Unraveling the relationship between serum parathyroid hormone levels and trabecular bone score: a cross-sectional study.

The TBS is a new method for clinicians to assess the bone quality. It is directly related to the mechanical strength of bone and helps predict fracture risk. The present analysis aimed to investigate the associations between serum PTH levels and TBS by analyzing data from the National Health and Nutrition Examination Survey (NHANES). A total of 3516 participants from the NHANES 2005-2006 were included in this cross-sectional study. The independent variable was serum PTH, and the outcome variable was TBS. The associations of serum PTH levels with TBS were examined using multivariable linear regression models. After adjusting for covariates, there was a negative association between serum PTH level and TBS (ß = - 0.0034; 95% confidence interval, - 0.0050 to - 0.0017). However, in the subgroup analysis stratified by gender, race, and age, this association became negative only in Non-Hispanic White (ß = - 0.0047, 95% CI: -  0.0071 to -  0.0048) and young people (age < 60) (ß = - 0.0036, 95% CI: - 0.0057, - 0.0016), regardless of gender. In addition, the association of serum PTH with TBS was an U-shaped curve, with a point of inflection at 6.71 pmol/L. This study showed that serum PTH level was negatively associated with TBS. Maintaining PTH levels in a lower reasonable clinical range may be beneficial to bone health, especially for young non-Hispanic white.

Effect of Tranexamic Acid on Hidden Blood Loss in Percutaneous Endoscopic Transforaminal Lumbar Interbody Fusion: A Retrospective Study.

Purpose: Percutaneous endoscopic transforaminal lumbar interbody fusion (PE-TLIF) has become one of the most popular minimally invasive surgeries today. However, the issue of hidden blood loss (HBL) in this surgery has received little attention. This study aims to examine the HBL in PE-TLIF surgery and the effect of tranexamic acid (TXA) on blood loss. Methods: In our research, We conducted a retrospective analysis of 300 patients who underwent PE-TLIF from September 2019 to August 2023. They were divided into 2 groups based on whether they received intravenous TXA injection before surgery. The variables compared included: demographic data, pre-and postoperative hemoglobin (HB), hematocrit (HCT), platelets (PLT), red blood cells (RBC), total blood loss (TBL), visible blood loss (VBL), HBL, operation time, postoperative hospital stay, inflammatory markers, coagulation parameters, and adverse events. Results: Regarding demographic characteristics, besides the operation time, no significant differences were observed between the two groups. Compared with the control group, the TXA group showed a significant reduction trend in TBL, HBL, and VBL (P < 0.05). On the first day after surgery, there were significant differences in prothrombin (PT), activated partial thromboplastin time (APTT), and D-dimer (D-D) levels between the two groups. Similarly, HCT also found similar results on the third day after surgery. No adverse events occurred in either group. Conclusion: Research has found that there is a significant amount of HBL in patients undergoing PE-TLIF. Intravenous injection of TXA can safely and effectively reduce perioperative HBL and VBL. Additionally, compared to the control group, the TXA group shows a significant reduction in operation time.

Diminished representational momentum for physical states in patients with depressive disorder.

The representational momentum for physical state changes refers to the fact that we remember objects as more changed in physical state than they actually were. It has been well documented that depressive disorder is associated with impairment of time perception. Thus, the present work was conducted with the aim to investigate the representational momentum for physical state changes in patients with depressive disorder, firstly. Forty patients with depressive disorder and forty-two healthy controls were administrated with the task of representational momentum for physical state changes and task of time perception. The stimulus comprises 10 videos showing object state changes (e.g., ice melting). During playing, the video would stop and immediately be obscured by mosaics at a specific point. Participants select from three detection images (the exact frame of the video just be masked, the frame after that, and the frame before that) to test representational momentum and estimate the duration of the video in seconds to test time perception. The depressive group showed diminished representational momentum (i.e., lower scores on the task of representational momentum) than normal controls (U = 215.00, Z = -5.83, p < 0.001). In addition, the scores on the task of representational momentum were significantly positively related with the scores on the task of time perception among depressive group (r = 0.446, p = 0.004). The findings indicate that patients with depressive disorder may exhibit diminished representational momentum for physical states, which may be correlated with their impairment of time perception.

CD3, CD8, IFN-γ, tumor and stroma inflammatory cells as prognostic indicators for surgically resected SCLC: evidences from a 10-year retrospective study and immunohistochemical analysis.

Current clinical guidelines limit surgical intervention to patients with cT1-2N0M0 small cell lung cancer (SCLC). Our objective was to reassess the role of surgery in SCLC management, and explore novel prognostic indicators for surgically resected SCLC. We reviewed all patients diagnosed with SCLC from January 2011 to April 2021 in our institution. Survival analysis was conducted using the Kaplan-Meier method, and independent prognostic factors were assessed through the Cox proportional hazard model. In addition, immunohistochemistry (IHC) staining was performed to evaluate the predictive value of selected indicators in the prognosis of surgically resected SCLC patients. In the study, 177 SCLC patients undergoing surgical resection were ultimately included. Both univariate and multivariate Cox analysis revealed that incomplete postoperative adjuvant therapy emerged as an independent risk factor for adverse prognosis (p < 0.001, HR 2.96). Survival analysis revealed significantly superior survival among pN0-1 patients compared to pN2 patients (p < 0.0001). No significant difference in postoperative survival was observed between pN1 and pN0 patients (p = 0.062). Patients with postoperative stable disease (SD) exhibited lower levels of tumor inflammatory cells (TIC) (p = 0.0047) and IFN-γ expression in both area and intensity (p < 0.0001 and 0.0091, respectively) compared to those with postoperative progressive disease (PD). Conversely, patients with postoperative SD showed elevated levels of stromal inflammatory cells (SIC) (p = 0.0453) and increased counts of CD3+ and CD8+ cells (p = 0.0262 and 0.0330, respectively). Survival analysis indicated that high levels of SIC, along with low levels of IFN-γ+ cell area within tumor tissue, may correlate positively with improved prognosis in surgically resected SCLC (p = 0.017 and 0.012, respectively). In conclusion, the present study revealed that the patients with pT1-2N1M0 staging were a potential subgroup of SCLC patients who may benefit from surgery. Complete postoperative adjuvant therapy remains an independent factor promoting a better prognosis for SCLC patients undergoing surgical resection. Moreover, CD3, CD8, IFN-γ, TIC, and SIC may serve as potential indicators for predicting the prognosis of surgically resected SCLC.

A Controlled Clinical Study of Accelerated High-Dose Theta Burst Stimulation in Patients with Obsessive-Compulsive Disorder.

Background: Obsessive-compulsive disorder (OCD) is frequently treated using a combination of counseling, drugs, and, more recently various transcranial stimulation protocols, but all require several weeks to months for clinically significant improvement, so there is a need for treatments with faster onset. This study investigated whether an accelerated high-dose theta burst stimulation (ahTBS) protocol significantly improves the efficacy of OCD compared to traditional 1-Hz repetitive transcranial magnetic stimulation (rTMS) in the routine clinical setting. Method: Forty-five patients with OCD were randomized into two groups and treated with ahTBS or 1-Hz rTMS for 5 days. Patients were assessed at baseline at the end of treatment using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Results: After 5 days of treatment, there was a significant decrease in Y-BOCS scores in both groups (p < 0.001), and the difference between the two groups was not statistically significant (group × time interaction, F = 1.90, p=0.18). There was also no statistically significant difference in other secondary outcome indicators, including depression, anxiety symptoms, and response rate. However, the ahTBS group had a greater trend in response rate. Neuropsychological testing showed no negative cognitive side effects of either treatment. Conclusion: Accelerated high-dose TBS is as safe and has comparable short-term efficacy to traditional 1-Hz rTMS for the clinical treatment of OCD. Further research is needed to explore optimal ahTBS parameters, validate the utility of this treatment modality, and identify factors predictive of rapid clinical response to guide clinical decision-making. This trial is registered with NCT05221632.

Process Optimization of Polishing Titanium Alloy Material with a Pulsating Air Jet.

Titanium alloy is a widely used metal material, which can be applied in fields such as healthcare, petroleum exploration, aerospace, etc. In this paper, a new method for polishing the titanium alloy by a pulsating air jet is proposed. Compared with traditional abrasive jet polishing, this method has the advantages of simple structure, low nozzle wear, and high polishing flexibility. The working principle and material removal mechanism of the pulsating air jet polishing (PAJP) are introduced. Combined with orthogonal experiments, range analysis and variance analysis were used to find out the influence degree of each process parameter on the PAJP of titanium alloy, and the optimal level of each parameter was found. Through the experiments, a prediction model of surface roughness was established by regression analysis, and the predicted value was compared with the measured value. The maximum relative error of the prediction model was 10.3%, and the minimum relative error was 1.1%. The average relative error was 6.2%.

Intense electric field optical sensor based on Fabry-Perot interferometer utilizing LiNbO3 crystal.

A novel intense electric field optical sensor based on Fabry-Perot interferometer utilizing LiNbO3 crystal is proposed and demonstrated. Compared to the traditional bulk-type electric field optical sensors, this sensor unit requires only a LiNbO3 and two collimators, eliminating the need for quarter wave-plate and allowing for measurement of electric field without limitation by half wave voltage. The Vernier effect, generated by birefringence of LiNbO3, is utilized to enhance the sensitivity of electric field measurement, which does not require additional reference cavity. Both theoretical and experimental results illustrate that the wavelength shift of the sensor is linear function of the measured electric field. In the range of 0∼1010 kV/m, the sensor's measurement sensitivity is 2.22 nm/E (V/µm) with detection limit of 1.27 × 10-2 E. Additionally, an MZI is proposed for temperature compensation, resulting in a standard deviation of spectrum variation after compensation of only 5.01 × 10-3. Applications using this sensor confirmed that it is expected to find widespread use in measurements of intense transient electric fields.

Enhanced toluene gas-sensing properties of MEMS sensor based on Pt-loaded SnO2nanoparticles.

Rapid detection of low concentration toluene is highly desirable in environment monitoring, industrial processes, medical diagnosis, etc. In this study, we prepared Pt-loaded SnO2monodispersed nanoparticles through hydrothermal method and assembled a sensor based on micro-electro-mechanical system (MEMS) to detect toluene. Compared with the pure SnO2, the 2.92 wt% Pt-loaded SnO2sensor exhibits a 2.75 times higher gas sensitivity to toluene at about 330 °C. Meanwhile, the 2.92 wt% Pt-loaded SnO2sensor also has a stable and good response to 100 ppb of toluene. Its theoretical detection limit is calculated as low as 12.6 ppb. Also, the sensor has a short response time of ∼10 s to different gas concentrations, as well as the excellent dynamic response-recovery characteristics, selectivity, and stability. The improved performance of Pt-loaded SnO2sensor can be explained by the increase of oxygen vacancies and chemisorbed oxygen species. The electronic and chemical sensitization of Pt to SnO2-based sensor, together with small size and fast gas diffusion of the MEMS design ensured fast response and ultra-low toluene detection. This provides new ideas and decent prospect for developing miniaturized, low-power-consumption, and portable application of gas sensing devices.

Increased EEG gamma power under exposure to drug-related cues: a translational index for cue-elicited craving in METH-dependent individuals.

BACKGROUND: This study explored the feasibility of using EEG gamma-band (30-49 Hz) power as an index of cue-elicited craving in METH-dependent individuals. METHODS: Twenty-nine participants dependent on methamphetamine (METH) and 30 healthy participants were instructed to experience a METH-related virtual reality (VR) social environment. RESULTS: Individuals with METH dependence showed significantly stronger self-reported craving and higher gamma power in a VR environment than healthy individuals. In the METH group, the VR environment elicited a significant increase in gamma power compared with the resting state. The METH group then received a VR counterconditioning procedure (VRCP), which was deemed useful in suppressing cue-induced reactivity. After VRCP, participants showed significantly lower self-reported craving scores and gamma power when exposed to drug-related cues than the first time. CONCLUSIONS: These findings suggest that the EEG gamma-band power may be a marker of cue-induced reactivity in patients with METH dependence.

Virtual-reality-based social cognition and interaction training for patients with schizophrenia: A preliminary efficacy study.

Background: Social cognition and interaction training (SCIT) is a psychosocial intervention program for patients with psychosis, designed to improve their social functioning by improving social cognition. Although the feasibility and efficacy of SCIT have been verified, patients with schizophrenia tend to suffer from motivational deficits and low treatment adherence. It has been suggested that using virtual reality (VR) technology might be effective in addressing these issues. In this study, we aimed to develop a VR-based SCIT and compare its efficacy with that of traditional SCIT. Materials and methods: We developed a novel VR-based social cognition and interaction training (VR-SCIT) that combines traditional SCIT (TR-SCIT) intervention with VR technology. Participants were randomly assigned in a 1:1:1 ratio to the VR-SCIT (n = 28), TR-SCIT (n = 30), or waiting-list groups (n = 29). All treatments were combined with treatment-as-usual. Assessments of social cognition (i.e., Chinese version of Face-Affective Identification Task, Chinese version of Social Cognition Screening Questionnaire) and social functioning (i.e., Chinese version of Personal and Social Performance Scale) were administered from baseline to post-intervention. Results: Patients receiving VR-SCIT and TR-SCIT showed a significantly greater improvement on the assessments of emotion perception (Cohen's d was 1.66, 0.55, and 0.10 for VR-SCIT, TR-SCIT, and Waiting-list, respectively), hostile attributional bias (Cohen's d was 0.48, 0.44, and 0.05 for VR-SCIT, TR-SCIT, and Waiting-list, respectively), metacognition (Cohen's d was 1.66, 0.76, and 0.06 for VR-SCIT, TR-SCIT, and waiting-list, respectively), and social functioning (Cohen's d was 1.09, 0.90, and 0.20 for VR-SCIT, TR-SCIT, and waiting-list, respectively) from baseline to post-intervention, compared to those in waiting-list group. Additionally, VR-SCIT showed an advantage over TR-SCIT in improving emotion perception and metacognition with higher treatment compliance. Conclusion: These preliminary findings indicate that VR-SCIT is a feasible and promising method for improving social cognition and social functioning in patients with schizophrenia.

Altered EEG Microstates Dynamics During Cue-Induced Methamphetamine Craving in Virtual Reality Environments.

Background: Cue-induced craving is widely considered to be the most important risk factor for relapse during abstinence from methamphetamine (Meth). There is limited research regarding electroencephalography (EEG) microstates of Meth-dependent patients under exposure to drug-related cues. Our objective was to investigate whether EEG microstate temporal characteristics could capture neural correlates of cue-induced Meth craving in virtual reality (VR) environments. Methods: EEG recordings of 35 Meth-dependent patients and 30 healthy controls (HCs) were collected during eyes-open state and cue-induced state, respectively. Group differences and condition differences in temporal parameters of four microstate classes were compared. Results: The results demonstrated the greater presence of microstate B in both Meth-dependent patients and HCs during the cue-induced condition, compared to resting state. In addition, for Meth-dependent patients, microstate C occurred significantly less frequently, along with a tendency of increased occurrence for class D during the cue-induced condition, compared to resting state. However, the change direction of class C and class D in HCs was completely opposite to that of Meth-dependent patients. The cue-induced condition also elicited different changes in transition probability between Meth-dependent patients and HCs. Conclusion: This study explored the features of EEG microstates in Meth-dependent patients during the cue-induced condition, which can improve our understanding of Meth addiction and contribute to the development of effective assessments and intervention tools.

Establishment and Verification of Prognostic Nomograms for Young Women With Breast Cancer Bone Metastasis.

Purpose: The prognosis of patients with metastatic breast cancer usually varies greatly among individuals. At present, the application of nomogram is very popular in metastatic tumors. The present study was conducted to identify independent survival predictors and construct nomograms among young women with breast cancer bone metastasis (BCBM). Patients and Methods: We searched the Surveillance, Epidemiology, and End Results (SEER) database to identify young women diagnosed with BCBM between 2010 and 2016. We first analyzed the potential risk factors of overall survival (OS) and cancer-specific survival (CSS) by applying univariate Cox regression analysis. Then we conducted multivariate Cox analysis to identify independent survival predictors. Based on significant independent predictors, we developed and validated novel prognostic nomograms by using the R version 4.1.0 software. Results: We finally identified 715 eligible young women with BCBM for survival analysis, of which 358 patients were in the training set, and 357 patients in the validation set. Approximately four-fifths of patients are between 31 and 40 years old. The 5-year OS and CSS rates of this research population were 41.9 and 43.3%, respectively. Multivariate analysis revealed seven independent predictors of both OS and CSS, including race, tumor subtype, tumor size, surgical treatment, brain metastasis, liver metastasis, and lung metastasis. Based on these predictors, we developed and validated OS and CSS nomograms. The C-index of the OS nomogram reached 0.728 and 0.73 in the training and validation sets, respectively. The C-index of the CSS nomogram reached 0.743 and 0.695 in the training and validation sets, respectively. Meanwhile, high quality calibration plots were revealed in both OS and CSS nomograms. Conclusion: The current novel nomograms can provide an individualized survival evaluation of young women with BCBM and instruct clinicians to treat them appropriately.

Determination of Bridge Prestress Loss under Fatigue Load Based on PSO-BP Neural Network.

During the service period of a prestressed concrete bridge, as the number of cyclic loads increases, cumulative fatigue damage and prestress loss will occur inside the structure, which will affect the safety, durability, and service life of the structure. Based on this, this paper studies the loss of bridge prestress under fatigue load. First, the relationship between the prestress loss of the prestressed tendons and the residual deflection of the test beam is analyzed. Based on the test results and the main influencing factors of fatigue and creep, a concrete fatigue and creep calculation model is proposed; then, based on the static cracking check calculation method and POS-BP neural network algorithm, a prestressed concrete beam fatigue cracking check model under repeated loads is proposed. Finally, the mechanical performance of the prestressed concrete beam after fatigue loading is analyzed, and the influence of the fatigue load on the bearing capacity of the prestressed concrete beam is explored. The results show that the bridge prestress loss characterization model based on the POS-BP neural network algorithm has the advantages of high calculation efficiency and strong applicability.

Identification and comparison of novel circular RNAs with associated co-expression and competing endogenous RNA networks in postmenopausal osteoporosis.

BACKGROUND: Circular RNAs (circRNAs) are emerging as crucial regulators in various human diseases. So far, the expression profile and regulatory mechanism of circRNAs in postmenopausal osteoporosis (PMOP) are less studied and should be deciphered urgently. Herein, we aimed to reveal key circRNAs affecting PMOP and clarify their compounding regulatory actions. METHODS: To reveal key circRNAs affecting PMOP and clarify their compounding regulatory actions, whole transcriptome sequencing and bioinformatics analysis were performed to identify differentially expressed circRNAs (DECs). The expression pattern and regulatory networks of DECs in peripheral blood mononuclear cells (PBMCs) were unearthed. RESULTS: A total of 373 DECs comprising 123 intronic, 100 antisense, 70 exonic, 55 intergenic, and 25 sense-overlapping circRNAs were identified. Among these, 73 circRNAs were upregulated and 300 were downregulated. These DECs exerted pivotal functions in the pathogenesis of PMOP as demonstrated by Gene Ontology (GO) annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The circRNA-miRNA-mRNA co-expression network comprising 28 DECs, 145 miRNAs, and 175 differentially expressed mRNAs predicted the possible mechanism of the pathogenesis and progression of PMOP. CONCLUSION: The results of the present study provided a further comprehension of circRNA-associated competing endogenous RNA regulatory mechanism in PMOP. The steadily expressed and disease-specific DECs may serve as promising diagnostic and prognostic biomarkers for PMOP.

Neural Stochastic Differential Equations with Neural Processes Family Members for Uncertainty Estimation in Deep Learning.

Existing neural stochastic differential equation models, such as SDE-Net, can quantify the uncertainties of deep neural networks (DNNs) from a dynamical system perspective. SDE-Net is either dominated by its drift net with in-distribution (ID) data to achieve good predictive accuracy, or dominated by its diffusion net with out-of-distribution (OOD) data to generate high diffusion for characterizing model uncertainty. However, it does not consider the general situation in a wider field, such as ID data with noise or high missing rates in practice. In order to effectively deal with noisy ID data for credible uncertainty estimation, we propose a vNPs-SDE model, which firstly applies variants of neural processes (NPs) to deal with the noisy ID data, following which the completed ID data can be processed more effectively by SDE-Net. Experimental results show that the proposed vNPs-SDE model can be implemented with convolutional conditional neural processes (ConvCNPs), which have the property of translation equivariance, and can effectively handle the ID data with missing rates for one-dimensional (1D) regression and two-dimensional (2D) image classification tasks. Alternatively, vNPs-SDE can be implemented with conditional neural processes (CNPs) or attentive neural processes (ANPs), which have the property of permutation invariance, and exceeds vanilla SDE-Net in multidimensional regression tasks.

Highly Compressible, Thermally Conductive, yet Electrically Insulating Fluorinated Graphene Aerogel.

Carbon-based aerogels have drawn substantial attention for a wide scope of applications. However, the high intrinsic electrical conductivity limits their potential thermal management application in electronic packaging materials. Herein, a highly compressible, thermally conductive, yet electrically insulating fluorinated graphene aerogel (FGA) is developed through a hydrofluoric acid-assisted hydrothermal process. The macroscopic-assembled FGA constituting of tailored interconnected graphene networks with tunable fluorine coverage shows excellent elasticity and fatigue resistance for compression, despite a low density of 10.6 mg cm-3. Moreover, the aerogel is proved to be highly insulating, with the observed lowest electrical conductivity reaching 4 × 10-7 S cm-1. Meanwhile, the aerogel exhibits prominent heat dissipation performance in a typical cooling procedure, which can be used to fabricate thermoconductive polymer composites for electronic packaging.

Monitoring Strain Response of Epoxy Resin during Curing and Cooling Using an Embedded Strain Gauge.

The present work describes the monitoring system of the real-time strain response on the curing process of epoxy resin from the initial point of curing to the end, and the change in strain during temperature changes. A simple mould was designed to embed the strain gauge, thermometer, and quartz standard sample into the epoxy resin, so that the strain and the temperature were simultaneously measured and recorded. A cryogenic-grade epoxy resin was tested and the Differential Scanning Calorimetry (DSC) was used to analyse the curing process. Based on the DSC results, three curing processes were adopted to investigate their influence on strain response as well as residual strain of the epoxy resin. Moreover, impact strength of the epoxy resin with various curing temperatures were tested and the results indicate that the curing plays a crucial role on the mechanical properties. The method will find cryogenic application of epoxy adhesives and epoxy resin based composites to monitor the strain during the curing process as well as the cryogenic service.

Self-Assembled Boron Nitride Nanotube Reinforced Graphene Oxide Aerogels for Dielectric Nanocomposites with High Thermal Management Capability.

Thermally conductive polymeric composites are highly promising in current energy devices such as light-emitting diodes, integrated circuits, and solar cells to achieve appropriate thermal management. However, the introduction of traditional thermoconductive fillers into a polymer usually results in low thermal conductivity enhancement. Here, an ideal dielectric epoxy nanocomposite with ultrahigh thermal conductivity is successfully fabricated using three-dimensional interconnected boron nitride nanotube reinforced graphene oxide nanosheet (3D-BNNT-GONS) aerogels as fillers. The nanocomposite exhibits a nearly 20-fold increase in thermal conductivity with only 11.6 vol % loading fraction. Meanwhile, the nanocomposite possesses excellent insulation performance, including low dielectric constant, low dielectric loss, and high breakdown strength. A heating and cooling process reveals that the nanocomposite has a fast response of surface temperature, indicating high thermal management capability.