Instance-level 6D pose estimation based on multi-task parameter sharing for robotic grasping.

Six-dimensional pose estimation task predicts its 3D rotation matrix and 3D translation matrix in the world coordinate system by inputting the color image or depth image of the target object. Existing methods usually use deep neural networks to directly predict or regress object poses based on keypoint methods. The prediction results usually have deviations depending on whether the surface shape of the object is prominent or not and the size of the object. To solve this problem, we propose the six-dimensional pose estimation based on multi-task parameter sharing (PMP) framework to incorporate object category information into the pose estimation network through the form of an object classification auxiliary task. First, we extract the image features and point cloud features of the target object separately, and fuse them point by point; then, we share the confidence of each keypoint in pose estimation task and the knowledge of the classification task, get the key points with higher confidence, and predict the object pose; finally, the obtained object pose is passed through an iterative optimization network to obtain the final pose. The experimental results on the LineMOD dataset show that the proposed method can improve the accuracy of pose estimation and narrow the gap in the prediction accuracy of objects with different shapes. We also tested on a new dataset of small-scale objects, which contains object RGBD images and accurate 3D point cloud information. The proposed method is applied to the grasping experiment on the UR5 robotic arm, which satisfies the real-time pose estimation results during the grasping process.

Erratum: Retraction notice to "Integrated the embedding delivery system and targeted oxygen scavenger enhances free radical scavenging capacity" [Food Chem.: X 17 (2023) 100558].

[This corrects the article DOI: 10.1016/j.fochx.2022.100558.].

The association between leptin and diabetes: A meta-analysis.

PURPOSE: The study object was to determine the relationship between leptin and diabetes. METHODS: We searched for the literature on the relationship between leptin and diabetes from PubMed, EMBASE, Cochrane Library, and CNKI databases. We carried out the meta-analysis by calculating the Std. Mean Difference (SMD) and 95% confidence intervals (CIs) to study the relationship between leptin and diabetes. We performed the Chi-square-based Q test and I2 statistics to evaluate the potential heterogeneity, and the sensitivity analysis was performed to evaluate the stability of our results. Moreover, Begg's test was performed to evaluate the publication bias. RESULTS: There are 10 studies in this study for meta-analysis, which include 1879 patients (diabetic (n = 1024); and nondiabetic patients (n = 855)). The results indicated that the levels of serum leptin were significantly increased in patients with diabetes (SMD = 1.78, 95% CI [0.81, 2.76]), especially those with gestational diabetes mellitus compared with controls (SMD = 3.03, 95% CI [1.21, 4.86]). However, the results showed that there was no difference in serum leptin levels between type 2 diabetes and controls (SMD = 0.34, 95% CI [-1.06, 1.74]). CONCLUSIONS: Our analysis indicated that the levels of serum leptin were significantly elevated in patients with diabetes especially those with gestational diabetes mellitus compared with controls.

Benzoic acid inhibits intrinsic ion migration for efficient and stable perovskite solar cells.

An efficient perovskite solar cell (PSC) has the following characteristics: (1) large perovskite grain size; (2) small ion migration; (3) low defect density states. Here, benzoic acid was employed as an additive to a perovskite solution to improve the thin film quality. Surprisingly, 1.0%-BA can implement all of these features. Therefore, the power conversion efficiency (PCE) of the champion PSC is 18.05%, which is superior to that of the control device (15.42%). In addition, BA-doped PSC kept 86% of its primary PCE after 30 days (RH: 35%), but the control device only retained 75% under the same conditions. The improvement of its stability is because of the inhibition of the cation migration of perovskite by the addition of BA and the passivation of perovskite defects. The results can acquire a better understanding of the potential applications of small organic molecules in improving the PCE and stability of PSC devices.

Facet-Dependent Fe2O3/BiVO4(110)/BiVO4(010)/Fe2O3 Dual S-Scheme Photocatalyst as an Efficient Visible-Light-Driven Peroxymonosulfate Activator for Norfloxacin Degradation.

A lack of eco-friendly, highly active photocatalyst for peroxymonosulfate (PMS) activation and unclear environmental risks are significant challenges. Herein, we developed a double S-scheme Fe2O3/BiVO4(110)/BiVO4(010)/Fe2O3 photocatalyst to activate PMS and investigated its impact on wheat seed germination. We observed an improvement in charge separation by depositing Fe2O3 on the (010) and (110) surfaces of BiVO4. This enhancement is attributed to the formation of a dual S-scheme charge transfer mechanism at the interfaces of Fe2O3/BiVO4(110) and BiVO4(010)/Fe2O3. By introducing PMS into the system, photogenerated electrons effectively activate PMS, generating reactive oxygen species (ROS) such as hydroxyl radicals (·OH) and sulfate radicals (SO4·-). Among the tested systems, the 20% Fe2O3/BiVO4/Vis/PMS system exhibits the highest catalytic efficiency for norfloxacin (NOR) removal, reaching 95% in 40 min. This is twice the catalytic efficiency of the Fe2O3/BiVO4/PMS system, 1.8 times that of the Fe2O3/BiVO4 system, and 5 times that of the BiVO4 system. Seed germination experiments revealed that Fe2O3/BiVO4 heterojunction was beneficial for wheat seed germination, while PMS had a significant negative effect. This study provides valuable insights into the development of efficient and sustainable photocatalytic systems for the removal of organic pollutants from wastewater.

Spatially Decoupled H2O2 Activation Pathways and Multi-Enzyme Activities in Rod-Shaped CeO2 with Implications for Facet Distribution.

CeO2, particularly in the shape of rod, has recently gained considerable attention for its ability to mimic peroxidase (POD) and haloperoxidase (HPO). However, this multi-enzyme activities unavoidably compete for H2O2 affecting its performance in relevant applications. The lack of consensus on facet distribution in rod-shaped CeO2 further complicates the establishment of structure-activity correlations, presenting challenges for progress in the field. In this study, the HPO-like activity of rod-shaped CeO2 is successfully enhanced while maintaining its POD-like activity through a facile post-calcination method. By studying the spatial distribution of these two activities and their exclusive H2O2 activation pathways on CeO2 surfaces, this study finds that the increased HPO-like activity originated from the newly exposed (111) surface at the tip of the shortened rods after calcination, while the unchanged POD-like activity is attributed to the retained (110) surface in their lateral area. These findings not only address facet distribution discrepancies commonly reported in the literature for rod-shaped CeO2 but also offer a simple approach to enhance its antibacterial performance. This work is expected to provide atomic insights into catalytic correlations and guide the design of nanozymes with improved activity and reaction specificity.

Enhanced control of periodontitis by an artificial intelligence-enabled multimodal-sensing toothbrush and targeted mHealth micromessages: A randomized trial.

AIM: Treatment of periodontitis, a chronic inflammatory disease driven by biofilm dysbiosis, remains challenging due to patients' poor performance and adherence to the necessary oral hygiene procedures. Novel, artificial intelligence-enabled multimodal-sensing toothbrushes (AI-MST) can guide patients' oral hygiene practices in real-time and transmit valuable data to clinicians, thus enabling effective remote monitoring and guidance. The aim of this trial was to assess the effect of such a system as an adjunct to clinical practice guideline-conform treatment. MATERIALS AND METHODS: This was a single-centre, double-blind, standard-of-care controlled, randomized, parallel-group, superiority trial. Male and female adults with generalized Stage II/III periodontitis were recruited at the Shanghai Ninth People's Hospital, China. Subjects received a standard-of-care oral hygiene regimen or a technology-enabled, theory-based digital intervention consisting of an AI-MST and targeted doctor's guidance by remote micromessaging. Additionally, both groups received guideline-conform periodontal treatment. The primary outcome was the resolution of inflamed periodontal pockets (≥4 mm with bleeding on probing) at 6 months. The intention-to-treat (ITT) analysis included all subjects who received the allocated treatment and at least one follow-up. RESULTS: One hundred patients were randomized and treated (50 tests/controls) between 1 February and 30 November 2022. Forty-eight tests (19 females) and 47 controls (16 females) were analysed in the ITT population. At 6 months, the proportion of inflamed periodontal pockets decreased from 80.7% (95% confidence interval [CI] 76.5-84.8) to 52.3% (47.7-57.0) in the control group, and from 81.4% (77.1-85.6) to 44.4% (39.9-48.9) in the test group. The inter-group difference was 7.9% (1.6-14.6, p < .05). Test subjects achieved better levels of oral hygiene (p < .001). No significant adverse events were observed. CONCLUSIONS: The tested digital health intervention significantly improved the outcome of periodontal therapy by enhancing the adherence and performance of self-performed oral hygiene. The model breaks the traditional model of oral health care and has the potential to improve efficiency and reduce costs (NCT05137392).

A Fusion Network with Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.

Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. In this work, we presented a fusion network with stacked denoise autoencoder and meta learning (SDA-NN-ML) to recognize gait phase and predict gait percentage from IMU signals. Experiments were conducted to detect the four lateral walking gait phases and predict their percentage in 10 healthy subjects across different speeds. The performance of SDA-NN-ML and other widely used algorithms including Support Vector Machine (SVM), Adaptive Boosting (AdaBoost) and Long Short Term Memory (LSTM) were evaluated. The cross-subject recognition accuracy of SDA-NN-ML (89.94%) decreased by 4.62% compared to the training accuracy, which outperformed SVM (8.60%), AdaBoost (5.61%), and LSTM (7.12%). For real-time and cross-subject prediction of gait phase percentage, the RMSE of SDA-NN-ML (0.2043) outperformed that of a single regression network (0.2426). With a signal noise ratio of 100:30, the cross-subject recognition accuracy decreased by a mere 5.70%, while the prediction result (RMSE) of SDA-NN-ML increased by 0.0167 when compared to the noise-free results. SDA-NN-ML demonstrates a stable multi-step-ahead prediction ability with an accuracy higher than 82.50% and an RMSE of less than 0.23 when the ahead time is less than 200 ms. The results demonstrated that the proposed method has high accuracy and robust performance in lateral walking gait recognition and prediction.

Accuracy of robotic surgery for dental implant placement: A systematic review and meta-analysis.

OBJECTIVES: To systematically analyze the accuracy of robotic surgery for dental implant placement. MATERIALS AND METHODS: PubMed, Embase, and Cochrane CENTRAL were searched on October 25, 2023. Model studies or clinical studies reporting the accuracy of robotic surgery for dental implant placement among patients with missing or hopeless teeth were included. Risks of bias in clinical studies were assessed. Meta-analyses were undertaken. RESULTS: Data from 8 clinical studies reporting on 109 patients and 242 implants and 13 preclinical studies were included. Positional accuracy was measured by comparing the implant plan in presurgery CBCT and the actual implant position in postsurgery CBCT. For clinical studies, the pooled (95% confidence interval) platform deviation, apex deviation, and angular deviation were 0.68 (0.57, 0.79) mm, 0.67 (0.58, 0.75) mm, and 1.69 (1.25, 2.12)°, respectively. There was no statistically significant difference between the accuracy of implants placed in partially or fully edentulous patients. For model studies, the pooled platform deviation, apex deviation, and angular deviation were 0.72 (0.58, 0.86) mm, 0.90 (0.74, 1.06) mm, and 1.46 (1.22, 1.70)°, respectively. No adverse event was reported. CONCLUSION: Within the limitation of the present systematic review, robotic surgery for dental implant placement showed suitable implant positional accuracy and had no reported obvious harm. Both robotic systems and clinical studies on robotic surgery for dental implant placement should be further developed.

Does intra-oral scan improve the impression accuracy of full-arch implant-supported prostheses: A systematic review and meta-analysis.

OBJECTIVES: The present study aimed to systematically review the studies comparing the accuracy of intraoral scan (IOS) and conventional implant impressions (CI) in completely edentulous patients. MATERIALS AND METHODS: Electronic searches were performed in PubMed, Embase and Cochrane CENTRAL up to December 1, 2023. Clinical studies and in vitro studies reporting the accuracy of digital full arch impressions were included. The primary outcome is the 3-dimensional deviations between the study reference models. A risk of bias assessment was performed for clinical studies. A stratified meta-analysis and a single-armed meta-analysis were conducted. RESULTS: A total of 49 studies were included, with 8 clinical studies and 41 in vitro studies. For comparison between IOS and conventional impressions, studies were categorized into two groups based on the different measurement methods employed: RMS and CMM. In studies using RMS, the result favored the IOS in the unparalleled situation with the mean difference of -99.29 µm (95% CI: [-141.38, -57.19], I2 = 81%), while the result was opposite with the mean difference of 13.62 µm (95% CI: [10.97, 16.28], I2 = 26%) when implants were paralleled. For different brands of IOS, the accuracy ranged from 76.11 µm (95% CI: [42.36, 109.86]) to 158.63 µm (95% CI: [-14.68, 331.93]). CONCLUSIONS: Accuracy of intraoral scan is clinically acceptable in edentulous arches, especially for unparalleled implants. More clinical studies are needed to verify the present finding.

A Wearable Upper Limb Exoskeleton System and Intelligent Control Strategy.

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer's upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19-30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions.

Thermal and Magnetic Dual-Responsive Catheter-Assisted Shape Memory Microrobots for Multistage Vascular Embolization.

Catheters navigating through complex vessels, such as sharp turns or multiple U-turns, remain challenging for vascular embolization. Here, we propose a novel multistage vascular embolization strategy for hard-to-reach vessels that releases untethered swimming shape-memory magnetic microrobots (SMMs) from the prior catheter to the vessel bifurcation. SMMs, made of organo-gel with magnetic particles, ensure biocompatibility, radiopacity, thrombosis, and fast thermal and magnetic responses. An SMM is initially a linear shape with a 0.5-mm diameter at 20 °C inserted in a catheter. It transforms into a predetermined helix within 2 s at 38 °C blood temperature after being pushed out of the catheter into the blood. SMMs enable agile swimming in confined and tortuous vessels and can swim upstream using helical propulsion with rotating magnetic fields. Moreover, we validated this multistage vascular embolization in living rabbits, completing 100-cm travel and renal artery embolization in 2 min. After 4 weeks, the SMMs maintained the embolic position, and the kidney volume decreased by 36%.

Neurokinin-1 receptor antagonist aprepitant regulates autophagy and apoptosis via ROS/JNK in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) has a poor prognosis and limited treatment options. Aprepitant, a selective NK-1R antagonist, can inhibit the growth of various tumours in vitro and in vivo. However, it remains unclear whether aprepitant has cytotoxic effects on iCCA. METHODS: We measured the expression of SP/NK-1R in clinical samples of iCCA by immunohistochemistry. Then, we detected the cytotoxic effects of aprepitant on iCCA cells via MTT, EdU and colony formation assay. We constructed a subcutaneous xenograft model of BALB/c nude mice by using HCCC-9810 and RBE cell lines to explore the effects of aprepitant in vivo. To elucidate the potential mechanisms, we explored the pro-apoptotic effect of aprepitant by flow cytometric, western blotting, ROS detection and JC-1 staining. Furthermore, we detected the autophagic level of HCCC-9810 and RBE by western blotting, mRFP-eGFP-LC3 adenovirus transfection and electron microscope. RESULTS: SP/NK-1R is significantly expressed in iCCA. Aprepitant inhibited human iCCA xenograft growth and dose-dependently decreased the viability of RBE and HCCC-9810 cells. Aprepitant-induced mitochondria-dependent apoptosis through ROS/JNK pathway. Additionally, pretreatment with z-VAD-fmk partly reversed the effect of aprepitant on cell viability, while NAC completely attenuated the cytotoxic effects of aprepitant in vitro. Furthermore, we observed the dynamic changes of autophagosome in RBE and HCCC-9810 cells treated with aprepitant. CONCLUSION: SP/NK-1R signalling is significantly activated in iCCA and promotes the proliferation of iCCA cells. By contrast, aprepitant can induce autophagy and apoptosis in iCCA cells via ROS accumulation and subsequent activation of JNK.

[99mTc]Tc-HYNIC-ALUG SPECT/CT in the initial staging of 227 consecutive patients with newly diagnosed prostate cancer: a 5-year monocentric retrospective study.

Purpose: The purpose of this study was to assess the effectiveness of [99mTc]Tc-HYNIC-ALUG SPECT/CT in the initial staging of patients with newly diagnosed PCa. Methods: A retrospective analysis was conducted on 227 consecutive patients who underwent [99mTc]Tc-HYNIC-ALUG SPECT/CT imaging for the primary staging of newly diagnosed PCa. The presence and location of PSMA-positive lesions were determined, and the maximum standardized uptake values (SUVmax) of the primary prostate tumor were also measured. The metastatic findings and SUVmax were stratified according to International Society of Urological Pathology (ISUP) grade, prostate-specific antigen (PSA) levels, and D'Amico classification. Furthermore, the [99mTc]Tc-HYNIC-ALUG SPECT/CT findings were compared to the histopathological findings in patients who had undergone radical prostatectomy with pelvic lymph node dissection (PLND). Results: Of the 227 patients, 92.1% (209/227) had positive [99mTc]Tc-HYNIC-ALUG SPECT/CT findings. Advanced disease was detected in 38.8% (88/227) of the patients and was positively correlated with increasing ISUP grade and PSA levels. Lymph node metastases (both pelvic and extrapelvic), bone metastases, and visceral metastases were detected in 30.0% (68/227), 25.6% (58/227), and 3.1% (7/227) of the patients, respectively. For the 129 patients who underwent radical prostatectomy with PLND, the sensitivity of [99mTc]Tc-HYNIC-ALUG SPECT/CT in the evaluation of PCa was 90.7% (117/129). The sensitivity, specificity, accuracy, and positive and negative predictive values for detecting pelvic lymph node metastases on [99mTc]Tc-HYNIC-ALUG SPECT/CT were 23.5% (12/51), 93.6% (73/78), 65.9% (85/129), 70.6% (12/17), and 65.2% (73/112), respectively. Among the 209 patients with PSMA-avid primary prostate disease, the SUVmax of the primary prostate tumor was significantly associated with ISUP grade (p<0.0001), PSA levels (p<0.0001), D'Amico classification (p<0.0001), and advanced disease (p<0.0001). Receiver operating characteristic (ROC) analysis revealed that a PSA level >19.8 ng/ml and SUVmax of the primary prostate tumor >7.4 had a sensitivity of 71.6% and 71.6% and specificity of 76.9% and 82.6%, respectively, for detecting metastatic disease. Conclusions: [99mTc]Tc-HYNIC-ALUG SPECT/CT emerges as a valuable imaging tool for the initial staging of newly diagnosed PCa. The presence of advanced disease and the SUVmax of the primary prostate tumor were positively correlated with ISUP grade and PSA levels.

The role of the transcriptional repressor CssR in Corynebacterium glutamicum in response to phenolic compounds.

The cssR gene (ncgl1578) of Corynebacterium glutamicum encodes a repressor of the TetR (tetracycline regulator) family. Its role in the stress response to antibiotics/heavy metals has been investigated, but how CssR functions in response to phenolic compounds in C. glutamicum has been rarely studied. In this study, we applied transcriptomic analysis, ß-galactosidase analysis, qRT-PCR, and EMSAs to analyze the target genes and functions of CssR in response to phenolic compounds. Consistent with the upregulation of genes involved in the degradation of phenolic compounds, the ΔcssR mutant was more resistant to various phenolic compounds than was the wild-type strain. Furthermore, the addition of phenolic compounds induced the expression of corresponding genes (ncgl0283, ncgl1032, ncgl1111, ncgl2920, ncgl2923, and ncgl2952) in vivo. However, the DNA binding activity of CssR to the promoter of phenolic compound-degrading genes was undetected in vitro. Additionally, we also found that CssR indirectly negatively regulates the expression of cell wall/membrane/envelope biogenesis-related genes, which may enhance resistance to stress caused by phenolic compounds. Together, our findings demonstrate that CssR is a key regulator that copes with stress conditions induced by phenolic compounds, thus greatly expanding our understanding of the functions of TetR family transcription factors.

Rapid hyperspectral photothermal mid-infrared spectroscopic imaging from sparse data for gynecologic cancer tissue subtyping.

Ovarian cancer detection has traditionally relied on a multi-step process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. Our method significantly accelerates data collection by capturing a combination of highresolution and interleaved, lower-resolution infrared band images and applying computational techniques for data interpolation. We effectively minimize data collection requirements by leveraging sparse data acquisition and employing curvelet-based reconstruction algorithms. This approach enhances imaging speed without compromising image quality and ensures robust tissue segmentation. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled datasets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology. It represents a significant leap forward from traditional histopathological methods, offering profound implications for cancer diagnostics and treatment decision-making.

Early Succession of Community Structures and Biotic Interactions of Gut Microbes in Eriocheir sinensis Megalopa after Desalination.

As an enduring Chinese freshwater aquaculture product, the Eriocheir sinensis has a high economic value and is characterized by a catadromous life style that undergoes seawater-freshwater migration. However, little is known about their gut microbial status as they move from saltwater to freshwater acclimatization. Here, we sampled and cultivated Eriocheir sinensis megalopa from three aquaculture desalination ponds and investigated their gut microbiota diversity, community structures and biotic interactions from megalopa stage to the first juvenile stage after desalination for 9 days. Our results revealed that during the transition from megalopa to the first juvenile in Eriocheir sinensis, a significant change in gut microbial composition was observed (for instance, changes in relative abundance of dominant phyla), which was, however, not influenced by different sampling sites. The species diversity (such as the richness) of the gut microbiota showed a hump-shaped pattern along the succession. However, the compositional differences of the gut microbes showed constantly increasing patterns during the succession after freshwater adaption for all three sampling sites. Further co-occurrence analysis also showed that the complexity of the ecological networks in gut microbes was significantly enhanced during the development, such as increasing numbers of network links, connectivity and modularity, and was confirmed by decreasing average path length and proportions of negative links. Taken together, the differences in community structures and biological interactions of gut microorganisms were more pronounced in Eriocheir sinensis megalopa during desalination than in diversity and species compositions. This implies that the gut microbes of Eriocheir sinensis megalopa would become more robust and adaptive during the developmental process.

Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) is indeed a significant cause of mortality and morbidity in individuals with coronary heart disease. Ferroptosis, an iron-dependent cell death, is characterized by the accumulation of intracellular lipid peroxides, which is implicated in cardiomyocyte injury. This study aims to identify biomarkers that are indicative of ferroptosis in the context of AMI, and to examine their potential roles in immune infiltration. METHODS: Firstly, the GSE59867 dataset was used to identify differentially expressed ferroptosis-related genes (DE-FRGs) in AMI. We then performed gene ontology (GO) and functional enrichment analysis on these DE-FRGs. Secondly, we analyzed the GSE76591 dataset and used bioinformatic methods to build ceRNA networks. Thirdly, we identified hub genes in protein-protein interaction (PPI) network. After obtaining the key DE-FRGs through the junction of hub genes with ceRNA and least absolute shrinkage and selection operator (LASSO). ImmucellAI was applied to estimate the immune cell infiltration in each sample and examine the relationship between key DE-FRGs and 24 immunocyte subsets. The diagnostic performance of these genes was further evaluated using the receiver operating characteristic (ROC) curve analysis. Ultimately, we identified an immune-related ceRNA regulatory axis linked to ferroptosis in AMI. RESULTS: Among 56 DE-FRGs identified in AMI, 41 of them were integrated into the construction of competitive endogenous RNA (ceRNA) networks. TLR4 and PIK3CA were identified as key DE-FRGs and PIK3CA was confirmed as a diagnostic biomarker for AMI. Moreover, CD4_native cells, nTreg cells, Th2 cells, Th17 cells, central-memory cells, effector-memory cells, and CD8_T cells had higher infiltrates in AMI samples compared to control samples. In contrast, exhausted cells, iTreg cells, and Tfh cells had lower infiltrates in AMI samples. Spearman analysis confirmed the correlation between 24 immune cells and PIK3CA/TLR4. Ultimately, we constructed an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA. CONCLUSION: Our comprehensive analysis has identified PIK3CA as a robust and promising biomarker for this condition. Moreover, we have also identified an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA, which may play a key role in regulating ferroptosis during AMI progression.

Continuous Locomotion Mode and Task Identification for an Assistive Exoskeleton Based on Neuromuscular-Mechanical Fusion.

Human walking parameters exhibit significant variability depending on the terrain, speed, and load. Assistive exoskeletons currently focus on the recognition of locomotion terrain, ignoring the identification of locomotion tasks, which are also essential for control strategies. The aim of this study was to develop an interface for locomotion mode and task identification based on a neuromuscular-mechanical fusion algorithm. The modes of level and incline and tasks of speed and load were explored, and seven able-bodied participants were recruited. A continuous stream of assistive decisions supporting timely exoskeleton control was achieved according to the classification of locomotion. We investigated the optimal algorithm, feature set, window increment, window length, and robustness for precise identification and synchronization between exoskeleton assistive force and human limb movements (human-machine collaboration). The best recognition results were obtained when using a support vector machine, a root mean square/waveform length/acceleration feature set, a window length of 170, and a window increment of 20. The average identification accuracy reached 98.7% ± 1.3%. These results suggest that the surface electromyography-acceleration can be effectively used for locomotion mode and task identification. This study contributes to the development of locomotion mode and task recognition as well as exoskeleton control for seamless transitions.

Drug-related side effects and adverse reactions in the treatment of migraine: a bibliometric and visual analysis.

Background: Migraine imposes a substantial global burden, impacting patients and society. Pharmacotherapy, as a primary treatment, entails specific adverse reactions. Emphasizing these reactions is pivotal for improving treatment strategies and enhancing patients' well-being. Thus, we conducted a comprehensive bibliometric and visual analysis of relevant literature. Methodology: We conducted a comprehensive search on the Science Citation Index Expanded within the Web of Science, restricting the literature for analysis based on criteria such as document type, publication date, and language. Subsequently, we utilized various analytical tools, including VOSviewer, Scimago Graphica, the R package 'bibliometrix', CiteSpace, and Excel programs, for a meticulous examination and systematic organization of data concerning journals, authors, countries/regions, institutions, keywords, and references. Results: By August 31, 2023, the literature was distributed across 379 journals worldwide, authored by 4,235 individuals from 1726 institutions. It featured 2,363 keywords and 38,412 references. 'HEADACHE' led in publication count, with 'SILBERSTEIN S' as the most prolific author. The United States ranked highest in publication volume, with 'UNIV COPENHAGEN' leading among institutions. Conclusion: Our research findings indicate that researchers in the field continue to maintain a focus on the calcitonin gene-related peptide (CGRP) system and explore diverse mechanisms for drug development through the application of novel biotechnological approaches. Furthermore, it is imperative to enhance the assessment of clinical trial outcomes, consistently monitor the efficacy and safety of prominent drugs such as Erenumab and Fremanezumab. There is a need for further evaluation of acute and preventive treatments tailored to different populations and varying types of migraine.