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Simple Summary: The prognosis of PCa at diagnosis is assessed by classification systems that aim to group homogenous sets of patients. However, great heterogeneity exists within these risk groups, in terms of prognostic factors and treatment options. The aim of this study was to assess the prognostic impact and predictors of adverse tumor grade in very favorable low- and intermediate-risk prostate cancer patients treated with robot-assisted radical prostatectomy at a high-volume tertiary referral center. Objectives: To assess the prognostic impact and predictors of adverse tumor grade in very favorable low- and intermediate-risk prostate cancer (PCa) patients treated with robot-assisted radical prostatectomy (RARP). Methods: Data of low- and intermediate PCa risk-class patients were retrieved from a prospectively maintained institutional database. Adverse tumor grade was defined as pathology ISUP grade group > 2. Disease progression was defined as a biochemical recurrence event and/or local recurrence and/or distant metastases. Associations were assessed by Cox's proportional hazards and logistic regression model. Results: Between January 2013 and October 2020, the study evaluated a population of 289 patients, including 178 low-risk cases (61.1%) and 111 intermediate-risk subjects (38.4%); unfavorable tumor grade was detected in 82 cases (28.4%). PCa progression, which occurred in 29 patients (10%), was independently predicted by adverse tumor grade and biopsy ISUP grade group 2, with the former showing stronger associations (hazard ratio, HR = 4.478; 95% CI: 1.840–10.895; p = 0.001) than the latter (HR = 2.336; 95% CI: 1.057–5.164; p = 0.036). Older age and biopsy ISUP grade group 2 were independent clinical predictors of adverse tumor grade, associated with larger tumors that eventually presented non-organ-confined disease. Conclusions: In a very favorable PCa patient population, adverse tumor grade was an unfavorable prognostic factor for disease progression. Active surveillance in very favorable intermediate-risk patients is still a hazard, so molecular and genetic testing of biopsy specimens is needed. [ABSTRACT FROM AUTHOR]

This study aims to highlight the importance of a systematic approach to process capability assessment and the importance of following a sequence of steps. Statistical process control provides several different ways of assessing process capability. This study evaluates the process capability of crown cap manufacturing through capability indices. In addition to calculating the indices, the evaluation involves extensive data analysis. Before calculating the capability indices, the assumptions for their correct selection and use were also verified. Several statistical tests were used to verify each assumption. The research value of the study lies in pointing out that not all tests led to the same conclusions. It highlights the importance of selecting the appropriate test type for the evaluated process quality characteristics. [ABSTRACT FROM AUTHOR]

In genomic studies, univariate analysis is commonly used to discover susceptible variants. It applies univariate regression for each variant and tests the significance of the regression coefficient or slope parameter. This strategy, however, may miss signals that are jointly detectable with other variants. Multivariate analysis is another popular approach, which tests grouped variants with a predefined group, e.g., based on a gene, pathway, or physical location. However, the power will be diminished if the modeling assumption is not suited to the data. Therefore, data-adaptive testing that relies on fewer modeling assumptions is preferable. Possible approaches include a data-adaptive test proposed by Ueki (2021), which applies to various data-adaptive regression models using a generalization of Yanai's generalized coefficient of determination. While several regression models are possible choices for the data-adaptive test, this paper focuses on the fused lasso that can count for the effect of adjacent variants and investigates its performance through comparison with other existing tests. Simulation studies demonstrate that the test using fused lasso has a high power compared to the existing tests including the univariate regression test, saturated regression test, SKAT (sequence kernel association test), burden test, SKAT-O (optimized sequence kernel association test), and the tests using lasso, ridge, and elastic net when assuming a similar effect of adjacent variants. [ABSTRACT FROM AUTHOR]

This study concerns the management of operational risk in truck transport using the reliability theory of risks. In this regard, the risk analysis of changes in the vehicle unavailability represents an important topic. In this study, the authors present their own method for analysing the phase changes in risk corresponding to successive sections (phases) of vehicle mileage. The presented risk analysis method is based on an integrated assessment of losses associated with the costs of incidental repairs and losses caused by lost income during vehicle downtime. This includes the following: assessment of differences in average risk and differences in the coefficient of variation in the time series of vehicle mileage phases, indicating the outliers and extremes of phase risk, identifying their physical causes and testing the statistical significance of phase risk differences. The proposed method is described mathematically and verified experimentally based on the operational data concerning trucks from two selected brands (20 trucks from each brand). We show that the method can be used to predict the continuity of transport services in the short term (one-year horizon). The method could also be useful to compare vehicles of different brands in the context of their sensitivity to operational risks. [ABSTRACT FROM AUTHOR]

The material developed focuses on the analysis of energy efficiency trends in Poland, utilising ODEX indicators for the sectors of industry, transport, households and in general, from 2011 to 2021. The objective of the study is to assess the progress made in energy efficiency and to forecast future trends in these sectors. The methods employed are based on statistical modelling of time series, taking into account sector-specific energy consumption dynamics. The following techniques were employed: linear regression, cluster analysis to identify patterns of change, statistical hypothesis testing for energy efficiency and simplified autoregressive models. The results demonstrated significant improvements in energy efficiency in the industrial sector, stability of the ODEX indicator in the transport sector and gradual improvements in households and overall. The prediction indicates an upward trend in the ODEX indicator in the short term, suggesting an increase in energy demand. However, it also predicts a decline in the long term, which may indicate the effectiveness of future energy efficiency strategies and investments. Consequently, the necessity for continued efforts to increase energy efficiency and further research into the factors influencing energy efficiency in different economic sectors is emphasised. [ABSTRACT FROM AUTHOR]

The Omicron variants BA.1, BA.2, and BA.5 caused several waves of SARS-CoV-2 in Germany in 2022. In this comparative study, public health data on SARS-CoV-2 infections from Mecklenburg-Western Pomerania, Germany, between January and October 2022 were examined retrospectively using Pearson's chi-squared tests and Fisher's exact tests for testing for statistical significance. Compared to BA.5 infections, BA.1 and BA.2 infections affected younger individuals aged up to 19 years significantly more often, whereas BA.5 infections occurred significantly more frequently in patients between 40 and 59 years of age when compared to BA.1 and BA.2. Infections with all three variants predominantly caused flu-like symptoms; nevertheless, there were significant differences between the reported symptoms of BA.1, BA.2, and BA.5 infections. Especially, the symptoms of 'fever', 'severe feeling of sickness', 'loss of taste', and 'loss of smell' were significantly more often present in patients with BA.5 infections compared to BA.1 and BA.2 cases. Additionally, BA.2 and BA.5 cases reported significantly more often the symptoms of 'runny nose' and 'cough' than BA.1-infected cases. Our findings indicate remarkable differences in the clinical presentations among the sub-lineages, especially in BA.5 infections. Furthermore, the study demonstrates a powerful tool to link epidemiological data with genetic data in order to investigate their potential impact on public health. [ABSTRACT FROM AUTHOR]

This study examines the relationships between state-provided paid-leave availability and enrollment in public health and nutrition programs (SNAP, Medicaid, WIC) among single low-income women following a birth in the U.S. We hypothesize that women in paid leave states will be less likely to participate in publicly available health and nutrition programs. Data are from the Survey of Income and Program Participation (SIPP), a nationally representative panel survey data set (N = 1168). Descriptive tests of significance and probit regression models are used to examine the relationship between paid-leave availability and participation in SNAP, Medicaid, and WIC following a birth. A descriptive analysis suggests significantly lower enrollment in SNAP but not Medicaid or WIC for single low-income women in paid-leave states compared to those in non-paid-leave states. The finding of significantly lower post-birth SNAP participation in paid-leave states holds in probit models that include potentially relevant mother, household, and state controls. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a common neurodegenerative disorder with a prolonged prodromal phase. Higher urinary bis(monoacylglycerol)phosphate (BMP) levels associate with LRRK2 (leucine-rich repeat kinase 2) and GBA1 (glucocerebrosidase) mutations, and are considered as potential noninvasive biomarkers for predicting those mutations and PD progression. However, their reliability has been questioned, with inadequately investigated genetics, cohorts, and population. In this study, multiple statistical hypothesis tests were employed on urinary BMP levels and sequences of 90 PD-risk single nucleotide polymorphisms (SNPs) from Parkinson's Progression Markers Institution (PPMI) participants. Those SNPs were categorized into four groups based on their impact on BMP levels in various cohorts. Variants rs34637584 G/A and rs34637584 A/A (LRRK2 G2019S) were identified as the most relevant on increasing urinary BMP levels in the PD cohort. Meanwhile, rs76763715 T/T (GBA1) was the primary factor elevating BMP levels in the prodromal cohort compared to its T/C and C/C variants (N370S) and the PD cohort. Proteomics analysis indicated the changed transport pathways may be the reasons for elevated BMP levels in prodromal patients. Our findings demonstrated that higher urinary BMP levels alone were not reliable biomarkers for PD progression or gene mutations but might serve as supplementary indicators for early diagnosis and treatment. [ABSTRACT FROM AUTHOR]

The internal validity of a causal inference made based on an observational study is often subject to debate. The potential outcomes framework of causal inference stipulates that causal inference is essentially a missing data problem, and we follow this spirit to define the ideal sample as the combination of the observed data and the missing/counterfactual data for regression models. The robustness of a causal inference can be quantified by the probability of a robust inference for internal validity in regression, i.e., the PIVR, which is the probability of rejecting the null hypothesis again for the ideal sample provided the same null hypothesis has been already rejected for the observed sample. Drawing on the relationship between the PIVR and the mean counterfactual outcomes, we formalize a conceptual framework of quantifying the robustness of a regression-based causal inference based on a joint distribution about the mean counterfactual outcomes, holding the observed sample fixed. Interpretatively, the PIVR is the statistical power of the null hypothesis significance testing that is thought to be built on the ideal sample. We demonstrate the conceptual framework of quantifying the robustness of a regression-based causal inference with an empirical example. [ABSTRACT FROM AUTHOR]

En-bloc retraction is a common procedure in orthodontic therapy. The application of palatal root torque moments is required to control incisor inclination during retraction, yet studies comparing forces and moments with respect to different mechanics are lacking. This study aimed to investigate the forces and moments during orthodontic en-bloc retraction using a robotic biomechanical simulation system, comparing two distinct approaches: (I) compound technique [stainless steel (SS) combined with nickel-titanium (NiTi)] using industrially pretorqued retraction-torque-archwires (RTA) in combination with NiTi closed coil springs; (II) conventional sliding mechanics using SS archwires with manually applied anterior twist bends in combination with elastic chains. Two dimensions (0.017" × 0.025" and 0.018" × 0.025") and ten archwires per group were investigated using 0.022" slot self-ligating brackets. Kruskal–Wallis tests with a significance level of α = 0.05 were conducted. The biomechanical simulation showed that en-bloc retraction was characterized by a series of tipping and uprighting movements, differing significantly regarding the examined mechanics. Collateral forces and moments occurred in all groups. Notably, RTA exhibited fewer extrusive forces. The most bodily movement was achieved with the compound technique and the 0.018" × 0.025" RTA. Sliding mechanics exhibited maximum palatal root torque moments of more than 20 Nmm, exceeding recommended values. [ABSTRACT FROM AUTHOR]

(1) Background: The relationship between sleep bruxism (SB) and psychological distress has been investigated in numerous studies and is heterogeneous. Different diagnostic procedures have been applied to determine SB. The aim of this study was to directly compare the association between psychological distress and SB diagnosed by different accepted methods. (2) Methods: Data of N = 45 subjects were analyzed, including group comparisons and correlation analyses. Following diagnostic methods for the determination of SB were used in one sample: self-report, clinical assessment, polysomnography with audio–video recording and a novel diagnostic sheet with analyzing software. Psychological distress was measured using the global severity index (GSI) of the Symptom Checklist-90-Standard (SCL-90-S). (3) Results: The GSI did not differ significantly between subjects with and without SB, regardless of the underlying diagnostic classification (p > 0.05). In-depth correlation analyses of self-report and clinical data revealed a weak-to-medium correlation with the GSI (r = 0.12–0.44). Due to non-normally distributed data, a test of statistical significance was not possible. Variables of instrumental methods such as the SB index (amount of SB activity per hour) of polysomnography (PSG) showed almost no correlation with psychological distress (r = −0.06–0.05). (4) Conclusions: Despite these limitations, the results provide an indication that the choice of diagnostic procedure may elucidate the variance in the correlation between SB and psychological distress. [ABSTRACT FROM AUTHOR]

Popular theories that explain or predict behavioural intentions are based on people's attitudes and subjective norms. Their application is based on the (often implicit) assumption that people regard a subject (e.g., preventing the spread of COVID-19) as sufficiently important for them to formulate stable attitudes and subjective norms about it. As this assumption rarely holds for all people, the influence of attitudes and subjective norms in determining behavioural intentions changes depending on the importance of the subject. In other words, importance has a moderating effect on the relationship between intentions, attitudes, and subjective norms. We hypothesise that, as importance declines, the influence on intentions of attitudes decreases and the influence of subjective norms increases. This has important implications for efforts to encourage the adoption of preventative behaviours in relation to COVID-19 because promotional strategies designed to modify attitudes differ markedly from those designed to modify subjective norms. We test this hypothesis by analysing three different large-scale surveys about people's intentions, involvement, attitudes, and subjective norms regarding the spread of COVID-19 in New Zealand. The results support our hypothesis and highlight the importance of distinguishing between when the formation of behavioural intentions depends mainly on attitudes and when it depends mainly on subjective norms. [ABSTRACT FROM AUTHOR]

The paper makes a case that the current discussions on replicability and the abuse of significance testing have overlooked a more general contributor to the untrustworthiness of published empirical evidence, which is the uninformed and recipe-like implementation of statistical modeling and inference. It is argued that this contributes to the untrustworthiness problem in several different ways, including [a] statistical misspecification, [b] unwarranted evidential interpretations of frequentist inference results, and [c] questionable modeling strategies that rely on curve-fitting. What is more, the alternative proposals to replace or modify frequentist testing, including [i] replacing p-values with observed confidence intervals and effects sizes, and [ii] redefining statistical significance, will not address the untrustworthiness of evidence problem since they are equally vulnerable to [a]–[c]. The paper calls for distinguishing between unduly data-dependant 'statistical results', such as a point estimate, a p-value, and accept/reject H 0 , from 'evidence for or against inferential claims'. The post-data severity (SEV) evaluation of the accept/reject H 0 results, converts them into evidence for or against germane inferential claims. These claims can be used to address/elucidate several foundational issues, including (i) statistical vs. substantive significance, (ii) the large n problem, and (iii) the replicability of evidence. Also, the SEV perspective sheds light on the impertinence of the proposed alternatives [i]–[iii], and oppugns [iii] the alleged arbitrariness of framing H 0 and H 1 which is often exploited to undermine the credibility of frequentist testing. [ABSTRACT FROM AUTHOR]

(1) Background: The aim of this prospective study was to evaluate measurement software in comparison with manual measurements using inter-observer and intra-observer variability on radiographs in the preoperative planning of total knee arthroplasty. (2) Methods: Two independent observers retrospectively measured the mechanical lateral proximal femoral angle (mLPFA), the mechanical lateral distal femoral angle (mLDFA), the joint line convergence angle (JLCA), the mechanical medial proximal tibial angle (mMPTA), the mechanical lateral distal tibial angle (mLDTA), the hip–knee angle or mechanical tibial–femoral axis angle (HKA), and the anatomical–mechanical angle (AMA) on 55 long-leg anteroposterior radiographs manually twice, followed by measurements using dedicated software. Variability between manual and computer-aided planning was assessed, and all measurements were performed a second time after 14 days in order to assess intra-observer variability. (3) Results: Concerning intra-observer variability, no statistically significant difference was observed regarding the software-based measurements. However, significant differences were noted concerning intra-observer variability when measuring the mLDFA and AMA manually. Testing for statistical significance regarding variability between manual and software-based measurements showed that the values varied strongly between manual and computer-aided measurements. Statistically significant differences were detected for mLPFA, mLDFA, mMPTA, and mLPTA on day 1, and mLPFA, mMPTA, and mLPTA on day 15, respectively. (4) Conclusions: Preoperative planning of leg axis angles and alignment using planning software showed less inter- and intra-observer variability in contrast to manual measurements, and results differed with respect to manual planning. We believe that the planning software is more reliable and faster, and we would recommend its use in clinical settings. [ABSTRACT FROM AUTHOR]

The Kaplan–Meier (KM) estimator is widely used in medical research to estimate the survival function from lifetime data. KM estimation is a powerful tool to evaluate clinical trials due to simple computational requirements, its use of a logrank hypothesis test, and the ability to censor patients. However, KM estimation has several constraints and fails to generalize to ordinal variables of clinical interest, such as toxicity and ECOG performance. We devised weighted trajectory analysis (WTA) to combine the advantages of KM estimation with the ability to visualize and compare treatment groups for ordinal variables and fluctuating outcomes. To assess statistical significance, we developed a new hypothesis test analogous to the logrank test. We demonstrated the functionality of WTA through 1000-fold clinical trial simulations of unique stochastic models of chemotherapy toxicity and schizophrenia disease course. With increments in sample size and hazard ratio, we compared the performance of WTA to KM estimation and the generalized estimating equation (GEE). WTA generally required half the sample size to achieve comparable power to KM estimation; advantages over the GEE included its robust nonparametric approach and summary plot. We also applied WTA to real clinical data: the toxicity outcomes of melanoma patients receiving immunotherapy and the disease progression of patients with metastatic breast cancer receiving ramucirumab. The application of WTA demonstrated that using traditional methods such as KM estimation can lead to both type I and II errors by failing to model illness trajectory. This article outlines a novel method for clinical outcome assessment that extends the advantages of Kaplan–Meier estimates to ordinal outcome variables. [ABSTRACT FROM AUTHOR]

Simple Summary: In Sri Lanka, the authors are encouraging a cost-effective way to reduce the number of people developing oral cancer, which is a common cancer among men. The authors wanted to find out how well dentists can find signs of oral cancer and potential problems in their patients, and they did this by asking dentists questions in an online survey. Surprisingly, most of the dentists thought it would be better to only check people who are at a higher risk for oral cancer instead of checking everyone. Only about two thirds of the dentists regularly look for signs of oral cancer when people come for dental check-ups. The authors found that these dentists, on average, had noticed about 34 patients with concerning signs in the past year. Almost all the dentists believed that they needed more training to spot these problems. So, while opportunistic screening at the dentist's office is good, dental professionals also need to focus on other ways to prevent oral cancer, like checking high-risk groups and giving dentists more confidence to spot potential issues. In Sri Lanka, opportunistic screening is encouraged as a cost-effective tool to bring down the prevalence of oral cancer, which is the most common cancer among males. The objectives of the study were to determine the practices, attitudes, and level of competency of dental surgeons regarding the early detection of oral cancer and oral potentially malignant disorders (OPMDs) through opportunistic screening. A prospective study was conducted online via a Google form using a pretested, self-administered questionnaire of 22 close-ended questions and 3 open-ended questions. Out of the 137 dental surgeons who responded, 88% (121/137) of the participants believed that screening high-risk target groups would be more effective in the early detection of oral cancer rather than opportunistic screening. Only 64% (88/137) of the participants frequently check for oral cancer and OPMDs when patients visit for dental treatment. Participants recalled an average of 34 patients (4628/137) with clinically suspicious lesions being diagnosed during examination at general dental practice during the past year, and 98% (134/137) of the participants believed that they should receive additional training in order to identify and diagnose clinically suspicious OPMDs and oral cancer. Opportunistic screening in general dental practice as an oral-cancer prevention strategy is appreciable, but due emphasis should be given to other prevention strategies such as population screening and screening high-risk target groups. The level of confidence of general dental practitioners in the early detection of oral cancer has to be raised in order to achieve higher standards in oral cancer prevention through opportunistic screening. [ABSTRACT FROM AUTHOR]

Simple Summary: LCMR1 is a subunit of the mediator complex, also known as MED19, which is involved in various life activities and is closely related to the occurrence and development of tumors. In this study, we knocked down LCMR1 in large cell lung cancer cells and found that high expression of LCMR1 in LCLC indicates a poor prognosis. Meanwhile, blocking LCMR1 in the 95D LCLC cell line reduced proliferation and metastasis in vitro and in living organisms. LCMR1 inhibits the transcription of HLAs, a gating factor of cancer-specific antigen-presenting. Lung cancer is notorious for its high global morbidity and mortality. Here, we examined whether the LCMR1 gene, which we previously cloned from a human large-cell lung carcinoma cell line, contributes to the proliferation and metastasis of large-cell lung carcinoma. To this end, we performed pan-cancer and non-small cell lung cancer (NSCLC) cell line-based LCMR1 expression profiling. Results revealed that LCMR1 was expressed at high levels in most solid tumors, including NSCLC. LCMR1 expression was the highest in the 95D large cell lung cancer cell line. Functional studies using lentivirus-based knockdown revealed that LCMR1 was critical for the proliferation, migration, and invasion of cultured large cell lung cancer cells. Moreover, blocking this gene significantly reduced tumor growth in a 95D cell xenograft mouse model. A multiple sequence-based assay revealed a mechanism by which LCMR1 diminished the RNA Pol II occupancy at the promoter of human leukocyte antigen (HLA)-encoding genes to prevent their transcription. The HLA genes play vital roles in cancer-specific antigen presentation and anticancer immunity. A correlation assay using TCGA database identified a negative relationship between the expression levels of LCMR1 and HLA coding genes. Taken together, our findings demonstrate that LCMR1 is required for large cell lung cancer cell growth and invasion and suggest its potential as a valid target in clinical treatment. [ABSTRACT FROM AUTHOR]

Polymeric materials show great promise for use in a variety of dental applications. Manufacturers generally provide flexural strength information based on standardized (ISO and ASTM) specimen dimensions and loading conditions. It is not clear, however, if flexural strength data are predictive of the clinical performance of dental crowns. The objectives of this study were, therefore, to determine whether flexural strengths, as measured via three-point bending (3PB), would be predictive of failure loads assessed via crunch-the-crown (CTC) tests. Three brands of polymers (Trilor, Juvora, and Pekkton) were fabricated into rectangular bars and fully contoured crowns (10 specimens of each polymer brand, 30 specimens of each shape). Differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), and burn off tests were used to characterize/confirm the materials. Bars were tested blindly in 3PB to determine flexural strength, and crowns were CTC-tested to determine failure load after luting to resin abutments. The statistical significance of the test results was evaluated via one-way ANOVA (α = 0.05) and Pearson's correlation coefficient, while regression analysis was used to test for a correlation between 3PB and CTC results. The fracture mechanisms and failure surface characteristics were characterized using scanning electron microscopy (SEM). There were significant differences (p < 0.05) in the mean crown failure loads (Trilor (7033 N) > Juvora (5217 N) > Pekkton (3023 N)) and mean flexural strengths of the bars (Trilor (468 MPa) > Juvora (197 MPa) = Pekkton (192 MPa)). The mode of crown fracture was different between the materials and included deformation (Juvora), ductile-to-brittle fracture (Pekkton), and a combination of cracks and deformation (Trilor). Flexural strengths did not correlate with the corresponding crown failure loads for any of the materials tested. These results suggest that dental practitioners should not rely on the flexural strengths reported from three-point bending tests, as advertised by the manufacturer, to predict the performance of polymeric crowns. [ABSTRACT FROM AUTHOR]

Particle swarm optimization (PSO) is a population-based heuristic algorithm that is widely used for optimization problems. Phasor PSO (PPSO), an extension of PSO, uses the phase angle θ to create a more balanced PSO due to its increased ability to adjust the environment without parameters like the inertia weight w. The PPSO algorithm performs well for small-sized populations but needs improvements for large populations in the case of rapidly growing complex problems and dimensions. This study introduces a competitive coevolution process to enhance the capability of PPSO for global optimization problems. Competitive coevolution disintegrates the problem into multiple sub-problems, and these sub-swarms coevolve for a better solution. The best solution is selected and replaced with the current sub-swarm for the next competition. This process increases population diversity, reduces premature convergence, and increases the memory efficiency of PPSO. Simulation results using PPSO, fuzzy-dominance-based many-objective particle swarm optimization (FMPSO), and improved competitive multi-swarm PPSO (ICPPSO) are generated to assess the convergence power of the proposed algorithm. The experimental results show that ICPPSO achieves a dominating performance. The ICPPSO results for the average fitness show average improvements of 15%, 20%, 30%, and 35% over PPSO and FMPSO. The Wilcoxon statistical significance test also confirms a significant difference in the performance of the ICPPSO, PPSO, and FMPSO algorithms at a 0.05 significance level. [ABSTRACT FROM AUTHOR]

(1) Background: Fire department cadets preparing to become firefighters and paramedics experience high levels of stress when participating in incidents like traffic accidents and fires. Stress adversely affects health, and coping with it proves difficult. Unfortunately, there is no single method that reduces stress completely in humans. One non-invasive method for lowering stress hormone levels is craniosacral therapy. (2) Methods: Fifty-seven firefighting cadets aged 18–24 years (21.63 ± 1.41) participated in the study. They were randomly assigned to either a test group or a control group. Participants' blood levels of cortisol and CRH (corticotropin-releasing hormone) were assessed before and after the study. The study group underwent 5-week craniosacral therapy (1× per week). (3) Results: The Kruskal–Wallis test showed that the therapy group's results were statistically significant for CRH values (p-value = 0.00067) and for cortisol values (p-value ≤ 0.0001). Wilxocon and Dunn tests showed statistical significance for cortisol after CS therapy between the control and study groups (p = 0.0377), and for CRH between the control and study groups before (p = 0.00634) and after the study (p = 0.000887), and in the study group before and after the study (p = 0.0101). (4) Conclusions: The application of craniosacral therapy reduced stress hormone levels in male firefighter cadets. The results indicate that craniosacral therapy (five sessions, one per week) has an effect on the reduction of stress hormones. [ABSTRACT FROM AUTHOR]

In the context of climate warming, flash drought has become increasingly frequent, posing significant threats to agriculture, ecosystems, and the environment. Xinjiang, located in an arid and semi-arid region, necessitates a thorough investigation into the distinctions between flash drought and traditional drought, as well as an exploration of the driving forces behind both types of drought. In this study, soil moisture data from ERA5-Land were utilized to construct a framework for the identification of flash drought and traditional drought based on historical events. The Geodetector was employed to explore the factors that influence the spatial heterogeneity of these two drought forms. The findings illuminate that (1) in terms of spatial distribution, traditional drought predominated in southern Xinjiang, while flash drought exhibited greater prominence in northern Xinjiang. (2) Regarding changes in trends, both flash drought and traditional drought exhibited an increasing trend in frequency since the 1990s, with the frequency trend of flash drought passing the significance test (α ≤ 0.05). Additionally, the severity of both flash drought and traditional drought displayed a noteworthy and statistically significant increase within sliding windows ranging from 46 to 62 years. (3) Concerning the driving forces, precipitation emerged as the principal driving force behind both flash drought and traditional drought. Furthermore, human activities exerted a more substantial influence on traditional drought, and the interactions involving human activities had the potential to significantly amplify the explanatory power of the spatial heterogeneity for both drought types. (4) In terms of the drought risk, a notable variation in the risk of flash drought was observed across various ecological zones, with the highest risk occurring in mildly fragile ecological zones. Furthermore, when comparing the results from 1995 to 2019, the flash drought risk exhibited a marked increase in severely fragile ecological zones. This study enriches the understanding of the dynamics of flash drought and traditional drought in Xinjiang and carries important implications for enhancing the precision of drought monitoring and early warning systems. [ABSTRACT FROM AUTHOR]

Symmetry in a differential evolution (DE) transforms a solution without impacting the family of solutions. For symmetrical problems in differential equations, DE is a strong evolutionary algorithm that provides a powerful solution to resolve global optimization problems. DE/best/1 and DE/rand/1 are the two most commonly used mutation strategies in DE. The former provides better exploitation while the latter ensures better exploration. DE/Neighbor/1 is an improved form of DE/rand/1 to maintain a balance between exploration and exploitation which was used with a random neighbor-based differential evolution (RNDE) algorithm. However, this mutation strategy slows down convergence. It should achieve a global minimum by using 1000 × D, where D is the dimension, but due to exploration and exploitation balancing trade-offs, it can not achieve a global minimum within the range of 1000 × D in some of the objective functions. To overcome this issue, a new and enhanced mutation strategy and algorithm have been introduced in this paper, called DE/Neighbor/2, as well as an improved random neighbor-based differential evolution algorithm. The new DE/Neighbor/2 mutation strategy also uses neighbor information such as DE/Neighbor/1; however, in addition, we add weighted differences after various tests. The DE/Neighbor/2 and IRNDE algorithm has also been tested on the same 27 commonly used benchmark functions on which the DE/Neighbor/1 mutation strategy and RNDE were tested. Experimental results demonstrate that the DE/Neighbor/2 mutation strategy and IRNDE algorithm show overall better and faster convergence than the DE/Neighbor/1 mutation strategy and RNDE algorithm. The parametric significance test shows that there is a significance difference in the performance of RNDE and IRNDE algorithms at the 0.05 level of significance. [ABSTRACT FROM AUTHOR]

Differential evolution (DE) stands out as a straightforward yet remarkably powerful evolutionary algorithm employed for real-world problem-solving purposes. In the DE algorithm, few parameters are used, and the population is evolved by applying various operations. It is difficult in evolutionary computation algorithms to maintain population diversity. The main issue is the sub-population of the DE algorithm that helps improve convergence speed and escape from the local optimum. Evolving sub-populations by maintaining diversity is an important issue in the literature that is considered in this research. A solution is proposed that uses sub-populations to promote greater diversity within the population and improve the algorithm performance. DE, heterogeneous distributed differential evolution (HDDE), multi-population ensemble differential evolution (MPEDE), and the proposed improved multi-population ensemble differential evolution (IMPEDE) are implemented using parameter settings; population sizes of 100 NP, 150 NP, and 200 NP; and dimensions of 10D, 30D, and 50D for performance comparison. Different combinations of mutations are used to generate the simulated results. The simulation results are generated using 1000, 3000, and 5000 iterations. Experimental outcomes show the superior results of the proposed IMPEDE over existing algorithms. The non-parametric significance Friedman test confirms that there is a significant difference in the performance of the proposed algorithm and other algorithms used in this study by considering a 0.05 level of significance using six benchmark functions. [ABSTRACT FROM AUTHOR]

Beatrix Frangepán (* c. 1480, +(27 March) 1510) from the Counts of Veglia (Krk), Modrus and Zengg was a descendant from one of the leading families of the Hungarian–CroatianHungarian–Croatian late Medieval Kingdom. She became wife of Crown Prince János Corvinus-Hunyadi and later of Margrave Georg Hohenzollern-Brandenburg. From her first marriage, she had three children. One of these, Kristóf, who died young, was buried together with his father in Lepoglava (Croatia). Recently, successful archaeogenetic analyses have been performed on the remains of János and Kristóf Corvinus-Hunyadi; and in the course of these studies, the family background of Kristóf's mother, Beatrix Frangepán, became an important factor. The present study provides a nine-generation family tree of Beatrix Frangepan as a complementary data pool for an eventual expansion of the archaeogenetic studies. Preliminary results of archaeological study of the supposed grave of Beatrix Frangepán are also reported. [ABSTRACT FROM AUTHOR]

In most Western European societies, surnames pass from generation to generation and in cases where surnames are shared by fathers to children, the Y chromosome passes down from fathers to male offspring in the same way as surnames do. The aim of this study was to ascertain the patrilineal relationship between individuals with the surname "Castilla" and their respective Y-chromosome haplotypes. The toponymic surname "Castilla" is part of the Spanish royal family. Genealogical studies of this surname have allowed the formulation of different hypotheses about its origin, most of which were centered in Burgos. To shed some light on the origin of the surname Castilla and to investigate the possible co-ancestry behind the living carriers of this surname, markers located in the Y chromosome-specific region were analyzed in a sample of 102 men whose paternal surname was Castilla. The study aimed to establish the minimum number of founders and the expansion time of the lineages from our sample. Two major haplogroups were identified: R1b and E1b1b-M81. The high frequency of the E1b1b-M81 haplogroup in comparison to that of the general Spanish population, its low haplotype diversity, and its young TMRCA (323+/− 255 years CE) are compatible with the historical timing of the obligation to use surnames. However, the coincidence of the most common haplogroup in the Castilla sample and the most frequent haplogroup in the Spanish general population, R1b, makes it difficult to identify founder haplotypes/haplogroups in the history of the Castilla surname. [ABSTRACT FROM AUTHOR]

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations. [ABSTRACT FROM AUTHOR]

The Qilian Mountains (QMs) act as the "water tower" of the Hexi Corridors, playing an important role in the regional ecosystem security and economic development. Therefore, it is of great significance to understand the spatiotemporal characteristics of precipitation in the QMs. This study evaluated the performance of 21 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) from 1959 to 1988 based on ERA5 and in situ datasets. In addition, the precipitation changing trend from 2015 to 2100 was projected according to four shared socioeconomic pathways (SSPs): namely, SSP126, SSP245, SSP370, and SSP585. The results have shown the following: (1) all CMIP6 models could reflect the same precipitation changing trend, based on the observed datasets (−2.01 mm·10a−1), which was slightly lower than that of ERA5 (2.82 mm·10a−1). Multi-mode ensemble averaging (MME) showed that the projected precipitation-change trend of the four scenarios was 5.73, 9.15, 12.23, and 16.14 mm·10a−1, respectively. (2) The MME and ERA5 showed the same precipitation spatial pattern. Also, during the period 1959–1988, the MME in spring, summer, autumn and winter was 130.07, 224.62, 95.96, and 29.07 mm, respectively, and that of ERA5 was 98.57, 280.77, 96.85, and 22.64 mm, respectively. The largest precipitation difference in summer was because of strong convection and variable circulation. (3) From 2015 to 2100, the snow-to-rain ratio was between 0.1 and 1.1, and the snow-to-rain ratio climate tendency rate was concentrated in the range of −10~0.1 mm·10a−1. Both of these passed the significance test (p < 0.05). The projected rainfall of all four SSPs all showed an increasing trend with values of 6.20, 11.31, 5.64, and 20.41 mm·10a−1, respectively. The snowfall of the four SSPs all showed a decreasing trend with values of 0.42, 2.18, 3.34, and 4.17 mm·10a−1, respectively. [ABSTRACT FROM AUTHOR]

Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt. In previous studies, LSEM was fitted as a sequence of models separately evaluated as each value of the moderator variables. In this article, a joint estimation approach is proposed that is a simultaneous estimation method across all moderator values and also allows some model parameters to be invariant with respect to the moderator. Moreover, sufficient details on the main estimation functions in the R package sirt are provided. The practical implementation of LSEM is demonstrated using illustrative datasets and an empirical example. Moreover, two simulation studies investigate the statistical properties of parameter estimation and significance testing in LSEM. [ABSTRACT FROM AUTHOR]

This paper aims to develop a machine-learning model based on a gradient-boosting algorithm to predict the energy-saving awareness of households using a questionnaire survey and 11-month energy data collected from more than 200 smart houses in Kitakyushu, Japan. We utilize the LightGBM (light gradient boosting machine) classifier to perform feature selection for the prediction. By using this approach, we demonstrate that the key features are the standard deviations of electricity purchased between 8 a.m. and 9 a.m. and electricity consumed between 7 p.m. and 9 p.m. Next, by using k-means clustering we split the households based on the obtained features into three groups. Finally, by using statistical hypothesis testing, we prove that these three groups have statistically distinct levels of energy-saving awareness. This model enables us to detect eco-friendly households from their energy data, which may support energy policymaking. [ABSTRACT FROM AUTHOR]

The travel source–sink phenomenon is a typical urban traffic anomaly that reflects the imbalanced dissipation and aggregation of human mobility activities. It is useful for pertinently balancing urban facilities and optimizing urban structures to accurately sense the spatiotemporal ranges of travel source–sinks, such as for public transportation station optimization, sharing resource configurations, or stampede precautions among moving crowds. Unlike remote sensing using visual features, it is challenging to sense imbalanced and arbitrarily shaped source–sink areas using human mobility trajectories. This paper proposes a density-based adaptive clustering method to identify the spatiotemporal ranges of travel source–sink patterns. Firstly, a spatiotemporal field is utilized to construct a stable neighborhood of origin and destination points. Then, binary spatiotemporal statistical hypothesis tests are proposed to identify the source and sink core points. Finally, a density-based expansion strategy is employed to detect the spatial areas and temporal durations of sources and sinks. The experiments conducted using bicycle trajectory data in Shanghai show that the proposed method can accurately extract significantly imbalanced dissipation and aggregation events. The travel source–sink patterns detected by the proposed method have practical reference, meaning that they can provide useful insights into the redistribution of bike-sharing and station resources. [ABSTRACT FROM AUTHOR]

The JAYA algorithm is a population-based meta-heuristic algorithm proposed in recent years which has been proved to be suitable for solving global optimization and engineering optimization problems because of its simplicity, easy implementation, and guiding characteristic of striving for the best and avoiding the worst. In this study, an improved discrete JAYA algorithm based on reinforcement learning and simulated annealing (QSA-DJAYA) is proposed to solve the well-known traveling salesman problem in combinatorial optimization. More specially, firstly, the basic Q-learning algorithm in reinforcement learning is embedded into the proposed algorithm such that it can choose the most promising transformation operator for the current state to update the solution. Secondly, in order to balance the exploration and exploitation capabilities of the QSA-DJAYA algorithm, the Metropolis acceptance criterion of the simulated annealing algorithm is introduced to determine whether to accept candidate solutions. Thirdly, 3-opt is applied to the best solution of the current iteration at a certain frequency to improve the efficiency of the algorithm. Finally, to evaluate the performance of the QSA-DJAYA algorithm, it has been tested on 21 benchmark datasets taken from TSPLIB and compared with other competitive algorithms in two groups of comparative experiments. The experimental and the statistical significance test results show that the QSA-DJAYA algorithm achieves significantly better results in most instances. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing (HF) can trigger induced seismicity, but documented occurrences tend to be localized compared with the regional extent of industry operations. Factors that determine intrinsic geological susceptibility of a given region to induced seismicity remain incompletely understood. To address this uncertainty, we have developed a stochastic modeling approach to enable statistical testing of hypotheses regarding the distribution of induced seismicity. For reference, we adopted a null hypothesis that HF-induced seismic events are randomly associated with HF wells. Realizations of synthetic induced-seismicity catalogs are generated based on the Gutenberg–Richter relationship for magnitudes and explicit assumed spatial relationship(s) between HF wells and other known features, such as mapped structural corridors. Uncertainties in observed event locations and magnitudes are also considered. Based on 1000 independent realizations for each test scenario, normalized correlation coefficients, Bayesian information criteria and other statistical measures are used to quantify the similarity of synthetic catalogs to the observed seismicity distribution. We applied this approach to induced seismicity associated with HF operations within the Montney Formation, in western Canada. Three hypotheses were tested, each showing a statistically significant improvement over the null hypothesis. A previous machine-learning-based model for Seismogenic Activation Potential (SAP) showed the highest correlation between observed and synthetically generated seismicity catalogs. Our method has been developed using cloud-based computing and is easily adapted to other regions and data types. [ABSTRACT FROM AUTHOR]

Occlusal rest provides support for removable partial dentures (RPD). Rest seats are ideally prepared in enamel, but the abutment teeth might be restored or need restorations. This study compared the fracture strength of abutments restored with composite to amalgam restorations after rest seat preparation. Disto-occlusal cavities were prepared in 30 extracted human maxillary premolars. The specimens were allocated in three groups (n = 10) based on the type of restoration. All the specimens were exposed to thermomechanical aging followed by cycling loading. Fracture strength was tested using a universal testing machine, and then, the fracture mode was recorded. The data were analyzed using Kruskal–Wallis test with a significance level set at 0.05. The fracture mode was recorded as catastrophic or non-catastrophic. The fracture strength between all tested groups showed no significant difference. The highest and lowest fracture strength were recorded on amalgam and Tetric N-Ceram groups, respectively. Composite Tetric N-Ceram showed equal distribution of fracture sites on the restorative materials and teeth, it also displayed the highest number of non-catastrophic fractures unlike other groups where the fracture occurred more within the restorations. The fracture strength of composite was comparable to that of amalgam restorations with prepared rest seats. [ABSTRACT FROM AUTHOR]

Despite mammography (MG) being among the most widespread techniques in breast cancer screening, tumour detection and classification remain challenging tasks due to the high morphological variability of the lesions. The extraction of radiomics features has proved to be a promising approach in MG. However, radiomics features can suffer from dependency on factors such as acquisition protocol, segmentation accuracy, feature extraction and engineering methods, which prevent the implementation of robust and clinically reliable radiomics workflow in MG. In this study, the variability and robustness of radiomics features is investigated as a function of lesion segmentation in MG images from a public database. A statistical analysis is carried out to assess feature variability and a radiomics robustness score is introduced based on the significance of the statistical tests performed. The obtained results indicate that variability is observable not only as a function of the abnormality type (calcification and masses), but also among feature categories (first-order and second-order), image view (craniocaudal and medial lateral oblique), and the type of lesions (benign and malignant). Furthermore, through the proposed approach, it is possible to identify those radiomics characteristics with a higher discriminative power between benign and malignant lesions and a lower dependency on segmentation, thus suggesting the most appropriate choice of robust features to be used as inputs to automated classification algorithms. [ABSTRACT FROM AUTHOR]

In the first part of this article, we discuss and generalize the complete convergence introduced by Hsu and Robbins in 1947 to the r-complete convergence introduced by Tartakovsky in 1998. We also establish its relation to the r-quick convergence first introduced by Strassen in 1967 and extensively studied by Lai. Our work is motivated by various statistical problems, mostly in sequential analysis. As we show in the second part, generalizing and studying these convergence modes is important not only in probability theory but also to solve challenging statistical problems in hypothesis testing and changepoint detection for general stochastic non-i.i.d. models. [ABSTRACT FROM AUTHOR]

The paper focuses on analysing the current tax behaviour of Slovak citizens and their inclination to tax evasion. Inclination to tax evasion is defined in this research based on respondents' answers to questions focused on their tax morale. The data processed in this research was obtained from a questionnaire survey on a sample of 1067 respondents. Intentional sampling was used to ensure the same structure of respondents. In terms of tax evasion acceptance, we identified three groups of people: honest, dishonest, and unconscious. The research confirmed that 78% of the population is prone to tax evasion, and only 22% have never evaded paying taxes and would not do so knowingly or unconsciously. By applying the statistical hypothesis testing, we also found out that except for sex (women are less prone to tax evasion), inclination to tax evasion also depends on education, age, main source of income and experience. Finally, three types of logistic regression models to predict the inclination of a specific tax behaviour were constructed and evaluated based on the total accuracy metric and validated on the ex-post set. [ABSTRACT FROM AUTHOR]

As a typical application of geodesy, the GNSS/INS (Global Navigation Satellite System and Inertial Navigation System) integrated navigation technique was developed and has been applied for decades. For the integrated systems with multiple sensors, data fusion is one of the key problems. As a well-known data fusion algorithm, the Kalman filter can provide optimal estimates with known parameters of the models and noises. In the literature, however, the data fusion algorithm of the GNSS/INS integrated navigation and positioning systems is performed under a certain norm, and performance of the conventional filtering algorithms are improved only under this fixed and limited frame. The mixed norm-based data fusion algorithm is rarely discussed. In this paper, a mixed norm-based data fusion algorithm is proposed, and the hypothesis test statistics are constructed and adopted based on the chi-square distribution. Using the land vehicle data collected through the multi-GNSS and the IMU (Inertial Measurement Unit), the proposed algorithm is tested and compared with the conventional filtering algorithms. Results show that the influences of the outlying measurements and the uncertain noises are weakened with the proposed data fusion algorithm, and the precision of the estimates is further improved. Meanwhile, the proposed algorithm provides an open issue for geodetic applications with mixed norms. [ABSTRACT FROM AUTHOR]

Simple Summary: No measures of the changes occurring in the liver in the case of outflow deprivation during hepatectomies are available. This study investigated four indexes obtained using hyperspectral imaging in a pig model, measured in different liver lobes, before and after hepatic vein occlusion. The variations of StO2% and deoxy-Hb were considerably good markers of venous liver congestion. Introduction. The changes occurring in the liver in cases of outflow deprivation have rarely been investigated, and no measurements of this phenomenon are available. This investigation explored outflow occlusion in a pig model using a hyperspectral camera. Methods. Six pigs were enrolled. The right hepatic vein was clamped for 30 min. The oxygen saturation (StO2%), deoxygenated hemoglobin level (de-Hb), near-infrared perfusion (NIR), and total hemoglobin index (THI) were investigated at different time points in four perfused lobes using a hyperspectral camera measuring light absorbance between 500 nm and 995 nm. Differences among lobes at different time points were estimated by mixed-effect linear regression. Results. StO2% decreased over time in the right lateral lobe (RLL, totally occluded) when compared to the left lateral (LLL, outflow preserved) and the right medial (RML, partially occluded) lobes (p < 0.05). De-Hb significantly increased after clamping in RLL when compared to RML and LLL (p < 0.05). RML was further analyzed considering the right portion (totally occluded) and the left portion of the lobe (with an autonomous draining vein). StO2% decreased and de-Hb increased more smoothly when compared to the totally occluded RLL (p < 0.05). Conclusions. The variations of StO2% and deoxy-Hb could be considered good markers of venous liver congestion. [ABSTRACT FROM AUTHOR]

The application of voltage reduction in medium and low voltage grids to reduce peak power demand or energy consumption has been implemented since the 1980s using several approaches. Conservation Voltage Reduction (CVR), as one such approach, uses a voltage control device to reduce or increase the voltage setpoint on a busbar, thereby reducing or increasing the amount of active and reactive power supply in the network. Voltage regulation for CVR is always implemented according to established network planning standards in each country. Research in this field has proven that a CVR factor ( C V R f ) of 0.7–1.5 for peak demand reduction can be achieved. This is an evaluation metric of CVR. The aim of this research is to determine and validate C V R f for peak demand reduction by comparing actual results obtained during regular tap changes with other randomly distributed periods outside tap change operations, using a set of measurement data. It is important to understand CVR deployment capability by evaluating CVR potentials from historical random tap operations before a robust network-wide deployment is introduced. This research provides such guidance. It also provides a novel approach to determining tap changes from voltage measurements using a time-based algorithm. A C V R f ranging from 0.95 to 1.61 was estimated using a measurement dataset from a test field. The result of the entire evaluation shows that the C V R f are smaller during peak PV production and greater during peak demand periods. Further evaluation using statistical hypotheses testing and a control chart was used to validate the evaluation. [ABSTRACT FROM AUTHOR]

Background: Chronic post-herpetic neuralgia (CPHN) is a symptomatic condition that afflicts adults and elderly individuals. The chronicity of this symptomatology can be conditioned by the epigenetic modifications induced by the virus on the processes of neurotransmission and sensitivity to pain. The aim of this study is to investigate whether manipulating endogenous bioelectrical activity (EBA), responsible for neurotransmission processes and contributing to the induction of epigenetic modifications, can alleviate pain symptoms. Methods: This manipulation was carried out with the antalgic neuromodulation (ANM) treatment of radioelectric asymmetric conveyer (REAC) technology. Pain assessment before and after treatment was performed using a numerical analog scale (NAS) and a simple descriptive scale (SDS). Results: The results of the analysis showed an over four-point decrease in NAS scale score and over one point decrease in SDS scale score, with a statistical significance for both tests of p < 0.005. Conclusions: The results obtained in this study demonstrate how REAC ANM manipulation of EBA can lead to improvement in epigenetically conditioned symptoms such as CPHN. These results should prompt further research to expand knowledge and ensure optimized therapeutic outcomes. [ABSTRACT FROM AUTHOR]

Simple Summary: The number of pigmented moles is the most important risk factor for melanoma. This "real world" study conducted in 25 Australian childcare centers is the first to show it is possible to prevent a significant proportion of pigmented moles in young Caucasian children by dressing them in UPF 30-50+ clothing that covers at least half their body on a daily basis. Regularly wearing this clothing for 3.5 years was sufficient to prevent almost one-quarter of the pigmented moles that young children developed on their skin. This should, by implication, reduce their risk of developing melanoma in the future. Primary health care providers should stress the importance of garment coverage when recommending sun protection for children and should lobby for all sun-protective clothing standards to assess and report garment coverage, in addition to the transmission of ultraviolet radiation through the fabric (reported as UPF), on clothing labels and packaging for children's clothing, including school uniforms. Numerous pigmented moles are associated with sun exposure and melanomarisk. This cluster randomized controlled trial aimed to determine if sun-protective clothing could prevent a significant proportion of the moles developing in young children (ACTRN12617000621314; Australian New Zealand Clinical Trials Registry. Twenty-five childcare centers in Townsville (19.25° S), Australia, were matched on shade provision and socioeconomic status. One center from each pair was randomized to the intervention arm and the other to the control arm. Children at 13 intervention centers wore study garments and legionnaire hats at childcare and received sun-protective swimwear and hats for home use, while children at the 12 control centers did not. The 1–35-month-old children (334 intervention; 210 control) were examined for moles at baseline (1999–2002) and were re-examined annually for up to 4 years. Both groups were similar at baseline. Children at intervention centers acquired fewer new moles overall (median 12.5 versus 16, p = 0.02; 0.46 versus 0.68 moles/month, p = 0.001) and fewer new moles on clothing-protected skin (6 vs. 8; p = 0.021 adjusted for confounding and cluster sampling) than controls. Intervention children had 24.3% fewer new moles overall (26.5 versus 35) and 31.6% (13 versus 19) fewer moles on clothing-protected skin than controls after 3.5 years. Sunlight's influence on nevogenesis is mitigated when children regularly wear UPF 30-50+ clothing covering half their body, implying that increased clothing cover reduces melanoma risk. Sun-protective clothing standards should mandate reporting of the percentage of garment coverage for childrenswear. [ABSTRACT FROM AUTHOR]

Using multisource sea ice fusion data, the spatiotemporal characteristics of sea ice cover were analyzed for the marginal seas of East Asia for the period 2005–2021. The results show that there were obvious differences in the beginning and end dates of the sea ice in the different sea areas. The northern Sea of Japan had the longest ice period, and Laizhou Bay and Bohai Bay in the Bohai Sea had the shortest ice period. The time when the largest sea ice extent appeared was relatively stable and mostly concentrated in late January to mid-February. There were obvious spatial differences in the duration of the sea ice cover in the marginal seas of East Asia. The duration of the sea ice cover gradually decreased from high latitude to low latitude and from nearshore to open seas. The annual average duration of the sea ice cover was more than 100 days in most of the Sea of Japan and approximately 20 days in most of Laizhou Bay and Bohai Bay. The melting speed was significantly faster than the freezing speed in the Bohai Sea and Yellow Sea, resulting in asymmetric changes in the daily sea ice extent in the two seas. The increasing trends in the maximum sea ice extent and total sea ice extent were 0.912 × 105 km2/10 yr and 0.722 × 107 km2/10 yr, respectively, from 2005 to 2013, both of which passed the significance test at the 0.05 level. [ABSTRACT FROM AUTHOR]

In particular, the data allow us to calculate the I p i -value, which is defined as " I the probability under a specified statistical model that a statistical summary of the data would be equal to or more extreme than its observed value i " [[1]], and practically reflects the degree of data compatibility with the null hypothesis. (2) " I p-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone. i " They can only tell us how consistent the data are with the null hypothesis. Conventionally, if the I p i -value is lower than the 0.05 significance level, we reject the null hypothesis and accept the alternative hypothesis. At the beginning of our research training, we learned about hypothesis testing, I p i -values, and statistical inference. [Extracted from the article]

Simple Summary: There is a wide range of choices for combining PD-1/PD-L1 checkpoint inhibitors with other measures in treating tumors, but certain choices of regimens are still controversial. We aimed to investigate the therapeutic efficacy and potential side effects of combination therapy with anti-PD-1/PD-L1 compared to anti-PD-1/PD-L1 monotherapy. Meanwhile, we also explored whether different combination strategies would yield consistent efficacy across different types of tumors. Our study can provide important and useful information for clinicians and encourage the enrollment of more clinical trials for anti-PD-1/PD-L1 combination therapy. Objective: In recent years, the anti-programmed cell death protein-1 and its ligand (PD-1/PD-L1) or combination therapies have been recommended as an alternative emerging choice of treatment for oncology patients. However, the efficacy and adverse events of different combination strategies for the treatment of tumors remain controversial. Methods: PubMed, Embase, Cochrane Library, the American Society of Clinical Oncology (ASCO), and the European Society of Medicine Oncology (ESMO) were searched from database inception until 16 February 2022. The endpoints of objective response rate (ORR), disease control rate (DCR), overall survival (OS), progression-free survival (PFS), and adverse events (AEs) were analyzed from different treatment schemes and tumor types. The protocol was registered in PROSPERO (CRD42022328927). Results: This meta-analysis included forty-eight eligible studies. Combination therapy has improved ORR (RR = 1.40, p < 0.001), DCR (RR = 1.22, p < 0.001), and PFS (the median survival ratio (MSR) was estimated to be 1.475 p < 0.001) compared to anti-PD-1/PD-L1 but had no significant benefit on OS (MSR was estimated to be 1.086 p = 0.117). Besides, combination treatment strategies are more toxic in any grade AEs (RR = 1.13, p < 0.001) and grade 3–5 AEs (RR = 1.81, p < 0.001). Conclusions: Treatment with PD-1/PD-L1 inhibitors in combination with other antitumor therapies improve patients' ORR, DCR, and PFS compared to anti-PD-1/PD-L1. However, it is regrettable that there is no benefit to OS and an increased risk of AEs in combinatorial therapies. [ABSTRACT FROM AUTHOR]

Simple Summary: Different cells present in the tumor microenvironment can deeply influence both cancer spreading and the success of therapy in solid tumors, including colorectal carcinoma (CRC). In particular, tumor-associated fibroblasts (TAF) exert potent immunosuppressive effects leading to the impairment of anti-tumor surveillance and interfering with the function of therapeutic antibodies. Herein, we show that CRC-derived TAF can be turned by zoledronic acid (ZA), in soluble form or as antibody-drug conjugate (ADC), into efficient stimulators of anti-tumor lymphocytes. The ADC, made of the anti-EGFR cetuximab (Cet), used in CRC therapy, and ZA (Cet-ZA) can induce the proliferation of lymphocytes that become able to kill both tumor cells and TAF. The double result is a direct anti-cancer effect and the neutralization of the inhibitory activity exerted by its stroma. The major advantage of the Cet-ZA ADC formulation is the precise delivery of ZA to EGFR+ cells, targeting TAF (potentially immunosuppressive), besides CRC cells. Tumor-associated fibroblasts (TAF) exert immunosuppressive effects in colorectal carcinoma (CRC), impairing the recognition of tumor cells by effector lymphocytes, including Vδ2 T cells. Herein, we show that CRC-derived TAF can be turned by zoledronic acid (ZA), in soluble form or as antibody-drug conjugate (ADC), into efficient stimulators of Vδ2 T cells. CRC-TAF, obtained from patients, express the epidermal growth factor receptor (EGFR) and the butyrophilin family members BTN3A1/BTN2A1. These butyrophilins mediate the presentation of the phosphoantigens, accumulated in the cells due to ZA effect, to Vδ2 T cells. CRC-TAF exposed to soluble ZA acquired the ability to trigger the proliferation of Vδ2 T cells, in part represented by effector memory cells lacking CD45RA and CD27. In turn, expanded Vδ2 T cells exerted relevant cytotoxic activity towards CRC cells and CRC-TAF when primed with soluble ZA. Of note, also the ADC made of the anti-EGFR cetuximab (Cet) and ZA (Cet-ZA), that we recently described, induced the proliferation of anti-tumor Vδ2 T lymphocytes and their activation against CRC-TAF. These findings indicate that ZA can educate TAF to stimulate effector memory Vδ2 T cells; the Cet-ZA ADC formulation can lead to the precise delivery of ZA to EGFR+ cells, with a double targeting of TAF and tumor cells. [ABSTRACT FROM AUTHOR]

In many fields, complicated issues can now be solved with the help of Artificial Intelligence (AI) and Machine Learning (ML). One of the more modern Metaheuristic (MH) algorithms used to tackle numerous issues in various fields is the Beluga Whale Optimization (BWO) method. However, BWO has a lack of diversity, which could lead to being trapped in local optimaand premature convergence. This study presents two stages for enhancing the fundamental BWO algorithm. The initial stage of BWO's Opposition-Based Learning (OBL), also known as OBWO, helps to expedite the search process and enhance the learning methodology to choose a better generation of candidate solutions for the fundamental BWO. The second step, referred to as OBWOD, combines the Dynamic Candidate Solution (DCS) and OBWO based on the k-Nearest Neighbor (kNN) classifier to boost variety and improve the consistency of the selected solution by giving potential candidates a chance to solve the given problem with a high fitness value. A comparison study with present optimization algorithms for single-objective bound-constraint optimization problems was conducted to evaluate the performance of the OBWOD algorithm on issues from the 2022 IEEE Congress on Evolutionary Computation (CEC'22) benchmark test suite with a range of dimension sizes. The results of the statistical significance test confirmed that the proposed algorithm is competitive with the optimization algorithms. In addition, the OBWOD algorithm surpassed the performance of seven other algorithms with an overall classification accuracy of 85.17% for classifying 10 medical datasets with different dimension sizes according to the performance evaluation matrix. [ABSTRACT FROM AUTHOR]

Sparse data with a high portion of zeros arise in various disciplines. Modeling sparse high-dimensional data is a challenging and growing research area. In this paper, we provide statistical methods and tools for analyzing sparse data in a fairly general and complex context. We utilize two real scientific applications as illustrations, including a longitudinal vaginal microbiome data and a high dimensional gene expression data. We recommend zero-inflated model selections and significance tests to identify the time intervals when the pregnant and non-pregnant groups of women are significantly different in terms of Lactobacillus species. We apply the same techniques to select the best 50 genes out of 2426 sparse gene expression data. The classification based on our selected genes achieves 100% prediction accuracy. Furthermore, the first four principal components based on the selected genes can explain as high as 83 % of the model variability. [ABSTRACT FROM AUTHOR]

Simple Summary: Sodium butyrate (NaB) is a short-chain fatty acid produced by intestinal microbial fermentation of dietary fiber. It has been shown to be effective in inhibiting colorectal cancer (CRC), but the mechanism is not known. We verified the ability of NaB to induce ferroptosis and the effect on relevant genotypes in normal intestinal cells and colorectal tumor cells, respectively. Moreover, better inhibition of tumor cells was observed when NaB was combined with Erastin (a ferroptosis-positive drug), suggesting that NaB combined with Erastin might have a stronger anti-CRC effect. Colorectal cancer (CRC) is one of the most common malignancies, and effective treatment and prevention methods are lacking. Sodium butyrate (NaB) is a short-chain fatty acid produced by intestinal microbial fermentation of dietary fiber. It has been shown to be effective in inhibiting CRC, but the mechanism is not known. Methods: Human normal intestinal epithelial cell line FHT and colorectal tumor cell line HCT-116 were treated with NaB alone or in combination with different programmed cell death inhibitors. Cell activity was then assessed with MTT assays and PI staining; ferroptosis with Fe2+, glutathione (GSH), and lipid peroxidation assays; signaling pathway screening with PCR arrays; and CD44, SCL7A11, and GPX4 expression with Western blotting. A CD44-overexpressing HCT-116 cell line was constructed to determine the effect of the overexpression of CD44 on NaB-induced ferroptosis. The synergistic effect of co-treatment with NaB and Erastin was assessed by isobolographic analysis. Results: NaB induced apoptosis and ferroptosis in HCT-116 cells but only induced low-level apoptosis in FHC cells. Moreover, NaB significantly increased intracellular Fe2+ and promoted GSH depletion and lipid peroxidation in HCT-116 cells. Ferroptosis-related qPCR array analysis identified CD44/SLC7A11 as a potential effector molecular of NaB-induced ferroptosis. NaB significantly inhibited the expression of CD44 and SLC7A11 in mouse CRC tissues. A CD44 overexpressed HCT-116 cell line was used to verify that CD44/SLC7A11 was a key signaling pathway that NaB-induced GSH depletion, lipid peroxidation accumulation, and ferroptosis in HCT-116 cells. Examination of whether NaB can increase the effect of ferroptosis agents showed that NaB, in combination with Erastin, a ferroptosis inducer, further promoted HCT-116 cell death and increased changes of ferroptosis markers. Conclusions: Our results suggest that NaB induces ferroptosis in CRC cells through the CD44/SLC7A11 signaling pathway and has synergistic effects with Erastin. These results may provide new insights into CRC prevention and the combined use of NaB and ferroptosis-inducing agents. [ABSTRACT FROM AUTHOR]

Simple Summary: We have recently reported that the cytosolic C-terminal domain (CTD) of the tumour suppressor PTCH1, the Hedgehog proteins receptor, interacts with the autophagy-related protein ATG101 and impairs autophagic flux. In this study, we identified the interaction region and found that it is absent in a subset of colorectal, stomach and endometrial cancers. We demonstrated that truncation mutants lack the ability to constraint autophagy, resulting in a proliferative advantage and reduced sensitivity to autophagy inducers or glycolysis inhibitors in cell lines harbouring endogenous PTCH1 CTD mutations compared to isogenic cells expressing wild-type PTCH1. In summary, this study highlights the importance of the PTCH1-ATG101 interaction in the regulation of basal and stimulated autophagy and the metabolic flexibility in cancer cells. The Hedgehog receptor, Patched1 (PTCH1), is a well-known tumour suppressor. While the tumour suppressor's activity is mostly ascribed to its function as a repressor of the canonical Smoothened/Gli pathway, its C-terminal domain (CTD) was reported to have additional non-canonical functions. One of them is the reduction of autophagic flux through direct interaction with the Unc-51, like the autophagy activating kinase (ULK) complex subunit autophagy-related protein-101 (ATG101). With the aim of investigating whether this function of PTCH1 is important in cancer cell fitness, we first identified frameshift mutations in the CTD of PTCH1 in cancer databases. We demonstrated that those mutations disrupt PTCH1 interaction with ATG101 and increase autophagic flux. Using deletion mutants of the PTCH1 CTD in co-immunoprecipitation studies, we established that the 1309–1447 region is necessary and sufficient for interaction with ATG101. We next showed that the three most common PTCH1 CTD mutations in endometrial, stomach and colon adenocarcinomas that cause frameshifts at S1203, R1308 and Y1316 lack the ability to interact with ATG101 and limit autophagic flux, determined by bafilomycin A1-sensitive accumulation of the autophagy markers LC3BII and p62. We next engineered PTCH1 indel mutations at S1223 by CRISPR/Cas9 in SW620 colon cancer cells. Comparison of two independent clones harbouring PTCH1 S1223fs mutations to their isogenic parental cell lines expressing wild-type PTCH1 showed a significant increase in basal and rapamycin-stimulated autophagic flux, as predicted by loss of ATG101 interaction. Furthermore, the PTCH1 CTD mutant cells displayed increased proliferation in the presence of rapamycin and reduced sensitivity to glycolysis inhibitors. Our findings suggest that loss of the PTCH1-ATG101 interaction by mutations in the CTD of PTCH1 in cancer might confer a selective advantage by stimulating autophagy and facilitating adaptation to nutrient deprivation conditions. [ABSTRACT FROM AUTHOR]

Background: This randomized clinical trial was conducted to assess whether sleep bruxism (SB) is associated with an increased rate of technical complications (ceramic defects) in lithium disilicate (LiDi) or zirconia (Z) molar single crowns (SCs). Methods: Adult patients were classified as affected or unaffected by SB based on structured questionnaires, clinical signs, and overnight portable electromyography (BruxOff) and block randomized into four groups according to SB status and crown material (LiDi or Z): LiDi-SB (n = 29), LiDi-no SB (n = 24), Z-SB (n = 23), and Z-no SB (n = 27). Differences in technical complications (main outcome) and survival and success rates (secondary outcomes) one year after crown cementation were assessed using Fisher's exact test with significance level α = 0.05. Results: No technical complications occurred. Restoration survival rates were 100% in the LiDi-SB and LiDi-no SB groups, 95.7% in the Z-SB group, and 96.3% in the Z-no SB group (p > 0.999). Success rates were 96.6% in the LiDi-SB group, 95.8% in the LiDi-no SB group (p > 0.999), 91.3% in the Z-SB group, and 96.3% in the Z-no SB group (p ≥ 0.588). Conclusions: With a limited observation time and sample size, no effect of SB on technical complication, survival, and success rates of molar LiDi and Z SCs was detected. [ABSTRACT FROM AUTHOR]