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Irritable bowel syndrome (IBS) is a functional bowel disorder frequently associated with other pain syndromes and psychiatric conditions, including depression and anxiety. These abnormalities coincide with alterations in the brain’s structure, particularly in the thalamus and cingulate system. Acupuncture has been demonstrated to be highly effective in treating IBS. However, it remains unclear how white matter (WM) tracts change after acupuncture treatment, and whether the neuroplasticity of these tracts can serve as a neural marker to assist in the development of novel treatments. In this study, we aim to answer these questions by investigating longitudinal changes in the WM of the thalamus and cingulate system in a group of diarrhea-predominant irritable bowel syndrome (IBS-D) patients before and after acupuncture treatment. We found that after acupuncture treatment, as IBS symptoms improved, there were significant changes in the microstructure of the right thalamus radiation (TR) (p

PurposeTo develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs).Material and methodsThe study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples. The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. Features from DTL and radiomics were extracted and integrated using X-ray images. The optimal fusion feature model was identified through least absolute shrinkage and selection operator logistic regression. Evaluation of the predictive capabilities for OVFs classification involved eight machine learning models, assessed through receiver operating characteristic curves employing the “One-vs-Rest” strategy. The Delong test was applied to compare the predictive performance of the superior RadImageNet model against the ImageNet model.ResultsFollowing pre-training separately on RadImageNet and ImageNet datasets, feature selection and fusion yielded 17 and 12 fusion features, respectively. Logistic regression emerged as the optimal machine learning algorithm for both DLR models. Across the training set, internal validation set, external validation set, and prospective validation set, the macro-average Area Under the Curve (AUC) based on the RadImageNet dataset surpassed those based on the ImageNet dataset, with statistically significant differences observed (P

Ischemic stroke (IS) refers to local brain tissue necrosis which is caused by impaired blood supply to the carotid artery or vertebrobasilar artery system. As the second leading cause of death in the world, IS has a high incidence and brings a heavy economic burden to all countries and regions because of its high disability rate. In order to effectively treat IS, a large number of drugs have been designed and developed. However, most drugs with good therapeutic effects confirmed in preclinical experiments have not been successfully applied to clinical treatment due to the low accumulation efficiency of drugs in IS areas after systematic administration. As an emerging strategy for the treatment of IS, stimuli-responsive nanomedicines have made great progress by precisely delivering drugs to the local site of IS. By response to the specific signals, stimuli-responsive nanomedicines change their particle size, shape, surface charge or structural integrity, which enables the enhanced drug delivery and controlled drug release within the IS tissue. This breakthrough approach not only enhances therapeutic efficiency but also mitigates the side effects commonly associated with thrombolytic and neuroprotective drugs. This review aims to comprehensively summarize the recent progress of stimuli-responsive nanomedicines for the treatment of IS. Furthermore, prospect is provided to look forward for the better development of this field.

Secondary spinal cord injury (SSCI) is the second stage of spinal cord injury (SCI) and involves vasculature derangement, immune response, inflammatory response, and glial scar formation. Bioactive additives, such as drugs and cells, have been widely used to inhibit the progression of secondary spinal cord injury. However, the delivery and long-term retention of these additives remain a problem to be solved. In recent years, hydrogels have attracted much attention as a popular delivery system for loading cells and drugs for secondary spinal cord injury therapy. After implantation into the site of spinal cord injury, hydrogels can deliver bioactive additives in situ and induce the unidirectional growth of nerve cells as scaffolds. In addition, physical and chemical methods can endow hydrogels with new functions. In this review, we summarize the current state of various hydrogel delivery systems for secondary spinal cord injury treatment. Moreover, functional modifications of these hydrogels for better therapeutic effects are also discussed to provide a comprehensive insight into the application of hydrogels in the treatment of secondary spinal cord injury.

Iridoid glycoside is the important secondary metabolite and the main active component in Rehmannia glutinosa. However, the mechanisms that underlie the regulation of iridoid glycoside biosynthesis remain poorly understood in R. glutinosa. Herein, the analysis of RNA-seq data revealed that 3,394 unigenes related to the biosynthesis of secondary metabolites were identified in R. glutinosa. A total of 357 unigenes were involved in iridoid glycoside synthesis, in which the highly conservative genes, such as DXS, DXR, GPPS, G10H, and 10HGO, in organisms were overexpressed. The analysis of the above genes confirmed that the co-occurrence ratio of DXS, DXR, and GPPS was high in plants. Further, our results showed that under normal and 5-azacytidine (5-azaC) treatment, the expression levels of DXS, DXR, GPPS, G10H, and 10HGO were consistent with the iridoid glycoside accumulation in R. glutinosa, in which the application of the different concentrations of 5-azaC, especially 50 μM 5-azaC, could significantly upregulate the expression of five genes above and iridoid glycoside content. In addition, the changes in the spatiotemporal specificity of degree and levels of DNA methylation were observed in R. glutinosa, in which the hemi-methylation was the main reason for the change in DNA methylation levels. Similar to the changes in 5-methyl cytosine (5mC) content, the DNA demethylation could be induced by 5-azaC and responded in a dose-dependent manner to 15, 50, and 100 μM 5-azaC. Taken together, the expression of iridoid glycoside synthesis gene was upregulated by the demethylation in R. glutinosa, followed by triggering the iridoid glycoside accumulation. These findings not only identify the key genes of iridoid glycoside synthesis from R. glutinosa, but also expand our current knowledge of the function of methylation in iridoid glycoside accumulation.

ObjectivesTo investigate the association between the perivascular adipose tissue (PVAT) fat attenuation index (FAI) derived from coronary computed tomography angiography (CCTA) and the prevalence of in-stent restenosis (ISR) in patients with coronary stent implantation.MethodsA total of 117 patients with previous coronary stenting referred for invasive coronary angiography (ICA) were enrolled in this retrospective observational analysis. All patients underwent CCTA between July 2016 and November 2021. The deep learning-based (DL-based) method was used to analyze and measure the peri-stent FAI value. Additionally, the relationship between hematological and biochemical parameters collected from all the patients was also explored. The least absolute shrinkage and selection operator (LASSO) method was applied to the most useful feature selection, and binary logistic regression was used to test the association between the selected features and ISR. The predictive performance for ISR of the identified subgroups was evaluated by calculating the area under the curve (AUC) of receiver operator curves plotted for each model. The Pearson correlation coefficient was used to assess the correlation of peri-stent FAI values with degrees of ISR.ResultsThe peri-stent FAI values in the ISR group were significantly higher than those in the non-ISR group (−78.1 ± 6.2 HU vs. −87.2 ± 7.3 HU, p < 0.001). The predictive ISR features based on the LASSO analysis were peri-stent FAI, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), and high-sensitivity c-reactive protein (hs-CRP), with an AUC of 0.849, 0.632, 0.620, and 0.569, respectively. Binary logistic regression analysis determined that peri-stent FAI was uniquely and independently associated with ISR after adjusting for other risk factors (odds ratio [OR] 1.403; 95% CI: 1.211 to 1.625; p < 0.001). In the subgroup analysis, the AUCs of the left anterior descending coronary artery (LAD), left circumflex coronary artery (LCx), and right coronary artery (RCA) stents groups were 0.80, 0.87, and 0.96, respectively. The Pearson's correlation coefficient indicated a term moderately correlation between ISR severity and peri-stent FAI values (r = 0.579, P < 0.001).ConclusionsThe peri-stent FAI can be used as an independently non-invasive biomarker to predict ISR risk and severity after stent implantation.

Acupuncture is a traditional Chinese medicine treatment that has widely been used to modulate gastrointestinal dysfunction caused by irritable bowel syndrome (IBS) and to alleviate the resulting pain. Recent studies have shown that gastrointestinal dysfunction caused by IBS is associated with dysregulation of the brain's central and peripheral nervous system, while functional magnetic resonance imaging (fMRI) helps explore functional abnormality of the brain. However, previous studies rarely used fMRI to study the correlations between brain functional connection, interaction, or segregation (e.g., network degree and clustering coefficient) and acupuncture stimulation in IBS. To bridge this knowledge gap, we study the changed brain functional connection, interaction, and segregation before and after acupuncture stimulation for diarrhea-dominant IBS (IBS-D) with the help of complex network methods based on fMRI. Our results indicate that the abnormal functional connections (FCs) in the right hippocampus, right superior occipital gyrus, left lingual gyrus, left middle occipital gyrus, and the cerebellum, and abnormal network degree in right middle occipital gyrus, where normal controls are significantly different from IBS-D patients, are improved after acupuncture stimulation. These changed FCs and the network degree before and after acupuncture stimulation have significant correlations with the changed clinical information including IBS symptom severity score (r = −0.54, p = 0.0065) and IBS quality of life (r = 0.426, p = 0.038). We conclude that the changes of the brain functional connection, interaction, and segregation in the hippocampus, middle and superior occipital gyrus, cerebellum, and the lingual gyrus may be related to acupuncture stimulation. The abnormal functional connection, interaction, and segregation in IBS-D may be improved after acupuncture stimulation.

The aim of this study was to screen synergistic substances included in existing artificial feeds in order to improve the fertility and survival rate of Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), an efficient pest predator. To this end, we analyzed the potential effects of glucose and trehalose on the growth, development, and reproduction of H. axyridis and evaluated the effect of three different artificial feeds on the energy stress of H. axyridis. The artificial diets contained fresh pork liver, honey, sucrose, vitamin C, and royal jelly, which was marked it as Diet1. The glucose was added to diet1, which was marked it as diet2, while adding trehalose to diet1 was marked as diet3. The pre-oviposition period of H. axyridis on Diet 1 was slower than that of Diet 2 and Diet 3. Additionally, the spawning quantity and incubation rate of insects on Diet 2 and Diet 3 were significantly higher than that of those on Diet 1. Finally, the larval developmental time on Diet 1 was significantly slower than that of Diet 2 and Diet 3. These results indicate that the addition of an appropriate amount of glucose or trehalose may affect positively the growth, development, and reproduction of H. axyridis. In addition, further studies showed that ATP, amino acids and fatty acids content in the H. axyridis also increased after the addition of the synergistic substance. All these results show that proper adjustment of stored energy anabolic and catabolism is important to maintain the metabolic balance of the insect’s entire life cycle and the addition of glucose or trehalose has a certain effect on the life indicators of H. axyridis.

Objectives: The specific intrinsic network coupling abnormalities in mild traumatic brain injury (mTBI) patients are poorly understood. Our objective is to compare the correlations among the default mode, salience, and central executive networks in patients with mTBI and healthy controls.Methods: This 2-year prospective study included 32 acute mTBI patients and 37 healthy comparisons. We calculated the functional connectivity scores among the default mode, salience, and central executive networks. Then we conducted multilevel correlation analysis to investigate component correlations, global graph, and local functional connectivity changes.Results: Patients with mTBI showed significant increased functional connectivity between the anterior part of the default mode network and the salience network compared with controls (p = 0.013, false discovery rate correction). Hyper-connectivity between the default mode and salience network was significantly positively correlated with the dimensional change card sort score in patients with mTBI (r = 0.40, p = 0.037). The average path length of mTBI patients was significantly higher than that of controls (p = 0.028).Conclusions: Aberrant functional coupling between the default mode and salience networks were identified in acute mTBI patients. Our finding has great potential to improve our understanding of the network architecture of mTBI.