Risk factors and prediction model of delirium in elderly patients after hip arthroplasty.

Objective: To analyze the risk factors of delirium in elderly patients after hip arthroplasty and to construct a prediction model. Methods: Clinical data of 248 elderly patients who underwent hip arthroplasty in the Department of Traumatology and Orthopedics at Wuhan Fourth Hospital were retrospectively collected from November 2021 to February 2023. Logistic regression analysis was used to identify the risk factors of delirium after hip arthroplasty, and a nomogram prediction model was constructed using the RMS package of R4.1.2 software. The accuracy and stability of the model was evaluated based on the Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic (ROC) curve. Results: Age, nighttime sleep, anesthesia method, intraoperative blood loss, hypoxemia, and C-reactive protein (CRP) level were all risk factors of delirium after the hip arthroplasty (P<0.05). These factors were used to construct a nomogram prediction model that was internally validated using the Bootstrap method. The prediction model had the area under ROC curve (AUC) of 0.980 (95% CI: 0.964-0.996), indicating that it has certain predictive value for postoperative delirium. When the optimal cut off value was selected, the sensitivity and specificity were 92.7% and 92.3%, respectively, indicating that the prediction model is effective. Conclusions: Age, short nighttime sleep, general anesthesia, high intraoperative blood loss, hypoxemia, and high CRP levels are independent risk factors for delirium after hip arthroplasty. The nomogram prediction model constructed based on these risk factors can effectively predict delirium in elderly patients after hip arthroplasty.

Computed Tomography-Based Radiomics Analysis for Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients.

PURPOSE: Previous studies have pointed out that magnetic resonance- and fluorodeoxyglucose positron emission tomography-based radiomics had a high predictive value for the response of the neoadjuvant chemotherapy (NAC) in breast cancer by respectively characterizing tumor heterogeneity of the relaxation time and the glucose metabolism. However, it is unclear whether computed tomography (CT)-based radiomics based on density heterogeneity can predict the response of NAC. This study aimed to develop and validate a CT-based radiomics nomogram to predict the response of NAC in breast cancer. METHODS: A total of 162 breast cancer patients (110 in the training cohort and 52 in the validation cohort) who underwent CT scans before receiving NAC and had pathological response results were retrospectively enrolled. Grades 4 to 5 cases were classified as response to NAC. According to the Miller-Payne grading system, grades 1 to 3 cases were classified as nonresponse to NAC. Radiomics features were extracted, and the optimal radiomics features were obtained to construct a radiomics signature. Multivariate logistic regression was used to develop the clinical prediction model and the radiomics nomogram that incorporated clinical characteristics and radiomics score. We assessed the performance of different models, including calibration and clinical usefulness. RESULTS: Eight optimal radiomics features were obtained. Human epidermal growth factor receptor 2 status and molecular subtype showed statistical differences between the response group and the nonresponse group. The radiomics nomogram had more favorable predictive efficacy than the clinical prediction model (areas under the curve, 0.82 vs 0.70 in the training cohort; 0.79 vs 0.71 in the validation cohort). The Delong test showed that there are statistical differences between the clinical prediction model and the radiomics nomogram ( z = 2.811, P = 0.005 in the training cohort). The decision curve analysis showed that the radiomics nomogram had higher overall net benefit than the clinical prediction model. CONCLUSION: The radiomics nomogram based on CT radiomics signature and clinical characteristics has favorable predictive efficacy for the response of NAC in breast cancer.

Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma.

PURPOSE: Lymphovascular invasion (LVI) impairs surgical outcomes in lung adenocarcinoma (LAC) patients. Preoperative prediction of LVI is challenging by using traditional clinical and imaging parameters. The purpose of this study was to investigate the value of the radiomics nomogram integrating clinical factors, CT features, and maximum standardized uptake value (SUVmax) to predict LVI and outcome in LAC and to evaluate the additional value of the SUVmax to the PET/CT-based radiomics nomogram. METHODS: A total of 272 LAC patients (87 LVI-present LACs and 185 LVI-absent LACs) with PET/CT scans were retrospectively enrolled, and 160 patients with SUVmax ≥ 2.5 of them were used for PET radiomics analysis. Clinical data and CT features were analyzed to select independent LVI predictors. The performance of the independent LVI predictors and SUVmax was evaluated. Two-dimensional (2D) and three-dimensional (3D) CT radiomics signatures (RSs) and PET-RS were constructed with the least absolute shrinkage and selection operator algorithm and radiomics scores (Rad-scores) were calculated. The radiomics nomograms, incorporating Rad-score and independent clinical and CT factors, with SUVmax (RNWS) or without SUVmax (RNWOS) were built. The performance of the models was assessed with respect to calibration, discrimination, and clinical usefulness. All the clinical, PET/CT, pathologic, therapeutic, and radiomics parameters were assessed to identify independent predictors of progression-free survival (PFS). RESULTS: CT morphology was the independent LVI predictor. SUVmax provided better discrimination capability compared with CT morphology in the training set (P < 0.001) and test set (P = 0.042). A total of 1409 CT and PET radiomics features were extracted and reduced to 8, 8, and 10 features to build the 2D CT-RS, 3D CT-RS, and the PET-RS, respectively. There was no significant difference in AUC between the 2D-RS and 3D-RS (P > 0.05), and 2D CT-RS showed a relatively higher AUC than 3D CT-RS. The CT-RS, the CT-RNWOS, and the CT-RNWS showed good discrimination in the training set (AUC [area under the curve], 0.799, 0.796, and 0.851, respectively) and the test set (AUC, 0.818, 0.822, and 0.838, respectively). There was significant difference in AUC between the CT-RNWS and CT-RNWOS (P = 0.044) in the training set. Decision curve analysis (DCA) demonstrated the CT-RNWS outperformed the CT-RS and the CT-RNWOS in terms of clinical usefulness. Furthermore, DCA showed the PETCT-RNWS provided the highest net benefit compared with the PET-RNWS and CT-RNWS. PFS was significantly different between the pathologic and RNWS-predicted LVI-present and LVI-absent patients (P < 0.001). Carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), pathologic LVI, histologic subtype, and SUVmax were independent predictors of PFS in the 244 CT-RNWS-predicted cohort; and CA125, NSE, pathologic LVI, and SUVmax were the independent predictors of PFS in the 141 PETCT-RNWS-predicted cohort. CONCLUSIONS: The radiomics nomogram, incorporating Rad-score, clinical and PET/CT parameters, shows favorable predictive efficacy for LVI status in LAC. Pathologic LVI and SUVmax are associated with LAC prognosis.

Long non-coding RNA CCAT1 promotes glioma cell proliferation via inhibiting microRNA-410.

BACKGROUND AND AIM: Long non-coding RNAs have been confirmed to play a critical role in various cancers. In the present study, the effect of long non-coding RNA (lncRNA) CCAT1 on glioma cell proliferation and its potential mechanism were investigated. METHODS AND RESULTS: Real-time PCR results showed that lncRNA-CCAT1 expression was significantly upregulated in glioma cancer tissues and cell lines compared with controls. After inhibiting CCAT1 expression in glioma cell line U251 with siRNA-CCAT1 (si-CCAT1), the cell viability and cell colony formation were decreased, the cell cycle was arrested in G1 phase, and the cell apoptosis was increased. As reported in bioinformatics software starbase2.0, a total of 22 microRNAs were potentially targeted by CCAT1. It was confirmed that miR-410 was altered most by si-CCAT1. After up-regulating CCAT1 expression in U251 cells, miR-410 level was decreased. Luciferase reporter assay confirmed that CCAT1 targeted miR-410. Correlation analysis showed that CCAT1 expression was negatively related to miR-410 expression in glioma cancer tissues. In addition, down-regulation of miR-410 reversed the inhibitory effect of si-CCAT1 on glioma proliferation. CONCLUSION: These data demonstrated that lncRNA-CCAT1 promoted glioma cell proliferation via inhibiting miR-410, providing a new insight about the pathogenesis of glioma proliferation.

[Amplitude Changes of Low Frequency Fluctuation in Brain Spontaneous Nervous Activities Induced by Needling at Hand Taiyin Lung Channel].

OBJECTIVE: To observe amplitude changes of low frequency fluctuation in brain spontaneous nervous activities induced by needling at Hand Taiyin Lung Channel, and to preliminarily explore the possible brain function network of Hand Taiyin Lung Channel. METHODS: By using functional magnetic resonance imaging (fMRI), 16 healthy volunteers underwent resting-state scanning (R1) and scanning with retained acupuncture at Hand Taiyin Lung Channel (acupuncture, AP). Data of fMRI collected were statistically calculated using amplitude of low frequency fluctuations (ALFF). RESULTS: Under R1 significantly enhanced ALFF occurred in right precuneus, left inferior parietal lobule, bilateral superior temporal gyrus, bilateral middle frontal gyrus, left superior frontal gyrus, left inferior frontal gyrus, left medial frontal gyrus. Under AP significantly enhanced ALFF occurred in right precuneus, bilateral superior frontal gyrus, cerebellum, bilateral middle frontal gyrus, right medial frontal gyrus, and so on. Compared with R1, needing at Hand Taiyin Lung Channel could significantly enhance ALFF in right gyrus subcallosum and right inferior frontal gyrus. Significant decreased ALFF appeared in right postcentral gyrus, left precuneus, left superior temporal gyrus, left middle temporal gyrus, and so on. CONCLUSION: Needing at Hand Taiyin Lung Channel could significantly change fixed activities of cerebral cortex, especially in right subcallosal gyrus, right inferior frontal gyrus, and so on.

TGF-ß induced miR-132 enhances the activation of TGF-ß signaling through inhibiting SMAD7 expression in glioma cells.

Transforming growth factors ß (TGF-ß) pathway has been proven to play important roles in oncogenesis and angiogenesis of gliomas. MiR-132 might be related to TGF-ß signaling pathway and high miR-132 expression was reported to be a biomarker of poor prognosis in patients diagnosed with glioma. However, the expression regulation way involved in TGF-ß pathway and clinical significance of miR-132 have not been investigated in glioma cells. Here we reported that the mRNA level of miR-132 and TGF-ß concentration were both increased in patients with brain glioma. Correlation analysis revealed that TGF-ß concentration was positively correlated with mRNA level of miR-132. In addition, the mRNA level of miR-132 was up-regulated by TGF-ß in a concentration-dependent and time-dependent manner. Furthermore, we found that miR-132 was involved in modulation of the TGF-ß signaling pathway and down-regulation of SMAD7 expression by directly targeting the SMAD7 3'-UTR. MiR-132 was negatively correlated with SMAD7 in patients with brain glioma. Taken together, our results suggest that miR-132 could be stimulated by TGF-ß and might enhance the activation of TGF-ß signaling through inhibiting SMAD7 expression in glioma cells. These findings contribute to a better understanding of the mechanism of the activation of TGF-ß signaling by miR-132.

[Effect of acupuncture at pericardium points of amplitude of low frequency fluctuations of healthy people in resting state functional magnetic resonance imaging].

OBJECTIVE: To observe the effect of acupuncture at the whole points of Hand Jueyin pericardium meridian on the amplitude of low frequency fluctuations (ALFF) of healthy people in resting state (R1) functional magnetic resonance imaging (fMRI). METHODS: Totally 16 healthy subjects received structure scan of T1 and T2. Then two fMRI scans were conducted for each participant. fMRI included the resting-state scan (R1; the scanning time was 8 min 6 s), the stimulating-acupoint scan (AP; the scanning time was 8 min 6 s). fMRI data acquisition from structure scanning and function scanning were processed with format conversion and statistical analysis. RESULTS: Under R1 state, brain regions with activated ALFF signals included bilateral superior frontal gyrus, medial frontal gyrus, middle occipital gyrus, precuneus, superior temporal gyrus, and cingulate gyrus. Under the AP state, brain regions with activated ALFF signals were bilateral superior frontal gyrus, medial frontal gyrus, middle temporal gyrus, left fusiform gyrus, precuneus, posterior cingulate, and declivis. Compared with R1 state, obvious difference of ALFF signal areas of the brain caused by acupuncture at pericardium were: bilateral cuneus, precuneus, left posterior cingulate gyrus, right middle occipital gyrus, and right occipital lingual gyrus. CONCLUSION: Acupuncture at the whole points of Hand Jueyin pericardium meridian could significantly change inherent activity states of the cerebral cortex, especially in bilateral superior frontal gyrus, medial frontal gyrus, and precuneus.

Dehydration in cerebral venous sinus thrombosis.

AIMS: This study aimed to unravel the dehydration status of patients with cerebral venous sinus thrombosis (CVST) to facilitate the understanding of dehydration in CVST. METHODS: This was a multicenter retrospective study and three populations were recruited, namely, patients with CVST, CVST mimics, and healthy subjects. Blood samples were obtained 1-2 days after admission to assess dehydration status. Stata 15.1 was performed for statistical analysis. RESULTS: A total of 208 patients were diagnosed with CVST, 237 with CVST mimics, and 200 healthy individuals were enrolled. The urine specific gravity (USG, 1.020 [1.014, 1.029] vs. 1.017 [1.011, 1.021]) was higher in patients with CVST than in those with mimics (all p < 0.001). The percentage of USG >1.03 was also higher in CVST (22.6%) than in its mimics (6.3%, p < 0.001). With the development of CVST, USG (acute vs. sub-acute vs. chronic, 1.022 [1.015, 1.033] vs. 1.021 [1.015, 1.031] vs. 1.019 [1.014, 1.025]) decreased. All dehydration-related markers could not differentiate CVST from its mimics and healthy populations, and they were not associated with CVST severity and prognosis (p > 0.05). CONCLUSION: High levels of USG, especially USG >1.013, were more common in patients with CVST. Dehydration-related indices could not characterize CVST and were not associated with CVST severity and prognosis.

Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels.

INTRODUCTION: Time in range (TIR) as assessed by continuous glucose monitoring (CGM) measures an individual's glucose fluctuations within set limits in a time period and is increasingly used together with HbA1c in patients with diabetes. HbA1c indicates the average glucose concentration but provides no information on glucose fluctuation. However, before CGM becomes available for patients with type 2 diabetes (T2D) worldwide, especially in developing nations, fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) are still the common biomarkers used for monitoring diabetes conditions. We investigated the importance of FPG and PPG to glucose fluctuation in patients with T2D. We used machine learning to provide a new estimate of TIR based on the HbA1c, together with FPG and PPG. METHODS: This study included 399 patients with T2D. (1) Univariate and (2) multivariate linear regression models and (3) random forest regression models were developed to predict the TIR. Subgroup analysis was performed in the newly diagnosed T2D population to explore and optimize the prediction model for patients with different disease history. RESULTS: Regression analysis suggests that FPG was strongly linked to minimum glucose, while PPG was strongly correlated with maximum glucose. After FPG and PPG were incorporated into the multivariate linear regression model, the prediction performance of TIR was improved compared with the univariate correlation between HbA1c and TIR, and the correlation coefficient (95% CI) increased from 0.62 (0.59, 0.65) to 0.73 (0.72, 0.75) (p < 0.001). The random forest model significantly outperformed the linear model (p < 0.001) in predicting TIR through FPG, PPG and HbA1c, with a stronger correlation coefficient 0.79 (0.79, 0.80). CONCLUSIONS: The results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients' disease status and providing necessary interventions for glycaemic control.

Bandwidth extension of seismometer by using a novel topology leaf spring.

A novel topology leaf spring as a substitute for the traditional spring was designed to expand the effective bandwidth of a seismometer. The finite element analysis showed that the seismometer with the new topology spring has better performance than that with the traditional spring. Compared with the traditional pendulum, the proposed topology structure was featured with lower natural frequency and higher spurious frequency. The bandwidth of the proposed seismometer was enhanced to [2 s, 72 Hz] with an increase of 43% over the traditional seismometer bandwidth of [1 s, 51 Hz] as well as the signal distortion of the seismometer was also reduced with the proposed topology spring.

Beta-asarone protects against MPTP-induced Parkinson's disease via regulating long non-coding RNA MALAT1 and inhibiting α-synuclein protein expression.

OBJECTIVE: Numerous long non-coding RNAs (lncRNA) have been identified in neurodegenerative disorders including Parkinson's disease (PD). Emerging evidence demonstrates that ß-asarone functions as neuroprotective effects in both in vitro and in vivo models. However, the role of ß-asarone and its potential mechanism in PD remain not completely clear. METHODS: MPTP-induced PD mouse model and SH-SY5Y cells subjected to MPP+ as its in vitro model were used to evaluate the effects of ß-asarone on PD. LncRNA MALAT1 and α-synuclein expression were determined by real-time PCR and western blot methods. RESULTS: ß-Asarone significantly increased the TH+ cells number and decreased the expression levels of MALAT1 and α-synuclein in midbrain tissue of PD mice. RNA pull-down and immunoprecipitation assays confirmed that MALAT1 associated with α-synuclein, leading to the increased stability of α-synuclein and its expression in SH-SY5Y cells. ß-asarone elevated the viability of cells exposed to MPP+. Either overexpressed MALAT1 or α-synuclein could canceled the protective effect of ß-asarone on cell viability. In PD mice, pcDNA-MALAT1 also decreased the TH+ cells number and increased the α-synuclein expression in PD mice with treatment of ß-asarone. CONCLUSION: ß-Asarone functions as a neuroprotective effect in both in vivo and in vitro models of PD via regulating MALAT1 and α-synuclein expression.

MicroRNA-214 participates in the neuroprotective effect of Resveratrol via inhibiting α-synuclein expression in MPTP-induced Parkinson's disease mouse.

BACKGROUNDS AND AIMS: MicroRNAs (miRNAs) have been reported to be involved in degenerative disorders including Parkinson's disease (PD). α-synuclein expression is strong associated with the pathogenesis of PD. In the present study, we investigated whether the regulation of α-synuclein expression by miR-214 is the potential mechanism underlying the neuroprotective effect of Resveratrol. METHODS: The PD mouse model was established with the injection of MPTP (1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine) and the human neuroblastoma cell line, SH-SY5Y, was administrated with MPP+. RESULTS: The midbrain of PD mice and MPP+ treated SH-SY5Y cells had the lower expression levels of miR-214 and higher mRNA and protein expression of α-synuclein, which were reversed by Resveratrol administration. MiR-214 mimic down-regulated expression of α-synuclein and its 3'-UTR activity, while the levels were up-regulated by miR-214 inhibitor. In addition, the cell viability, elevated by Resveratrol, was also decreased by miR-214 inhibitor or overexpressed α-synuclein. In vivo, miR-214 inhibitor down-regulated TH+ cells of ipsilateral and up-regulated α-synuclein expression compared with the group treated with Resveratrol. CONCLUSION: The loss of miR-214 in PD resulted in the increase of α-synuclein expression, which was the potential mechanism underlying the neuroprotective effects of Resveratrol.