Alpha tACS on Parieto-Occipital Cortex Mitigates Motion Sickness Based on Multiple Physiological Observation.

Approximately one third of the population is prone to motion sickness (MS), which is associated with the dysfunction in the integration of sensory inputs. Transcranial alternating current stimulation (tACS) has been widely used to modulate neurological functions by affecting neural oscillation. However, it has not been applied in the treatment of motion sickness. This study aims to investigate changes in brain oscillations during exposure to MS stimuli and to further explore the potential impact of tACS with the corresponding frequency and site on MS symptoms. A total of 19 subjects were recruited to be exposed to Coriolis stimuli to complete an inducing session. After that, they were randomly assigned to tACS stimulation group or sham stimulation group to complete a stimulation session. Electroencephalography (EEG), electrocardiogram, and galvanic skin response were recorded during the experiment. All the subjects suffering from obvious MS symptoms after inducing session were observed that alpha power of four channels of parieto-occipital lobe significantly decreased (P7: t =3.589, p <0.001; P8: t =2.667, p <0.05; O1: t =3.556, p <0.001; O2: t =2.667, p <0.05). Based on this, tACS group received the tACS stimulation at 10Hz from Oz to CPz. Compared to sham group, tACS stimulation significantly improved behavioral performance and entrained the alpha oscillation in individuals whose alpha power decrease during the inducing session. The findings show that parieto-occipital alpha oscillation plays a critical role in the integration of sensory inputs, and alpha tACS on parieto-occipital can become a potential method to mitigate MS symptoms.

Incidence and Survival of Patients With Malignant Primary Spinal Cord Tumors: A Population-Based Analysis.

OBJECTIVE: Epidemiological studies on spinal cord tumors are rare, and studies on primary intramedullary tumors are even rarer. The incidence and survival of patients with primary intramedullary spinal cord tumors have not been well documented. We aimed to study the incidence and survival of patients with primary spinal cord malignant and borderline malignant tumors based on data from the Surveillance, Epidemiology, and End Results (SEER) database and provide information for revealing the epidemiology and exploring the prognosis of patients with primary intramedullary tumors. METHODS: Patients in the SEER database with microscopically diagnosed malignant and borderline malignant primary spinal cord tumors from 2000 and 2019 were included in this study. We analyzed the distribution of patients according to the demographic and clinical characteristics. Then, we extracted the incidence rate and 5-year relative survival for the whole cohort and different subgroups of the cohort. Finally, multivariate Cox proportional hazards models were used to analyze the independent prognostic factors associated with overall survival. RESULTS: A total of 5,211 patients with malignant and borderline malignant primary spinal cord tumors were included in this cohort study. Ependymoma, astrocytoma (including oligodendrogliomas and glioblastoma), lymphoma and hemangioblastoma were the most common pathological types. The age-adjusted incidence rates of primary spinal cord ependymoma was 0.18 per 100,000. The incidence rate for females was significantly lower than that for males. The incidence rate was highest in Caucasian. The incidence rate of ependymoma was significantly higher than that of other pathological types. The incidence of astrocytoma was highest among people aged 0-19 years, the incidence of ependymoma was highest among people aged 40-59 years, and the incidence of lymphoma was highest among people aged 60 years or older. The 5-year observed survival and relative survival rates for the whole cohort were 82.80% and 86.00%, respectively. Patients diagnosed with ependymoma had significantly better survival than their counterparts. We also found the impact of surgery and chemotherapy on the prognosis of patients with different tumors varies a lot. CONCLUSION: We conducted a population-based analysis of malignant and borderline malignant primary spinal cord tumors with the aim of revealing the epidemiology and survival of patients with primary intramedullary spinal cord tumors. Despite some shortcomings, this study provides valuable information to help us better understand the epidemiological characteristics of primary intramedullary spinal cord tumors.

Dynamics of polarization-tuned mirror symmetry breaking in a rotationally symmetric system.

Lateral momentum conservation is typically kept in a non-absorptive rotationally symmetric system through mirror symmetry via Noether's theorem when illuminated by a homogeneous light wave. Therefore, it is still very challenging to break the mirror symmetry and generate a lateral optical force (LOF) in the rotationally symmetric system. Here, we report a general dynamic action in the SO(2) rotationally symmetric system, originating from the polarization-tuned mirror symmetry breaking (MSB) of the light scattering. We demonstrate theoretically and experimentally that MSB can be generally applied to the SO(2) rotationally symmetric system and tuned sinusoidally by polarization orientation, leading to a highly tunable and highly efficient LOF (9.22 pN/mW/µm-2) perpendicular to the propagation direction. The proposed MSB mechanism and LOF not only complete the sets of MSB of light-matter interaction and non-conservative force only using a plane wave but also provide extra polarization manipulation freedom.

Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

Associations of sex-related and thyroid-related hormones with risk of metabolic dysfunction-associated fatty liver disease in T2DM patients.

BACKGROUND: We aimed to examine sex-specific associations between sex- and thyroid-related hormones and the risk of metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with type 2 diabetes mellitus (T2DM). METHODS: Cross-sectional analyses of baseline information from an ongoing cohort of 432 T2DM patients (185 women and 247 men) in Xiamen, China were conducted. Plasma sex-related hormones, including estradiol (E2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), progesterone, and total testosterone (TT), and thyroid-related hormones, including free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), and parathyroid hormone (PTH), were measured using chemiluminescent immunoassays. MAFLD was defined as the presence of hepatic steatosis (diagnosed by either hepatic ultrasonography scanning or fatty liver index (FLI) score > 60) since all subjects had T2DM in the present study. RESULTS: Prevalence of MAFLD was 65.6% in men and 61.1% in women with T2DM (P = 0.335). For men, those with MAFLD showed significantly decreased levels of FSH (median (interquartile range (IQR)):7.2 (4.9-11.1) vs. 9.8 (7.1-12.4) mIU/ml) and TT (13.2 (10.4-16.5) vs. 16.7 (12.8-21.6) nmol/L) as well as increased level of FT3 (mean ± standard deviation (SD):4.63 ± 0.68 vs. 4.39 ± 0.85 pmol/L) than those without MAFLD (all p-values < 0.05). After adjusting for potential confounding factors, FSH and LH were negative, while progesterone was positively associated with the risk of MAFLD in men, and the adjusted odds ratios (ORs) (95% confidence intervals (CIs)) were 0.919 (0.856-0.986), 0.888 (0.802-0.983), and 8.069 (2.019-32.258) (all p-values < 0.05), respectively. In women, there was no statistically significant association between sex- or thyroid-related hormones and the risk of MAFLD. CONCLUSION: FSH and LH levels were negative, whereas progesterone was positively associated with the risk of MAFLD in men with T2DM. Screening for MAFLD and monitoring sex-related hormones are important for T2DM patients, especially in men.

Digital transformation and environmental, social, and governance greenwashing: Evidence from China.

This paper examines the relationship between digital transformation(DT) and environmental, social, and governance(ESG) greenwashing using Chinese listed companies as a sample from 2012 to 2022. Furthermore, it analyzes the enterprise and regional heterogeneity as well as the influencing mechanisms on this relationship. The research results indicate that corporate digital transformation significantly inhibits ESG greenwashing, with a more pronounced effect on companies in non-high-pollution industries, high-tech industries, and the eastern region. In addition, mechanism tests reveal that internal control and financing constraints play a partial mediating role. Digital transformation suppresses ESG greenwashing by enhancing the quality of internal control and alleviating financing constraints. The primary contribution of this paper lies in demonstrating that digital transformation can serve as a strategic tool to mitigate ESG greenwashing. This enriches the research on the outcomes of digital transformation as well as the factors influencing ESG greenwashing. The conclusions of this paper provide theoretical foundations and policy recommendations for better ESG development by enterprises and governments in emerging markets. At the same time, this paper has a certain guiding role for the introduction and implementation of policies to encourage digital transformation.

Monolithic integrated optoelectronic chip for vector force detection.

Sensors with a small footprint and real-time detection capabilities are crucial in robotic surgery and smart wearable equipment. Reducing device footprint while maintaining its high performance is a major challenge and a significant limitation to their development. Here, we proposed a monolithic integrated micro-scale sensor, which can be used for vector force detection. This sensor combines an optical source, four photodetectors, and a hemispherical silicone elastomer component on the same sapphire-based AlGaInP wafer. The chip-scale optical coupling is achieved by employing the laser lift-off techniques and the flip-chip bonding to a processed sapphire substrate. This hemispherical structure device can detect normal and shear forces as low as 1 mN within a measurement range of 0-220 mN for normal force and 0-15 mN for shear force. After packaging, the sensor is capable of detecting forces over a broader range, with measurement capabilities extending up to 10 N for normal forces and 0.2 N for shear forces. It has an accuracy of detecting a minimum normal force of 25 mN and a minimum shear force of 20 mN. Furthermore, this sensor has been validated to have a compact footprint of approximately 1.5 mm2, while maintaining high real-time response. We also demonstrate its promising potential by combining this sensor with fine surface texture perception in the fields of compact medical robot interaction and wearable devices.

Multicomponent Synthesis of Imidazole-Based Ionizable Lipids for Highly Efficient and Spleen-Selective Messenger RNA Delivery.

The spleen emerges as a pivotal target for mRNA delivery, prompting a continual quest for specialized and efficient lipid nanoparticles (LNPs) designed to enhance spleen-selective transfection efficiency. Here we report imidazole-containing ionizable lipids (IMILs) that demonstrate a pronounced preference for mRNA delivery into the spleen with exceptional transfection efficiency. We optimized IMIL structures by constructing and screening a multidimensional IMIL library containing multiple heads, tails, and linkers to perform a structure-activity correlation analysis. Following high-throughput in vivo screening, we identified A3B7C2 as a top-performing IMIL in spleen-specific mRNA delivery via the formulated LNPs, achieving a remarkable 98% proportion of splenic transfection. Moreover, A3B7C2-based LNPs are particularly potent in splenic dendritic cell transfection. Comparative analyses revealed that A3B7C2-based LNPs achieved a notable 2.8-fold and 12.9-fold increase in splenic mRNA transfection compared to SM102 and DLin-MC3-DMA lipid formulations, respectively. Additionally, our approach yielded an 18.3-fold enhancement in splenic mRNA expression compared to the SORT method without introducing additional anionic lipids. Collectively, these IMILs highlight promising avenues for further research in spleen-selective mRNA delivery. This work offers valuable insights for the swift discovery and rational design of ionizable lipid candidates tailored for spleen-selective transfection, thereby facilitating the application of mRNA therapeutics in spleen-related interventions.

Helper Lipid-Enhanced mRNA Delivery for Treating Metabolic Dysfunction-Associated Fatty Liver Disease.

Lipid nanoparticles (LNPs) represent the forefront of mRNA delivery platforms, yet achieving precise delivery to specific cells remains a challenge. The current targeting strategies complicate the formulation and impede the regulatory approval process. Here, through a straightforward regulation of helper lipids within LNPs, we introduce an engineered LNP designed for targeted delivery of mRNA into hepatocytes for metabolic dysfunction-associated fatty liver disease (MAFLD) treatment. The optimized LNP, supplied with POPC as the helper lipid, exhibits a 2.49-fold increase in mRNA transfection efficiency in hepatocytes compared to that of FDA-approved LNPs. CTP:phosphocholine cytidylyltransferase α mRNA is selected for delivery to hepatocytes through the optimized LNP system for self-calibration of phosphatidylcholine levels to prevent lipid droplet expansion in MAFLD. This strategy effectively regulates lipid homeostasis, while demonstrating proven biosafety. Our results present a mRNA therapy for MAFLD and open a new avenue for discovering potent lipids enabling mRNA delivery to specific cells.

Accurate object localization facilitates automatic esophagus segmentation in deep learning.

BACKGROUND: Currently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We aimed to improve the performance of esophagus segmentation in deep learning by applying a strategy that involves locating the object first and then performing the segmentation task. METHODS: A total of 100 cases with thoracic computed tomography scans from two publicly available datasets were used in this study. A modified CenterNet, an object location network, was employed to locate the center of the esophagus for each slice. Subsequently, the 3D U-net and 2D U-net_coarse models were trained to segment the esophagus based on the predicted object center. A 2D U-net_fine model was trained based on the updated object center according to the 3D U-net model. The dice similarity coefficient and the 95% Hausdorff distance were used as quantitative evaluation indexes for the delineation performance. The characteristics of the automatically delineated esophageal contours by the 2D U-net and 3D U-net models were summarized. Additionally, the impact of the accuracy of object localization on the delineation performance was analyzed. Finally, the delineation performance in different segments of the esophagus was also summarized. RESULTS: The mean dice coefficient of the 3D U-net, 2D U-net_coarse, and 2D U-net_fine models were 0.77, 0.81, and 0.82, respectively. The 95% Hausdorff distance for the above models was 6.55, 3.57, and 3.76, respectively. Compared with the 2D U-net, the 3D U-net has a lower incidence of delineating wrong objects and a higher incidence of missing objects. After using the fine object center, the average dice coefficient was improved by 5.5% in the cases with a dice coefficient less than 0.75, while that value was only 0.3% in the cases with a dice coefficient greater than 0.75. The dice coefficients were lower for the esophagus between the orifice of the inferior and the pulmonary bifurcation compared with the other regions. CONCLUSION: The 3D U-net model tended to delineate fewer incorrect objects but also miss more objects. Two-stage strategy with accurate object location could enhance the robustness of the segmentation model and significantly improve the esophageal delineation performance, especially for cases with poor delineation results.

Non-equilibrium compression achieving high sensitivity and linearity for iontronic pressure sensors.

Flexible pressure sensors with high sensitivity and linearity are highly desirable for robot sensing and human physiological signal detection. However, the current strategies for stabilizing axial microstructures (e.g., micro-pyramids) are mainly susceptible to structural stiffening during compression, thereby limiting the realization of high sensitivity and linearity. Here, we report a bending-induced non-equilibrium compression process that effectively enhances the compressibility of microstructures, thereby crucially improving the efficiency of interfacial area growth of electric double layer (EDL). Based on this principle, we fabricate an iontronic flexible pressure sensor with vertical graphene (VG) array electrodes. Ultra-high sensitivity (185.09 kPa-1) and linearity (R2 = 0.9999) are realized over a wide pressure range (0.49 Pa-66.67 kPa). It also exhibits remarkable mechanical stability during compression and bending. The sensor is successfully employed in a robotic gripping task to recognize the targets of different materials and shapes based on a multilayer perception (MLP) neural network. It opens the door to realizing haptic sensing capabilities for robotic hands and prosthetic limbs.

Competition between biodetoxification fungus and lactic acid bacterium in the biorefinery processing chain for production of cellulosic L-lactic acid.

Biodetoxification fungus selectively degrades toxic inhibitors generated from pretreatment of lignocellulose without consuming fermentable sugars. However, one barrier for practical application is the sustained cell viability in the consequent fermentation step to compete the fermentable sugars with fermenting strains, resulting in sugar loss and reduced target product yield. This study investigated the competitive growth property between the biodetoxification fungus Paecilomyces variotii FN89 and the L-lactic acid bacterium Pediococcus acidilactici ZY271 under varying temperature and lactic acid osmatic stress. The results show that the L-lactic acid bacterium Ped. acidilactici ZY271 showed less thermotolerance to Pae. variotii FN89 at high temperature of 45 °C to 50 °C in both synthetic medium and wheat straw hydrolysate. In the higher temperature environment, the growth of the biodetoxification strian failed to compete with the lactic acid fermentation strain and was quickly eliminated from the fermentation system. The high temperature fermentation facilitated a fast transition from the detoxification stage to the fermentation stage for higher production of L-lactic acid.

Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories.

A lane-changing (LC) maneuver may cause the follower in the target lane (new follower) to decelerate and give up space, potentially affecting crash risk and traffic flow efficiency. In congested flow, a more aggressive LC maneuver occurs where the lane changer is partially next to the new follower and creates negative gaps, namely negative gap forced LC (NGFLC). Although NGFLC forms the foundation of sideswipe crashes, little has been done to address its impacts and the contributing factors. To tackle this issue, a total of 15,810 LC trajectory samples are extracted from three drone videos at different locations. These samples are categorized into NGFLC and normal LC groups for comparative analysis. Five commonly used conflict indicators are extended into two-dimensional to evaluate the crash risk of LC maneuver. The change of time gaps during LC maneuver are examined to quantify the impact of LC on traffic flow efficiency. We find that NGFLCs significantly increase crash risk, reflected by the number of hazardous LC events and potential crash areas compared to normal LC. Additionally, results reveal that both the lane changer and the new follower tend to maintain a larger time gap after NGFLCs. Factors including time headway, relative speed, and historical gaps in the target lane significantly affect NGFLC incidence. Once the movement of the leader in the original lane is taken into account, the prediction accuracy improves from 81% to 91%. The transferability tests indicate that the findings about the negative impact of NGFLC and the accuracy of its prediction model are consistent across different locations. These findings hold implications for driving assistance systems to better predict and mitigate NGFLCs.

Evaluating the performance of traffic conflict measures in real-time crash risk prediction using pre-crash vehicle trajectories.

The primary objective of this study was to evaluate the performance of traffic conflict measures for real-time crash risk prediction. Drone recordings were collected from a freeway section in Nanjing, China, over a year. Twenty rear-end crashes and their associated trajectories were obtained. Vehicle trajectories preceding the crash were segmented based on different time periods to represent varying crash conditions. The Extreme Value Theory (EVT) approach combined with a block maxima sampling method was then employed to investigate the generalized extreme value (GEV) distributions of extremely risky events under non-crash and crash conditions. The prediction performance was demonstrated by the differences in GEV distributions under these two conditions. Within the proposed modeling framework, the performances of Time-to-Collision (TTC), Deceleration Rate to Avoid a Crash (DRAC), and Absolute value of Derivative of Instantaneous Acceleration (ADIA) were examined and compared. The results revealed a decreasing trend in the prediction performances as the preceding time window before a crash increased. For any given length of crash conditions, TTC consistently outperformed DRAC and ADIA. Notably, TTC's reliability in crash risk prediction became more uncertain when forecasting crashes more than 2 s in advance. This study provided the optimal thresholds for TTC and ADIA for practical application in crash early warning. The methods and results in this study have the potential to be used for crash risk assessments in autonomous vehicles.

3,3'-((3,4,5-trifluoropHenyl)methylene)bis(4-hydroxy-2H-chromen-2-one) inhibit lung cancer cell proliferation and migration.

Lung cancer is a major public health challenge and, despite therapeutic improvements, is the first leading cause of cancer worldwide. The current cure rate from advanced cancer treatment is excessively low. Therefore, it is of great importance to identify novel, potent and less toxic anticancer agents for the treatment of lung cancer. The aim of our research is to synthesize a new biscoumarin 3,3'-((3,4,5-trifluorop -phenyl)methylene)bis(4-hydroxy-2H-chromen-2-one) (C35) as an anticancer agent. C35 was simply prepared by 4-hydroxycoumarin and 3,4,5-trifluorobenzaldehyde under ethanol and its structure was analyzed by spectroscopic analyses. The anti-proliferation effect of C35 was detected using CCK-8 assay. Migration abilities were measured by Transwell assay. The expression of correlated proteins was determined by Western blot. The results showed that C35 displayed strong cytostatic effects on lung cancer cell proliferation. In addition, C35 possessed a significant inhibition of migration by reducing the expression of matrix metalloproteinases-2 (MMP-2) and MMP-9 in lung cancer cells. Furthermore, C35 treatment suppressed the phosphorylation of p38 in lung cancer cells. Moreover, in vivo experiments were carried out, in which we treated Lewis tumor-bearing C57 mice via intraperitoneal injection of C35. Results showed that C35 inhibited tumor growth in vivo. In conclusion, our study demonstrated the anticancer activity of C35 via suppression of lung cancer cell proliferation and migration, which is possibly involved with the inhibition of the p38 pathway.

Explainable Deep-Learning Prediction for Brain-Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion.

Predicting the potential for recovery of motor function in stroke patients who undergo specific rehabilitation treatments is an important and major challenge. Recently, electroencephalography (EEG) has shown potential in helping to determine the relationship between cortical neural activity and motor recovery. EEG recorded in different states could more accurately predict motor recovery than single-state recordings. Here, we design a multi-state (combining eyes closed, EC, and eyes open, EO) fusion neural network for predicting the motor recovery of patients with stroke after EEG-brain-computer-interface (BCI) rehabilitation training and use an explainable deep learning method to identify the most important features of EEG power spectral density and functional connectivity contributing to prediction. The prediction accuracy of the multi-states fusion network was 82%, significantly improved compared with a single-state model. The neural network explanation result demonstrated the important region and frequency oscillation bands. Specifically, in those two states, power spectral density and functional connectivity were shown as the regions and bands related to motor recovery in frontal, central, and occipital. Moreover, the motor recovery relation in bands, the power spectrum density shows the bands at delta and alpha bands. The functional connectivity shows the delta, theta, and alpha bands in the EC state; delta, theta, and beta mid at the EO state are related to motor recovery. Multi-state fusion neural networks, which combine multiple states of EEG signals into a single network, can increase the accuracy of predicting motor recovery after BCI training, and reveal the underlying mechanisms of motor recovery in brain activity.

Effect of respiratory muscle training in patients with stable chronic obstructive pulmonary disease: A systematic review and meta-analysis.

Objectives: Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder characterized by progressive airflow limitation. This meta-analysis aims to evaluate the effectiveness of respiratory muscle training (RMT) on key pulmonary function parameters, inspiratory muscle strength and quality of life in patients with stable COPD. Methods: A comprehensive search was conducted in the databases including PubMed, Cochrane, Web of Science, Embase, and ClinicalTrials.gov, from their inception to June 12, 2023. Randomized controlled trials (RCTs) evaluating the impact of RMT on stable COPD were included for meta-analysis. Results: In total, 12 RCTs involving 453 participants were included in the meta-analysis. RMT demonstrated a significant increase in maximal inspiratory pressure (PImax, MD, 95% CI: 14.34, 8.17 to 20.51, P < 0.001) but not on maximal expiratory pressure (PEmax). No significant improvement was observed in 6-Min walk test (6MWT), dyspnea, forced expiratory volume in 1 s (FEV1), forced vital capacity ratio (FVC) and quality of life between RMT and control groups. However, subgroup analysis revealed a significant negative effect of RMT alone on FEV1/FVC (MD, 95% CI: 2.59, -5.11 to -0.06, P = 0.04). When RMT was combined with other interventions, improvements in FEV1/FVC and FEV1 were found, although not statistically significant. Conclusion: RMT can effectively improve maximal inspiratory pressure in stable COPD patients, but the effect is slight in improving lung function, dyspnea and quality of life. It is recommended to combine with other treatment strategies to comprehensively improve the prognosis of COPD patients.

A logistic-tent chaotic mapping Levenberg Marquardt algorithm for improving positioning accuracy of grinding robot.

The precision of workpiece machining is critically influenced by the geometric errors in the kinematics of grind robots, which directly affect their absolute positioning accuracy. To tackle this challenge, this paper introduces a logistic-tent chaotic mapping Levenberg Marquardt algorithm designed to accurately identify and compensate for this geometric error. the approach begins with the construction of a forward kinematic model and an error model specific to the robot. Then the algorithm is adopted to identify and compensate for the geometric error. The method establishes a mapping interval around the initial candidate solutions derived from iterative applications of the Levenberg Marquardt algorithm. Within this interval, the logistic-tent chaotic mapping method generates a diverse set of candidate solutions. These candidates are evaluated based on their fitness values, with the optimal solution selected for subsequent iterations. Empirical compensation experiments have validated the proposed method's precision and effectiveness, demonstrating a 6% increase in compensation accuracy and a 47.68% improvement in efficiency compared to existing state-of-the-art approaches. This process not only minimizes the truncation error inherent in the Levenberg Marquardt algorithm but also significantly enhances solution efficiency. Moreover, simulation experiments on grind processes further validate the method's ability to significantly improve the quality of workpiece machining.

Optimizing transseptal puncture guided by three-dimensional mapping: the role of a unipolar electrogram in a needle tip.

AIMS: A three-dimensional electroanatomic mapping system-guided transseptal puncture (3D-TSP), without fluoroscopy or echocardiography, has been only minimally reported. Indications for 3D-TSP remain unclear. Against this background, this study aims to establish a precise technique and create a workflow for validating and selecting eligible patients for fluoroless 3D-TSP. METHODS AND RESULTS: We developed a new methodology for 3D-TSP based on a unipolar electrogram derived from a transseptal needle tip (UEGM tip) in 102 patients (the derivation cohort) with intracardiac echocardiography (ICE) from March 2018 to February 2019. The apparent current of injury (COI) was recorded at the muscular limbus of the foramen ovalis (FO) on the UEGM tip (sinus rhythm: 2.57 ± 0.95 mV, atrial fibrillation: 1.92 ± 0.77 mV), which then disappeared or significantly reduced at the central FO. Changes in the COI, serving as a major criterion to establish a 3D-TSP workflow, proved to be the most valuable indicator for identifying the FO in 99% (101/102) of patients compared with three previous techniques (three minor criteria) of reduction in atrial unipolar or bipolar potential and FO protrusion. A total of 99.9% (1042/1043) patients in the validation cohort underwent successful 3D-TSP through the workflow from March 2019 to July 2023. Intracardiac echocardiography guidance was required for 6.6% (69/1042) of patients. All four criteria were met in 740 patients, resulting in a 100% pure fluoroless 3D-TSP success rate. CONCLUSION: In most patients, fluoroless 3D-TSP was successfully achieved using changes in the COI on the UEGM tip. Patients who met all four criteria were considered suitable for 3D-TSP, while those who met none required ICE guidance.

Burden of depression in adolescents in the Western Pacific Region from 1990 to 2019: An age-period-cohort analysis of the Global Burden of Disease study.

BACKGROUND: Depression is a highly prevalent and disabling mental health condition among adolescents. The epidemiology of depression in adolescents has been changing over time, reflecting changes in risk factors as well as disease concepts and diagnosis. However, few studies have characterized the longitudinal epidemiology of depression in adolescents. Understanding trends of disease burden provides key insights to improve resource allocation and design targeted interventions for this vulnerable population. The Western Pacific Region (WPR) is home to over 1.3 billion people with tremendous diversity in culture and socioeconomic development. The epidemiology of adolescent depression in WPR remains largely unknown. In this study, we aimed to estimate trends of disease burden attributable to depressive disorders among adolescents aged 10-24 years in WPR countries between 1990 and 2019, and to investigate period and cohort effects using the Global Burden of Disease (GBD) study database. METHODS: The study utilized data from the Global Burden of Disease, Injuries, and Risk Factors Study 2019, concentrating on adolescents aged 10 to 24 years with depression. We conducted an in-depth analysis of depression, including its age-standardized prevalence, incidence, and Disability-Adjusted Life Years (DALYs), across diverse demographics such as regions, ages, genders, and socio-demographic indexes, spanning from 1990 to 2019. RESULTS: The analysis found decreasing trends in the prevalence, incidence, and DALYs of adolescent depression in the WPR between 1990-2019, although some countries like Australia and Malaysia showed increases. Specifically, the prevalence of adolescent depression in the region decreased from 9,347,861.6 cases in 1990 to 5,551,341.1 cases in 2019. The incidence rate declined from 2,508.6 per 100,000 adolescents in 1990 to 1,947.9 per 100,000 in 2019. DALYs decreased from 371.9 per 100,000 in 1990 to ASR 299.7 per 100,000 in 2019. CONCLUSION: This study found an overall decreasing trend in adolescent depression burden in the Western Pacific Region between 1990 and 2019, with heterogeneity across countries. For 30 years, the 20-24 age group accounted for the majority of depression among adolescents Widening inequality in depression burden requires policy attention. Further analysis of risk factors contributing to epidemiological trends is warranted to inform prevention strategies targeting adolescent mental health in the region.