EMPT: a sparsity Transformer for EEG-based motor imagery recognition.

Introduction: Transformer network is widely emphasized and studied relying on its excellent performance. The self-attention mechanism finds a good solution for feature coding among multiple channels of electroencephalography (EEG) signals. However, using the self-attention mechanism to construct models on EEG data suffers from the problem of the large amount of data required and the complexity of the algorithm. Methods: We propose a Transformer neural network combined with the addition of Mixture of Experts (MoE) layer and ProbSparse Self-attention mechanism for decoding the time-frequency-spatial domain features from motor imagery (MI) EEG of spinal cord injury patients. The model is named as EEG MoE-Prob-Transformer (EMPT). The common spatial pattern and the modified s-transform method are employed for achieving the time-frequency-spatial features, which are used as feature embeddings to input the improved transformer neural network for feature reconstruction, and then rely on the expert model in the MoE layer for sparsity mapping, and finally output the results through the fully connected layer. Results: EMPT achieves an accuracy of 95.24% on the MI EEG dataset for patients with spinal cord injury. EMPT has also achieved excellent results in comparative experiments with other state-of-the-art methods. Discussion: The MoE layer and ProbSparse Self-attention inside the EMPT are subjected to visualisation experiments. The experiments prove that sparsity can be introduced to the Transformer neural network by introducing MoE and kullback-leibler divergence attention pooling mechanism, thereby enhancing its applicability on EEG datasets. A novel deep learning approach is presented for decoding EEG data based on MI.

Choriocapillaris reduction accurately discriminates against early-onset Alzheimer's disease.

INTRODUCTION: This study addresses the urgent need for non-invasive early-onset Alzheimer's disease (EOAD) prediction. Using optical coherence tomography angiography (OCTA), we present a choriocapillaris model sensitive to EOAD, correlating with serum biomarkers. METHODS: Eighty-four EOAD patients and 73 controls were assigned to swept-source OCTA (SS-OCTA) or the spectral domain OCTA (SD-OCTA) cohorts. Our hypothesis on choriocapillaris predictive potential in EOAD was tested and validated in these two cohorts. RESULTS: Both cohorts revealed diminished choriocapillaris signals, demonstrating the highest discriminatory capability (area under the receiver operating characteristic curve: SS-OCTA 0.913, SD-OCTA 0.991; P < 0.001). A sparser SS-OCTA choriocapillaris correlated with increased serum amyloid beta (Aß)42, Aß42/40, and phosphorylated tau (p-tau)181 levels (all P < 0.05). Apolipoprotein E status did not affect choriocapillaris measurement. DISCUSSION: The choriocapillaris, observed in both cohorts, proves sensitive to EOAD diagnosis, and correlates with serum Aß and p-tau181 levels, suggesting its potential as a diagnostic tool for identifying and tracking microvascular changes in EOAD. HIGHLIGHTS: Optical coherence tomography angiography may be applied for non-invasive screening of Alzheimer's disease (AD). Choriocapillaris demonstrates high sensitivity and specificity for early-onset AD diagnosis. Microvascular dynamics abnormalities are associated with AD.

Systematic investigation of the material basis, effectiveness and safety of Thesium chinense Turcz. and its preparation Bairui Granules against lung inflammation.

BACKGROUND: Thesium chinense Turcz. (Named as Bai Rui Cao in Chinese) and its preparations (e.g., Bairui Granules) have been used to treat inflammatory diseases, such as acute mastitis, lobar pneumonia, tonsillitis, coronavirus disease 2019 (COVID-19), and upper respiratory tract infection. However, the material basis, pharmacological efficiency, and safety have not been illustrated. METHODS: Anti-inflammatory activity-guided isolation of constituents has been performed using multiple column chromatography, and their structures were elucidated by NMR spectroscopy and ECD calculations. The inhibitory effects on lung inflammation and safety of the crude ethanol extract (CE), Bairui Granules (BG), and the purified active constituents were evaluated using lipopolysaccharide (LPS)-stimulated acute lung inflammation (ALI) mice model or normal mice. RESULTS: Seven new compounds (1-7) and fifty-six known compounds (8-63) were isolated from T. chinense, and fifty-four were reported from this plant for the first time. The new flavonoid glycosides 1-2, new fatty acids 4-5, new alkaloid 7 as well as the known constituents including flavonoid aglycones 8-11, lignans 46-54, alkaloids 34 and 45, coumarins 57, phenylpropionic acids 27, and simple aromatic compounds 39, 44 and 58 exhibited anti-inflammatory activity. Network pharmacology analysis indicated that anti-inflammation of T. chinense was attributed to flavonoids and alkaloids by regulating inflammation-related proteins (e.g., TNF, NF-κB, TGF-ß). Furthermore, constituents of T. chinense including kaempferol-3-O-glucorhamnoside (KN, also named as Bairuisu I, 19), astragalin (AG, Bairuisu II, 12), and kaempferol (KF, Bairuisu III, 8), as well as CE and BG could alleviate lung inflammation caused by LPS in mice by preventing neutrophils infiltration and the expression of the genes for pro-inflammatory cytokines NLRP3, caspase-1, IL-1ß, and COX-2. After a 28-day subacute toxicity test, BG at doses of 4.875 g/kg and 9.750 g/kg (equivalent to onefold and twofold the clinically recommended dose) and CE at a dose of 11.138 g/kg (equivalent to fourfold the clinical dose of BG) were found to be safe and non-toxic. CONCLUSIONS: The discovery of sixty-three constituents comprehensively illustrated the material basis of T. chinense. T. chinense and Bairui Granules could alleviate lung inflammation by regulating inflammation-related proteins and no toxicity was observed under the twofold of clinically used doses.

Synergistic Effects of MOFs and Noble Metals in Photocatalytic Reactions: Mechanisms and Applications.

Photocatalytic technology can efficiently convert solar energy to chemical energy and this process is considered as one of the green and sustainable technology for practical implementation. In recent years, metal-organic frameworks (MOFs) have attracted widespread attention due to their unique advantages and have been widely applied in the field of photocatalysis. Among them, noble metals have contributed significant advances to the field as effective catalysts in photocatalytic reactions. Importantly, noble metals can also form a synergistic catalytic effect with MOFs to further improve the efficiency of photocatalytic reactions. However, how to precisely control the synergistic effect between MOFs and noble metals to improve the photocatalytic performance of materials still needs to be further studied. In this review, the synergistic effects of MOFs and noble metal catalysts in photocatalytic reactions are firstly summarized in terms of noble metal nanoparticles, noble metal monoatoms, noble metal compounds, and noble metal complexes, and focus on the mechanisms and advantages of these synergistic effects, so as to provide useful guidance for the further research and application of MOFs and contribute to the development of the field of photocatalysis.

Comparison of the efficacy and complications of tolterodine and α-adrenergic receptor blockers in improving ureteral stent-related symptoms: A systematic review and meta-analysis.

OBJECTIVE: We conducted a systematic evaluation of the therapeutic efficacy and complications of tolterodine and α-adrenergic receptor blockers in alleviating ureteral stent-related symptoms. METHODS: Until August 2023, we conducted a comprehensive literature search on PubMed, Embase, Web of Science, and Cochrane Library to identify randomized controlled trials evaluating the efficacy and complications of tolterodine and α-adrenergic receptor blockers in treating ureteral stent-related symptoms. Two reviewers independently screened studies and extracted data. The scores from various domains of the Ureteral Stent Symptom Questionnaire (USSQ) were summarized and compared, and statistical analysis was performed using RevMan 5.4.0 software. RESULTS: A total of 8 studies met the inclusion criteria for our analysis. These studies were conducted at different centers. All studies were randomized controlled trials, involving a total of 487 patients, with 244 patients receiving α-adrenergic receptor blockers and 243 patients receiving tolterodine. The results showed that tolterodine demonstrated significantly better improvement in body pain (MD, 1.56; 95% CI [0.46, 2.66]; p = 0.005) (MD, 0.46; 95% CI [0.12, 0.80]; p = 0.008) (MD, 3.21; 95% CI [1.89, 4.52]; p = 0.00001) among patients after ureteral stent placement compared to α-adrenergic receptor blockers at different time points. Additionally, at 4 weeks, tolterodine showed superior improvement in general health (MD, 0.15; 95% CI [0.03, 0.27]; p = 0.01) and urinary symptoms (MD, 1.62; 95% CI [0.59, 2.66]; p = 0.002) compared to α-adrenergic receptor blockers, while at 6 weeks, tolterodine showed better improvement in work performance (MD, -1.60; 95% CI [-2.73, -0.48]; p = 0.005) compared to α-adrenergic receptor blockers. Additionally, the incidence of dry mouth (RR, 4.21; 95% CI [1.38, 12.87]; p = 0.01) is higher with the use of tolterodine compared to α-adrenergic receptor blockers. However, there were no significant statistical differences between the two drugs in other outcomes. CONCLUSION: This meta-analysis suggests that tolterodine is superior to α-adrenergic receptor blockers in improving physical pain symptoms after ureteral stent placement, while α-adrenergic receptor blockers are more effective than tolterodine in enhancing work performance. Additionally, the incidence of dry mouth is higher with the use of tolterodine compared to α-adrenergic receptor blockers. However, higher-quality randomized controlled trials are needed to further investigate this issue.

Dynamic risk assessment of a coal slurry preparation system based on the structure-variable Dynamic Bayesian Network.

In order to strengthen the safety management of coal slurry preparation systems, a dynamic risk assessment method was established by using the bow-tie (BT) model and the Structure-variable Dynamic Bayesian Network (SVDBN). First, the BT model was transformed into a static Bayesian network (BN) model of the failure of a coal slurry preparation system by using the bow-tie model and the structural similarity of the Bayesian cognitive science, based on the SVDBN recursive reasoning algorithm. The risk factors of the coal slurry preparation system were deduced using the Python language in two ways, and at the same time, preventive measures were put forward according to the weak links. In order to verify the accuracy and feasibility of this method, the simulation results were compared with those obtained using GeNIe software. The reasoning results of the two methods were very similar. Without considering maintenance factors, the failure rate of the coal slurry preparation system gradually increases with increasing time. When considering maintenance factors, the reliability of the coal slurry preparation system will gradually be maintained at a certain threshold, and the maintenance factors will increase the reliability of the system. The proposed method can provide a theoretical basis for the risk assessment and safety management of coal slurry preparation systems.

Nanotechnology-driven strategies to enhance the treatment of drug-resistant bacterial infections.

The misuse of antibiotics has led to increased bacterial resistance, posing a global public health crisis and seriously endangering lives. Currently, antibiotic therapy remains the most common approach for treating bacterial infections, but its effectiveness against multidrug-resistant bacteria is diminishing due to the slow development of new antibiotics and the increase of bacterial drug resistance. Consequently, developing new a\ntimicrobial strategies and improving antibiotic efficacy to combat bacterial infection has become an urgent priority. The emergence of nanotechnology has revolutionized the traditional antibiotic treatment, presenting new opportunities for refractory bacterial infection. Here we comprehensively review the research progress in nanotechnology-based antimicrobial drug delivery and highlight diverse platforms designed to target different bacterial resistance mechanisms. We also outline the use of nanotechnology in combining antibiotic therapy with other therapeutic modalities to enhance the therapeutic effectiveness of drug-resistant bacterial infections. These innovative therapeutic strategies have the potential to enhance bacterial susceptibility and overcome bacterial resistance. Finally, the challenges and prospects for the application of nanomaterial-based antimicrobial strategies in combating bacterial resistance are discussed. This article is categorized under: Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease.

The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations.

OBJECTIVES: 18F-fluorodeoxyglucose (FDG) PET/CT has been widely used for the differential diagnosis of cancer. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may make it difficult to differentiate between benign and malignant lesions. It is crucial to find reliable quantitative metabolic parameters to further support the diagnosis. This study aims to evaluate the value of the quantitative metabolic parameters derived from dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting epidermal growth factor receptor (EGFR) mutation status. METHODS: We included 147 patients with lung lesions to perform FDG PET/CT dynamic plus static imaging with informed consent. Based on the results of the postoperative pathology, the patients were divided into benign/malignant groups, adenocarcinoma (AC)/squamous carcinoma (SCC) groups, and EGFR-positive (EGFR+)/EGFR-negative (EGFR-) groups. Quantitative parameters including K1, k2, k3, and Ki of each lesion were obtained by applying the irreversible two-tissue compartmental modeling using an in-house Matlab software. The SUV analysis was performed based on conventional static scan data. Differences in each metabolic parameter among the group were analyzed. Wilcoxon rank-sum test, independent-samples T-test, and receiver-operating characteristic (ROC) analysis were performed to compare the diagnostic effects among the differentiated groups. P < 0.05 were considered statistically significant for all statistical tests. RESULTS: In the malignant group (N = 124), the SUVmax, k2, k3, and Ki were higher than the benign group (N = 23), and all had-better performance in the differential diagnosis (P < 0.05, respectively). In the AC group (N = 88), the SUVmax, k3, and Ki were lower than in the SCC group, and such differences were statistically significant (P < 0.05, respectively). For ROC analysis, Ki with cut-off value of 0.0250 ml/g/min has better diagnostic specificity than SUVmax (AUC = 0.999 vs. 0.70). In AC group, 48 patients further underwent EGFR testing. In the EGFR (+) group (N = 31), the average Ki (0.0279 ± 0.0153 ml/g/min) was lower than EGFR (-) group (N = 17, 0.0405 ± 0.0199 ml/g/min), and the difference was significant (P < 0.05). However, SUVmax and k3 did not show such a difference between EGFR (+) and EGFR (-) groups (P>0.05, respectively). For ROC analysis, the Ki had a cut-off value of 0.0350 ml/g/min when predicting EGFR status, with a sensitivity of 0.710, a specificity of 0.588, and an AUC of 0.674 [0.523-0.802]. CONCLUSION: Although both techniques were specific, Ki had a greater specificity than SUVmax when the cut-off value was set at 0.0250 ml/g/min for the differential diagnosis of lung cancer. At a cut-off value of 0.0350 ml/g/min, there was a 0.710 sensitivity for EGFR status prediction. If EGFR testing is not available for a patient, dynamic imaging could be a valuable non-invasive screening method.

Monocytes release cystatin F dimer to associate with Aß and aggravate amyloid pathology and cognitive deficits in Alzheimer's disease.

BACKGROUND: Understanding the molecular mechanisms of Alzheimer's disease (AD) has important clinical implications for guiding therapy. Impaired amyloid beta (Aß) clearance is critical in the pathogenesis of sporadic AD, and blood monocytes play an important role in Aß clearance in the periphery. However, the mechanism underlying the defective phagocytosis of Aß by monocytes in AD remains unclear. METHODS: Initially, we collected whole blood samples from sporadic AD patients and isolated the monocytes for RNA sequencing analysis. By establishing APP/PS1 transgenic model mice with monocyte-specific cystatin F overexpression, we assessed the influence of monocyte-derived cystatin F on AD development. We further used a nondenaturing gel to identify the structure of the secreted cystatin F in plasma. Flow cytometry, enzyme-linked immunosorbent assays and laser scanning confocal microscopy were used to analyse the internalization of Aß by monocytes. Pull down assays, bimolecular fluorescence complementation assays and total internal reflection fluorescence microscopy were used to determine the interactions and potential interactional amino acids between the cystatin F protein and Aß. Finally, the cystatin F protein was purified and injected via the tail vein into 5XFAD mice to assess AD pathology. RESULTS: Our results demonstrated that the expression of the cystatin F protein was specifically increased in the monocytes of AD patients. Monocyte-derived cystatin F increased Aß deposition and exacerbated cognitive deficits in APP/PS1 mice. Furthermore, secreted cystatin F in the plasma of AD patients has a dimeric structure that is closely related to clinical signs of AD. Moreover, we noted that the cystatin F dimer blocks the phagocytosis of Aß by monocytes. Mechanistically, the cystatin F dimer physically interacts with Aß to inhibit its recognition and internalization by monocytes through certain amino acid interactions between the cystatin F dimer and Aß. We found that high levels of the cystatin F dimer protein in blood contributed to amyloid pathology and cognitive deficits as a risk factor in 5XFAD mice. CONCLUSIONS: Our findings highlight that the cystatin F dimer plays a crucial role in regulating Aß metabolism via its peripheral clearance pathway, providing us with a potential biomarker for diagnosis and potential target for therapeutic intervention.

Identification of Biomarkers, Pathways, Immune Properties of Mitophagy Genes, and Prediction Models for Intervertebral Disc Degeneration.

Background: Intervertebral disc degeneration (IDD) is the leading cause of low back pain (LBP). The mechanism of IDD development and progression is not fully understood. Peripheral biomarkers are increasingly vital non-radioactive methods in early detection and diagnosis for IDD. Nevertheless, less attention has been paid to the role of mitophagy genes in the progress of IDD. This study aimed to identify the mitophagy disease-causing genes in the process of IDD and mitophagy diagnostic biomarkers for IDD. Methods: Mitophagy-related differentially expressed genes (MRDEGs) related to IDD were investigated by analyzing the microarray datasets of IDD cases from GEO, PathCards and Molecular Signatures Databases. We used R software, WGCNA, PPI, mRNA-miRNA, mRNA-TF, GO, KEGG, GSEA, GSVA and Cytoscape to analyze and visualize the data. We further used ssGSEA for immunoinfiltration analysis to obtain different immune cell infiltration. LASSO model was developed to screen for genes that met the diagnostic gene model requirements. Finally, qRT-PCR, Western blotting and HE were used to verify hub genes and their expression from clinical IDD samples. Results: We identified 14 MRDEGs and 12 hub genes. GO, KEGG, GSEA and GSVA analyses demonstrated that hub genes were critical for the development of IDD. LASSO diagnostic model consisted of six hub genes, among which SQSTM1, ATG7 and OPTN were significantly different between the two IDD disease subtypes. At the same time, SQSTM1 also had a high correlation with immune characteristic subtypes. The results of qRT-PCR and Western blotting also indicated that these genes were significantly differentially expressed in nucleus pulposus cells (NPCs) of the IDD group. Conclusion: We explored an association between MRDEGs-associated signature in IDD and validated that hub genes like SQSTM1 might serve as biomarkers for diagnostic and therapeutic targets for IDD. Meanwhile, this study can provide new insights into the functional characteristics and mechanism of mitophagy in the development of IDD.

PA28γ coordinates the cross-talk between cancer-associated fibroblasts and tumor cells to promote OSCC progression via HDAC1/E2F3/IGF2 signaling.

PA28γ overexpression is aberrant and accompanied by poor patient prognosis in various cancers, the precise regulatory mechanism of this crucial gene in the tumor microenvironment remains incompletely understood. In this study, using oral squamous cell carcinoma as a model, we demonstrated that PA28γ exhibits high expression in cancer-associated fibroblasts (CAFs), and its expression significantly correlates with the severity of clinical indicators of malignancy. Remarkably, we found that elevated levels of secreted IGF2 from PA28γ+ CAFs can enhance stemness maintenance and promote tumor cell aggressiveness through the activation of the MAPK/AKT pathway in a paracrine manner. Mechanistically, PA28γ upregulates IGF2 expression by stabilizing the E2F3 protein, a transcription factor of IGF2. Further mechanistic insights reveal that HDAC1 predominantly mediates the deacetylation and subsequent ubiquitination and degradation of E2F3. Notably, PA28γ interacts with HDAC1 and accelerates its degradation via a 20S proteasome-dependent pathway. Additionally, PA28γ+ CAFs exert an impact on the tumor immune microenvironment by secreting IGF2. Excitingly, our study suggests that targeting PA28γ+ CAFs or secreted IGF2 could increase the efficacy of PD-L1 therapy. Thus, our findings reveal the pivotal role of PA28γ in cell interactions in the tumor microenvironment and propose novel strategies for augmenting the effectiveness of immune checkpoint blockade in oral squamous cell carcinoma.

Sex-specific association of serum dehydroepiandrosterone and its sulfate levels with osteoporosis in type 2 diabetes.

INTRODUCTION: This study is to investigate the relation between serum dehydroepiandrosterone (DHEA) and its sulfate (DHEAS) levels and the risk of osteoporosis in patients with T2DM. MATERIALS AND METHODS: This cross-sectional study involved 938 hospitalized patients with T2DM. Linear regression models were used to explore the relationship between DHEA and DHEAS and the BMD at different skeletal sites. Multinominal logistic regression models and the restricted cubic spline (RCS) were used to evaluate the associations of DHEA and DHEAS with the risks of osteopenia and/or osteoporosis. RESULTS: In postmenopausal women with T2DM, after adjustment for confounders including testosterone and estradiol, DHEA showed a significant positive correlation with lumbar spine BMD (P = 0.013). Moreover, DHEAS exhibited significant positive correlations with BMD at three skeletal sites: including femoral neck, total hip, and lumbar spine (all P < 0.05). Low DHEA and DHEAS levels were associated with increased risk of osteopenia and/or osteoporosis (all P < 0.05) and the risk of osteoporosis gradually decreased with increasing DHEAS levels (P overall = 0.018, P-nonlinear = 0.559). However, DHEA and DHEAS levels in men over the age of 50 with T2DM were not associated with any of above outcomes. CONCLUSION: In patients with T2DM, independent of testosterone and estradiol, higher DHEA and DHEAS levels are associated with higher BMD and lower risk of osteopenia/osteoporosis in postmenopausal women but not men over the age of 50.

Rational design of comb-like 1D-1D ZnO-ZnSe heterostructures toward their excellent performance in flexible photodetectors.

One-dimensional (1D) Zn-based heterostructures have attracted considerable interest in the field of photodetection because of their tunable properties, flexibility, and unique optoelectronic properties. However, designing 1D multi-component Zn-based heterostructures for advanced photodetectors is still a great challenge. Herein, comb-like 1D-1D ZnO-ZnSe heterostructures with ZnO and ZnSe nanowires (NWs) comprising the shaft and teeth of a comb are reported. The length of the ZnO NWs can be modulated in the range of 300-1200 nm. Microstructural characterizations confirm that the 1D heterostructure clearly shows the spatial distribution of individual components. The well-designed structure displays an extended broadband photoresponse and higher photosensitivity than pure ZnSe NWs. Furthermore, ZnSe NWs with an appropriate length of ZnO branches show increased photoresponses of 3835% and 798% compared to those of pure ZnSe NWs under green and red-light irradiation, respectively. In addition, the integrated flexible photodetector presents excellent folding endurance after 1000 bending tests. This well-designed structure has significant potential for other 1D-based semiconductors in optoelectronic applications.

Synthetic bacteria designed using ars operons: a promising solution for arsenic biosensing and bioremediation.

The global concern over arsenic contamination in water due to its natural occurrence and human activities has led to the development of innovative solutions for its detection and remediation. Microbial metabolism and mobilization play crucial roles in the global cycle of arsenic. Many microbial arsenic-resistance systems, especially the ars operons, prevalent in bacterial plasmids and genomes, play vital roles in arsenic resistance and are utilized as templates for designing synthetic bacteria. This review novelty focuses on the use of these tailored bacteria, engineered with ars operons, for arsenic biosensing and bioremediation. We discuss the advantages and disadvantages of using synthetic bacteria in arsenic pollution treatment. We highlight the importance of genetic circuit design, reporter development, and chassis cell optimization to improve biosensors' performance. Bacterial arsenic resistances involving several processes, such as uptake, transformation, and methylation, engineered in customized bacteria have been summarized for arsenic bioaccumulation, detoxification, and biosorption. In this review, we present recent insights on the use of synthetic bacteria designed with ars operons for developing tailored bacteria for controlling arsenic pollution, offering a promising avenue for future research and application in environmental protection.

Assessing the Risk of Bias in Randomized Clinical Trials With Large Language Models.

Importance: Large language models (LLMs) may facilitate the labor-intensive process of systematic reviews. However, the exact methods and reliability remain uncertain. Objective: To explore the feasibility and reliability of using LLMs to assess risk of bias (ROB) in randomized clinical trials (RCTs). Design, Setting, and Participants: A survey study was conducted between August 10, 2023, and October 30, 2023. Thirty RCTs were selected from published systematic reviews. Main Outcomes and Measures: A structured prompt was developed to guide ChatGPT (LLM 1) and Claude (LLM 2) in assessing the ROB in these RCTs using a modified version of the Cochrane ROB tool developed by the CLARITY group at McMaster University. Each RCT was assessed twice by both models, and the results were documented. The results were compared with an assessment by 3 experts, which was considered a criterion standard. Correct assessment rates, sensitivity, specificity, and F1 scores were calculated to reflect accuracy, both overall and for each domain of the Cochrane ROB tool; consistent assessment rates and Cohen κ were calculated to gauge consistency; and assessment time was calculated to measure efficiency. Performance between the 2 models was compared using risk differences. Results: Both models demonstrated high correct assessment rates. LLM 1 reached a mean correct assessment rate of 84.5% (95% CI, 81.5%-87.3%), and LLM 2 reached a significantly higher rate of 89.5% (95% CI, 87.0%-91.8%). The risk difference between the 2 models was 0.05 (95% CI, 0.01-0.09). In most domains, domain-specific correct rates were around 80% to 90%; however, sensitivity below 0.80 was observed in domains 1 (random sequence generation), 2 (allocation concealment), and 6 (other concerns). Domains 4 (missing outcome data), 5 (selective outcome reporting), and 6 had F1 scores below 0.50. The consistent rates between the 2 assessments were 84.0% for LLM 1 and 87.3% for LLM 2. LLM 1's κ exceeded 0.80 in 7 and LLM 2's in 8 domains. The mean (SD) time needed for assessment was 77 (16) seconds for LLM 1 and 53 (12) seconds for LLM 2. Conclusions: In this survey study of applying LLMs for ROB assessment, LLM 1 and LLM 2 demonstrated substantial accuracy and consistency in evaluating RCTs, suggesting their potential as supportive tools in systematic review processes.

Personalized therapy guided by longitudinal liquid biopsies for treatment of leptomeningeal disease from lung adenocarcinoma: A case report.

Molecular-based targeted therapies have significantly benefited certain patients with cancer; however, those with leptomeningeal disease (LMD) persistently exhibit a poor prognosis and are often excluded from clinical trials. Tumor-derived cell-free (cf)DNA, found in the cerebrospinal fluid (CSF) of patients with LMD, can assist in diagnosis and tracking of disease progression. However, the utilization of CSF to direct targeted cancer therapy has yet to be extensively explored. The present study reported the case of a patient with lung adenocarcinoma and LMD who was monitored by performing a series of liquid biopsies of CSF and blood. Targeted sequencing was performed on cfDNA from the CSF and plasma, and the variant allele frequencies (VAFs) of BRAF and NRAS mutations were assessed and analyzed in conjunction with the clinical presentation of the patient. The patient then underwent serial chemotherapy, radiation therapy, immunotherapy and targeted treatment based on the results of the liquid biopsies. Upon the LMD diagnosis, a BRAF p.V600E mutation was detected in plasma cfDNA. Consequently, the patient was treated with vemurafenib and responded favorably to this consolidation treatment for 13 months. After a relapse in July 2018, both BRAF p.V600E and NRAS p.Q61K mutations were detected in CSF supernatant and sediment cell samples, suggesting drug resistance. Therefore, the treatment strategy for the patient changed to cobimetnib plus vemurafenib. Notably, the changes of VAF in the CSF supernatant samples were associated with the clinical status of the patient. The patient survived for 33 months post-LMD diagnosis. The present case report highlights the potential use of liquid biopsy in personalized therapy, as it was instrumental in informing the combinational treatment plan of the patient, which ultimately proved beneficial.

Dorsal root ganglion-derived exosomes deteriorate neuropathic pain by activating microglia via the microRNA-16-5p/HECTD1/HSP90 axis.

BACKGROUND: The activated microglia have been reported as pillar factors in neuropathic pain (NP) pathology, but the molecules driving pain-inducible microglial activation require further exploration. In this study, we investigated the effect of dorsal root ganglion (DRG)-derived exosomes (Exo) on microglial activation and the related mechanism. METHODS: A mouse model of NP was generated by spinal nerve ligation (SNL), and DRG-derived Exo were extracted. The effects of DRG-Exo on NP and microglial activation in SNL mice were evaluated using behavioral tests, HE staining, immunofluorescence, and western blot. Next, the differentially enriched microRNAs (miRNAs) in DRG-Exo-treated microglia were analyzed using microarrays. RT-qPCR, RNA pull-down, dual-luciferase reporter assay, and immunofluorescence were conducted to verify the binding relation between miR-16-5p and HECTD1. Finally, the effects of ubiquitination modification of HSP90 by HECTD1 on NP progression and microglial activation were investigated by Co-IP, western blot, immunofluorescence assays, and rescue experiments. RESULTS: DRG-Exo aggravated NP resulting from SNL in mice, promoted the activation of microglia in DRG, and increased neuroinflammation. miR-16-5p knockdown in DRG-Exo alleviated the stimulating effects of DRG-Exo on NP and microglial activation. DRG-Exo regulated the ubiquitination of HSP90 through the interaction between miR-16-5p and HECTD1. Ubiquitination alteration of HSP90 was involved in microglial activation during NP. CONCLUSIONS: miR-16-5p shuttled by DRG-Exo regulated the ubiquitination of HSP90 by interacting with HECTD1, thereby contributing to the microglial activation in NP.

Electron wave and quantum optics in graphene.

In the last decade, graphene has become an exciting platform for electron optical experiments, in some aspects superior to conventional two-dimensional electron gases (2DEGs). A major advantage, besides the ultra-large mobilities, is the fine control over the electrostatics, which gives the possibility of realising gap-less and compact p-n interfaces with high precision. The latter host non-trivial states, \eg, snake states in moderate magnetic fields, and serve as building blocks of complex electron interferometers. Thanks to the Dirac spectrum and its non-trivial Berry phase, the internal (valley and sublattice) degrees of freedom, and the possibility to tailor the band structure using proximity effects, such interferometers open up a completely new playground based on novel device architectures. In this review, we introduce the theoretical background of graphene electron optics, fabrication methods used to realise electron-optical devices, and techniques for corresponding numerical simulations. Based on this, we give a comprehensive review of ballistic transport experiments and simple building blocks of electron optical devices both in single and bilayer graphene, highlighting the novel physics that is brought in compared to conventional 2DEGs. After describing the different magnetic field regimes in graphene p-n junctions and nanostructures, we conclude by discussing the state of the art in graphene-based Mach-Zender and Fabry-Perot interferometers.

CD44v5 domain regulates crosstalk between TNBC cells and tumor-associated macrophages by enhancing the IL-4R/STAT3 axis.

Triple-negative breast cancer (TNBC) has greater infiltration of M2-like macrophages (TAMs), which enhances cancer cell invasion and leads to a poor prognosis. TNBC progression is mediated by both tumor cells and the tumor microenvironment (TME). Here we elucidate the mechanism of the interaction between TNBC cells and TAMs. In this study, we confirmed that CD44v5 is highly expressed in TNBC, which drives TNBC cell metastasis and promotes TAM polarization by co-localizing with IL4Rα and inhibiting its internalization and degradation, thereby promoting activation of the STAT3/IL6 signaling axis. At the same time, TAMs also facilitate TNBC cell metastasis by secreting IL-4, IL-6, and other cytokines, in which the IL-4/IL-4R/STAT3/IL-6 signaling axis plays the same role for TNBC cells responding to TAMs. Moreover, we found that the above progress could be suppressed when the CD44v5 domain was blocked. We demonstrated that the CD44v5/IL-4R/STAT3/IL-6 signaling pathway plays a key role in TNBC cell metastasis, and in TNBC cells inducing TAM polarization and responding to TAMs, promoting metastasis. Collectively, we suggest that the CD44v5 domain may be a promising target for regulating the TME of TNBC as well as treating TNBC.

Automated Design of Fault Diagnosis CNN Network for Satellite Attitude Control Systems.

Despite the dominance of unsupervised and self-supervised anomaly detection methods in the current satellite fault diagnosis domain, supervised anomaly detection offers a superior alternative for high-sensitivity detection and lightweight deployment requirements specific to subsystems or components, such as attitude control systems (ACSs). This article addresses the issues of over-design and insufficient accuracy in the CNN network design for satellite ACS fault diagnosis by introducing the modified particle swarm optimization-advanced convolution blocks-based CNN (MPSO-ACBCNN) method. First, we present the ACBCNN, a lightweight, flexible-layer CNN architecture. This architecture leverages advanced convolution blocks (ACBs), which incorporate numerous efficient design elements to enhance feature extraction capabilities within power spectral density (PSD) graphs of various fault samples, and employs classical dense connection methods to prevent the issue of gradient vanishing. Second, we devise the MPSO-ACBCNN algorithm to optimize the ACBCNN fault diagnosis architecture for specified ACS using MPSO. In MPSO-ACBCNN, several optimizations to the canonical PSO are implemented, including the fitness design that balances the tradeoff between total parameter quantity and the training effectiveness, and methods to ensure feasible solutions, etc. Finally, numerical experimental results demonstrate the effectiveness and superiority of MPSO-ACBCNN in fault diagnosis for ACS.