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Objectives Recent studies have indicated that radiomics may have excellent performance and clinical application prospects in the differential diagnosis of benign and malignant vertebral compression fractures (VCFs). However, multimodal magnetic resonance imaging (MRI)‐based radiomics model is rarely used in the differential diagnosis of benign and malignant VCFs, and is limited to lumbar. Herein, this study intends to develop and validate MRI radiomics models for differential diagnoses of benign and malignant VCFs in patients. Methods This cross‐sectional study involved 151 adult patients diagnosed with VCF in The First Affiliated Hospital of Soochow University in 2016–2021. The study was conducted in three steps: (i) the original MRI images were segmented, and the region of interest (ROI) was marked out; (ii) among the extracted features, those features with Pearson's correlation coefficient lower than 0.9 and the top 15 with the highest variance and Lasso regression coefficient less than and more than 0 were selected; (iii) MRI images and combined data were studied by logistic regression, decision tree, random forest and extreme gradient boosting (XGBoost) models in training set and the test set (ratio of 8:2), respectively; and the models were further verified and evaluated for the differential diagnosis performance. The evaluated indexes included area under receiver (AUC) of operating characteristic curve, accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and 95% confidence intervals (CIs). The AUCs were used to assess the predictive performance of different machine learning modes for benign and malignant VCFs. Results A total of 1144 radiomics features, and 14 clinical features were extracted. Finally, 12 radiomics features were included in the radiomics model, and 12 radiomics features with 14 clinical features were included in the combined model. In the radiomics model, the differential diagnosis performance in the logistic regression model with the AUC of 0.905 ± 0.026, accuracy of 0.817 ± 0.057, sensitivity of 0.831 ± 0.065, and negative predictive value of 0.813 ± 0.042, was superior to the other three. In the combined model, XGBoost model had the superior differential diagnosis performance with specificity (0.979 ± 0.026) and positive predictive value (0.971 ± 0.035). Conclusion The multimodal MRI‐based radiomics model performed well in the differential diagnosis of benign and malignant VCFs, which may provide a tool for clinicians to differentially diagnose VCFs.

Purpose: The purpose of this study is that the teaching style of college physical education (PE) teachers affects the establishment of college students' exercise habits. Design/methodology/approach: This study uses the teaching style scale for 32 PE teachers and the autonomic motivation and exercise habits scale for 320 college students in the form of self-report. Findings: Chinese college PE teachers mainly use the teacher-centered reproduction style, and the practice style is the most frequently used. The overall teaching style of college PE teachers was significantly negatively correlated with autonomous motivation and exercise habits. PE teachers' teaching style can negatively affect college students' autonomous motivation, and college students' autonomous motivation can positively affect their exercise habits. Originality/value: There is a significant negative correlation between the teaching style of college PE teachers and the exercise habits of college students. However, it cannot directly affect the establishment of college students' exercise habits, but is achieved through the mediating role of college students' autonomous motivation.

Abstract O6-methylguanine-DNA methyltransferase (MGMT) has been demonstrated to be an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable radiomics model based on MRI data to predict the MGMT promoter methylation status of GBM. A total of 183 patients with glioblastoma were included in this retrospective study. The visually accessible Rembrandt images (VASARI) features were extracted for each patient, and a total of 14676 multi-region features were extracted from enhanced, necrotic, “non-enhanced, and edematous” areas on their multiparametric MRI. Twelve individual radiomics models were constructed based on the radiomics features from different subregions and different sequences. Four single-sequence models, three single-region models and the combined radiomics model combining all individual models were constructed. Finally, the predictive performance of adding clinical factors and VASARI characteristics was evaluated. The ComRad model combining all individual radiomics models exhibited the best performance in test set 1 and test set 2, with the area under the receiver operating characteristic curve (AUC) of 0.839 (0.709–0.963) and 0.739 (0.581–0.897), respectively. The results indicated that the radiomics model combining multi-region and multi-parametric MRI features has exhibited promising performance in predicting MGMT methylation status in GBM. The Modeling scheme that combining all individual radiomics models showed best performance among all constructed moels.

Abstract In the global ecosystem, wetlands are vital carbon sinks, playing a crucial role in absorbing greenhouse gases such as carbon dioxide and mitigating global warming. Accurate estimation of wetland carbon content is essential for research on wetland carbon sinks. However, the carbon cycle of wetlands is complex, and the carbon sinking of wetlands is affected by climate, topography, water level conditions, vegetation types, soil types, and other factors. This has caused significant challenges in the estimation of wetland carbon sinks. In current studies, most research has focused on the impact of individual factors on wetland carbon sinks, often ignoring the interaction between various factors, which further leads to uncertainty in wetland carbon measurements. This paper aims to elucidate the process of the wetland carbon cycle, summarize the factors affecting wetland carbon sinks, and explore the interplay between various factors and their influence on wetland carbon sinks, aiming to provide theoretical support for the study of wetland carbon sinks. Additionally, this paper reviews the advantages and disadvantages of current wetland carbon measurement methods, proposes research directions for combining machine learning methods, identifies existing difficulties in current wetland carbon measurement, and offers suggestions to serve as a reference for future wetland carbon sink estimation and wetland management. Graphical Abstract

ObjectiveThis retrospective observational study investigates the heterogeneity of hepatic and pancreatic fat deposition and its implications for metabolic health in individuals with obesity.MethodsA total of 706 patients with obesity underwent an MRI to quantify liver and pancreatic fat. Patients were classified into four groups based on fat deposition: no fat (None), fatty pancreas only (NAFPD), fatty liver only (NAFLD), and both conditions (NAFLD+NAFPD). Biochemical profiles, insulin resistance (Homeostatic Model Assessment for Insulin Resistance, HOMA-IR), and β-cell function were analyzed. A series of multiple linear regressions were used to investigate the independent effects of characteristics on glucose, insulin, and C-peptide at 0h. Another multiple linear regression was performed to evaluate the effects of basic characteristics on average liver fat, mean pancreatic fat, and visceral fat.ResultsThe majority (76.63%) exhibited both NAFLD and NAFPD, highlighting the heterogeneity of fat deposition among individuals with obesity. Groups with fatty liver displayed significantly higher fasting glucose, insulin, C-peptide, and HOMA-IR levels than those without fatty liver (P < 0.01). Fatty pancreas alone did not significantly influence these metabolic parameters (P > 0.05). This underscores the greater metabolic impact of hepatic fat compared to pancreatic fat.ConclusionsThe study confirms the complex heterogeneity of fat deposition in obesity, with the fatty liver being a more influential factor in metabolic disturbances than the fatty pancreas. The prevalent co-occurrence of NAFLD and NAFPD in this population underscores the need for targeted management strategies focusing on hepatic fat reduction to mitigate metabolic risk.

Although income and living conditions of residents have greatly improved in recent years, people’s subjective well-being does not seem to increase daily. This study aimed to explore income, self-rated health, and psychological capital on subjective well-being, using data from the China General Social Survey conducted in 2017. A total of 1136 elderly as subsamples data were selected from 12 582 participants, involving general sociodemographic characteristics, income, self-rated health, psychological capital, and subjective well-being. SPSS v26.0 macro was used for descriptive statistics, ANOVA and correlation analysis. PROCESS v3.4 macro was performed to examine multiple mediating effects of self-rated health and psychological capital. The elderly residing in urban ( P = .016) and having completed 9-year compulsory education ( P = .016) reported higher subjective well-being scores. The findings revealed that subjective well-being was positively associated with income, health, and psychological capital among the aged adults (all P

BackgroundIndividualized cortical functional networks parcellation has been reported as highly reproducible at 3.0 T. However, in view of the complexity of cortical networks and the greatly increased sensitivity provided by ultra-high field 5.0 T MRI, the parcellation consistency between different magnetic fields is unclear.PurposeTo explore the consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI based on spatial and functional connectivity analysis.Materials and methodsThirty healthy young participants were enrolled. Each subject underwent resting-state fMRI at both 3.0 T and 5.0 T in a random order in less than 48 h. The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. Dice coefficient was used to evaluate the spatial consistency of parcellated networks between 3.0 T and 5.0 T. Functional connectivity (FC) consistency was evaluated using the Euclidian distance and Graph-theory metrics.ResultsA functional cortical atlas consisting of 18 networks was individually parcellated at 3.0 T and 5.0 T. The spatial consistency of these networks at 3.0 T and 5.0 T for the same subject was significantly higher than that of inter-individuals. The FC between the 18 networks acquired at 3.0 T and 5.0 T were highly consistent for the same subject. Positive cross-subject correlations in Graph-theory metrics were found between 3.0 T and 5.0 T.ConclusionIndividualized cortical functional networks at 3.0 T and 5.0 T showed consistent and stable parcellation results both spatially and functionally. The 5.0 T MR provides finer functional sub-network characteristics than that of 3.0 T.

Abstract Purpose This study investigated and compared the effects of Gd enhancement on brain tumours with a half-dose of contrast medium at 5.0 T and with a full dose at 3.0 T. Methods Twelve subjects diagnosed with brain tumours were included in this study and underwent MRI after contrast agent injection at 3.0 T (full dose) or 5.0 T (half dose) with a 3D T1-weighted gradient echo sequence. The postcontrast images were compared by two independent neuroradiologists in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective image quality score on a ten-point Likert scale. Quantitative indices and subjective quality ratings were compared with paired Student's t tests, and interreader agreement was assessed with the intraclass correlation coefficient (ICC). Results A total of 16 enhanced tumour lesions were detected. The SNR was significantly greater at 5.0 T than at 3.0 T in grey matter, white matter and enhanced lesions (p

Background Since the comprehensive implementation of the contracted family doctor service in 2016, the willingness of residents to have their first contact in primary care has gradually increased, but the effectiveness evaluation of contracted residents' first contact in primary care needs to be further explored. Objective To understand the current status of contracted residents' first contact evaluation, explore its influencing factors and propose improvement strategies. Methods A multi-stage stratified random sampling method was used to select 54 community health service institutions/township health centers in three cities in Shandong Province, with a total of 4 000 contracted residents. The first contact dimension questionnaire of the Chinese version of the Primary Care Quality Assessment Scale (PCAT) was used to conduct the survey, comparing the first contact dimension scores of contracted residents with different characteristics and using multiple linear regression to analyse the factors affecting the first contact evaluation of contracted residents. Results A total of 3 859 valid questionnaires were collected, with the effective recovery rate of 96.48%. Among them, 2 086 (54.1%) were residents of township health centers and 1 773 (45.9%) were residents of community health centers; the total score of the first contact dimension in the three regions was 3.49, with the highest score being "Is your contracted institution open on Saturdays and Sundays?" (3.74) ; the item with the lowest score was "During non-business hours, if you were sick at night, would your contracted facility have a doctor or nurse available?" (3.05). The results of the multiple linear regression analysis showed that the contracted facility, personal monthly income, education level, marital status, occupation, physical health and diagnosis of chronic disease were the factors influencing the scores of the first contact dimension of contracted residents (P

Abstract Intrinsic immunosuppressive tumor microenvironment (ITM) and insufficient tumor infiltration of T cells severely impede the progress of glioblastoma (GBM) immunotherapy. In this study, it is identify that inhibiting the expression of glucose transporter 1 (GLUT1) can facilitate the prevention of lactate excretion from tumor glycolysis, which significantly alleviates the lactate‐driven ITM by reducing immunosuppressive tumor‐associated macrophages (TAMs) and regulatory T cells (Tregs). Simultaneously, the findings show that the generated inflammatory cytokine IFN‐γ during immune activation aggravates the immune escape by upregulating immune checkpoint programmed death‐ligand 1 (PD‐L1) in tumor cells and TAMs. Therefore, an injectable thermogel loaded with a GLUT1 inhibitor BAY‐876 and a PD‐1/PD‐L1 blocker BMS‐1 (Gel@B‐B) for dual‐regulation of metabolism and immunity of GBM is developed. Consequently, in situ injection of Gel@B‐B significantly delays tumor growth and prolongs the survival of the orthotopic GBM mouse model. By actively exposing tumor antigens to antigen‐presenting cells, the GBM vaccine combined with Gel@B‐B is found to significantly increase the fraction of effector T cells (Th1/CTLs) in the tumor microenvironment, thereby remarkably mitigating tumor recurrence long‐term. This study may provide a promising strategy for GBM immunotherapy.

Abstract While canonical Wnt signaling is well recognized for its crucial regulatory functions in cell fate decisions, the role of non-canonical Wnt signaling in adult stem cells remains elusive and contradictory. Here, we identified Mcam, a potential member of the non-canonical Wnt signaling, as an important negative regulator of mammary gland epithelial cells (MECs) by genome-scale CRISPR-Cas9 knockout (GeCKO) library screening. Loss of Mcam increases the clonogenicity and regenerative capacity of MECs, and promotes the proliferation, differentiation, and ductal morphogenesis of mammary epithelial in knockout mice. Mechanically, Mcam knockout recruits and polarizes macrophages through the Il4-Stat6 axis, thereby promoting secretion of the non-canonical Wnt ligand Wnt5a and its binding to the non-canonical Wnt signaling receptor Ryk to induce the above phenotypes. These findings reveal Mcam roles in mammary gland development by orchestrating communications between MECs and macrophages via a Wnt5a/Ryk axis, providing evidences for non-canonical Wnt signaling in mammary development.

BackgroundMotor impairment is the most prevalent consequence following a stroke. Interhemispheric homotopic connectivity, which varies regionally and hierarchically along the axis of the somatomotor-association cortex, plays a critical role in sustaining normal motor functions. However, the impact of strokes occurring in various locations on homotopic connectivity is not fully understood. This study aimed to explore how motor deficits resulting from acute strokes in different locations influence homotopic connectivity.MethodsEighty-four acute ischemic stroke patients with dyskinesia were recruited and divided into four demographically-matched subgroups based on stroke locations: Group 1 (G1; frontoparietal, n = 15), Group 2 (G2; radiation coronal, n = 16), Group 3 (G3; basal ganglia, n = 30), and Group 4 (G4; brain stem, n = 23). An additional 37 demographically-matched healthy controls were also recruited in the study. Multimodal MRI data, motor function assessments, and cognitive tests were gathered for analysis. Interhemispheric homotopic functional and structural connectivity were measured using resting-state functional MRI and diffusion tensor imaging, respectively. These measurements were then correlated with motor function scores to investigate the relationships.ResultsVoxel-mirrored homotopic connectivity (VMHC) analysis showed that strokes in the frontoparietal and basal ganglia regions led to diminished homotopic connectivity in the somatosensory/motor cortex. In contrast, strokes in the radiation coronal and brainstem regions affected subcortical motor circuits. Structural homotopic connectivity analysis using diffusion tensor imaging showed that frontoparietal and basal ganglia strokes predominantly affected association fibers, while radiation coronal and brainstem strokes caused widespread disruption in the integrity of both cortical-cortical and cortical-subcortical white matter fibers. Correlation analyses demonstrated significant associations between the Fugl-Meyer Assessment (FMA), Modified Barthel Index (MBI), and National Institutes of Health Stroke Scale (NIHSS) scores with the VMHC in the inferior temporal gyrus for G1 (G1; r = 0.838, p < 0.001; r = 0.793, p < 0.001; and r = −0.834, p < 0.001, respectively). No statistically significant associations were observed in Groups 2, 3, and 4.ConclusionOur results suggest that motor deficits following strokes in various regions involve distinct pathways from cortical to subcortical areas. Alterations in lesion topography and regional functional homotopy provide new insights into the understanding of neural underpinnings of post-stroke dyskinesia.

The use of pumps as turbines has been gaining more and more attention in recent years. The present work mainly investigates the influence of blade wrap angle on the internal flow and pressure fluctuation characteristics of centrifugal pumps as turbines. Five different wrap angles (35°,45°, 55°, 65°, and 75°) for a forward-curved impeller were numerically analyzed under multiple operating conditions. The accuracy of numerical simulation was validated by experimental results. The results show that maximum efficiency is achieved with a blade wrap angle of 35°, and the highest efficiency flow point gradually decreases as the blade wrap angle increases. It is found by conducting entropy production theory analysis that the high-entropy production rate regions in PATs are concentrated in the volute tongue and impeller blade inlet regions, and that the entropy production rate at the impeller inlet region increases and then decreases as the blade wrap angle decreases. In addition, pressure pulsation was affected not only by dynamic and static interference but also by an irregular vortex around the impeller; its magnitude under Qt is higher than 0.8Qt for blade wrap angles of 55° and 75°. The primary frequency of pressure pulsation within the impeller is the axial frequency fn and its multiples, and the frequency with the largest amplitude is 3fn. The periodicity of vortices is closely related to the periodicity of pressure pulsation. And it is suggested that a PAT with a 35° blade wrap angle is advantageous for improving the stability of a turbine.

Abstract To explore the stability and repeatability of diffusion-weighted imaging (DWI) of normal pancreas with different field of views (FOV) on 5.0 T magnetic resonance imaging (MRI) system. Twenty healthy subjects underwent two sessions of large FOV (lFOV) and reduced FOV (rFOV) DWI sequence scanning. Two radiologists measured the apparent diffusion coefficient (ADC) values and the signal-to-noise ratio (SNR) of the pancreatic head, body, and tail on DWI images, simultaneously, using a 5-point scale, evaluate the artifacts and image quality. One radiologist re-measured the ADC on DWI images again after a 4-week interval. The test-retest repeatability of two scan sessions were also evaluated. Intra-observer and inter-observer at lFOV and rFOV, the ADC values were not significantly different (P > 0.05), intraclass correlation coefficients (ICCs) and coefficient of variations were excellence (ICCs 0.85–0.99, CVs

Armeniacae semen amarum—seeds of Prunus armeniaca L. (Rosaceae) (ASA), also known as Kuxingren in Chinese, is a traditional Chinese herbal drug commonly used for lung disease and intestinal disorders. It has long been used to treat coughs and asthma, as well as to lubricate the colon and reduce constipation. ASA refers to the dried ripe seed of diverse species of Rosaceae and contains a variety of phytochemical components, including glycosides, organic acids, amino acids, flavonoids, terpenes, phytosterols, phenylpropanoids, and other components. Extensive data shows that ASA exhibits various pharmacological activities, such as anticancer activity, anti-oxidation, antimicrobial activity, anti-inflammation, protection of cardiovascular, neural, respiratory and digestive systems, antidiabetic effects, and protection of the liver and kidney, and other activities. In clinical practice, ASA can be used as a single drug or in combination with other traditional Chinese medicines, forming ASA-containing formulas, to treat various afflictions. However, it is important to consider the potential adverse reactions and pharmacokinetic properties of ASA during its clinical use. Overall, with various bioactive components, diversified pharmacological actions and potent efficacies, ASA is a promising drug that merits in-depth study on its functional mechanisms to facilitate its clinical application.

Traumatic brain injury (TBI) leads to structural damage in the brain, and is one of the major causes of disability and death in the world. Herein, we developed a composite injectable hydrogel (HA/Gel) composed of hyaluronic acid (HA) and gelatin (Gel), loaded with vascular endothelial growth factor (VEGF) and salvianolic acid B (SAB) for treatment of TBI. The HA/Gel hydrogels were formed by the coupling of phenol-rich tyramine-modified HA (HA-TA) and tyramine-modified Gel (Gel-TA) catalyzed by horseradish peroxidase (HRP) in the presence of hydrogen peroxide (H2O2). SEM results showed that HA/Gel hydrogel had a porous structure. Rheological test results showed that the hydrogel possessed appropriate rheological properties, and UV spectrophotometry results showed that the hydrogel exhibited excellent SAB release performance. The results of LIVE/DEAD staining, CCK-8 and Phalloidin/DAPI fluorescence staining showed that the HA/Gel hydrogel possessed good cell biocompatibility. Moreover, the hydrogels loaded with SAB and VEGF (HA/Gel/SAB/VEGF) could effectively promote the proliferation of bone marrow mesenchymal stem cells (BMSCs). In addition, the results of H&E staining, CD31 and α-SMA immunofluorescence staining showed that the HA/Gel/SAB/VEGF hydrogel possessed good in vivo biocompatibility and pro-angiogenic ability. Furthermore, immunohistochemical results showed that the injection of HA/Gel/SAB/VEGF hydrogel to the injury site could effectively reduce the volume of defective tissues in traumatic brain injured mice. Our results suggest that the injection of HA/Gel hydrogel loaded with SAB and VEGF might provide a new approach for therapeutic brain tissue repair after traumatic brain injury.

Acute lung injury (ALI) is a common condition, particularly in the COVID-19 pandemic, which is distinguished by sudden onset of respiratory insufficiency with tachypnea, oxygen-refractory cyanosis, reduced lung compliance and diffuse infiltration of pulmonary alveoli. It is well-established that increasing activity of toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) signaling axis and the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome activation are associated with the pathogenesis of ALI. Since ALI poses a huge challenge to human health, it is urgent to tackle this affliction with therapeutic intervention. Qinhuo Shanggan oral solution (QHSG), a traditional Chinese herbal formula, is clinically used for effective medication of various lung diseases including ALI, with the action mechanism obscure. In the present study, with the rat model of lipopolysaccharide (LPS)-induced ALI, QHSG was unveiled to ameliorate ALI by alleviating the pathological features, reversing the alteration in white blood cell profile and impeding the production of inflammatory cytokines through down-regulation of TLR4/NF-κB signaling cascade and inhibition of NLRP3 inflammasome activation. In LPS-stimulated RAW264.7 mouse macrophages, QHSG was discovered to hinder the generation of inflammatory cytokines by lessening TLR4/NF-κB signaling pathway activity and weakening NLRP3 inflammasome activation. Taken together, QHSG may resolve acute lung injury, attributed to its anti-inflammation and immunoregulation by attenuation of TLR4/NF-κB signaling cascade and inhibition of NLRP3 inflammasome activation. Our findings provide a novel insight into the action mechanism of QHSG and lay a mechanistic foundation for therapeutic intervention in acute lung injury with QHSG in clinical practice.

Abstract Sensitive and reliable determination of thrombin is relevant in the realms of medical and biological research as it serves as an essential biomarker of a number of blood-related illnesses. Herein, we integrate allosteric probe-based specific identification of thrombin and dual signal amplification to present an unique fluorescent technique for label-free and sensitive thrombin detection. Based on DNA polymerase and endonuclease-assisted signal amplification, the method exhibits a high sensitivity with a low limit of detection of 2.3 pM, while maintaining an excellent selectivity and stability. More importantly, the approach is successfully applied in analyzing the effect of nalbuphine on coagulation function of mice. Overall, this approach possesses the advantages of high specificity and sensitivity in label-free detection of thrombin, which is promising in the diagnosis of blood-related diseases.

[Introduction] Based on an offshore wind farm construction project in Qidong, Jiangsu Province, the numerical simulation study on mechanical characteristics of submarine cable during laying process was carried out and the local stress distribution of the suspension span of submarine cables under different trenching depths was analyzed. [Method] A numerical model of submarine cable laying based on ABAQUS numerical simulation software was established. [Result] Results show that the stress of the lifting point at the trailing edge of the submarine cable increases significantly during the burial process compared with that before the burial operation. This is the most dangerous position as the cable at this position has the largest stress during the whole burial process. The trenching depth has a significant effect on the stress at the lifting point at the trailing edge of the cable. With the increase of the trenching depth, the stress at the lifting point at the trailing edge increases correspondingly. [Conclusion] The selection of cable material at the lifting point should be protected in the cable laying operation, and the yield stress parameters of the cable should be mainly based on the stress analysis results of the cable in the burial operation. The research results can provide a reference for submarine cable laying operation.

In recent years, with the development of artificial intelligence, especially deep learning technology, researches on automatic detection of cerebrovascular diseases on medical images have made tremendous progress and these models are gradually entering into clinical practice. However, because of the complexity and flexibility of the deep learning algorithms, these researches have great variability on model building, validation process, performance description and results interpretation. The lack of a reliable, consistent, standardized design protocol has, to a certain extent, affected the progress of clinical translation and technology development of computer aided detection systems. After reviewing a large number of literatures and extensive discussion with domestic experts, this position paper put forward recommendations of standardized design on the key steps of deep learning-based automatic image detection models for cerebrovascular diseases. With further research and application expansion, this position paper would continue to be updated and gradually extended to evaluate the generalizability and clinical application efficacy of such tools.

Diagnosis of fluids is extremely significant at high temperatures and high pressures. As an advanced imaging technique, high-energy proton radiography has great potential for application to the diagnosis of high-density fluids. In high-energy proton radiography, an angular collimator can control the proton flux and thus enable material diagnosis and reconstruction of density. In this paper, we propose a multi-material diagnostic method using angular collimators. The method is verified by reconstructing the density distribution from the proton flux obtained via theoretical calculations and numerical simulations. We simulate a 20 GeV proton imaging system using the Geant4 software toolkit and obtain the characteristic parameters of single-material objects. We design several concentric spherical objects to verify the method. We discuss its application to detonation tests. The results show that this method can determine the material and boundary information about each component of a multi-material object. Thus, it can be used to diagnose a mixed material and reconstruct densities in a detonation.

The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result of the challenges associated with manually evaluating magnetic resonance imaging (MRI) images in clinical practice. In this study, we built a computer-aided diagnosis (CAD) system for glioma detection, grading, segmentation, and knowledge discovery based on artificial intelligence algorithms. Neuroimages are specifically represented using a type of visual feature known as the histogram of gradients (HOG). Then, through a two-level classification framework, the HOG features are employed to distinguish between healthy controls and patients, or between different glioma grades. This CAD system also offers tumor visualization using a semi-automatic segmentation tool for better patient management and treatment monitoring. Finally, a knowledge base is created to offer additional advice for the diagnosis of brain tumors. Based on our proposed two-level classification framework, we train models for glioma detection and grading, achieving area under curve (AUC) of 0.921 and 0.806, respectively. Different from other systems, we integrate these diagnostic tools with a web-based interface, which provides the flexibility for system deployment.

IntroductionThis study aims to develop an imaging model based on multi-parametric MR images for distinguishing between prostate cancer (PCa) and prostate hyperplasia.MethodsA total of 236 subjects were enrolled and divided into training and test sets for model construction. Firstly, a multi-view radiomics modeling strategy was designed in which different combinations of radiomics feature categories (original, LoG, and wavelet) were compared to obtain the optimal input feature sets. Minimum-redundancy maximum-relevance (mRMR) selection and least absolute shrinkage selection operator (LASSO) were used for feature reduction, and the next logistic regression method was used for model construction. Then, a Swin Transformer architecture was designed and trained using transfer learning techniques to construct the deep learning models (DL). Finally, the constructed multi-view radiomics and DL models were combined and compared for model selection and nomogram construction. The prediction accuracy, consistency, and clinical benefit were comprehensively evaluated in the model comparison.ResultsThe optimal input feature set was found when LoG and wavelet features were combined, while 22 and 17 radiomic features in this set were selected to construct the ADC and T2 multi-view radiomic models, respectively. ADC and T2 DL models were built by transferring learning from a large number of natural images to a relatively small sample of prostate images. All individual and combined models showed good predictive accuracy, consistency, and clinical benefit. Compared with using only an ADC-based model, adding a T2-based model to the combined model would reduce the model’s predictive performance. The ADCCombinedScore model showed the best predictive performance among all and was transformed into a nomogram for better use in clinics.DiscussionThe constructed models in our study can be used as a predictor in differentiating PCa and BPH, thus helping clinicians make better clinical treatment decisions and reducing unnecessary prostate biopsies.

Background and objectiveThis study aims to examine the role of neurovascular coupling (NVC) in vascular cognitive impairment (VCI) by investigating the relationship between white matter lesion (WML) burden, NVC, and cognitive deficits. Additionally, we aim to explore the potential of NVC as a tool for understanding the neural mechanisms underlying VCI.MethodsThis study included thirty-eight small vessel disease cognitive impairment (SVCI) patients, 34 post-stroke cognitive impairment (PSCI) patients, and 43 healthy controls (HC). Comprehensive assessments, including neuroimaging and neuropsychological testing, were conducted to evaluate cognitive function. WML burden was measured and correlated with NVC coefficients to examine the relationship between white matter pathology and NVC. Mediation analysis was employed to explore the link relationship between NVC, WML burden, and cognitive function.ResultsThe present study showed that NVC was significantly reduced in the SVCI and PSCI groups compared with HCs at both whole-brain and brain region level. The analysis revealed notable findings regarding NVC in relation to WML burden and cognitive function in VCI patients. Specifically, reduced NVC coefficients were observed within higher order brain systems responsible for cognitive control and emotion regulation. Mediation analysis demonstrated that NVC played a mediating role in the relationship between WML burden and cognitive impairment.ConclusionThis study reveals the mediating role of NVC in the relationship between WML burden and cognitive function in VCI patients. The results demonstrate the potential of the NVC as an accurate measure of cognitive impairment and its ability to identify specific neural circuits affected by WML burden.

A fish bone penetrating the digestive tract is a common emergency, and its removal often requires endoscopy. We report herein a case in which a fish bone punctured the throat; its front end was close to the common carotid artery, but its back end could not be visualized. Subsequently, we compared the pharyngeal CT and carotid CTA of the patient and found that the fishbone had shifted. So we considered that the end of the fish bone could be rediscovered and successfully removed by a video laryngoscope. Finally, with the patient under deep sedation with maintained spontaneous breathing, the fish bone was removed using video laryngoscopy. This case highlights the importance of rechecking CT scans and the use of laryngoscopy when determining the location of a shifted foreign body at different times and when selecting the removal method.

Abstract Background The Wnt signaling pathway is a complex network of protein interactions that functions most commonly in embryonic development and cancer, but is also involved in normal physiological processes in adults. The canonical Wnt signaling pathway regulates cell pluripotency and determines the differentiation fate of cells during development. The canonical Wnt signaling pathway (also known as the Wnt/β-catenin signaling pathway) is a recognized driver of colon cancer and one of the most representative signaling pathways. As a functional effector molecule of Wnt signaling, the modification and degradation of β-catenin are key events in the Wnt signaling pathway and the development and progression of colon cancer. Therefore, the Wnt signaling pathway plays an important role in the pathogenesis of diseases, especially the pathogenesis of colorectal cancer (CRC). Objective Inhibit the Wnt signaling pathway to explore the therapeutic targets of colorectal cancer. Methods Based on studying the Wnt pathway, master the biochemical processes related to the Wnt pathway, and analyze the relevant targets when drugs or inhibitors act on the Wnt pathway, to clarify the medication ideas of drugs or inhibitors for the treatment of diseases, especially colorectal cancer. Results Wnt signaling pathways include: Wnt/β-catenin or canonical Wnt signaling pathway, planar cell polarity (Wnt-PCP) pathway and Wnt-Ca2+ signaling pathway. The Wnt signaling pathway is closely related to cancer cell proliferation, stemness, apoptosis, autophagy, metabolism, inflammation and immunization, microenvironment, resistance, ion channel, heterogeneity, EMT/migration/invasion/metastasis. Drugs/phytochemicals and molecular preparations for the Wnt pathway of CRC treatment have now been developed. Wnt inhibitors are also commonly used clinically for the treatment of CRC. Conclusion The development of drugs/phytochemicals and molecular inhibitors targeting the Wnt pathway can effectively treat colorectal cancer clinically.

Abstract Out-of-step oscillation separation devices based on apparent impedance angle trajectory are widely used in the power grid in China, and their reliability is of great importance. In this paper, the influence mechanism of series compensation on apparent impedance angle trajectory is analyzed. It reveals that series compensation capacitors reduce the equivalent impedance angle and consequently the apparent impedance angle cannot pass through all four zones, resulting in the risk of failure for the separation devices. A revised method of apparent impedance angle based on compensation principle is discussed, and then an improved out-of-step oscillation detection criterion is proposed. In view of the fact that the apparent impedance angle at the moment of maximum current is equal to the equivalent impedance angle during an oscillation process, a practical algorithm based on the compensated apparent impedance angle is proposed. RTDS tests are conducted to verify the effectiveness of the new criterion, considering transmission lines with a high series compensation level.

The prediction of parking occupancy is of great importance to urban planning. As the number of cars increases and parking resources become limited, the lack of parking supply has become a challenge for urban design. Previous works ignore the correlation between car parks when predicting parking occupancy, which limits the accuracy of the prediction. To address this issue, this study proposes a Temporal-GCN-based correlated parking prediction model (CPPM) to forecast the temporal occupancy of car parks. In particular, the model utilises Convolutional Neural Networks (CNN) and Bayesian probabilities to extract street view similarities in car parks, as well as their spatial correlations, cosine similarity is used to calculate the activity type similarity, and Graph Convolutional Networks (GCN) and Gate Recurrent Units (GRU) are integrated to predict spatio-temporal car park occupancy, taking into account both temporal parking records, similarities in car parks, and their spatial correlations. We conducted two case studies in Ningbo and Beijing, China, integrating over 10 million parking sensing records and corresponding street view images of parking lots to predict parking occupancy. The results show that our model has outstanding performance over the baselines and can be extended for various types of car parks in cities of different sizes and different levels of development. The results also reveal the parking preferences of the citizens of Ningbo and Beijing, which is valuable for a quantitative understanding of commuters’ parking patterns and behaviour and can be used as a guide for urban planning and management.

BackgroundThis study aimed to examine depressive symptoms associated with interpersonal sensitivity, sleep quality, and psychological capital among postgraduate students during static campus management after the COVID-19 pandemic in China.MethodsResearch data were obtained during static campus management (10–19 April 2022) after the reappearance of COVID-19 in cities in eastern China. We collected data through an online questionnaire, and the anonymous self-reported questionnaire included the Patient Health Questionnaire, the interpersonal sensitivity subscale of Symptom Checklist-90, the Psychological Capital Questionnaire, and the Pittsburgh Sleep Quality Index. analysis of variance was performed using t-test and ANOVA. The PROCESS macro was used to determine the relationship between interpersonal sensitivity and depression, together with the independent and serial mediating role of psychological capital and sleep quality.ResultsA total of 2,554 postgraduate students were included in this study. The prevalence of mild, moderate, and severe depressive symptoms was 30.97, 6.58, and 1.45%, respectively. Interpersonal sensitivity was significantly associated with depressive symptoms (direct effect = 0.183, p < 0.001). Between interpersonal sensitivity and depressive symptoms, psychological capital and sleep quality played a single mediating role (indirect effect = 0.136 and 0.100, p < 0.001, respectively) and a chain mediating role together (indirect effect = 0.066, p < 0.001).ConclusionInterpersonal sensitivity has a significant influence on depression among Chinese graduate students. Psychological capital and sleep quality may not only independently mediate the relationship between interpersonal sensitivity and depression, but also co-play a chain-mediating role in the pathway from interpersonal sensitivity to depression. Positive psychological interventions and sleep guidance may be beneficial in alleviating depressive symptoms.

Polypropylene (PP) fiber is widely used in construction, transportation, automobile, textile, electronic and electrical appliances, chemical industry, and other fields; however, its nonresistance to UV degradation must be further studied. Herein, 2-hydroxy-4-methoxybenzophenone-5-sulfonic acid (UVSA) anion was inserted into zinc-aluminum-layered double hydroxide (ZnAl-LDH) by coprecipitation, and the organic-inorganic synergistic UV-stabilized material UVSA-LDH was successfully synthesized. Furthermore, a new UVSA-LDH/PP fiber with UV aging resistance was prepared by adding UVSA-LDH to the PP matrix through the melt spinning method. The insertion of UVSA improved the ultraviolet absorption of ZnAl-LDH, and the existence of LDH laminates inhibited the thermal degradation of organic UVSA. Moreover, the addition of UVSA-LDH greatly enhanced the thermal stability and UV aging degradation resistance of PP fiber. As expected, compared with pure PP fiber, the thermal decomposition temperature of 3 wt% UVSA-LDH/PP composite fiber increased by 38 °C, and the fiber strength retention was as high as 94.56% after aging for 6 days. Therefore, this organic-inorganic synergistic UVSA-LDH has potential application prospect as a UV-stabilized material for PP fiber.

In recent years, calcium reduction diffusion has emerged as a new method for in situ regeneration of Nd–Fe–B sludge. In this work, rotation calcium thermal reduction diffusion technology was used for the first time to solve the issue of batch regeneration of Nd–Fe–B sludge to a certain extent, and regenerated Nd–Fe–B powder with uniform size and good dispensability was prepared. The effect of rotation rate on the properties of regenerated Nd–Fe–B powder was mainly studied. We found that the magnetic properties of the regenerated magnetic powder initially increased and then decreased with increasing rotation rate. When the rotation rate was 10 rpm, the magnetization of regenerated magnetic powder reached 138.22 emu/g, which was 10.2% higher than that of the purified sludge. The regenerated magnetic powder was doped with rare earth-rich alloy powder and high remanence alloy powder to control the composition, where the regenerated sintered magnet was prepared. The density reached 7.51 g/cm3 and the maximum magnetic energy product reached 42.87 MGOe, laying a foundation for the short-process in situ regeneration of Nd–Fe–B sludge.

BackgroundA greatly growing body of literature has revealed the mediating role of DNA methylation in the influence path from childhood maltreatment to psychiatric disorders such as post-traumatic stress disorder (PTSD) in adult. However, the statistical method is challenging and powerful mediation analyses regarding this issue are lacking.MethodsTo study how the maltreatment in childhood alters long-lasting DNA methylation changes which further affect PTSD in adult, we here carried out a gene-based mediation analysis from a perspective of composite null hypothesis in the Grady Trauma Project (352 participants and 16,565 genes) with childhood maltreatment as exposure, multiple DNA methylation sites as mediators, and PTSD or its relevant scores as outcome. We effectively addressed the challenging issue of gene-based mediation analysis by taking its composite null hypothesis testing nature into consideration and fitting a weighted test statistic.ResultsWe discovered that childhood maltreatment could substantially affected PTSD or PTSD-related scores, and that childhood maltreatment was associated with DNA methylation which further had significant roles in PTSD and these scores. Furthermore, using the proposed mediation method, we identified multiple genes within which DNA methylation sites exhibited mediating roles in the influence path from childhood maltreatment to PTSD-relevant scores in adult, with 13 for Beck Depression Inventory and 6 for modified PTSD Symptom Scale, respectively.ConclusionOur results have the potential to confer meaningful insights into the biological mechanism for the impact of early adverse experience on adult diseases; and our proposed mediation methods can be applied to other similar analysis settings.

Primary cardiac intimal sarcoma, an extremely rare cardiac tumor subtype, is often mis-diagnosed owing to its rarity and non-specific clinical and radiological features. We report a case of cardiac intimal sarcoma mimicking atrial myxoma in which the clinical presentation and multimodality imaging are described in detail, and diagnostic challenges are highlighted.

The state of health (SOH) estimation accuracy of lithium-ion battery affects the safety and service life of batteries. Aimed at the problem in SOH estimation of lithium-ion battery, a cuckoo search support vector regression (CS-SVR) model based on the evidence reasoning (ER) rule was proposed for SOH estimation. The lithium-ion battery data from NASA Ames Center was used to perform the SOH estimation test. In this method, the average voltage and average temperature of battery discharge cycles were taken as model input, and a fusion belief degree matrix of input data was obtained by the ER rule. The SOH estimation result of the battery was obtained by inputting a fusion belief degree matrix into the SVR model optimized by the CS algorithm. The results show that the CS-SVR algorithm based on the ER rule has a better estimation performance than the five existing models.

Abstract In spite of the popularity of random forests (RF) as an efficient machine learning algorithm, methods for constructing the potential association for between patent foramen ovale (PFO) and cryptogenic stroke (CS) using this technique are still barely. For the vital regional study areas (atrial septum), RF was used to predict CS in patients with PFO using partial clinical data of patients and remotely sensed imaging examination data obtained from Tee imaging. We validated our method on a dataset of 151 consecutive patients with detected PFO at a large grade A hospital in China from November 2018 to December 2020, we obtained an area under the relative operating characteristic curve of 0.816, with 65% specificity at 73% sensitivity. The RF models accurately represented the relationship between the CS and remotely sensed predictor variables. Therein, maximum mobility, large right-to-left shunt during Valsalva maneuver, size of PFO in diastole and systole, and diastolic length of the tunnel present higher predictive value in CS. Our findings suggest that multi-Doppler sensor data by transesophageal echocardiography (TEE)-detected morphologic and functional characteristics of PFO may play important roles in the occurrence of CS. These results indicate that the established random forest model has the potential to predict CS in patients with PFO and great promise for application to clinical practice.

Background: The clinical applications of stromal vascular fraction (SVF) therapy for osteoarthritis (OA) have attracted academic and clinical attention. However, data of the effects of stromal vascular fraction therapy on regeneration of degenerated cartilage are limited in the literature. Meanwhile, there is a great need for a simple and non-invasive evaluation method to analyze the changes of joint cartilage qualitatively and quantitatively in clinical trials. This study entitled “stromal vascular fraction Therapy for Human Knee Osteoarthritis” was registered in ClinicalTrial.gov # NCT05019378.Materials and Methods: We designed and conducted a single center, open labeled clinical phase I/II study, and 6 osteoarthritis patients with both knee cartilage defect I-II were enrolled in this study. The two knees of each patient were randomly assigned to autologous stromal vascular fraction treatment group or non-treatment control group to evaluate the safety and therapeutic effect of stromal vascular fraction therapy for human knee osteoarthritis. We have also established a novel protocol to provide 3D MRI imaging for human knee cartilage enabling us to qualitatively and quantitatively evaluate cartilage degeneration and regeneration in this study.Results: The qualitative and quantitative evaluation of 3D Magnetic Resonance Imaging (MRI) imaging of knee cartilage demonstrated that the stromal vascular fraction therapy reduced the cartilage defects; and significant increase of cartilage value both in defect cartilage area and whole cartilage area of treated group and significant increase of thickness and area of both femoral and tibia cartilage in vertical sections of the stromal vascular fraction treated Group at 12 and 24 W post treatment in cartilage defect I-II osteoarthritis patients.Conclusion: This clinical phase I/II study indicated that stromal vascular fraction therapy is a safe clinical procedure and provided evidence that the stromal vascular fraction therapy significantly facilitated cartilage regeneration, opening the opportunity to a phase III trial investigating authentic efficacy of the procedure. This study is the first qualitative and quantitative evaluation of the efficacy of autologous stromal vascular fraction cellular therapy on cartilage regeneration. Through early and definite diagnosis of knee osteoarthritis patients, and providing safe and efficient therapy to facilitate cartilage regeneration, we will be able to control or reverse cartilage degeneration and completely change the epidemiology of osteoarthritis worldwide.

Background and purposePatients with asymptomatic carotid stenosis, even without stroke, are at high risk for cognitive impairment, and the neuroanatomical basis remains unclear. Using a novel edge-centric structural connectivity (eSC) analysis from individualized single-subject cortical thickness networks, we aimed to examine eSC and network measures in severe (> 70%) asymptomatic carotid stenosis (SACS).MethodsTwenty-four SACS patients and 24 demographically- and comorbidities-matched controls were included, and structural MRI and multidomain cognitive data were acquired. Individual eSC was estimated via the Manhattan distances of pairwise cortical thickness histograms.ResultsIn the eSC analysis, SACS patients showed longer interhemispheric but shorter intrahemispheric Manhattan distances seeding from left lateral temporal regions; in network analysis the SACS patients had a decreased system segregation paralleling with white matter hyperintensity burden and recall memory. Further network-based statistic analysis identified several eSC and subgraph features centred around the Perisylvian regions that predicted silent lesion load and cognitive tests.ConclusionWe conclude that SACS exhibits abnormal eSC and a less-optimized trade-off between physical cost and network segregation, providing a reference and perspective for identifying high-risk individuals.

IntroductionThe number of college students with mental problems has increased significantly, particularly during COVID-19. However, the clinical features of early-stage psychological problems are subclinical, so the optimal intervention treatment period can easily be missed. Artificial intelligence technology can efficiently assist in assessing mental health problems by mining the deep correlation of multi-dimensional data of patients, providing ideas for solving the screening of normal psychological problems in large-scale college students. Therefore, we propose a mental health assessment method that integrates traditional scales and multimodal intelligent recognition technology to support the large-scale and normalized screening of mental health problems in colleges and universities.MethodsFirstly, utilize the psychological assessment scales based on human-computer interaction to conduct health questionnaires based on traditional methods. Secondly, integrate machine learning technology to identify the state of college students and assess the severity of psychological problems. Finally, the experiments showed that the proposed multimodal intelligent recognition method has high accuracy and can better proofread normal scale results. This study recruited 1,500 students for this mental health assessment.ResultsThe results showed that the incidence of moderate or higher stress, anxiety, and depression was 36.3, 48.1, and 23.0%, which is consistent with the results of our multiple targeted tests.ConclusionTherefore, the interactive multimodality emotion recognition method proposed provides an effective way for large-scale mental health screening, monitoring, and intervening in college students' mental health problems.

ABSTRACT Many diverse pathogens have been discovered from reproductive-tract infections, but the relationship between the presence and abundance of particular pathogen species and disease manifestations is poorly defined. The present work examined the association of multiple common pathogens causing sexually transmitted infections (STIs) with cervicitis and vaginitis. The presence and abundance of 15 STI pathogens and the genotypes of human papillomavirus were determined in a cohort of 944 women that included 159 cervicitis patients, 207 vaginitis patients, and 578 healthy controls. Logistic regression and random forest models were constructed and validated in a separate cohort of 420 women comprising 52 cervicitis patients, 109 vaginitis patients, and 259 healthy controls. The frequency of individual STI pathogen species varied among the symptomatic patients and healthy controls. Abundance determination was necessary for most pathogens that were associated with the studied diseases. STI pathogens were more commonly associated with cervicitis than with vaginitis. Pathogen identification- and quantification-based diagnosis was observed for cervicitis with high sensitivity and specificity, but for vaginitis, the assay results would need to be combined with results of other diagnostic tests to firmly establish the pathogen-disease correlation. Integrated qualitative and quantitative detection of a selected panel of common STI pathogens can reveal their association with cervicitis and vaginitis. STI pathogen identification and quantification can be used to diagnose cervicitis and also help improve correct diagnosis of vaginitis. IMPORTANCE Scarce information exists with regard to whether STI pathogens can be defined as valid microbiological predictive markers for the diagnosis of cervicitis and vaginitis. We therefore conducted this study to assess the presence and abundance of a wide range of STI pathogens among patients having these two diseases and healthy controls as well. High sensitivity and specificity were observed for cervicitis by pathogen identification- and quantification-based diagnosis. In contrast, the assay results obtained for vaginitis would need to be combined with test results obtained by other diagnostic methods to decisively establish the pathogen-disease correlation. Simultaneous qualitative and quantitative detection of a selected panel of common STI pathogens and further coupling with machine learning models is worthwhile for establishing pathogen-based diagnosis of gynecological inflammations, which could be of great value in guiding the rational use of antimicrobials to control the spread of STIs.

IntroductionAnxiety often precedes depression, and the pathway from anxiety to depression may be affected by multiple exposures. Our research aims to explore the mediating effect of the social support availability (SSA) between anxiety and depression and how it is moderated by psychological capital.MethodsA cross-sectional study was conducted among Chinese emergency physicians at the top-level general hospitals in eastern China. Data were collected via the questionnaire including anxiety and depression subscales of Symptom Checklist-90, Psychological Capital Questionnaire as well as Social Support Rating Scale. The PROCESS v3.4 macro was employed to assess the mediating role of SSA and a moderating role of psychological capital.ResultsA total of 536 valid samples were filtered. Anxiety, depression, SSA, and psychological capital were significant correlated. Anxiety was positively associated with depression (β = 0.82, p < 0.001), and the SSA mediated the relationship between anxiety and depression (indirect effect = 0.013, 95%BootCI [0.005, 0.023]). Psychological capital (specifically, self-efficacy, hope and resilience) further played a moderating role in the relationship between SSA and depression (β = 0.06, p < 0.01).ConclusionThe mental health of emergency physicians should be concerned. In order to decrease anxiety and depression, SSA and psychological capital should be increased as the interventions for emergency physicians.

Nowadays, one of the leading causes of death in humans is cancer, which is still on the rise globally and is in great need of intense study on the pathogenic mechanism and effective therapy. Epigenetics is a discipline that studies heritable changes in gene expression without alteration of DNA sequence. Epigenetic changes mainly involve DNA methylation, histone modifications and non-coding RNA (ncRNA) expression, which are interconnected to play a crucial role in the initiation and progression of various malignancies. Curcumin is a type of plant-derived polyphenolic compound with strong bioactivity against various disorders, particularly cancer. Retrieving commonly used databases such as PubMed, Google Scholar and CNKI, we summarized recent advances in the efficacy of curcumin on cancer and its epigenetic regulation in terms of DNA methylation, histone modifications and ncRNA expression. Furthermore, we also focused on improving the bioavailability of curcumin by development of novel curcumin analogs with high bioavailability, nanoparticles-loaded drug delivery system for curcumin, and combination therapy of curcumin with other agents. This review provides comprehensive insights into the molecular mechanisms, on the basis of epigenetic regulation, underlying the clinical application of curcumin in cancer.

To investigate the prevalence of interpersonal sensitivity, anxiety, depression symptoms and associated risk factors among a large-scale sample of college students in China during the COVID-19 campus lockdown. The survey was conducted among undergraduate students at a university in eastern part of China in April 2022. The Chi-square test was used to compare the different variable groups and multivariable analysis was performed for the risk factors associated with interpersonal sensitivity, anxiety, and depression symptoms. A total of 12,922 college students were included, with an average age of (20.96 ± 1.66) years. The prevalence of interpersonal sensitivity, anxiety and depression symptoms in this study was 58.1, 22.7, and 46.8%, respectively. Male (OR = 1.16, p