Search

Background: No randomized controlled trials have compared implant and flap reconstruction. Recently, worse longitudinal outcomes have been suggested for flap reconstruction. The authors compared long-term oncologic outcomes of postmastectomy breast reconstruction using propensity score matching., Methods: A retrospective study of postmastectomy reconstruction was achieved using the Weill Cornell Breast Cancer Registry between 1998 and 2019. Patients were matched using propensity scores based on demographic, clinical, and surgical characteristics. Kaplan-Meier estimates, Cox-regression models, and restricted mean survival times (RMST) were used to evaluate patient outcomes., Results: Before matching, 1395 implant and 586 flap patients were analyzed. No difference in overall survival and recurrence were observed. Multivariable models showed decreased survival for Medicare/Medicaid [hazard ratio (HR), 3.09; 95% CI, 1.63 to 5.87; P < 0.001], pathologic stage II (HR, 2.98; 95% CI, 1.12 to 7.90; P = 0.028), stage III (HR, 4.88; 95% CI, 1.54 to 15.5; P = 0.007), 11 to 20 lymph nodes positive (HR, 3.66; 95% CI, 1.31 to 10.2; P = 0.013), more than 20 lymph nodes positive (HR, 6.41; 95% CI, 1.49 to 27.6; P = 0.013). RMST at 10 years after flap reconstruction showed 2 months of decreased survival time compared with implants (9.56 versus 9.74 years; 95% CI, -0.339 to -0.024; P = 0.024). After matching, 563 implant and 563 flap patients were compared. Reconstruction was not associated with overall survival and recurrence. RMST between implant and flap reconstruction showed no difference in each 5-year interval over 20 years., Conclusion: Postmastectomy breast reconstruction was not associated with a difference in long-term oncologic outcomes over a 20-year period., Clinical Question/level of Evidence: Therapeutic, III., (Copyright © 2023 by the American Society of Plastic Surgeons.)

The reproductive characteristics of understory bamboo and the effects of dieback on overstory tree seedlings through temporal changes in the environment at the forest floor have only been examined in a few bamboo species, due to the unpredictable occurrence of flowering events and long intervals between them but provide valuable information on tree regeneration and succession in a forest with dense dwarf bamboo cover. We investigated environmental conditions and assessed seedlings (< 30-cm tall) of the dwarf bamboo Sasa borealis and overstory tree species at 44-50 measurement points during 2016-2021, which included a S. borealis mass flowering event in 2017. We also conducted seed germination tests to determine germination rates and patterns in S. borealis. Environmental factors affecting seedling recruitment of S. borealis and of overstory trees were analysed using spatiotemporal generalized linear mixed models in the Bayesian framework. We observed gradual temporal changes in the environment, including increasing canopy openness and decreasing maximum height of dead S. borealis culms. The seeds germinated slowly and the emergence of current-year S. borealis seedlings peaked in spring-summer in 2019. The tree seedling density after 2019 increased significantly compared to that before the dieback. The model results suggest that tree seedling establishment was enhanced by increased light availability. Continuous field observation beginning before S. borealis dieback revealed gradually enhanced tree recruitment in response to slow decay of the remaining dead culms and slow recovery of S. borealis. The seedling regeneration pattern of understory bamboo partly contributes to a prolonged opportunity for overstory tree regeneration., (© 2023 John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.)

With big data becoming widely available in healthcare, machine learning algorithms such as random forest (RF) that ignores time-to-event information and random survival forest (RSF) that handles right-censored data are used for individual risk prediction alternatively to the Cox proportional hazards (Cox-PH) model. We aimed to systematically compare RF and RSF with Cox-PH. RSF with three split criteria [log-rank (RSF-LR), log-rank score (RSF-LRS), maximally selected rank statistics (RSF-MSR)]; RF, Cox-PH, and Cox-PH with splines (Cox-S) were evaluated through a simulation study based on real data. One hundred eighty scenarios were investigated assuming different associations between the predictors and the outcome (linear/linear and interactions/nonlinear/nonlinear and interactions), training sample sizes (500/1000/5000), censoring rates (50%/75%/93%), hazard functions (increasing/decreasing/constant), and number of predictors (seven, 15 including noise variables). Methods' performance was evaluated with time-dependent area under curve and integrated Brier score. In all scenarios, RF had the worst performance. In scenarios with a low number of events (⩽70), Cox-PH was at least noninferior to RSF, whereas under linearity assumption it outperformed RSF. Under the presence of interactions, RSF performed better than Cox-PH as the number of events increased whereas Cox-S reached at least similar performance with RSF under nonlinear effects. RSF-LRS performed slightly worse than RSF-LR and RSF-MSR when including noise variables and interaction effects. When applied to real data, models incorporating survival time performed better. Although RSF algorithms are a promising alternative to conventional Cox-PH as data complexity increases, they require a higher number of events for training. In time-to-event analysis, algorithms that consider survival time should be used., (© 2022 Wiley-VCH GmbH.)

Window mean survival time (WMST), a simple extension of restricted mean survival time (RMST), allows for clinicians to evaluate the mean survival difference between treatment groups in specific windows of time during the follow-up period of a trial. The advantages of WMST are numerous. Not only does it produce estimates of treatment effect that can be meaningfully interpreted, but also has power advantages over competing methods when hazards are non-proportional (NPH). WMST, like RMST, is currently underutilized due to clinicians' lack of familiarity with tests comparing mean survival times and the lack of tools to facilitate trial design with this endpoint. The aim of this article is to provide investigators with insights and software to design trials with WMST as the primary endpoint. Functions for performing power and sample size calculations are provided in the survWMST package in R available on GitHub., (© 2023 John Wiley & Sons Ltd.)

Recent observations, especially in cancer immunotherapy clinical trials with time-to-event outcomes, show that the commonly used proportional hazard assumption is often not justifiable, hampering an appropriate analysis of the data by hazard ratios. An attractive alternative advocated is given by the restricted mean survival time (RMST), which does not rely on any model assumption and can always be interpreted intuitively. Since methods for the RMST based on asymptotic theory suffer from inflated type-I error under small sample sizes, a permutation test was proposed recently leading to more convincing results in simulations. However, classical permutation strategies require an exchangeable data setup between comparison groups which may be limiting in practice. Besides, it is not possible to invert related testing procedures to obtain valid confidence intervals, which can provide more in-depth information. In this paper, we address these limitations by proposing a studentized permutation test as well as respective permutation-based confidence intervals. In an extensive simulation study, we demonstrate the advantage of our new method, especially in situations with relatively small sample sizes and unbalanced groups. Finally, we illustrate the application of the proposed method by re-analyzing data from a recent lung cancer clinical trial., (© 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

The restricted mean survival time (RMST) evaluates the expectation of survival time truncated by a prespecified time point, because the mean survival time in the presence of censoring is typically not estimable. The frequentist inference procedure for RMST has been widely advocated for comparison of two survival curves, while research from the Bayesian perspective is rather limited. For the RMST of both right- and interval-censored data, we propose Bayesian nonparametric estimation and inference procedures. By assigning a mixture of Dirichlet processes (MDP) prior to the distribution function, we can estimate the posterior distribution of RMST. We also explore another Bayesian nonparametric approach using the Dirichlet process mixture model and make comparisons with the frequentist nonparametric method. Simulation studies demonstrate that the Bayesian nonparametric RMST under diffuse MDP priors leads to robust estimation and under informative priors it can incorporate prior knowledge into the nonparametric estimator. Analysis of real trial examples demonstrates the flexibility and interpretability of the Bayesian nonparametric RMST for both right- and interval-censored data., (© 2022 The International Biometric Society.)

Delayed separation of survival curves is a common occurrence in confirmatory studies in immuno-oncology. Many novel statistical methods that aim to efficiently capture potential long-term survival improvements have been proposed in recent years. However, the vast majority do not consider stratification, which is a major limitation considering that most large confirmatory studies currently employ a stratified primary analysis. In this article, we combine recently proposed weighted log-rank tests that have been designed to work well under a delayed separation of survival curves, with stratification by a baseline variable. The aim is to increase the efficiency of the test when the stratifying variable is highly prognostic for survival. As there are many potential ways to combine the two techniques, we compare several possibilities in an extensive simulation study. We also apply the techniques retrospectively to two recent randomized clinical trials., (© 2023 Wiley-VCH GmbH.)

Despite advances in surgical and therapeutic approaches, high-grade serous ovarian carcinoma (HGSOC) prognosis remains poor. Surgery is an indispensable component of therapeutic protocols, as removal of all visible tumor lesions (cytoreduction) profoundly improves the overall survival. Enhanced predictive tools for assessing cytoreduction are essential to optimize therapeutic precision. Patients' immune status broadly reflects the tumor cell biological behavior and the patient responses to disease and treatment. Serum cytokine profiling is a sensitive measure of immune adaption and deviation, yet its integration into treatment paradigms is underexplored. This study is part of the IMPACT trial (NCT03378297) and aimed to characterize immune responses before and during primary treatment for HGSOC to identify biomarkers for treatment selection and prognosis. Longitudinal serum samples from 22 patients were collected from diagnosis until response evaluation. Patients underwent primary cytoreductive surgery or neoadjuvant chemotherapy (NACT) based on laparoscopy scoring. Twenty-seven serum cytokines analyzed by Bio-Plex 200, revealed two immune phenotypes at diagnosis: Immune High with marked higher serum cytokine levels than Immune Low. The immune phenotypes reflected the laparoscopy scoring and allocation to surgical treatment. The five Immune High patients undergoing primary cytoreductive surgery exhibited immune mobilization and extended progression-free survival, compared to the Immune Low patients undergoing the same treatment. Both laparoscopy and cytoreductive surgery induced substantial and transient changes in serum cytokines, with upregulation of the inflammatory cytokine IL-6 and downregulation of the multifunctional cytokines IP-10, Eotaxin, IL-4, and IL-7. Over the study period, cytokine levels uniformly decreased in all patients, leading to the elimination of the initial immune phenotypes regardless of treatment choice. This study reveals distinct pre-treatment immune phenotypes in HGSOC patients that might be informative for treatment stratification and prognosis. This potential novel biomarker holds promise as a foundation for improved assessment of treatment responses in patients with HGSOC. ClinicalTrials.gov Identifier: NCT03378297. [ABSTRACT FROM AUTHOR]

Background: In recent years, the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing globally. Despite advances in the diagnosis and treatment of AEG, the overall prognosis for AEG patients remains concerning. Therefore, analyzing prognostic factors for AEG patients of Siewert type II and constructing a prognostic model for AEG patients is important. Methods: Data of primary Siewert type II AEG patients from the SEER database from 2004 to 2015 were obtained and randomly divided into training and internal validation cohort. Additionally, data of primary Siewert type II AEG patients from the China Medical University Dandong Central Hospital from 2012 to 2018 were collected for external validation. Each variable in the training set underwent univariate Cox analysis, and variables with statistical significance (p < 0.05) were added to the LASSO equation for feature selection. Multivariate Cox analysis was then conducted to determine the independent predictive factors. A nomogram for predicting overall survival (OS) was developed, and its performance was evaluated using ROC curves, calibration curves, and decision curves. NRI and IDI were calculated to assess the improvement of the new prediction model relative to TNM staging. Patients were stratified into high-risk and low-risk groups based on the risk scores from the nomogram. Results: Age, Differentiation grade, T stage, M stage, and LODDS (Log Odds of Positive Lymph Nodes)were independent prognostic factors for OS. The AUC values of the ROC curves for the nomogram in the training set, internal validation set, and external validation set were all greater than 0.7 and higher than those of TNM staging alone. Calibration curves indicated consistency between the predicted and actual outcomes. Decision curve analysis showed moderate net benefit. The NRI and IDI values of the nomogram were greater than 0 in the training, internal validation, and external validation sets. Risk stratification based on the nomogram’s risk score demonstrated significant differences in survival rates between the high-risk and low-risk groups. Conclusion: We developed and validated a nomogram for predicting overall survival (OS) in patients with Siewert type II AEG, which assists clinicians in accurately predicting mortality risk and recommending personalized treatment strategies. [ABSTRACT FROM AUTHOR]

The past decade has witnessed a revolution in cancer treatment, shifting from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular immune-checkpoint inhibitors (ICIs). These immunotherapies release the host's immune system against the tumor and have shown unprecedented durable remission for patients with cancers that were thought incurable, such as metastatic melanoma, metastatic renal cell carcinoma (RCC), microsatellite instability (MSI) high colorectal cancer and late stages of non-small cell lung cancer (NSCLC). However, about 80% of the patients fail to respond to these immunotherapies and are therefore left with other less effective and potentially toxic treatments. Identifying and understanding the mechanisms that enable cancerous cells to adapt to and eventually overcome therapy can help circumvent resistance and improve treatment. In this review, we describe the recent discoveries on the oncoimmunological processes which govern the tumor microenvironment and their impact on the resistance to PD-1/PD-L1 checkpoint blockade. [ABSTRACT FROM AUTHOR]

Tissue biopsy remains the standard for diagnosing gastrointestinal stromal tumors (GISTs), although liquid biopsy is emerging as a promising alternative in oncology. In this pilot study, we advocate for droplet digital PCR (ddPCR) to diagnose GIST in tissue samples and explore its potential for early diagnosis via liquid biopsy, focusing on the PDGFRA D842V mutation and SEPT9 hypermethylated gene. We utilized ddPCR to analyze the predominant PDGFRA mutation (D842V) in surgical tissue samples from 15 GIST patients, correlating with pathologists' diagnoses. We expanded our analysis to plasma samples to compare DNA alterations between tumor tissue and plasma, also investigating SEPT9 gene hypermethylation. We successfully detected the PDGFRA D842V mutation in GIST tissues by ddPCR. Despite various protocols to enhance mutation detection in early-stage disease, it remained challenging, likely due to the low concentration of DNA in plasma samples. Additionally, the results of Area Under the Curve (AUC) for the hypermethylated SEPT9 gene, analyzing concentration, ratio, and abundance were 0.74 (95% Confidence Interval (CI): 0.52 to 0.97), 0.77 (95% CI: 0.56 to 0.98), and 0.79 (95% CI: 0.59 to 0.99), respectively. As a rare disease, the early detection of GIST through such biomarkers is particularly crucial, offering significant potential to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Ceramizable silicone rubber (CSR) composed of silicone rubber matrix and inorganic fillers can be transformed into a dense flame-retardant ceramic upon encountering high temperatures or flames. Conventionally, CSR can be sintered into a dense ceramic at temperatures above 1000 °C, which is higher than the melting point of a copper conductor used in a power cable. In this study, the vulcanization process and mass ratio of inorganic fillers of CSR were studied to lower its ceramization temperature to 950 °C. The electrical and mechanical properties of CSRs and their ceramic bulks were studied with various ratios of wollastonite and muscovite. It was found that the CSR samples could be successfully fabricated using a two-step vulcanization technique (at 120 °C and 150 °C, respectively). As a high ratio of muscovite filler was introduced into the CSR, the sample presented a high dc electrical resistivity of 6.713 × 1014 Ω·cm, and a low dielectric constant of 4.3 and dielectric loss of 0.025 at 50 Hz. After the thermal sintering (at 950 °C for 1 h) of the CSR sample with a high ratio of muscovite, the ceramic sample exhibits a dense microstructure without any pores. The ceramic also demonstrates excellent insulating properties, with a volume resistivity of 8.69 × 1011 Ω·cm, and a low dielectric loss of 0.01 at 50 Hz. Meanwhile, the three-point bending strength of the ceramic sample reaches a value of 110.03 MPa. This study provides a potential route to fabricate CSR used for fire-resistant cables. [ABSTRACT FROM AUTHOR]

Background: Several clinical prognostic models for diffuse large B‐cell lymphoma (DLBCL) have been proposed, including the most commonly used International Prognostic Index (IPI), the National Comprehensive Cancer Network IPI (NCCN‐IPI), and models incorporating beta‐2 microglobulin (β2M). However, the role of β2M in DLBCL patients is not fully understood. Methods: We identified 6075 patients with newly diagnosed DLBCL treated with immunochemotherapy registered in the Danish Lymphoma Registry. Results: A total of 3232 patients had data available to calculate risk scores from each of the nine considered risk models for DLBCL, including a model developed from our population. Three of four models with β2M and NCCN‐IPI performed better than the International Prognostic Indexes (IPI, age‐adjusted IPI, and revised IPI). Five‐year overall survival for high‐ and low‐risk patients were 43.6% and 86.4% for IPI and 34.9% and 96.2% for NCCN‐IPI. In univariate analysis, higher levels of β2M were associated with inferior survival, higher tumor burden (advanced clinical stage and bulky disease), previous malignancy and increased age, and creatinine levels. Furthermore, we developed a model (β2M‐NCCN‐IPI) by adding β2M to NCCN‐IPI (c‐index 0.708) with improved discriminatory ability compared to NCCN‐IPI (c‐index 0.698, p < 0.05) and 5‐year OS of 33.1%, 56.2%, 82.4%, and 96.4% in the high, high‐intermediate, low‐intermediate and low‐risk group, respectively. Conclusion: International Prognostic Indices, except for NCCN‐IPI, fail to accurately discriminate risk groups in the rituximab era. β2M, a readily available marker, could improve the discriminatory performance of NCCN‐IPI and should be re‐evaluated in the development setting of future models for DLBCL. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate the relationship between the severity of autism, emotional and behavioral problems of autistic children, internalized stigma, depressive symptoms, and primary caregiver parental stress. Specifically, we explored the mediating role of internal stigmatization and total difficulties of individuals with autism on parenting stress and depressive symptoms of the primary caregiver. Method: Mothers of 93 children with autism were included in the study. The mothers were given the Beck Depression Inventory (BDI), The Internalized Stigma of Mental Illness Scale (ISMI), the Autism Behavior Checklist, the Parenting Stress Index-Short Form, Strength, and Difficulties Questionnaire -Parent Form (SDQ-P). Results: As a result of our study, the emotional and behavioral problems of the child and the internalized stigmatization felt by the parent played a mediator role in the relationship between the child's autism severity and the parent's stress and depressive symptoms. Conclusions: Our findings highlight that internalized stigmatization and behavioral characteristics of individuals with autism are among the most critical problems for their primary caregivers. These results have important implications for the development of interventions aimed at reducing the internalized stigma experienced by primary caregivers of individuals with autism and for improving their mental health outcomes. [ABSTRACT FROM AUTHOR]

Background: This study aimed to develop a higher performance nomogram based on explainable machine learning methods, and to predict the risk of death of stroke patients within 30 days based on clinical characteristics on the first day of intensive care units (ICU) admission. Methods: Data relating to stroke patients were extracted from the Medical Information Marketplace of the Intensive Care (MIMIC) IV and III database. The LightGBM machine learning approach together with Shapely additive explanations (termed as explain machine learning, EML) was used to select clinical features and define cut-off points for the selected features. These selected features and cut-off points were then evaluated using the Cox proportional hazards regression model and Kaplan-Meier survival curves. Finally, logistic regression-based nomograms for predicting 30-day mortality of stroke patients were constructed using original variables and variables dichotomized by cut-off points, respectively. The performance of two nomograms were evaluated in overall and individual dimension. Results: A total of 2982 stroke patients and 64 clinical features were included, and the 30-day mortality rate was 23.6% in the MIMIC-IV datasets. 10 variables ("sofa (sepsis-related organ failure assessment)", "minimum glucose", "maximum sodium", "age", "mean spo2 (blood oxygen saturation)", "maximum temperature", "maximum heart rate", "minimum bun (blood urea nitrogen)", "minimum wbc (white blood cells)" and "charlson comorbidity index") and respective cut-off points were defined from the EML. In the Cox proportional hazards regression model (Cox regression) and Kaplan-Meier survival curves, after grouping stroke patients according to the cut-off point of each variable, patients belonging to the high-risk subgroup were associated with higher 30-day mortality than those in the low-risk subgroup. The evaluation of nomograms found that the EML-based nomogram not only outperformed the conventional nomogram in NIR (net reclassification index), brier score and clinical net benefits in overall dimension, but also significant improved in individual dimension especially for low "maximum temperature" patients. Conclusions: The 10 selected first-day ICU admission clinical features require greater attention for stroke patients. And the nomogram based on explainable machine learning will have greater clinical application. [ABSTRACT FROM AUTHOR]

This article presents a new method for synthesizing α-quaternary carbaldehydes through the chemoselective House-Meinwald rearrangement of trisubstituted epoxides. The authors used Brønsted acids as catalysts and identified optimal reaction conditions. The method allows for the synthesis of various carbaldehydes and has been validated for stereospecific reactions. The authors suggest that this method could be useful in the total synthesis of natural products. [Extracted from the article]

Recognizing the pivotal role of circadian rhythm in the human aging process and its scalability through wearables, we introduce CosinorAge, a digital biomarker of aging developed from wearable-derived circadian rhythmicity from 80,000 midlife and older adults in the UK and US. A one-year increase in CosinorAge corresponded to 8–12% higher all-cause and cause-specific mortality risks and 3–14% increased prospective incidences of age-related diseases. CosinorAge also captured a non-linear decline in resilience and physical functioning, evidenced by an 8–33% reduction in self-rated health and a 3–23% decline in health-related quality of life score, adjusting for covariates and multiple testing. The associations were robust in sensitivity analyses and external validation using an independent cohort from a disparate geographical region using a different wearable device. Moreover, we illustrated a heterogeneous impact of circadian parameters associated with biological aging, with young (<45 years) and fast agers experiencing a substantially delayed acrophase with a 25-minute difference in peak timing compared to slow agers, diminishing to a 7-minute difference in older adults (>65 years). We demonstrated a significant enhancement in the predictive performance when integrating circadian rhythmicity in the estimation of biological aging over physical activity. Our findings underscore CosinorAge's potential as a scalable, economic, and digital solution for promoting healthy longevity, elucidating the critical and multifaceted circadian rhythmicity in aging processes. Consequently, our research contributes to advancing preventive measures in digital medicine. [ABSTRACT FROM AUTHOR]

Background: Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited. Methods: Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment. Results: A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways. Conclusion: In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD. [ABSTRACT FROM AUTHOR]

Rapid development of tracking technologies allow the collection of high‐quality data on multiple simultaneously moving individuals. This, in turn, initiated the development of several methods to infer interactions among moving animals. However, the performance of these methods has not been studied systematically, especially with regard to the factors that are highly relevant for field ecologists, such as duration of the tracking period, its temporal resolution and the proportion of the tracked community.Here, we assessed the performance of three dynamic interaction indices (Coefficient of sociality, Correlation coefficient and Dynamic interaction) and two novel approaches based on step selection functions (SSF‐occurrence‐distribution and SSF‐distance). We tested these methods on the data simulated with a predator–prey system, reflecting three common types of interactions while on the move: avoidance (prey individuals fleeing from the predator), attraction (predator following and chasing prey) and neutral movement (no interactions between predator and prey). We assessed the ability of each method to correctly detect the modelled interaction type by manipulating the perceptual range of the predator, the proportion of tracked prey individuals, the temporal resolution and the duration of the tracking period.We found that the ability to correctly infer interactions increased for all methods with an increase in the perceptual range of the predator and the proportion of tracked prey individuals. In contrast, the duration of the tracking period affected the methods' performance differently: some methods (Cs and SSF‐distance) were insensitive to it, whereas the performance of other methods improved (DI and SSF‐occurrence‐distribution) and worsened (Cr) with the duration of the tracking period. The three dynamic interaction indices and SSF‐distance were rather robust to changes in data resolution.Despite using the predator–prey system as our study case, our findings are applicable to other systems in which two animals on move may interact. We formulate guidelines for field ecologists studying animal movement to select the most suitable method depending on the availability of tracking devices, the duration and resolution of the tracking they can afford, as well as perceptual ranges of study species. [ABSTRACT FROM AUTHOR]

For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under non-proportional hazard. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific non-proportional hazard situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles. [ABSTRACT FROM AUTHOR]

Major advancements in human pluripotent stem cell (hPSC) technology over recent years have yielded valuable tools for cardiovascular research. Multi-cell type 3-dimensional (3D) cardiac models in particular, are providing complementary approaches to animal studies that are better representatives than simple 2-dimensional (2D) cultures of differentiated hPSCs. These human 3D cardiac models can be broadly divided into two categories; namely those generated through aggregating pre-differentiated cells and those that form self-organizing structures during their in vitro differentiation from hPSCs. These models can either replicate aspects of cardiac development or enable the examination of interactions among constituent cell types, with some of these models showing increased maturity compared with 2D systems. Both groups have already emerged as physiologically relevant pre-clinical platforms for studying heart disease mechanisms, exhibiting key functional attributes of the human heart. In this review, we describe the different cardiac organoid models derived from hPSCs, their generation methods, applications in cardiovascular disease research and use in drug screening. We also address their current limitations and challenges as pre-clinical testing platforms and propose potential improvements to enhance their efficacy in cardiac drug discovery. [ABSTRACT FROM AUTHOR]

Deep learning has recently demonstrated the ability to predict long-term patient risk and its stratification when trained on imaging data such as chest radiographs. However, existing methods formulate estimating patient risk as a binary classification, typically ignoring or limiting the use of temporal information, and not accounting for the loss of patient follow-up, which reduces the fidelity of estimation and limits the prediction to a certain time horizon. In this paper, we demonstrate that deep survival and time-to-event prediction models can outperform binary classifiers at predicting mortality and risk of adverse health events. In our study, deep survival models were trained to predict risk scores from chest radiographs and patient demographic information in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial (25,433 patient data points used in this paper) for 2-, 5-, and 10-year time horizons. Binary classification models that predict mortality at these time horizons were built as baselines. Compared to the considered alternative, deep survival models improve the Brier score (5-year: 0.0455 [95% CI, 0.0427–0.0482] vs. 0.0555 [95% CI, (0.0535–0.0575)], p < 0.05) and expected calibration error (ECE) (5-year: 0.0110 [95% CI, 0.0080–0.0141] vs. 0.0747 [95% CI, 0.0718–0.0776], p < 0.05) for those fixed time horizons and are able to generate predictions for any time horizon, without the need to retrain the models. Our study suggests that deep survival analysis tools can outperform binary classification in terms of both discriminative performance and calibration, offering a potentially plausible solution for forecasting risk in clinical practice. [ABSTRACT FROM AUTHOR]

This report describes major pathomechanisms of disease in which the dysregulation of host inflammatory processes is a major factor, with cardiovascular disease (CVD) as a primary model, and reviews strategies for countermeasures based on synergistic interaction between various agents, including drugs and generally regarded as safe (GRAS) natural medical material (NMM), such as Ginkgo biloba, spice phytochemicals, and fruit seed flavonoids. The 15 well-defined CVD classes are explored with particular emphasis on the extent to which oxidative stressors and associated ischemia-reperfusion tissue injury contribute to major symptoms. The four major categories of pharmaceutical agents used for the prevention of and therapy for CVD: statins, beta blockers (β-blockers), blood thinners (anticoagulants), and aspirin, are presented along with their adverse effects. Analyses of major cellular and molecular features of drug- and NMM-mediated cardioprotective processes are provided in the context of their development for human clinical application. Future directions of the evolving research described here will be particularly focused on the characterization and manipulation of calcium- and calcineurin-mediated cascades of signaling from cell surface receptors on cardiovascular and immune cells to the nucleus, with the emergence of both protective and pathological epigenetic features that may be modulated by synergistically-acting combinations of drugs and phytochemicals in which phytochemicals interact with cells to promote signaling that reduces the effective dosage and thus (often) toxicity of drugs. [ABSTRACT FROM AUTHOR]

Although treatable with antiretroviral therapy, HIV infection persists in people living with HIV (PLWH). It is well known that the HIV virus finds refuge in places for which antiretroviral medications do not reach therapeutic levels, mainly the CNS. It is clear that as PLWH age, the likelihood of developing HIV-associated neurological deficits increases. At the biochemical level neurological dysfunction is the manifestation of altered cellular function and ineffective intercellular communication. In this review, we examine how intercellular signaling in the brain is disrupted in the context of HIV. Specifically, the concept of how the blood-brain barrier can be a convergence point for crosstalk, is explored. Crosstalk between the cells of the neurovascular unit (NVU) (endothelium, pericytes, astrocytes, microglia and neurons) is critical for maintaining proper brain function. In fact, the NVU allows for rapid matching of neuronal metabolic needs, regulation of blood-brain barrier (BBB) dynamics for nutrient transport and changes to the level of immunosurveillance. This review invites the reader to conceptually consider the BBB as a router or convergence point for NVU crosstalk, to facilitate a better understanding of the intricate signaling events that underpin the function of the NVU during HIV associated neuropathology. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer (LC) is one of the most common and serious types of cancer. Unfortunately, it is not easy to detect in the early stages of the disease due to the absence of symptoms. Many patients have late-stage LC when they are diagnosed, and this is associated with limited treatment options and poor survival rates. To try to improve this, we have assessed which proteins in LC patients are recognised by the immune response and could be used to screen at-risk patients for LC before symptoms appear. We have shown that panels of blood and sputum biomarkers may offer the most effective way to improve early LC detection. Lung cancer (LC) is one of the leading causes of cancer-related deaths. Pulmonary nodules are one of the risk factors, and their discovery rate has been increasing due to enhanced performance of chest CT scans, but more than 90% are non-malignant, causing unnecessary stress to patients and costs to healthcare providers. Early diagnosis of LC is associated with a 5-year survival rate of up to 75% following surgical resection, but LC is often diagnosed late due to a lack of symptoms and poor 5-year survival rates as low as 10%. The cost of LC diagnosis is high, with 40% of it associated with benign lesions, which are difficult to differentiate from malignant lesions. Tumour-associated antigens (TAAs) may provide one way in which LC could be diagnosed early using minimally-invasive techniques, under their association with immune responses and specificity for disease. Here we discuss the potential of cancer-testis antigens (CTAs) to act as non-invasive biomarkers for the early detection of non-small cell lung cancer. [ABSTRACT FROM AUTHOR]

Copyright of Cerdika : Jurnal Ilmiah Indonesia is the property of Publikasi Indonesia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Japanese traditional (Kampo) medicines containing ephedra may be used to treat colds during pregnancy. There are reports that ephedrine, a component of ephedra, has a risk of teratogenicity; however, the evidence remains equivocal. Objective: This study aimed to evaluate the risk of major congenital malformations (MCMs) associated with exposure to Kampo medicines containing ephedra during the first trimester of pregnancy using the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). Methods: To 23,730 mother–infant pairs who participated in the TMM BirThree Cohort Study from July 2013 to March 2017, questionnaires in early and middle pregnancy were distributed approximately at weeks 12 and 26 of pregnancy, respectively. Infants' risk of MCMs in women who used Kampo medicines containing ephedra or acetaminophen during the first trimester was assessed, and the odds ratios (ORs) were estimated with unadjusted and adjusted analyses. Results: Among 20,879 women, acetaminophen and Kampo medicines containing ephedra were used in 665 (3.19%) and 376 (1.80%) women, respectively, in the first trimester. Among the infants born to the mothers who used acetaminophen or Kampo medicine containing ephedra during the first trimester, 11 (1.65%) and 8 (2.13%), respectively, had overall MCMs. OR of overall MCMs was higher in women who used Kampo medicines containing ephedra than in those who used acetaminophen in the first trimester (adjusted OR, 1.45; 95% confidence interval (CIs), 0.57–3.71); however, the difference was not statistically significant. Conclusions: In this study, there was no statistically significant association between the use of Kampo medicines containing ephedra during the first trimester of pregnancy and the risk of MCMs. Although some point estimates of ORs exceeded 1.00, the absolute magnitude of any increased risks would be low. [ABSTRACT FROM AUTHOR]

Excavation‐induced rock failure and deformation near an underground opening boundary is closely associated with the intermediate principal stress, strain softening and rock mass dilation. By combining theoretical analysis and numerical simulation to explore the mechanical evolution of the roadway surrounding rock during excavation. The elastic–plastic criterion solutions for surrounding rock stress, displacement, and the plastic zone of a circular roadway were deduced by including the intermediate principal stress, strain softening and rock mass dilation, based on the Drucker–Prager criterion and the nonassociated flow rule. Furthermore, ABAQUS finite element software was utilized for numerical simulations to scrutinize the influence of mechanical parameters on stress redistribution, surface displacement, and plastic range. The results of the numerical simulations verify the reliability of the theoretical analysis and affirm the high consistency of the results with the theoretical solution. The research findings indicate that the strength of surrounding rock is significantly influenced by the intermediate principal stress, and the deformation and failure of rock mass are primarily impacted by rock mass dilation, while strain softening mainly affects the thickness of the fractured zone. Moreover, the study reveals that enhancing the residual strength of the surrounding rock can improve its resistance to deformation and failure. Furthermore, the excavation of the roadway is observed to increase the original rock stress in the surrounding rock, but increasing the ground support strength effectively controls the deformation and failure of surrounding rock. Ultimately, the research outcomes offer valuable references for engineering calculations and ground support design of surrounding rock in deep roadways. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunotherapy may be beneficial for pancreatic cancer (PC) patients with mismatch repair (MMR) deficiency. Although it is known that MMR deficiency (MMR-D) can result from mutations in MMR genes, the prevalence of these mutations and their impact on the formation of the MMR-D phenotype in PC have been insufficiently researched. Microsatellite instability (MSI) is a hallmark of MMR-D. Here, we estimated the frequency of germline and somatic mutations in the three MMR genes (MLH1, MSH2, and MSH6) in PC patients, estimated the prevalence of MSI, and assessed the relationship between MMR genes mutations and MSI status in PC. In our study of an unselected cohort of PC patients, we identified germline and somatic alterations in MMR genes, however these alterations did not contribute to the MMR-D phenotype. Our findings underscore the necessity of evaluating tumor MMR-D status in PC patients with confirmed Lynch syndrome when deciding whether to administer immunotherapy. Patients with pancreatic cancer (PC) showing mismatch repair (MMR) deficiency may benefit from immunotherapy. Microsatellite instability (MSI) is a hallmark of MMR deficiency (MMR-D). Here, we estimated the prevalence of MSI in PC, investigated germline and somatic mutations in the three MMR genes (MLH1, MSH2, and MSH6), and assessed the relationship between MMR genes mutations and MSI status in PC. Clinical specimens from PC patients were analyzed using targeted next-generation sequencing, including paired normal and tumor specimens from 155 patients, tumor-only specimens from 86 patients, and normal-only specimens from 379 patients. The MSI status of 235 PCs was assessed via PCR. Pathogenic/likely pathogenic (P/LP) germline variants in the MMR genes were identified in 1.1% of patients, while somatic variants were found in 2.6% of patients. No MSI-H tumors were detected. One patient carried two variants (P (VAF = 0.57) and LP (VAF = 0.25)) simultaneously; however, their germline/somatic status remains unknown due to the investigation focusing solely on the tumor and MSI analysis was not performed for this patient. MSI is rare in PC, even in tumors with MMR genes mutations. Our findings underscore the importance of assessing tumor MMR-D status in PC patients with confirmed Lynch syndrome when deciding whether to prescribe immunotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This study addresses the challenge of interpreting the efficacy of immunotherapy in biliary tract cancer (BTC) in terms of overall survival (OS). Traditional methods often rely on the proportional hazard assumption, which may not hold in this context. Instead, we performed a meta-analysis of available phase 3 trials using restricted median survival time (RMST) to measure temporal benefits, providing a clearer picture of the real effects of immunotherapy-based regimens. By incorporating anti-PD-1/anti-PD-L1 agents, our analysis confirmed improvements in estimated mean OS and progression-free survival (PFS) at 24 months, as indicated by RMST, of 1.21 (95% CI: 0.49–1.93) and 1.31 (95% CI: 0.66–1.96) months, respectively. This approach not only offers a more nuanced understanding of clinical benefits, but also aids healthcare providers and patients in making informed decisions about treatment options, emphasizing a methodology that can adapt to the complexities of data. Background: For biliary tract cancer (BTC), the addition of immunotherapy (durvalumab or pembrolizumab) to gemcitabine and cisplatin (GemCis) significantly improved overall survival (OS) in phase 3 clinical trials (RCTs). However, the interpretation and magnitude of the treatment effect is challenging because OS Kaplan–Meier curves violate the proportional hazards (PH) assumption. Analysis using restricted mean survival time (RMST) allows quantification of the benefits in the absence of PH. This systematic review and meta-analysis aims to assess the benefit of immunotherapy-based regimens for OS at 24 months using RMST analysis. Methods: A systematic review was conducted using studies published up to 8 November 2023. Only phase 3 RCTs evaluating the use of anti-PD-1/PD-L1 combined with GemCis and reporting OS were included. KM curves for OS were digitized, and the data were reconstructed. A meta-analysis for OS by RMST at 24 months was performed. Results: A total of 1754 participants from the TOPAZ-1 and KEYNOTE-966 trials were included. In TOPAZ-1, RMSTs at 24 months were 13.52 (7.92) and 12.21 (7.22) months with GemCis plus durvalumab and GemCis alone, respectively. In KEYNOTE-966, RMSTs at 24 months were 13.60 (7.76) and 12.45 (7.73) months with GemCis plus pembrolizumab and GemCis alone, respectively. Immunotherapy-based regimens showed a mean OS difference at 24 months by an RMST of 1.21 months [(95% CI: 0.49–1.93), p < 0.001, I2 = 0%]. Conclusions: Immunotherapy-based regimens improve OS in advanced BTC. Given this magnitude of benefit, it is essential to weigh up individual patient factors, preferences, and potential risks. RMST analysis provides valuable information to patients and physicians, facilitating decision-making in a value-based medical environment. [ABSTRACT FROM AUTHOR]

Quadrotors are widely applied in many fields, but they often face various external disturbances in actual operation. This makes it necessary to design a controller that can handle disturbances. Disturbance observer and adaptive control techniques are commonly used disturbance rejection techniques, the core idea of which is to estimate the disturbances in real time and incorporate the estimated values into the controller to suppress the disturbances. In this paper, various disturbance observers and adaptive control techniques, including nonlinear disturbance observers, extended state observers, neural networks, and fuzzy logic systems, are introduced, along with their variants or different structures. These techniques improve the adaptability and robustness of quadrotors to complex environments. Finally, future research directions for the disturbance rejection of quadrotors are also presented. [ABSTRACT FROM AUTHOR]

Traditional pedagogy is often critiqued for conventional teaching methods that prevent students from developing their problem-solving skills. Therefore, this study focused on investigating the effect of a STAD approach on the problemsolving skills of secondary level students in physics. Quasi Experiment was conducted to compare the STAD method (experimental group) with traditional teaching methods (control group). Experiment was performed in a selected school having at least two sections of tenth grade. There were 30 students in each section and sections were randomly assigned as experimental and control groups. A test constructed by researchers was used to measure problem-solving skills before and after the experiment. Materials such as work sheets, lesson plans, quizzes, and rewarding certificates were designed to implement STAD methodology in the physics classroom. The dependent variable, physics problem-solving skills, was measured using researcher constructed ten items test consisted of physics numerical. The same tool was used as both pre and post measurement of problem-solving skills. The statistics indicated that the students taught through STAD improved their problem-solving skills in numerical problems of physics compared to those who were taught through traditional method. Additionally, post-test performance of students in groups was significantly different and experimental group outperformed the control group in problem-solving skills. This study demonstrated that the STAD is an effective teaching strategy for enhancing problem-solving skills of students at secondary level while using content of physics numerical. [ABSTRACT FROM AUTHOR]

Interactions between tumor cells and immune cells in the tumor microenvironment (TME) play a vital role the mechanisms of immune evasion, by which cancer cells escape immune elimination. Thus, the characterization and quantification of different components in the TME is a hot topic in molecular biology and drug discovery. Since the development of transcriptome sequencing in bulk tissue, single cells and spatial dimensions, there are increasing methods emerging to deconvolute and subtype the TME. This review discusses and compares such computational strategies and downstream subtyping analyses. Integrative analyses of the transcriptome with other data, such as epigenetics and T-cell receptor sequencing, are needed to obtain comprehensive knowledge of the dynamic TME. Executive summary Measuring the composition of tumor microenvironment Accurate measurement of the tumor microenvironment (TME) composition is essential to our understanding of the interplays between tumor cells and other cell types in the TME. In bulk-RNAseq analysis, canonical marker gene sets provide interpretable results; deconvolution strategies that use prior knowledge from scRNAseq have shown better overall performance. Probabilistic models in scRNAseq will play a pivot role in transcriptome analysis as cell subtype-specific gene distributions can be transferred to other computational analyses as prior knowledge. Current spatial transcriptome sequencing suffers from spot-based input; integration with scRNAseq contributes to more accurate and efficient deconvolution to single-cell resolution. Subtyping the TME Clustering the percentage of TME composition can subtype the microenvironment and bridge connections to the immune phenotype. Cell–cell networks based on similarity present the distance between cell subtypes in a certain network; cell–cell casual networks show potential downstream signals triggered by cell–cell communication. Future perspective Integrating transcriptome analysis with genomics, epigenetics, proteomics, T-cell receptor sequencing data and environmental factors has demonstrated that omics analysis will contribute to a more comprehensive understanding of the TME by adding more dimensions of information to the model. Tracking the dynamic cell–cell causal networks in the TME during treatment will help decipher the mechanisms of immune evasion. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) represent a groundbreaking advance in the treatment of malignancies such as melanoma and non-small cell lung cancer, showcasing substantial therapeutic benefits. Nonetheless, the efficacy of ICIs is limited to a small subset of patients, primarily benefiting those with "hot" tumors characterized by significant immune infiltration. The challenge of converting "cold" tumors, which exhibit minimal immune activity, into "hot" tumors to enhance their responsiveness to ICIs is a critical and complex area of current research. Central to this endeavor is the activation of the cGAS-STING pathway, a pivotal nexus between innate and adaptive immunity. This pathway's activation promotes the production of type I interferon (IFN) and the recruitment of CD8+ T cells, thereby transforming the tumor microenvironment (TME) from "cold" to "hot". This review comprehensively explores the cGAS-STING pathway's role in reconditioning the TME, detailing the underlying mechanisms of innate and adaptive immunity and highlighting the contributions of various immune cells to tumor immunity. Furthermore, we delve into the latest clinical research on STING agonists and their potential in combination therapies, targeting this pathway. The discussion concludes with an examination of the challenges facing the advancement of promising STING agonists in clinical trials and the pressing issues within the cGAS-STING signaling pathway research. [ABSTRACT FROM AUTHOR]

Objectives: Our study aimed to assess the safety and efficacy of cardiac contractility modulation (CCM) therapy in patients with heart failure with reduced ejection fraction (HFrEF) depending on HF etiology. Methods: We enrolled 166 patients with optimal medical therapy-resistant HFrEF (median age 59 years, 83.7% males, median NYHA class − 2, median left ventricular ejection fraction (LVEF) − 29.0%) who underwent CCM therapy device implantation from 2013 to 2019 in four medical centers in Russia. The HF etiology was determined based on invasive coronary angiography or cardiac MRI data. Transthoracic echocardiography (TTE), 6-minute walking test (6MWT), and NTproBNP-tests were performed at a baseline and 12 months after the implantation. Results: The ischemic etiology of HF was revealed in 100 patients (61.5%) (ICM group); the non-ischemic group (NICM) evolved 66 patients (38.5%). Patients in the ICM group were significantly older (61[57–69] vs. 55 [42.8–61], p < 0.001), more frequently had hypertension (79% vs. 42.4%, p < 0.001) and chronic kidney disease (43% vs. 22.7%, p = 0.012). Patients in the NICM group had significantly more often atrial fibrillation (AF) (58% vs. 74%, p = 0.048), larger end-diastolic volume (EDV) (249 [208–309] vs. 220 [192–271], p = 0.019) and end-systolic volume (ESV) (183 [147–230] vs. 154 [128–199], p = 0.003). There were no significant differences in mortality between ICM and NICM groups (14.4 vs. 10.8%, p = 0.51). In 12 months, there was a significant increase in LVEF in the NICM group (+ 2.0 [2–6] vs. +7.7 [2–12], p < 0.001), while the improvement in the 6MWT (+ 75 [22–108] vs. +80 [10–160], p = 0.851) and NYHA class did not reach the level of significance. The subanalysis between patients with improved NYHA class and those without improvement revealed that patients without improvement more frequently had AF (56% vs. 89%; p < 0.01), chronic obstructive lung disease (18% vs. 35% p = 0.047), higher blood pressure (110 [105–120] vs. 120[110–129]; p = 0.032). Conclusion: In this multicenter retrospective study, patients with non-ischemic HFrEF showed a significantly higher improvement in LVEF and LV reverse remodeling following CCM therapy device implantation. There was no significant association between HF etiology and survival in drug-resistant HFrEF patients following CCM therapy. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the utility of deep learning (DL) automated segmentation-based MRI radiomic features and clinical-radiological characteristics in predicting early recurrence after curative resection of single hepatocellular carcinoma (HCC). Methods: This single-center, retrospective study included consecutive patients with surgically proven HCC who underwent contrast-enhanced MRI before curative hepatectomy from December 2009 to December 2021. Using 3D U-net-based DL algorithms, automated segmentation of the liver and HCC was performed on six MRI sequences. Radiomic features were extracted from the tumor, tumor border extensions (5 mm, 10 mm, and 20 mm), and the liver. A hybrid model incorporating the optimal radiomic signature and preoperative clinical-radiological characteristics was constructed via Cox regression analyses for early recurrence. Model discrimination was characterized with C-index and time-dependent area under the receiver operating curve (tdAUC) and compared with the widely-adopted BCLC and CNLC staging systems. Results: Four hundred and thirty-four patients (median age, 52.0 years; 376 men) were included. Among all radiomic signatures, HCC with5 mmtumorborderextensionandliver showed the optimal predictive performance (training set C-index, 0.696). By incorporating this radiomic signature, rim arterial phase hyperenhancement (APHE), and incomplete tumor "capsule," a hybrid model demonstrated a validation set C-index of 0.706 and superior 2-year tdAUC (0.743) than both the BCLC (0.550; p < 0.001) and CNLC (0.635; p = 0.032) systems. This model stratified patients into two prognostically distinct risk strata (both datasets p < 0.001). Conclusion: A preoperative imaging model incorporating the DL automated segmentation-based radiomic signature with rim APHE and incomplete tumor "capsule" accurately predicted early postsurgical recurrence of a single HCC. Critical relevance statement: The DL automated segmentation-based MRI radiomic model with rim APHE and incomplete tumor "capsule" hold the potential to facilitate individualized risk estimation of postsurgical early recurrence in a single HCC. Key Points: A hybrid model integrating MRI radiomic signature was constructed for early recurrence prediction of HCC. The hybrid model demonstrated superior 2-year AUC than the BCLC and CNLC systems. The model categorized the low-risk HCC group carried longer RFS. [ABSTRACT FROM AUTHOR]

Key Points: Question: Is administration of antenatal corticosteroids to individuals at risk of late preterm delivery, originally shown to improve short-term neonatal respiratory outcomes but with an increased rate of hypoglycemia, associated with adverse childhood neurodevelopmental outcomes at age 6 years or older? Findings: There were no statistically significant differences in the primary outcome, a General Conceptual Abilities score of less than 85, between the betamethasone (17.1%) and placebo (18.5%) groups. No differences in any secondary outcomes were observed. Meaning: In this follow-up study of a randomized clinical trial, antenatal corticosteroids in persons at risk of late preterm delivery were not associated with adverse effects on childhood neurodevelopmental outcomes at age 6 years or older. Importance: The Antenatal Late Preterm Steroids (ALPS) trial changed clinical practice in the United States by finding that antenatal betamethasone at 34 to 36 weeks decreased short-term neonatal respiratory morbidity. However, the trial also found increased risk of neonatal hypoglycemia after betamethasone. This follow-up study focused on long-term neurodevelopmental outcomes after late preterm steroids. Objective: To evaluate whether administration of late preterm (34-36 completed weeks) corticosteroids affected childhood neurodevelopmental outcomes. Design, Setting, and Participants: Prospective follow-up study of children aged 6 years or older whose birthing parent had enrolled in the multicenter randomized clinical trial, conducted at 13 centers that participated in the Maternal-Fetal Medicine Units (MFMU) Network cycle from 2011-2016. Follow-up was from 2017-2022. Exposure: Twelve milligrams of intramuscular betamethasone administered twice 24 hours apart. Main Outcome and Measures: The primary outcome of this follow-up study was a General Conceptual Ability score less than 85 (−1 SD) on the Differential Ability Scales, 2nd Edition (DAS-II). Secondary outcomes included the Gross Motor Function Classification System level and Social Responsiveness Scale and Child Behavior Checklist scores. Multivariable analyses adjusted for prespecified variables known to be associated with the primary outcome. Sensitivity analyses used inverse probability weighting and also modeled the outcome for those lost to follow-up. Results: Of 2831 children, 1026 enrolled and 949 (479 betamethasone, 470 placebo) completed the DAS-II at a median age of 7 years (IQR, 6.6-7.6 years). Maternal, neonatal, and childhood characteristics were similar between groups except that neonatal hypoglycemia was more common in the betamethasone group. There were no differences in the primary outcome, a general conceptual ability score less than 85, which occurred in 82 (17.1%) of the betamethasone vs 87 (18.5%) of the placebo group (adjusted relative risk, 0.94; 95% CI, 0.73-1.22). No differences in secondary outcomes were observed. Sensitivity analyses using inverse probability weighting or assigning outcomes to children lost to follow-up also found no differences between groups. Conclusion and Relevance: In this follow-up study of a randomized clinical trial, administration of antenatal corticosteroids to persons at risk of late preterm delivery, originally shown to improve short-term neonatal respiratory outcomes but with an increased rate of hypoglycemia, was not associated with adverse childhood neurodevelopmental outcomes at age 6 years or older. This prospective follow-up study of a randomized clinical trial evaluates whether antenatal corticosteroids administered to birthing parents at risk of late preterm delivery were associated with adverse neurodevelopmental effects on their offspring. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2DM) is recognized an independent risk factor for chronic kidney disease (CKD). The precise contribution and differential response to treatment strategies to reduce kidney dysfunction, depending on whether obesity is present alongside T2DM or not, remain to be fully clarified. Our objective was to improve our understanding of how obesity contributes to kidney function in patients with T2DM and coronary heart disease (CHD), who are highly predisposed to CKD, to assign the most effective dietary approach to preserve kidney function. Methods: 1002 patients with CHD and estimated glomerular filtration rate (eGFR)≥30 ml/min/1.73m2, were randomized to consume a Mediterranean diet (35% fat, 22% MUFA, < 50% carbohydrates) or a low-fat diet (28% fat, 12% MUFA, > 55% carbohydrates). Patients were classified into four groups according to the presence of T2DM and/or obesity at baseline: Non-Obesity/Non-T2DM, Obesity/Non-T2DM, Non-Obesity/T2DM and Obesity/T2DM. We evaluated kidney function using serum creatinine-based estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (uACR) before and after 5-years of dietary intervention. Results: Patients with Obesity/T2DM had the lowest baseline eGFR and the highest baseline uACR compared to non-diabetics (p < 0.05). After dietary intervention, the Mediterranean diet induced a lower eGFR decline in patients with Obesity/T2DM, compared to a low-fat diet but not in the other groups (p = 0.014). The Mediterranean diet, but not the low-fat diet, also reduced uACR only in patients with Obesity/T2DM (p = 0.024). Conclusions: Obesity provided an additive effect to T2DM resulting in a more pronounced decline in kidney function compared to T2DM alone when compared to non-diabetics. In patients with concomitant presence of T2DM and obesity, with more metabolic complications, consumption of a Mediterranean diet seemed more beneficial than a low-fat diet in terms of preserving kidney function. These findings provide valuable insights for tailoring personalized lifestyle modifications in secondary prevention of cardiovascular disease. Trial registration: URL, http://www.cordioprev.es/index.php/en. Clinicaltrials.gov number, NCT00924937 [ABSTRACT FROM AUTHOR]

Background: Studies on cross-informant agreement on adolescents' emotional and behavioral problems (EBPs) are sparse in low- and middle-income countries. This study aimed to assess parent-adolescent and teacher-adolescent agreement on EBPs and associated factors in Nepal. Methods: This cross-sectional survey included 1904 school-going adolescents aged 11–18, enrolled in government and private schools located in sixteen districts of Nepal. The Nepali versions of the Youth Self Report, Child Behavior Checklist, and Teacher's Report Form were administered to assess EBPs reported by adolescents, their parents, and teachers, respectively. Repeated measures analysis of variance (ANOVA) was done to assess mean differences in problem scores. Pearson's correlation was used to assess cross-informant agreement. Linear regression analysis was used to explore factors associated with cross-informant discrepancies in EBPs. Results: Adolescents reported significantly more problems than their parents and teachers. Mean Total Problem scores for the 90 common items in the adolescents' self-reports, parent reports, and teacher reports were 34.5 (standard deviation [SD]: 21.4), 24.1 (SD = 19.2), and 20.2 (SD = 17.5) respectively. Parent-adolescent agreement on Total Problems was moderate, whereas teacher-adolescent agreement was low. The parent-adolescent agreement was moderate to low for the two broadband scales and all syndrome scales, whereas the teacher-adolescent agreement was low for all scales. Female gender and ethnic minority status impacted both parent-adolescent and teacher-adolescent discrepancies. Family stress/conflicts impacted parent-adolescent discrepancies, while academic performance impacted teacher-adolescent discrepancies. Conclusions: Nepali adolescents reported more EBPs than their parents and teachers. The agreement between adolescents' self-reports and reports by their parents and teachers was moderate to low. Gender, caste/ethnicity, family stress/conflicts, and academic performance were associated with cross-informant discrepancies. It is crucial to collect information from different sources, consider context-specific needs, and discern factors influencing cross-informant discrepancies to accurately assess adolescents' EBPs and develop personalized approaches to treatment planning. [ABSTRACT FROM AUTHOR]