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IntroductionMolecular subgroups influence the vascular architecture within medulloblastomas, particularly the wingless (WNT) subgroup, which contributes to its propensity for primary tumor hemorrhage. Whether this mechanism affects intraoperative blood loss remains unknown. This study aimed to assess the association between WNT medulloblastoma and the predisposition for blood loss.MethodsThis was a retrospective observational study using data from a neuro-oncology center comprising molecular data on patients treated between December 31, 2014, and April 30, 2023. Differences between WNT and other subgroups in the risk of primary outcome-intraoperative blood loss were assessed using multivariable-adjusted linear regression.ResultsOf the 148 patients included in the analysis, 18 patients (12.2%) had WNT, 42 (28.4%) had sonic hedgehog (SHH) TP53-wildtype, 7 (4.7%) had SHH TP53-mutant, and 81 (54.7%) were non-WNT/ non-SHH. The WNT subgroup more frequently underwent primary intratumoral hemorrhage (22% vs. 3.8%; p = 0.011). The median intraoperative blood loss was 400.00 (interquartile range [IQR] 250, 500) mL for WNT and 300.00 [200, 400] mL for the other subgroups (p = 0.136), with an adjusted β of 135.264 (95% confidence intervals [CI], 11.701–258.827; p = 0.032). Similar results were observed in both midline and noninfiltrative margin medulloblastoma.DiscussionWNT medulloblastoma is typically associated with primary intratumoral hemorrhage and intraoperative blood loss. The validity of determining the surgical approach based on predicted molecular subtypes from imaging data is questionable. However, attempting to engage in risk communication with patients in a molecular-specific way is worthwhile to validate.

BackgroundHealthy aging is crucial to the quality of life of older adults, of which mental health is an essential part. Physical exercise strongly affects their mental health and can alleviate psychological problems to a certain extent. Nevertheless, the correlation between physical exercise and the mental health of older adults individuals, as well as the underlying mechanism by which physical exercise impacts mental health, remains rather ambiguous.MethodsWe utilized multiple linear regression models to investigate the relationship between physical activity and mental health in 3,240 persons aged 60 and up. The propensity score matching (PSM) method was used to assess the robustness of the regression results. In addition, sequential recursive models were employed to investigate the mediating role of social competence in the link between physical activity and mental health.Results and discussionWe discovered a strong favorable association between physical exercise and mental health, which was mediated by social competence. Furthermore, the effect of physical exercise on mental health differed across older persons from various socioeconomic backgrounds.ConclusionOlder adults should strengthen their understanding of the role of physical exercise. Sports organizations that serve older adults by providing resources and services to help them maintain physical fitness and by hosting sports activities and competitions according to their needs should be established.

In the context of Integrated Energy System (IES), accurate short-term power demand forecasting is crucial for ensuring system reliability, optimizing operational efficiency through resource allocation, and supporting effective real-time decision-making in energy management. However, achieving high forecasting accuracy faces significant challenges due to the inherent complexity and stochastic nature of IES’s short-term load profiles, resulting from diverse consumption patterns among end-users and the intricate coupling within the network of interconnected energy sources. To address this issue, a dedicated Short-Term Power Load Forecasting (STPLF) framework for IES is proposed, which relies on a newly developed hybrid deep learning architecture. The framework seamlessly combines Long Short-Term Memory (LSTM) with Temporal Convolutional Network (TCN), enhanced by an attention mechanism module. By merging these methodologies, the network leverages the parallel processing prowess of TCN alongside LSTM’s ability to retain long-range temporal information, thus enabling it to dynamically concentrate on relevant sections of time series data. This synergy leads to improved prediction accuracy and broader applicability. Furthermore, the integration of residual connections within the network structure serves to deepen its learning capabilities and enhance overall performance. Ultimately, results from a real case study of a user-level IES demonstrate that the Mean Absolute Percentage Error (MAPE) of the proposed framework on the test set is 2.35%. This error rate is lower than the averages of traditional methods (3.43%) and uncombined single submodules (2.80%).

In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.

Lobular capillary hemangioma (LCH), previously known as pyogenic granuloma, is a benign vascular lesion commonly found within the oral and nasal cavities. However, it is rarely encountered within the trachea, especially in pediatric patients, where it manifests as hemoptysis, cough, and wheeze, and is frequently misdiagnosed as bronchitis or asthma. There is limited literature on the presentation, behavior, and management of tracheal LCH. Herein, we describe a rare case of tracheal LCH in an 11-year-old boy with a history of hemoptysis, which was successfully managed with arterial embolization followed by electrocautery loop snaring via flexible bronchoscopy. No complications occurred during and after the procedure. A review of the relevant literature is also provided. Our case is unique, given the therapeutic strategy utilized for pediatric tracheal LCH, and reminds physicians to be aware of tracheal LCH in the differential diagnosis for hemoptysis.

ObjectiveEpilepsy dramatically affects the quality of life (QoL) of children, and resection surgery can improve their QoL by reducing seizures or completely controlling them. Children who have postoperative seizures tend to show a poorer QoL. The aim of the present study was to investigate the QoL of children with seizures after resection surgery and its influencing factors.MethodsIn the present study, we retrospectively reviewed 151 consecutive children who underwent resection surgery. We then divided them into two groups, seizure and seizure-free groups, according to the seizure outcomes 1 year after surgery. Variables were categorized into a number of factor types such as preoperative factors, surgery-related factors, postoperative factors, and family factors. QoL and seizure outcomes more than 3 years after surgery were assessed according to the ILAE seizure outcome classification and the CHEQOL-25 scale.ResultsForty-three (28.5%) of the 151 children had seizures 1 year after surgery, and two children died during the follow-up period. The mean CHEQOL-25 scale for children with seizures was 63.5 ± 18.2, and 20 (48.8%) patients had poor QoL. Surgery-related factors, such as surgical complications and surgical sequelae, were not statistically associated with QoL. Preoperative language development retardation or language dysfunction [odds ratio (OR) = 29.3, P = 0.012) and postoperative ILAE seizure outcome classification (OR = 1.9, P = 0.045)] were significantly associated with QoL.SignificanceChildren with seizures after resection surgery had a relatively poor QoL. Surgery-related factors, such as surgical complications and surgical sequelae, cannot predict the QoL. Preoperative language development retardation or language dysfunction and postoperative ILAE seizure outcome classification were independent predictors of the quality of life (QoL). For children who could not achieve the expected freedom from seizure after surgery, a lower ILAE grade (ILAE 1-3) is also an acceptable outcome since it predicts a higher QoL.

PurposeLymph node (LN) involvement is a key factor in ovarian clear cell carcinoma (OCCC) although, there several indicators can be used to define prognosis. This study examines the prognostic performances of each indicator for OCCC patients by comparing the number of lymph nodes examined (TNLE), the number of positive lymph nodes (PLN), lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS).Methods1,300 OCCC patients who underwent lymphadenectomy between 2004 and 2015 were extracted from the Surveillance Epidemiology and End Results (SEER) database. Primary outcomes were Overall Survival (OS) and the cumulative incidence of Cancer-Specific Survival (CSS). Kaplan–Meier’s and Fine-Gray’s tests were implemented to assess OS and CSS rates. After conducting multivariate analysis, nomograms using OS and CSS were constructed based upon an improved LN system. Each nomograms’ performance was assessed using Receiver Operating Characteristics (ROC) curves, calibration curves, and the C-index which were compared to traditional cancer staging systems.ResultsMultivariate Cox’s regression analysis was used to assess prognostic factors for OS, including age, T stage, M stage, SEER stage, and LODDS. To account for the CSS endpoint, a proportional subdistribution hazard model was implemented which suggested that the T stage, M stage, SEER stage, and LNR are all significant. This enabled us to develop a LODDS-based nomogram for OS and a LNR-based nomogram for CSS. C-indexes for both the OS and CSS nomograms were higher than the traditional American Joint Committee on Cancer (AJCC), 8th edition, staging system. Area Under the Curve (AUC) values for predicting 3- and 5-year OS and CSS between nomograms also highlighted an improvement upon the AJCC staging system. Calibration curves also performed with consistency, which was verified using a validation cohort.ConclusionsLODDS and LNR may be better predictors than N stage, TNLE, and PLNs. For OCCC patients, both the LODDS-based and LNR-based nomograms performed better than the AJCC staging system at predicting OS and CSS. However, further large sample, real-world studies are necessary to validate the assertion.

BackgroundTraditional Chinese medicine development policies (TCMDPs) are essential in improving the sustainable development of TCM undertakings, of which transmissions of policy information are closely related to the actual policy effectiveness. However, the inherent components of TCMDPs had not been explored from the structural dimension of policy design.MethodsBased on the policy modeling consistency (PMC) index model, we constructed a comprehensive evaluation system, including ten first-level and 40 second-level indicators, and focused on the TCMDPs released by the Chinese central government in the past 42 years (1980–2022) to conduct multi-dimensional inspections to TCMDPs by analyzing the overall policy quality, individual scoring performance, and indicators distribution characteristics.ResultsThis study pointed out that four policies were rated as “perfect,” 35 were rated as “superb,” 50 were rated as “excellent,” 28 were rated as “good,” and four were rated as “acceptable,” with total mean values of the PMC index being 7.530 ± 0.835. Although most TCMDPs had appropriate policy structure and consistency, the potential weaknesses in the design of TCMDPs also needed our attention through careful checks on the outlier policy samples. Besides, the existing TCMDPs had room for improvement regarding policy areas, guarantees and incentives, objects included, and issuing agencies.ConclusionsWe emphasized that the policy evaluation method used in this current study, the PMC index model, is scarce in the TCMDPs. These findings are helpful for fully understanding the strengths and weaknesses of TCMDPs and provide theoretical references for further studies optimizing TCMDPs.

Hypoxia is a critical problem in intensive Epinephelus coioides aquaculture systems. In the present study, the physiological responses of E. coioides muscle to acute hypoxic stress (DO = 0.6 ± 0.1 mg/L) and reoxygenation (DO = 6.0 ± 0.1 mg/L) were analyzed by transcriptome sequencing (RNA-seq) and quantitative real-time PCR (qRT–PCR). RNA-seq was conducted on the muscle tissues of E. coioides in the hypoxia-tolerant (EMS), hypoxia-sensitive (EMW), and normoxic (CM) groups. Among the three groups, a total of 277 differentially expressed genes (DEGs) were identified. KEGG analysis revealed that the pathways significantly enriched after hypoxic stress are involved in the immune response, glycolysis/gluconeogenesis, energy metabolism, vasodilation and proliferation, cell proliferation, and apoptosis. qRT‒PCR verified that the differentially expressed genes FIH-1, PHD-2, PPARα, BCL-XL, LDH-A, and Flt-1 were significantly upregulated after hypoxic stress and returned to normal levels after reoxygenation, suggesting that these DEGs play important roles in responding to hypoxia treatment. In addition, the HIF-1 signaling pathway was also activated under hypoxic stress, and qRT‒PCR confirmed that the expression level of HIF-1α was significantly elevated under acute hypoxic stress, indicating that the HIF-1 signaling pathway is the central pathway in the E. coioides hypoxic response mechanism and activates other related pathways to adapt to hypoxic stress. These pathways jointly regulate energy metabolism, substance synthesis, blood vessel proliferation, cell proliferation, and differentiation and prolong survival time. These results provide ideas for understanding physiological regulation after hypoxic stress and reoxygenation and provide basic insights for the future breeding of hypoxia-tolerant E. coioides.

This study examined the causal relationship between participation in the New Rural Cooperative Medical Scheme (NRCMS) and health status among relatively poor population in rural China. Data were obtained from the China Family Panel Studies (CFPS) conducted in 2018, which contained 4,507 samples. This study used propensity score matching (PSM) to examine the net effect of participation in the NRCMS on the health of the relatively poor population, and this effect was tested for equilibrium using nearest neighbor matching, radius matching, and kernel matching. This study showed that participation in the NRCMS has a significant and positive effect on the health status of the relatively poor population and the positive health effect may come from three channels, including the increased frequency of physical activity, the fact that an individual is more likely to seek medical care at a lower level of visit, and a plan to reduce health care expenditures.

Drawing on the social exchange theory, this study adopted a cross-level framework to investigate the influence of consumer group communication on consumer product image perception and brand memory. In addition, this paper examined the moderating role of consumer group involvement in the cross-level relationship between consumer group communication and consumer product image perception. Based on a sample of 116 groups and 530 consumers, results revealed that consumer group communication has a significant positive influence on brand memory formation across levels. Consumer product image perception plays a cross-layer mediated role between consumer group communication and brand memory. Group involvement plays a cross-level negative moderating role between consumer group communication and consumer product image perception, and moderates the mediating role of consumer product image perception between consumer group communication and consumer brand memory across different levels. Finally this paper discussed implications for research and practice.

Soil microorganisms play vital roles in regulating biogeochemical processes. The composition and function of soil microbial community have been well studied, but little is known about the responses of bacterial and fungal communities to different habitats of the same plant, especially the inter-kingdom co-occurrence pattern including bacteria and fungi. Herein, we used high-throughput sequencing to investigate the bacterial and fungal communities of five Phragmites australis habitats in the Yellow River Delta and constructed their inter-kingdom interaction network by network analysis. The results showed that richness did not differ significantly among habitats for either the bacterial or fungal communities. The distribution of soil bacterial community was significantly affected by soil physicochemical properties, whereas that of the fungal community was not. The main functions of the bacterial and fungal communities were to participate in the degradation of organic matter and element cycling, both of which were significantly affected by soil physicochemical properties. Network analysis revealed that bacteria and fungi participated in the formation of networks through positive interactions; the role of intra-kingdom interactions were more important than inter-kingdom interactions. In addition, rare species acted as keystones played a critical role in maintaining the network structure, while NO3−−N likely played an important role in maintaining the network topological properties. Our findings provided insights into the inter-kingdom microbial co-occurrence network and response of the soil microbial community composition and function to different P. australis habitats in coastal wetlands, which will deepen our insights into microbial community assembly in coastal wetlands.

Recent advances in measuring and modeling root water uptake along with refined electrical petrophysical models may help fill the existing gap in hydrological root model parametrization. In this paper, we discuss the choices to be made to combine root-zone hydrology and geoelectrical data with the aim of characterizing the active root zone. For each model and observation type we discuss sources of uncertainty and how they are commonly addressed in a stochastic inversion framework. We point out different degrees of integration in the existing hydrogeophysical approaches to parametrize models of root-zone hydrology. This paper aims at giving emphasis to stochastic approaches, in particular to Data Assimilation (DA) schemes, that are generally identified as the best way to combine geoelectrical data with Root Water Uptake (RWU) models. In addition, the study points out a more suitable objective function taken from the optimal transport theory that better captures complex geometry of root systems. Another pathway for improvement of geoelectrical data integration into RWU models using DA relies on the use of stem based methods as a leverage to introduce more extensive root knowledge into RWU macroscopic hydrological models.

Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the snowmelt period, and after snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in snowmelt timing may alter ecosystem N retention potential. Overall, we observed that snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after snowmelt.