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Surgical methods and outcomes of inguinal hernia repair in children, adolescents and young adults in a retrospective cohort study
Establishment and validation of a ResNet-based radiomics model for predicting prognosis in cervical spinal cord injury patients
Abstract Cervical spinal cord injury (cSCI) poses a significant challenge due to the unpredictable nature of recovery, which ranges from mild paralysis to severe long-term disability. Accurate prognostic models are crucial for guiding treatment and rehabilitation but are often limited by their reliance on clinical observations alone. Recent advancements in radiomics and deep learning have shown promise in enhancing prognostic accuracy by leveraging detailed imaging data. However, integrating these imaging features with clinical data remains an underexplored area. This study aims to develop a combined model using imaging and clinical signatures to predict the prognosis of cSCI patients six months post-injury, helping clinical decisions and improving rehabilitation plans. We retrospectively analyzed 168 cSCI patients treated at Zhongda Hospital from January 1, 2018, to June 30, 2023. The retrospective cohort was divided into training (134 patients) and testing sets (34 patients) to construct the model. An additional prospective cohort of 43 cSCI patients treated from July 1, 2023, to November 30, 2023, was used as a validation set. Radiomics features were extracted using Pyradiomics and ResNet deep learning from MR images. Clinical factors such as age, smoking history, drinking history, hypertension, diabetes, cardiovascular disease, traumatic brain injury, injury site, and treatment type were analyzed. The LASSO algorithm selected features for model building. Multiple machine learning models, including SVM, LR, NaiveBayes, KNN, RF, ExtraTrees, XGBoost, LightGBM, GradientBoosting, AdaBoosting, and MLP, were used. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) assessed the models’ performance. A nomogram was created to visualize the combined model. In Radiomics models, the SVM classifier achieved the highest area under the curve (AUC) of 1.000 in the training set and 0.915 in the testing set. Age, diabetes, and treatment were found clinical risk factors to develop a clinical model. The combined model, integrating radiomics and clinical features, showed strong performance with AUCs of 1.000 in the training set, 0.952 in the testing set and 0.815 in the validation set. And calibration curves and DCA confirmed the model’s accuracy and clinical usefulness. This study shows the potential of a combined radiomics and clinical model to predict the prognosis of cSCI patients.
Bidirectional rotational antagonistic shape memory alloy actuators for high-frequency artificial muscles
Abstract Shape memory alloys (SMA) are commonly utilized in compact actuators due to their high energy density, meaning possible work output in relation to their weight and volume. Their application area is limited by their poor dynamic behavior, caused by the thermal activation characteristics of SMA materials. Typical actuation frequencies of SMA-based actuators range from 1 Hz to 10 Hz. In this work, we introduce an actuator system architecture, termed bidirectional rotational antagonistic (BIRAN) SMA actuator, which uses bundles of thin SMA wires to generate repeated rotational movement at frequencies up to 200 Hz. This marks a new frequency record for electrically activated SMA wire-based actuator systems. The high frequency reported results from the combination of mechanical design, electronics, and control strategy. We describe the fabrication techniques and the power electronics development and demonstrate the system performance through a systematic experimental study. A bio-inspired robotic wing-flapping joint illustrates the expansion of possible SMA-based application areas, pushing the dynamic limitations of this actuator technology.
The coupled effect of climate change and LUCC on meteorological drought in a karst drainage basin, Southwest China
The impact of various calcium ion sources on the curing efficacy of MICP
Identifying the epileptic network by linking interictal functional and structural connectivity
Spatiotemporal evolution patterns of the coupling of carbon productivity and high-quality economic development in China
Abstract This study examines the spatiotemporal evolution of the coordinated development between carbon productivity (CP) and high-quality economic development (HQED) across 30 provinces in China from 2008 to 2021. Using the entropy weight method, coupling coordination degree (CCD), kernel density estimation, spatial autocorrelation analysis, and spatial econometric models, the research identifies several key findings: first, a coupling and coordination relationship characterized by mutual influence and restraint exists between carbon productivity and high-quality economic development. Both carbon productivity and high-quality economic development, along with their coupling coordination degree, have exhibited continuous growth, demonstrating a spatial distribution pattern of “higher in the east than in the west, and higher in the south than in the north,” accompanied by expanding spatial concentration and pronounced regional disparities. Second, the global Moran’s I for the coupling coordination degree is positive, indicating significant spatial effects between carbon productivity and high-quality economic development. The LISA map highlights that high–high clusters are concentrated in the economically advanced eastern coastal areas, while low–low clusters are predominantly located in underdeveloped central and western regions and energy-dependent heavy industrial provinces. Third, the spatial effects of coupling coordination degree are influenced by factors such as economic development level, urbanization, technological progress, environmental regulation, the proportion of the secondary industry, and marketization level. The significance of these factors varies in the decomposition effect. Finally, this study provides policy recommendations. Within the framework of China’s “dual-carbon” goals, promoting the coupling and coordinated development of carbon productivity and high-quality economic development, while fostering balanced regional growth, holds substantial practical importance.
Evolution of indirect reciprocity under emotion expression
Abstract Do emotion expressions impact the evolution of cooperation? Indirect Reciprocity offers a solution to the cooperation dilemma with prior work focusing on the role of social norms in propagating others’ reputations and contributing to evolutionarily stable cooperation. Recent experimental studies, however, show that emotion expressions shape pro-social behaviour, communicate one’s intentions to others, and serve an error-correcting function; yet, the role of emotion signals in the evolution of cooperation remains unexplored. We present the first model of IR based on evolutionary game theory that exposes how emotion expressions positively influence the evolution of cooperation, particularly in scenarios of frequent errors. Our findings provide evolutionary support for the existence of emotion-based social norms, which help foster cooperation among unrelated individuals.
Risk factors associated with medium- to long-term outcome and health-related quality of life of patients with conservatively treated rib fractures
Abstract Patients with rib fractures often suffer from prolonged pain and dyspnea. The purpose of this study was to evaluate the mid- and long-term outcomes and major predisposing risk factors for clinical limitations such as pain or reduced lung capacity in patients with conservatively managed rib fractures to provide a basis for optimizing current therapy. Patients who underwent conservative management of rib fractures between 2014 and 2018 at a level I trauma center were retrospectively reviewed. Inclusion criteria were Injury Severity Score (ISS) ≤ 16 points and a minimum follow-up of 3 years. Outcome parameters were the SF-36 physical and mental component summary score (PCS and MCS, respectively) as well as current pain and respiratory problems. Risk factors evaluated included age, body mass index (BMI), in-hospital days, number of rib fractures, fracture dislocation and serial rib fracture. PCS was comparable to the normal population. The correlation between age and PCS was significant, p = .002. BMI correlated significantly with PCS, p < .001, current pain, p = .034 and respiratory problems, p = .029. No significant correlations were observed for the number of rib fractures and in-hospital days. Fracture dislocation and serial rib fracture showed no effect on PCS, p = .134 and p = .914, respectively, and current pain, p = .916 and p = .357, respectively. In the medium- to long-term, conservative treatment of simple rib fractures or serial rib fractures showed good results, but was negatively affected by a high patient age or BMI.
Monitoring and early warning of ovarian cancer using high-dimensional non-parametric EWMA control chart based on sliding window
Abstract Ovarian tumors are a common ovarian dysfunction that affects women’s daily lives. Although ovarian tumors are generally sensitive to chemotherapy and initially respond well to platinum/taxane-based treatments, the postoperative recurrence rate remains high in advanced cases. Many researchers are dedicated to developing new methods for monitoring and predicting malignant tumors. Traditional approaches use dimensionality reduction techniques, like principal component analysis and deep learning, to select relevant features, followed by univariate or multivariate control charts for monitoring. However, these methods may overlook interactions between features and dimensionality reduction can result in loss of information, potentially affecting the accuracy of the model and leading to delayed alerts and reduced predictive performance. Therefore, this paper develops a new sliding window EWMA control chart based on high-dimensional empirical likelihood ratio tests. This control chart not only monitors data with unknown underlying distributions but is also applicable to high-dimensional data, allowing for monitoring without dimensionality reduction, thus simplifying the process and avoiding information loss. Monte Carlo results show that this method detects changes in indicators and issues alerts more rapidly than the dimensionality-reduced multivariate EWMA control charts. In addition, we further validated the effectiveness of this method through analysis of a tumor resection data example.
Long non-coding RNA AC133552.2: biomarker and therapeutic target in osteosarcoma via PANoptosis gene screening
Association of novel inflammatory markers with osteoporosis index in older spine osteoporosis patients: NHANES 1999–2018 cross-sectional study
Measuring space charge and electric field in axisymmetric dielectric barrier discharge using EFISH technique
Author Correction: Association between low fasting glucose of the living donor and risk of graft loss in the recipient after liver transplantation
Mechanisms creating homogamy in depressiveness in couples: A longitudinal study from Czechia
Abstract Couples often resemble each other in characteristics like depression, but the reasons for this homogamy (i.e., similarity) remain unclear. We investigated two potential mechanisms: preference for a self-similar partner and convergence (i.e., increasing similarity) over time. In a nationally representative sample of 2,793 Czech individuals who we surveyed three times in one year, we examined self-reports of participants’, their ideal partners’, and their actual partners’ “pessimism and depressiveness”. Participants preferred partners less depressive than themselves, yet their actual partners were more depressive than desired. Those who ended their relationships showed a greater ideal-versus-actual partner discrepancy than those who stayed together. In stable relationships, individuals adjusted their ideal preferences to align more closely with their actual partners over time. We identified four relationship classes with latent class growth modeling based on self and partner evaluations: both non-depressive, both depressive, self depressive and partner non-depressive, and self non-depressive and partner depressive. Romantic relationships were most stable when both partners were non-depressive and most likely to dissolve when both were depressive. While we failed to detect convergence overall, we found it within heterogamous (i.e., dissimilar) classes. Overall, our findings suggest that homogamy and heterogamy in depressiveness are complexly associated with relationship maintenance.
The protective and chemotherapeutical role of amygdalin in induced mammary cancer in experimental mice and upregulation of related genes
Abstract Breast cancer is a prominent health issue among oncological diseases in emerging nations. The study sought to assess the significant function of amygdalin as a protective and chemotherapeutical substance in combating this lethal condition, either independently or in conjunction with tamoxifen therapy. Breast cancer in mice was induced by 7,12-Dimethylbenz(a)anthracene (DMBA). Mice were divided into six groups, 15 mice in each group. (i) control group, (ii) carcinogenic group, (iii) tamoxifen-treated group, (iv) Amygdalin-treated group, (v) (Amygdalin + tamoxifen) group, (vi) Amygdalin protective group. Results revealed that DMBA-induced breast cancer caused a significant increase in biochemical parameters such as CEA, CA15.3, CA125, PRL, E2, urea, creatinine, ALT, AST, and ALP and a substantial increase in gene expression of TNF-α and BcL-2. In contrast, amygdalin administrations alone or in co-administration with tamoxifen could ameliorate breast cancer by declining TNF-α, BcL-2 and attenuating the biochemical parameters. Amygdalin administrations showed a significant increase in SOD and GPx antioxidants and upregulation of Caspase-3 and P53 in breast tissue. Moreover, flow cytometric analysis revealed that amygdalin administrations were correlated with CD20 and CD44 and promoted the cell cycle and apoptosis in carcinogenic mice. Indeed, the above results were confirmed by the histopathological examinations, which showed that the DMBA group had proliferated microductular carcinoma with marked mononuclear inflammatory cell infiltration, which decreased by the Amygdalin administrations. In conclusion, amygdalin administration may be effective in preventing breast cancer and exhibiting chemotherapeutic properties.
Placebo treatment entails resource-dependent downregulation of negative inputs
Abstract Clinical trials with antidepressants reveal significant improvements in placebo groups, with effects of up to 80% compared to real treatment. While it has been suggested that treatment expectations rely on cognitive control, direct evidence for affective placebo effects is sparse. Here, we investigated how cognitive resources at both the behavioral and neural levels influence the effects of positive expectations on emotional processing. Forty-nine healthy volunteers participated in a cross-over fMRI study where positive expectations were induced through an alleged oxytocin nasal spray and verbal instruction. Participants completed a spatial cueing task that manipulated attention to emotional face distractors while being scanned and were characterized regarding their general attention control ability. Placebo treatment improved mood and reduced distractibility from fearful compared to happy faces, particularly when more attentional resources were available for processing face distractors. This aligned with changes in activation and functional coupling within prefrontal-limbic networks, suggesting that expectations induce top-down regulation of aversive inputs. Additionally, neurobehavioral effects correlated with individual control ability. Our findings highlight the critical role of cognitive resources in verbally instructed placebo effects. This may be particularly relevant in patients with major depressive disorder, who often demonstrate enhanced negativity processing but have limited cognitive control capacity.