], BMI-adjusted WHR [WHRadj BMI]) with fasting glucose and insulin in Europeans from the Early Growth Genetics Consortium (n ≤ 298 142), the UK Biobank, the Genetic Investigation of Anthropometric Traits Consortium (n ≤ 697 734; females: n ≤ 434 794; males: n ≤ 374 754) and the Meta-Analyses of Glucose and Insulin-related traits Consortium (n ≤ 151 188; females: n ≤ 73 089; males: n ≤ 67 506), adjusting for maternal genetic effects, smoking, alcohol consumption, and age at menarche. RESULTS: We observed a null association for gestational variables, a negative association for birth weight, and positive associations for childhood BMI and adult traits (BMI, WHR, and WHRadj BMI). In female participants, increased birth weight causally decreased fasting insulin (betaIVW , -0.07, 95% confidence interval [CI] -0.11 to -0.03; p = 1.92 × 10-3 ), but not glucose levels, which was annulled by adjusting for age at menarche. In male participants, increased birth weight causally decreased fasting glucose (betainverse-variance-weighted (IVW) , -0.07, 95% CI -0.11 to -0.03; p = 3.22 × 10-4 ), but not insulin levels. In time-specific analyses, independent effects of birth weight were absent in female participants, and were more pronounced in male participants. Independent effects of childhood BMI were attenuated in both sexes; independent effects of adult traits differed by sex. CONCLUSIONS: Our findings provide evidence for causal and independent effects of sex- and time-specific anthropometric traits on glycaemic variables, and highlight the importance of considering multiple obesity exposures at different time points in the life course.

Implementation considerations for risk-tailored cancer screening in the population: A scoping review.

BACKGROUND: Risk-tailored screening has emerged as a promising approach to optimise the balance of benefits and harms of existing population cancer screening programs. It tailors screening (e.g., eligibility, frequency, interval, test type) to individual risk rather than the current one-size-fits-all approach of most organised population screening programs. However, the implementation of risk-tailored cancer screening in the population is challenging as it requires a change of practice at multiple levels i.e., individual, provider, health system levels. This scoping review aims to synthesise current implementation considerations for risk-tailored cancer screening in the population, identifying barriers, facilitators, and associated implementation outcomes. METHODS: Relevant studies were identified via database searches up to February 2023. Results were synthesised using Tierney et al. (2020) guidance for evidence synthesis of implementation outcomes and a multilevel framework. RESULTS: Of 4138 titles identified, 74 studies met the inclusion criteria. Most studies in this review focused on the implementation outcomes of acceptability, feasibility, and appropriateness, reflecting the pre-implementation stage of most research to date. Only six studies included an implementation framework. The review identified consistent evidence that risk-tailored screening is largely acceptable across population groups, however reluctance to accept a reduction in screening frequency for low-risk informed by cultural norms, presents a major barrier. Limited studies were identified for cancer types other than breast cancer. CONCLUSIONS: Implementation strategies will need to address alternate models of delivery, education of health professionals, communication with the public, screening options for people at low risk of cancer, and inequity in outcomes across cancer types.

A Stratified Approach for Managing Patients With Low Back Pain in Primary Care (SPLIT Program): A Before-and-After Study.

PURPOSE: To determine the effects of stratified primary care for low back pain (SPLIT program) in decreasing back-related disability for patients with low back pain (LBP) in primary care. METHODS: We conducted a before-and-after study. We compared health-related outcomes for 2 sequential, independent cohorts of patients with LBP recruited at 7 primary care units in Portugal. The first prospective cohort study characterized usual care (UC) and collected data from February to September 2018. The second was performed when the SPLIT program was implemented and collected data from November 2018 to October 2021. Between cohorts, physical therapists were trained in the implementation of the SPLIT program, which used the STarT Back Screening Tool to categorize patients for matched treatment. We compared back-related disability (Roland-Morris Disability Questionnaire, 0-24 points), pain (Numeric Pain Rating Scale, 0-10 points), perceived effect of treatment (Global Perceived Effect Scale, -5 to +5 points), and health-related quality of life (EuroQoL 5 dimensions 3 levels index, 0-1 points). RESULTS: We enrolled a total of 447 patients: 115 in the UC cohort (mostly treated with pharmacologic treatment) and 332 in the SPLIT cohort (all referred for a physical therapy intervention program). Over the study period of 6 months, patients in the SPLIT program showed significantly greater improvements in back-related disability (ß, -2.94; 95% CI, -3.63 to -2.24; P ≤ .001), pain (ß, -0.88; 95% CI, -1.18 to -0.57; P ≤ .001), perceived effect of treatment (ß, 1.40; 95% CI, 0.97 to 1.82; P ≤ .001), and health-related quality of life (ß, 0.11; 95% CI, 0.08 to 0.14; P ≤ .001) compared with UC. CONCLUSIONS: Patients in the SPLIT program for LBP showed greater benefits regarding health-related outcomes than those receiving UC.

Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.

In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs of depression. Nevertheless, only a limited number of research have taken into account the severity level as a multiclass variable. Besides, maintaining the equality of data distribution among all the classes rarely happens in practical communities. So, the inevitable class imbalance for multiple variables is considered a substantial challenge in this domain. Furthermore, this research emphasizes the significance of addressing class imbalance issues in the context of multiple classes. We introduced a new approach Feature group partitioning (FGP) in the data preprocessing phase which effectively reduces the dimensionality of features to a minimum. This study utilized synthetic oversampling techniques, specifically Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic (ADASYN), for class balancing. The dataset used in this research was collected from university students by administering the Burn Depression Checklist (BDC). For methodological modifications, we implemented heterogeneous ensemble learning stacking, homogeneous ensemble bagging, and five distinct supervised machine learning algorithms. The issue of overfitting was mitigated by evaluating the accuracy of the training, validation, and testing datasets. To justify the effectiveness of the prediction models, balanced accuracy, sensitivity, specificity, precision, and f1-score indices are used. Overall, comprehensive analysis demonstrates the discrimination between the Conventional Depression Screening (CDS) and FGP approach. In summary, the results show that the stacking classifier for FGP with SMOTE approach yields the highest balanced accuracy, with a rate of 92.81%. The empirical evidence has demonstrated that the FGP approach, when combined with the SMOTE, able to produce better performance in predicting the severity of depression. Most importantly the optimization of the training time of the FGP approach for all of the classifiers is a significant achievement of this research.

Precision nutrition in pediatric IBD: A position paper from the ESPGHAN special interest group for basic science and translational research, the IBD Porto group, and allied health professionals.

Stratified and precision nutrition refers to disease management or prevention of disease onset, based on dietary interventions tailored to a person's characteristics, biology, gut microbiome, and environmental exposures. Such treatment models may lead to more effective management of inflammatory bowel disease (IBD) and reduce risk of disease development. This societal position paper aimed to report advances made in stratified and precision nutritional therapy in IBD. Following a structured literature search, limited to human studies, we identified four relevant themes: (a) nutritional epidemiology for risk prediction of IBD development, (b) food-based dietary interventions in IBD, (c) exclusive enteral nutrition (EEN) for Crohn's disease (CD) management, and (d) pre- and probiotics for IBD management. There is scarce literature upon which we can make recommendations for precision or stratified dietary therapy for IBD, both for risk of disease development and disease management. Certain single-nucleotide polymorphisms related to polyunsaturated fatty acid (PUFA) metabolism may modify the effect dietary PUFA have in increasing the risk of IBD development. Non-colonic CD, mild-to-moderate CD, and high microbiota richness may predict success of EEN and may be used both for prediction of treatment continuation, but also for early cessation in nonresponders. There is currently insufficient evidence to make recommendations for precision or stratified dietary therapy for patients with established IBD. Despite the great interest in stratified and precision nutrition, we currently lack data to support conclusive recommendations. Replication of early findings by independent research groups and within structured clinical interventions is required.

ASSOCIATIONS BETWEEN VARIOUS TYPES OF MORTALITY AND TEMPERATURE VARIABILITY DISTINGUISHING THE INTRADAY AND INTERDAY EFFECTS IN SOUTH KOREA.

BACKGROUND: The association between temperature variability (TV) and elevated mortality risks is widely known. Yet, few studies investigated the distinct effects of intraday and interday temperature fluctuations considering age-specific, gender-specific, and cause-specific mortality stratified by four seasons. OBJECTIVES: We investigate the associations between total, intraday, and interday temperature variabilities and total, age-specific, gender-specific, cardiovascular, and respiratory mortality year-round and also stratified by four seasons. METHODS: We collected district-level daily data for temperature and total, age-specific, gender-specific, cardiovascular, and respiratory mortality in South Korea from 2011 to 2021 (N=3,113,425). TV indices (i.e., total TV, intraday TV, and interday TV) were computed as the standard deviations of daily minimum, maximum, and mean temperatures over a lag of one to seven days. The associations between TV and mortality were evaluated by a space-time-stratified case-crossover design with quasi-Poisson regression. RESULTS: Mortality risks varied based on the type of TV index. The associations also differed depending on the mortality type and the season. Year-round associations showed interday TV was generally associated with elevated mortality risks (total mortality: 0.30% (95% CI: 0.07%, 0.52%), 65+ mortality: 0.32% (95% CI: 0.07%, 0.58%), female mortality: 0.49% (95% CI: 0.16%, 0.82%), CVD mortality: 0.47% (95% CI: 0.02%, 0.92%) on lag0-7) while intraday TV was not significantly associated with increased risk of mortality except for the male mortality, 0.68% (95% CI: 0.04%, 1.32%) on lag0-7. Season-stratified analysis revealed that TV-related mortality risks were high consistently in the spring season and generally in the summer season while the associations were generally negative in fall and insignificant in winter. CONCLUSION: This study provided evidence on the season-stratified, independent impacts of intraday and interday temperature variabilities on total, age-specific, gender-specific, and cause-specific mortality risks in South Korea drawing attention to the need of targeted policies to alleviate the impacts on human health.

Stratified control of chemical crystallization in a pellet fluidized bed for pH-Adjusted fluoride and phosphate reduction: An experimental study.

Chemical crystallization granulation in a fluidized bed offers an environmentally friendly technology with significant promise for fluoride removal. This study investigates the impact of stratified pH control in a crystallization granulation fluidized bed for the removal of fluoride and phosphate on a pilot scale. The results indicate that using dolomite as a seed crystal, employing sodium dihydrogen phosphate (SDP) and calcium chloride as crystallizing agents, and controlling the molar ratio n(F):n(P):n(Ca) = 1:5:10 with an upflow velocity of 7.52 m/h, effectively removes fluoride and phosphate. Stratified pH control-maintaining weakly acidic conditions (pH = 6-7) at the bottom and weakly alkaline conditions (pH = 7-8) at the top-facilitates the induction of fluoroapatite (FAP) and calcium phosphate crystallization. This approach reduces groundwater fluoride levels from 9.5 mg/L to 0.2-0.6 mg/L and phosphate levels to 0.1-0.2 mg/L. Particle size analysis, scanning electron microscopy-energy-dispersive X-ray spectroscopy, and X-ray diffraction physical characterizations reveal significant differences in crystal morphology between the top and bottom layers, with the lower layer primarily generating high-purity FAP crystals. Further analysis shows that dolomite-induced FAP crystallization offers distinct advantages. SDP not only dissolves on the dolomite surface to provide active sites for crystallization but also, under weakly acidic conditions, renders both dolomite and FAP surfaces negatively charged. This allows for the effective adsorption of PO43-, HPO42-, and F- anions onto the crystal surfaces. This study provides supporting data for the removal of fluoride from groundwater through induced FAP crystallization in a chemical crystallization pellet fluidized bed.