Heterogeneous trajectories of kinesiophobia and their effects on rehabilitation outcomes after total knee arthroplasty: a prospective cohort study

Abstract Background Kinesiophobia is one of the most common and aversive psychological phenomena among patients after total knee arthroplasty (TKA). This study aimed to identify trajectories of kinesiophobia, examine factors distinguishing these trajectories, and clarify the association between trajectories of kinesiophobia and rehabilitation outcomes. Methods In this prospective cohort study, the patients who underwent TKA were recruited between December 2021 and April 2022 from three orthopedic wards of a tertiary hospital in China. Kinesiophobia was measured using the Tampa Scale for Kinesiophobia at baseline (T0), and then at 1 month (T1) and 3 months (T2) after TKA to perform latent class growth analysis. Meanwhile, rehabilitation outcomes were assessed at 3 months after TKA, using the Kessler Psychological Distress Scale, the Hospital for Special Surgery-Knee Scale, Barthel Index, and the Impact on Participation and Autonomy questionnaire. Results The four kinesiophobia trajectories identified were as follows: low stable group (n = 120), rapid recovering group (n = 31), slow recovering group (n = 48), and stable moderate group (n = 58). Body mass index, employment status, heart disease, and pain degree significantly predicted trajectory groups (all p < 0.05). Analysis of variance revealed significant differences between the four kinesiophobia trajectories concerning all rehabilitation outcomes, except for the activities of daily living. Conclusion Distinct kinesiophobia trajectories were identified, and nurses should assess the kinesiophobia of patients after TKA in the early phase. Patients in the slow recovering group are worthy of a specific focus because of their poor recovery after undergoing TKA. As important sources of psychosocial care, nurses need to customize psychological interventions for patients after TKA depending on each kinesiophobia trajectory

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder

Background: Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Methods: Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. Results: WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Conclusions: Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD

Thought Chart: tracking the thought with manifold learning during emotion regulation

Abstract The Nash embedding theorem demonstrates that any compact manifold can be isometrically embedded in a Euclidean space. Assuming the complex brain states form a high-dimensional manifold in a topological space, we propose a manifold learning framework, termed Thought Chart, to reconstruct and visualize the manifold in a low-dimensional space. Furthermore, it serves as a data-driven approach to discover the underlying dynamics when the brain is engaged in a series of emotion and cognitive regulation tasks. EEG-based temporal dynamic functional connectomes are created based on 20 psychiatrically healthy participants’ EEG recordings during resting state and an emotion regulation task. Graph dissimilarity space embedding was applied to all the dynamic EEG connectomes. In order to visualize the learned manifold in a lower dimensional space, local neighborhood information is reconstructed via k-nearest neighbor-based nonlinear dimensionality reduction (NDR) and epsilon distance-based NDR. We showed that two neighborhood constructing approaches of NDR embed the manifold in a two-dimensional space, which we named Thought Chart. In Thought Chart, different task conditions represent distinct trajectories. Properties such as the distribution or average length in the 2-D space may serve as useful parameters to explore the underlying cognitive load and emotion processing during the complex task. In sum, this framework is a novel data-driven approach to the learning and visualization of underlying neurophysiological dynamics of complex functional brain data

Microbial Interactions and Roles in Soil Fertility in Seasonal Freeze-Thaw Periods under Different Straw Returning Strategies

With the increase of world food demand, the intensity of cultivated land use also increased. To improve soil nutrient concentrations and crop yield, several straw returning techniques have been developed. Studies have shown that straw returning is beneficial to soil, but few studies have focused on the relationship between microbes and fertility in seasonal freeze-thaw periods. A two-year cropland experiment was set up that comprised three different straw return strategies, namely covering tillage with straw return for two years (CS), rotary tillage and straw return for two years (RS), rotary covering tillage with straw return (first year covering and the second year rotary tillage) (CRS), and conventional tillage with no straw return (CK). Illumina Miseq high throughput sequencing of 16S rRNA was applied to assess bacteria community structure. The relationship between bacteria community structure and changes in soil fertility induced by different straw incorporating during seasonal trends was studied. Our results showed that soil bacterial communities varied significantly during the soil seasonal freeze-thaw period in the northwest of Jilin province, China, and were influenced, to some extent, by the different straw returning procedures. Multidimensional analysis revealed that total phosphorus (TP), available nitrogen (AN), and total nitrogen (TN) were the major drivers of bacterial community structure. The co-occurrence network was divided into several modules. Notably, the major bacterial modules varied significantly in different sampling periods and different treatments. These results suggested that specific bacterial groups could contribute to soil fertility in relation to environmental fluctuations. Some bacterial groups (e.g., Pyrinomonadales, Rhizobiales, Sphingomonadales, and Xanthomonadales, in order level) were directly linked with specific environmental factors, indicating the key roles of these groups in soil fertility. In summary, the soil bacterial communities varied significantly during the freeze-thaw period and might play important roles in the degradation of straw. Thus, the straw return could enhance soil fertility

Genetic Association of Curative and Adverse Reactions to Tyrosine Kinase Inhibitors in Chinese advanced Non-Small Cell Lung Cancer patients

Epidermal growth factor receptor (EGFR) Tyrosine kinase inhibitor (TKI) is an effective targeted therapy for advanced non-small cell lung cancer (NSCLC) but also causes adverse drug reactions (ADRs) e.g., skin rash and diarrhea. SNPs in the EGFR signal pathway, drug metabolism/ transport pathways and miRNA might contribute to the interpersonal difference in ADRs but biomarkers for therapeutic responses and ADRs to TKIs in Chinese population are yet to be fully investigated. We recruited 226 Chinese advanced NSCLC patients who received TKIs erlotinib, gefitinib and icotinib hydrochloride and systematically studied the genetic factors associated with therapeutic responses and ADRs. Rs884225 (T > C) in EGFR 3′ UTR was significantly associated with lower risk of ADRs to erlotinib (p value = 0.0010, adjusted p value = 0.042). A multivariant interaction four-SNP model (rs884225 in EGFR 3′UTR, rs7787082 in ABCB1 intron, rs38845 in MET intron and rs3803300 in AKT1 5′UTR) was associated with ADRs in general and the more specific drug induced skin injury. The SNPs associated with both therapeutic responses and ADRs indicates they might share a common genetic basis. Our study provided potential biomarkers and clues for further research of biomarkers for therapeutic responses and ADRs in Chinese NSCLC patients