Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA.

Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.

Resistance Risk and Molecular Mechanism of Tomato Wilt Pathogen Fusarium oxysporum f. sp. lycopersici to Pyraclostrobin.

Tomato wilt disease caused by Fusarium oxysporum f. sp. lycopersici (Fol) results in a decrease in tomato yield and quality. Pyraclostrobin, a typical quinone outside inhibitor (QoI), inhibits the cytochrome bc1 complex to block energy transfer. However, there is currently limited research on the effectiveness of pyraclostrobin against Fol. In this study, we determined the activity of pyraclostrobin against Fol and found the EC50 values for pyraclostrobin against 100 Fol strains (which have never been exposed to QoIs before). The average EC50 value is 0.3739 ± 0.2413 µg/mL, indicating a strong antifungal activity of pyraclostrobin against Fol, as shown by unimodal curves of the EC50 values. Furthermore, we generated five resistant mutants through chemical taming and identified four mutants with high-level resistance due to the Cytb-G143S mutation and one mutant with medium-level resistance due to the Cytb-G137R mutation. The molecular docking results indicate that the Cytb-G143S or Cytb-G137R mutations of Fol lead to a change in the binding mode of Cytb to pyraclostrobin, resulting in a decrease in affinity. The resistant mutants exhibit reduced fitness in terms of mycelial growth (25 and 30 °C), virulence, and sporulation. Moreover, the mutants carrying the Cytb-G143S mutation suffer a more severe fitness penalty compared to those carrying the Cytb-G137R mutation. There is a positive correlation observed among azoxystrobin, picoxystrobin, fluoxastrobin, and pyraclostrobin for resistant mutants; however, no cross-resistance was detected between pyraclostrobin and pydiflumetofen, prochloraz, or cyazofamid. Thus, we conclude that the potential risk of resistance development in Fol toward pyraclostrobin can be categorized as ranging from low to moderate.

Analyzing lung cancer risks in patients with impaired pulmonary function through characterization of gut microbiome and metabolites.

BACKGROUND: Lung cancer (LC) is one of the most devastating diseases worldwide, there is growing studies confirm the role of impaired lung function in LC susceptibility. Moreover, gut microbiota dysbiosis is associated with LC severity. Whether alterations in gut microbiota and metabolites are associated with long-term lung dysfunction in LC patients remain unclear. Our study aimed to analyze the risk factors in LC patients with impaired pulmonary function based on the characteristics of the gut microbiome and metabolites. METHODS: Fecal samples from 55 LC patients and 28 benign pulmonary nodules patients were collected. Pulmonary ventilation function was graded according to the American Thoracic Society/ European Respiratory Society (ATS/ERS) method. LC patients were divided into 3 groups, including 20 patients with normal lung ventilation, 23 patients with mild pulmonary ventilation dysfunction and 12 patients with moderate or above pulmonary ventilation dysfunction. The fecal samples were analyzed using 16 S rRNA gene amplicon sequencing and metabolomics. RESULTS: The gut microbiome composition between LC patients and benign pulmonary nodules patients presented clearly differences based on Partial Least Squares Discriminant Analysis (PLS-DA). Pulmonary ventilation function was positively correlated with LC tumor stage, the richness and diversity of the gut microbiota in LC patients with moderate or above pulmonary ventilation dysfunction increased significantly, characterized by increased abundance of Subdoligranulum and Romboutsia. The metabolomics analysis revealed 69 differential metabolites, which were mainly enriched in beta-Alanine metabolism, styrene degradation and pyrimidine metabolism pathway. The area under the curve (AUC) combining the gut microbiome and metabolites was 90% (95% CI: 79-100%), indicating that the two species and four metabolites might regarded as biomarkers to assess the prediction of LC patients with impaired pulmonary function. CONCLUSIONS: Our results showed that microbiome and metabolomics analyses provide important candidate to be used as clinically diagnostic biomarkers and therapeutic targets related to lung cancer with impaired pulmonary function.

The Effect of Nationwide Organized Cancer Screening Programs on Gastric Cancer Mortality: A Synthetic Control Study.

BACKGROUND & AIMS: Nationwide organized gastric cancer (GC) screening programs have been running for decades in South Korea and Japan. This study conducted a quasi-experimental analysis to assess the population impact of these programs on GC mortality. METHODS: We used the flexible synthetic control method (SCM) to estimate the effect of the screening programs on age-standardized GC mortality and other upper gastrointestinal (UGI) diseases (esophageal cancer and peptic ulcer) among people aged ≥40 years. World Health Organization mortality data and country-level covariates from the World Bank and the Global Burden of Diseases study were used for the analyses. We compared postintervention trends in outcome with the counterfactual trend of the synthetic control and estimated average postintervention rate ratios (RRs) with associated 95% confidence intervals (CIs). A series of sensitivity analyses were conducted. RESULTS: The preintervention fits were acceptable for the analyses of South Korea and Japan's GC mortality but poor for Japan's other UGI disease mortality. The average postintervention RRs were 0.83 (95% CI, 0.71-0.96) for GC mortality and 0.72 (95% CI, 0.57-0.90) for other UGI disease mortality in South Korea. The RR reached 0.59 by the 15th year after the initiation of nationwide screening. For Japan, the average RRs were 0.97 (95% CI, 0.88-1.07) for GC mortality and 0.93 (95% CI, 0.68-1.28) for other UGI disease mortality. Sensitivity analysis reveals the result for Japan may potentially be biased. CONCLUSIONS: South Korea's nationwide GC screening has apparent benefits, whereas the Japanese program's effectiveness is uncertain. The experiences of South Korea and Japan could serve as a reference for other countries.

Changes in serum levels of pain mediators in hemiplegic shoulder pain.

OBJECTIVE: To provide a new insight into the diagnosis and treatment of hemiplegic shoulder pain (HSP) by investigating changes in serum pain mediators. DESIGN: Cross-sectional study. SUBJECTS/PATIENTS: Shoulder pain group (n = 34) and control group (n = 21). METHODS: Pain-free shoulder mobility, anxiety status, depression status, and shoulder pain were measured by passive range of motion (PROM), self-rating anxiety scale, self-rating depression scale (SDS), and visual analog scale, respectively. The enzyme-linked immunosorbent assay was used to test the serum pain mediators, including interleukin (IL)-1ß, IL-2, IL-6, IL-10, nerve growth factor (NGF), tumor necrosis factor-α (TNF-α), substance P (SP), calcitonin gene-related peptide (CGRP), bradykinin (BK), 5-hydroxytryptamine (5-HT), prostaglandin E2 (PGE2), and lysophosphatidic acid (LPA). RESULTS: Shoulder pain group pain-free PROM significantly lower than control (p < .01), and SDS index score of shoulder pain group was significantly higher than control (p < .05). The rate of spasticity in the flexor elbow muscles is higher in shoulder pain group (p < .01). CGRP, IL-10, and IL-2 were significantly upregulated in shoulder pain group compared with control (p < .01), whereas NGF, TNF-α, IL-6, 5-HT, PGE2, SP, LPA, BK, and IL-1ß were significantly decreased (p < .01). CONCLUSION: Patients with HSP have a higher risk of joint mobility disorders and depression; spasticity may be an important factor in the development of shoulder pain; CGRP is thought to be the major pain mediator in HSP, and HSP may not be inflammatory.

Autonomous motion and control of lower limb exoskeleton rehabilitation robot.

Introduction: The lower limb exoskeleton rehabilitation robot should perform gait planning based on the patient's motor intention and training status and provide multimodal and robust control schemes in the control strategy to enhance patient participation. Methods: This paper proposes an adaptive particle swarm optimization admittance control algorithm (APSOAC), which adaptively optimizes the weights and learning factors of the PSO algorithm to avoid the problem of particle swarm falling into local optimal points. The proposed improved adaptive particle swarm algorithm adjusts the stiffness and damping parameters of the admittance control online to reduce the interaction force between the patient and the robot and adaptively plans the patient's desired gait profile. In addition, this study proposes a dual RBF neural network adaptive sliding mode controller (DRNNASMC) to track the gait profile, compensate for frictional forces and external perturbations generated in the human-robot interaction using the RBF network, calculate the required moments for each joint motor based on the lower limb exoskeleton dynamics model, and perform stability analysis based on the Lyapunov theory. Results and discussion: Finally, the efficiency of the APSOAC and DRNNASMC algorithms is demonstrated by active and passive walking experiments with three healthy subjects, respectively.

Highly hydrostable and flexible opal photonic crystal film for enhanced up-conversion fluorescence sensor of COVID-19 antibody.

Efficient detection of related markers is significant for the early screening of COVID-19. Near infrared (NIR) light excited up-conversion fluorescence probes are ideal for biosensing but limited by the low luminescence efficiency. In this work, a novel highly stable opal photonic crystal (OPC) structure was designed to provide an OPC effect for up-conversion fluorescence enhancement, and sensitive Novel Coronavirus IgG up-conversion FRET-based sensor was further constructed. For the problems of water stability and mechanical stability of polymer OPC which cannot be solved for a long time, polymer spray combined with a flipped OPC film strategy is presented. Fragmented size OPC film was firmly fixed by polymer modification layer, which gave large size OPC film great water stability, mechanical stability and bending performance without affecting the fluorescence enhancement property. On this basis, the up-conversion emission intensity was enhanced significantly, and fluorescence resonant energy transfer (FRET) based Novel Coronavirus IgG antibody sensor was constructed. Monolayer up-conversion nanoparticles (UCNPs) on the surface of the polydopamine (PDA)/OPC film can make the fluorescent signal more sensitive, and effectively reduce the detection limit. The test device integrating NIR excitation and mobile phone realized the visual fast detection, showing remarkable sensing performance for COVID-19 antibodies with the limit of detection (LOD) of 0.1 ng mL-1. This detection platform will provide a more effective tool for early detection of the novel coronavirus.

Comparison of 3 CT Perfusion Software Packages in Estimation of Ischemic Lesions in Acute Ischemic Stroke Patients.

OBJECTIVE: The aim of this study was to compare 3 computed tomography perfusion (CTP) software packages in the estimation of infarct core volumes, hypoperfusion volumes, and mismatch volumes. METHODS: Forty-three patients with large vessel occlusion in the anterior circulation who underwent CTP imaging were postprocessed by 3 software packages: RAPID, advantage workstation (AW), and NovoStroke Kit (NSK). Infarct core volumes and hypoperfusion volumes were generated by RAPID with default settings. The AW and NSK threshold settings were the following: infarct core (cerebral blood flow [CBF] <8 mL/min/100 g, CBF <10 mL/min/100 g, CBF <12 mL/min/100 g, and cerebral blood volume [CBV] <1 mL/100 g) and hypoperfusion (T max >6 seconds). Mismatch volumes were then obtained for all the combinations of the settings. Bland-Altman, intraclass correlation coefficient (ICC), and Spearman ρ or Pearson correlation coefficient were applied for statistical analysis. RESULTS: In the estimation of infarct core volumes, good agreement was observed between AW and RAPID when CBV <1 mL/100 g (ICC, 0.767; P < 0.001). For hypoperfusion volumes, good agreement (ICC, 0.811; P < 0.001) and strong correlation ( r = 0.856; P < 0.001) were observed between NSK and RAPID. For mismatch volumes, the setting of CBF <10 mL/min/100 g combined with hypoperfusion with NSK resulted in moderate agreement (ICC, 0.699; P < 0.001) with RAPID, which was the best among all other settings. CONCLUSIONS: The estimation results varied among different software packages. Advantage workstation had the best agreement with RAPID in the estimation of infarct core volumes when CBV <1 mL/100 g. NovoStroke Kit had better agreement and correlation with RAPID in the estimation of hypoperfusion volumes. NovoStroke Kit also had moderate agreement with RAPID in estimating mismatch volumes.

Role of nano-hydrogels coated exosomes in bone tissue repair.

With the development of nanotechnology, nanomaterials are widely applied in different areas. Some nanomaterials are designed to be biocompatible and can be used in the medical field, playing an important role in disease treatment. Exosomes are nanoscale vesicles with a diameter of 30-200 nm. Studies have shown that exosomes have the effect of angiogenesis, tissue (skin, tendon, cartilage, et al.) repair and reconstruction. Nano-hydrogels are hydrogels with a diameter of 200 nm or less and can be used as the carrier to transport the exosomes into the body. Some orthopedic diseases, such as bone defects and bone infections, are difficult to handle. The emergence of nano-hydrogels coated exosomes may provide a new idea to solve these problems, improving the prognosis of patients. This review summarizes the function of nano-hydrogels coated exosomes in bone tissue repair, intending to illustrate the potential use and application of nano-hydrogels coated exosomes in bone disease.

Novel fast FFR derived from coronary CT angiography based on static first-pass algorithm: a comparison study.

BACKGROUND: Fractional flow reserve (FFR) is the invasive gold standard for evaluating coronary arterial stenosis. However, there have been a few non-invasive methods such as computational fluid dynamics FFR (CFD-FFR) with coronary CT angiography (CCTA) images that can perform FFR assessment. This study aims to develop a new method based on the principle of static first-pass of CT perfusion imaging technique (SF-FFR) and evaluate the efficacy in direct comparisons between CFD-FFR and the invasive FFR. METHODS: A total of 91 patients (105 coronary artery vessels) who were admitted from January 2015 to March 2019 were enrolled in this study, retrospectively. All patients underwent CCTA and invasive FFR. 64 patients (75 coronary artery vessels) were successfully analyzed. The correlation and diagnostic performance of SF-FFR method on per-vessel basis were analyzed, using invasive FFR as the gold standard. As a comparison, we also evaluated the correlation and diagnostic performance of CFD-FFR. RESULTS: The SF-FFR showed a good Pearson correlation (r = 0.70, P < 0.001) and intra-class correlation (r = 0.67, P < 0.001) with the gold standard. The Bland-Altman analysis showed that the average difference between the SF-FFR and invasive FFR was 0.03 (0.11-0.16); between CFD-FFR and invasive FFR was 0.04 (-0.10-0.19). Diagnostic accuracy and area under the ROC curve on a per-vessel level were 0.89, 0.94 for SF-FFR, and 0.87, 0.89 for CFD-FFR, respectively. The SF-FFR calculation time was about 2.5 s per case while CFD calculation was about 2 min on an Nvidia Tesla V100 graphic card. CONCLUSIONS: The SF-FFR method is feasible and shows high correlation compared to the gold standard. This method could simplify the calculation procedure and save time compared to the CFD method.

Opal photonic crystal-enhanced upconversion turn-off fluorescent immunoassay for salivary CEA with oral cancer.

The point-of-care test of tumor markers in saliva with high specificity and sensitivity for early diagnosis of oral cancer is of great interest and significance, but remaining a daunting challenge due to the low concentration of such biomarkers in oral fluid. Herein, a turn-off biosensor based on opal photonic crystal (OPC) enhanced upconversion fluorescence is proposed to detect the carcinoembryonic antigen (CEA) in saliva by applying fluorescence resonance energy transfer sensing strategy. Hydrophilic PEI ligands are modified on upconversion nanoparticles to enhance the sensitivity of biosensor by promoting sufficient contact between saliva and detection region. As a substrate for the biosensor, OPC can also provide a local-field effect for greatly enhanced upconversion fluorescence by coupling the stop band and excitation light, and a 66-fold amplification of the upconversion fluorescence signal was obtained. For the CEA detection in spiked saliva, such sensors showed a favorable linear relationship at 0.1-2.5 ng mL-1 and more than 2.5 ng mL-1, respectively. The limit of detection was down to 0.1 ng mL-1. Moreover, by monitoring real saliva, the effective discrepancy between patients and healthy people was confirmed, indicating remarkable practical application value in clinical early diagnosis and home-based self-monitoring of tumors.

Feature Pyramid Networks and Long Short-Term Memory for EEG Feature Map-Based Emotion Recognition.

The original EEG data collected are the 1D sequence, which ignores spatial topology information; Feature Pyramid Networks (FPN) is better at small dimension target detection and insufficient feature extraction in the scale transformation than CNN. We propose a method of FPN and Long Short-Term Memory (FPN-LSTM) for EEG feature map-based emotion recognition. According to the spatial arrangement of brain electrodes, the Azimuth Equidistant Projection (AEP) is employed to generate the 2D EEG map, which preserves the spatial topology information; then, the average power, variance power, and standard deviation power of three frequency bands (α, ß, and γ) are extracted as the feature data for the EEG feature map. BiCubic interpolation is employed to interpolate the blank pixel among the electrodes; the three frequency bands EEG feature maps are used as the G, R, and B channels to generate EEG feature maps. Then, we put forward the idea of distributing the weight proportion for channels, assign large weight to strong emotion correlation channels (AF3, F3, F7, FC5, and T7), and assign small weight to the others; the proposed FPN-LSTM is used on EEG feature maps for emotion recognition. The experiment results show that the proposed method can achieve Value and Arousal recognition rates of 90.05% and 90.84%, respectively.

Integrated dual-channel electrochemical immunosensor for early diagnosis and monitoring of periodontitis by detecting multiple biomarkers in saliva.

Periodontitis, as the sixth prevalence chronic inflammation worldwide, has inconspicuous and often-overlooked symptoms at early stage, eventually leading to permanent damage to the teeth and supporting tissues. The timely and accurate diagnosis of periodontitis and monitoring its progress appear to be particularly important for clinical treatment. Herein, a dual-channel electrochemical immunosensor was developed for the synchronized detection of two periodontitis-related biomarkers in saliva: interleukin-1ß (IL-1ß) and matrix metalloproteinase-8 (MMP-8). Owing to its miniaturization, detachability, and portability, this sensor has the potential to detect multiple biomarkers in a point-of-care manner for the early diagnosis and monitoring of periodontitis. The nanocomposites consisted of iridium oxide nanotubes and two-dimensional MXene nanosheets enhance the electrochemical performance of the sensor, achieving excellent sensitivity with wide detection ranges of 0.1-100 and 1-200 ng mL-1, low limits of detection of 0.014 and 0.13 ng mL-1, and relatively high correlation coefficients of 0.9911 and 0.9990 for IL-1ß and MMP-8, respectively. Furthermore, this device possesses excellent selectivity in complex samples without cross-talk, as well as high recovery and accuracy in spiked artificial saliva. Importantly, the dual-channel device achieves higher diagnostic accuracy for different stages of periodontitis when MMP-8 and IL-1ß were simultaneously monitored within clinicopathological saliva. This work proposes a considerable potential for early diagnosis and severity distinguishment of periodontitis in a point-of-care manner, which would be beneficial for progression prediction, treatment guidance, and prognosis assessment of periodontitis.

Strongly-adhesive easily-detachable carboxymethyl cellulose aerogel for noncompressible hemorrhage control.

Hemostats that can strongly adhere to wound tissue and are easy to remove when stopping bleeding are favored for the control of noncompressible hemorrhage. Here, we prepared a citric acid (CA)-crosslinked and N-hydroxysuccinimide (NHS) ester-activated carboxymethyl cellulose (CMC-NHS) aerogel for noncompressible hemostasis. CA was used to crosslink CMC to form a strengthened structure. NHS ester was introduced to activate the adhesion of CMC-NHS aerogel to wound tissue and promoted blood coagulation through the formation of amide crosslinks between CMC and erythrocytes and free blood proteins. The plentiful carboxyl groups could also trigger the intrinsic coagulation pathway. Thus, the aerogel could quickly adhere to wound tissue to stop bleeding, and then could be easily removed when fully hydrated as CMC was dissolved at the adhesion interface. The aerogel also had good biocompatibility and antibacterial capability. Overall, CMC-NHS aerogel is a competitive hemostat for the control of noncompressible hemorrhage.

Automated ASPECTS in acute ischemic stroke: comparison of the overall scores and Hounsfield unit values of two software packages and radiologists with different levels of experience.

BACKGROUND: ASPECTS is a simple, rapid, and semi-quantitative method for detecting early ischemic changes (EIC). However, the agreement between software applications and neuroradiologists varies greatly. PURPOSE: To compare ASPECTS calculated by using automated software tools to neuroradiologists evaluation in patients with acute ischemic stroke (AIS). MATERIAL AND METHODS: Retrospectively, 61 patients with large vessel occlusion (LVO) who underwent multimodal stroke computed tomography (CT) were evaluated using two automated ASPECTS software tools (NSK and RAPID) and three neuroradiologists with different experiences (two senior neuroradiologists and one junior neuroradiologist). Four weeks later, the same three neuroradiologists re-evaluated the ASPECTS in consensus using the baseline CT and follow-up non-contrast CT (NCCT). Interclass correlation coefficients (ICCs) and Pearson correlation coefficients were applied for statistical analysis. RESULTS: The HU value exhibited the greatest correlation in the insular lobe (r = 0.81; P < 0.001) and the lowest correlation in the internal capsule (r = 0.65; P < 0.001) between NSK and RAPID. Software analysis and human readers showed excellent agreement with the consensus reading. Compared with the consensus reading, the correlation of the two senior radiologists (ICC = 0.975 and 0.969, respectively) were higher than that of junior radiologist (ICC = 0.869), and the consistency values of the NSK and RAPID software tools after 6 h of onset to imaging (ICC = 0.894 and 0.874, respectively) were greater than those within 6 h of onset (ICC = 0.746 and 0.828, respectively). CONCLUSION: For patients experiencing AIS due to LVO, the ASPECTS calculated with automated software agrees well with the predefined consensus score but is inferior to that of senior radiologists.

Characterizing microbiota and metabolomics analysis to identify candidate biomarkers in lung cancer.

Background: Lung cancer is the leading malignant disease and cause of cancer-related death worldwide. Most patients with lung cancer had insignificant early symptoms so that most of them were diagnosed at an advanced stage. In addition to factors such as smoking, pollution, lung microbiome and its metabolites play vital roles in the development of lung cancer. However, the interaction between lung microbiota and carcinogenesis is lack of systematically characterized and controversial. Therefore, the purpose of this study was to excavate the features of the lung microbiota and metabolites in patients and verify potential biomarkers for lung cancer diagnosis. Methods: Lung tissue flushing solutions and bronchoalveolar lavage fluid samples came from patients with lung cancer and non-lung cancer. The composition and variations of the microbiota and metabolites in samples were explored using muti-omics technologies including 16S rRNA amplicon sequencing, metagenomics and metabolomics. Results: The metabolomics analysis indicated that 40 different metabolites, such as 9,10-DHOME, sphingosine, and cysteinyl-valine, were statistically significant between two groups (VIP > 1 and P < 0.05). These metabolites were significantly enriched into 11 signal pathways including sphingolipid, autophagy and apoptosis signaling pathway (P < 0.05). The analysis of lung microbiota showed that significant changes reflected the decrease of microbial diversity, changes of distribution of microbial taxa, and variability of the correlation networks of lung microbiota in lung cancer patients. In particular, we found that oral commensal microbiota and multiple probiotics might be connected with the occurrence and progression of lung cancer. Moreover, our study found 3 metabolites and 9 species with significantly differences, which might be regarded as the potential clinical diagnostic markers associated with lung cancer. Conclusions: Lung microbiota and metabolites might play important roles in the pathogenesis of lung cancer, and the altered metabolites and microbiota might have the potential to be clinical diagnostic markers and therapeutic targets associated with lung cancer.

Alignment analysis of Brainlab knee 3 navigation-guided total knee arthroplasty using the adjusted mechanical method.

Purpose: With the application of navigation technology in Total Knee Arthroplasty (TKA), TKA procedures have become various. Studies have shown that navigation can improve the alignment of patients' lower limbs. To verify this conclusion, we collected the clinical data from patients who underwent Brainlab knee 3 navigation-guided TKA. Brainlab knee 3 is a completely new software that takes a different approach to address the current challenges of navigated TKA. During the procedure, we applied the Adjusted Mechanical Alignment (AMA) principle and took soft tissue balance as a priority. We aim to explore the patients' lower limb alignment changes who underwent the Brainlab knee 3 navigation-guided TKA using the AMA method. Methods: Fifty consecutive patients who underwent total knee arthroplasty using the Brainlab knee3 knee navigation system (Smith&Nephew) from January to August 2021 by the same doctor (Yunsu Chen) in the Department of Joint Surgery of the Shanghai Sixth People's Hospital were included. Hip-Knee-Ankle Angle (HKAA), anatomic Femur Tibia Angle (FTA), Lateral Distal Femoral Angle (LDFA), and medial proximal tibia angle (MPTA) were measured on preoperative and postoperative full-length lower-limbs x-ray films or weight-bearing anterior and lateral knee radiographs for observational and descriptive study. The preoperative and postoperative knee alignment changes were analyzed through paired t-test or nonparametric Wilcoxon test using SPSS 25.0 software. Results: Pre-operative and post-operative HKAA both obeyed normal distribution. The mean preoperative HKAA was 169.8° (154.9-178.7°) with a standard deviation of 5.41; the postoperative HKAA was 175.7° (168.4-180.0°) with a standard deviation of 2.81. Using the two-sample paired t-test to analyze, the result showed P = 0.000 < 0.05; a statistically significant difference exists. The preoperative and postoperative FTA obeyed normal distribution as well. The mean preoperative FTA was 174.7° (163.4-179.9°) with a standard deviation of 3.90; postoperative 175.6° (167.0-179.9°) with a standard deviation of 2.77. Using the two-sample paired t-test to analyze, the result showed P = 0.140 > 0.05, the difference was not statistically significant. The preoperative LDFA was normally distributed, while postoperative LDFA was not. The mean preoperative LDFA was 90.7° (83.5-99.6°) with a standard deviation of 3.83; the median of postoperative LDFA was 91.6° (86.0-103.2°) with an interquartile range of 2.93. Using the two-sample paired Wilcoxon test, the result showed P = 0.052 > 0.05; the difference was not statistically significant. Preoperative MPTA obeyed normal distribution, while postoperative MPTA did not. The mean preoperative MPTA was 83.5° (72.7-92.9°), with a standard deviation of 3.66; the median of postoperative MPTA was 89.3° (84.6-95.6°), with an interquartile range of 1.45. Using the two-sample paired Wilcoxon test, the result shows P = 0.000 < 0.05; a statistically significant difference exists. Conclusion: In our study, AMA alignment was applied in Brainlab Knee3 computer navigation-assisted total knee arthroplasty. The femoral and tibial osteotomy angles were minimally adjusted according to soft tissue situations to reduce soft tissue release. We found AMA alignment provides good control of knee alignment in the coronal plane of the lower limbs, which is a reliable technique.

Screening of dopamine in living cells and animal model via graphene quantum dots anchored 3D macroporous nonenzymatic sensor.

A series of three-dimensional copper oxide (CuO) inverse opals anchored with carboxylated graphene quantum dots (CuO/cGQDs) have been fabricated for non-enzymatic tracking of dopamine (DA). Heterostructures composed of various building blocks are promising to construct versatile biosensing platforms. The optimal CuO/cGQDs modified electrode demonstrates sensitivities of 243.45 µA mM-1 cm-2 (50 nM-1888.5 µM) with the practical detection limit as low as 0.5 nM in mimic physiological environment (at + 0.45 V vs. Ag/AgCl). The extraordinary tolerance to various interferents enables the practical detection of intracellular DA amount in human neural cells. On this basis, the proposed biosensor attains precise evaluation of antipsychotic drug effects on stimulated DA release. Particularly, it successfully spots fluctuation of DA in plasma and cerebrospinal fluid in murine model of Parkinson's disease, which serves as a crucial tool to understand neuropathology and symptomatology of DA-related diseases. This study developed a reliable sensing platform and is expected to be applied to physiological and pathological studies.

Two-dimensional Ti3C2Tx MXene promotes electrophysiological maturation of neural circuits.

BACKGROUND: The ideal neural interface or scaffold for stem cell therapy shall have good biocompatibility promoting survival, maturation and integration of neural stem cells (NSCs) in targeted brain regions. The unique electrical, hydrophilic and surface-modifiable properties of Ti3C2Tx MXene make it an attractive substrate, but little is known about how it interacts with NSCs during development and maturation. RESULTS: In this study, we cultured NSCs on Ti3C2Tx MXene and examined its effects on morphological and electrophysiological properties of NSC-derived neurons. With a combination of immunostaining and patch-clamp recording, we found that Ti3C2Tx MXene promotes NSCs differentiation and neurite growth, increases voltage-gated current of Ca2+ but not Na+ or K+ in matured neurons, boosts their spiking without changing their passive membrane properties, and enhances synaptic transmission between them. CONCLUSIONS: These results expand our understanding of interaction between Ti3C2Tx MXene and NSCs and provide a critical line of evidence for using Ti3C2Tx MXene in neural interface or scaffold in stem cell therapy.