Targeted multiplex validation of CSF proteomic biomarkers: implications for differentiation of PCNSL from tumor-free controls and other brain tumors.

Introduction: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin's lymphoma that affects brain parenchyma, eyes, cerebrospinal fluid, and spinal cord. Diagnosing PCNSL can be challenging because imaging studies often show similar patterns as other brain tumors, and stereotactic brain lesion biopsy conformation is invasive and not always possible. This study aimed to validate a previous proteomic profiling (PMID: 32610669) of cerebrospinal fluid (CSF) and develop a CSF-based proteomic panel for accurate PCNSL diagnosis and differentiation. Methods: CSF samples were collected from patients of 30 PCNSL, 30 other brain tumors, and 31 tumor-free/benign controls. Liquid chromatography tandem-mass spectrometry targeted proteomics analysis was used to establish CSF-based proteomic panels. Results: Final proteomic panels were selected and optimized to diagnose PCNSL from tumor-free controls or other brain tumor lesions with an area under the curve (AUC) of 0.873 (95%CI: 0.723-0.948) and 0.937 (95%CI: 0.807- 0.985), respectively. Pathways analysis showed diagnosis panel features were significantly enriched in pathways related to extracellular matrices-receptor interaction, focal adhesion, and PI3K-Akt signaling, while prion disease, mineral absorption and HIF-1 signaling were significantly enriched with differentiation panel features. Discussion: This study suggests an accurate clinical test panel for PCNSL diagnosis and differentiation with CSF-based proteomic signatures, which may help overcome the challenges of current diagnostic methods and improve patient outcomes.

Quantitative Flow Ratio-Derived Index of Microcirculatory Resistance as a Novel Tool to Identify Microcirculatory Function in Patients with Ischemia and No Obstructive Coronary Artery Disease.

BACKGROUND: Coronary microvascular disease (CMVD) is associated with adverse cardiovascular outcomes. However, there is no reliable and noninvasive quantitative diagnostic method available for CMVD. The use of a pressure wire to measure the index of microcirculatory resistance (IMR) is possible, but it has inevitable practical restrictions. We hypothesized that computation of the quantitative flow ratio could be used to predict CMVD with symptoms of ischemia and no obstructive coronary artery disease (INOCA). METHODS: We retrospectively assessed the diagnostic efficiency of the quantitative flow ratio-derived index of microcirculatory resistance (QMR) in 103 vessels from 66 patients and compared it with invasive IMR using the thermodilution technique. RESULTS: Patients were divided into the CMVD group (41/66, 62.1%) and non-CMVD group (25/66, 37.9%). Pressure wire IMR measurements were made in 103 coronary vessels, including 44 left descending arteries, 18 left circumflex arteries, and 41 right coronary arteries. ROC curve analysis showed a good diagnostic performance of QMR for all arteries (area under the curve = 0.820, 95% confidence interval 0.736-0.904, p < 0.001) in predicting microcirculatory function. The optimal cut-off for QMR to predict microcirculatory function was 266 (sensitivity: 82.9%, specificity: 72.6%, and diagnostic accuracy: 76.7%). CONCLUSION: QMR is a promising tool for the assessment of coronary microcirculation. The assessment of the IMR without the use of a pressure wire may enable more rapid, convenient, and cost-effective assessment of coronary microvascular function.

Efficacy of a novel glioma therapy based on ferroptosis induced by layered double hydroxide loaded with simvastatin.

Glioma is the most common primary malignant tumor of the nervous system that starts in the glial cells. Its high invasiveness and recurrence pose major challenges to its effective treatment. Ferroptosis is a new type of programmed cell death characterized by intracellular iron overload and accumulation of lipid peroxides. Existing studies have demonstrated the efficacy of targeted ferroptosis therapy in the treatment of glioma. In this study, folic acid (FA)-modified layered double hydroxide loaded with simvastatin (SIM), a ferroptosis drug, was used to prepare a novel ferroptosis nanodrug (FA-LDH@SIM). The prepared nanodrug improved the therapeutic effect of SIM on glioma. Compared with free SIM, FA-LDH@SIM showed greater cytotoxicity, significantly inhibited glioma cell proliferation, and significantly inhibited glioma invasion and migration ability. Furthermore, SIM could induce changes in certain ferroptosis indicators, including increased intracellular LPO, ROS and MDA level, decreased GSH production, increased divalent iron level, and changes in mitochondrial morphology. Further experiments revealed that SIM induced ferroptosis in tumor cells by down-regulating HMGCR expression and inhibiting the mevalonate pathway to down-regulate GPX4 expression. In addition, the FA-LDH@SIM group significantly inhibited tumor growth after treatment in the animal glioma model. These results indicate that the FA-LDH@SIM nanodrug delivery system exhibits excellent anti-tumor effects both in vitro and in vivo, and is an effective method for the treatment of glioma.

Functionalized nanoparticles crossing the brain-blood barrier to target glioma cells.

Glioma is the most common tumor of the central nervous system (CNS), with a 5-year survival rate of <35%. Drug therapy, such as chemotherapeutic and immunotherapeutic agents, remains one of the main treatment modalities for glioma, including temozolomide, doxorubicin, bortezomib, cabazitaxel, dihydroartemisinin, immune checkpoint inhibitors, as well as other approaches such as siRNA, ferroptosis induction, etc. However, the filter function of the blood-brain barrier (BBB) reduces the amount of drugs needed to effectively target CNS tumors, making it one of the main reasons for poor drug efficacies in glioma. Thus, finding a suitable drug delivery platform that can cross the BBB, increase drug aggregation and retainment in tumoral areas and avoid accumulation in non-targeted areas remains an unsolved challenge in glioma drug therapy. An ideal drug delivery system for glioma therapy should have the following features: (1) prolonged drug life in circulation and effective penetration through the BBB; (2) adequate accumulation within the tumor (3) controlled-drug release modulation; (4) good clearance from the body without significant toxicity and immunogenicity, etc. In this regard, due to their unique structural features, nanocarriers can effectively span the BBB and target glioma cells through surface functionalization, providing a new and effective strategy for drug delivery. In this article, we discuss the characteristics and pathways of different nanocarriers for crossing the BBB and targeting glioma by listing different materials for drug delivery platforms, including lipid materials, polymers, nanocrystals, inorganic nanomaterials, etc.

A novel suture bridge anchor fixation technique to treat inferior pole fractures of patella: A retrospective clinical study.

The traditional surgical methods to the fracture of the inferior patellar fracture include steel wire tension band fixation and inferior patellar resection, which have many disadvantages. In order to overcome the disadvantages of traditional surgery, we innovated and improved the double row anchor suture bridge technology to the treat the inferior patellar fracture. This study is to investigate the method, technique and clinical efficacy of double-row anchor suture bridge technique in the treatment of inferior pole fractures of patella. Between January 2019 and March 2021, 36 patients with inferior pole fractures of patella underwent the surgery with the double-row anchor suture bridge technique. 28 injury cases were caused by falls while 8 injury cases were from car crashes. The operation time, amount of intraoperative bleeding and complications were recorded. Radiological assessments and Bostman score were performed 1, 3, and 6 months post-operation and at the most recent follow-ups. The study sample consisted of 19 males and 17 females, aged 31 to 72 years old. The operation time was (54-76) minutes. All incisions healed in 1 stage. No complications such as incision infection, flap necrosis and nerve injury occurred. Patients in this group were followed up for 10 to 18 months, with an average follow-up of 12 months. All fractures healed in 10 to 20 weeks, with an average healing time of 12 weeks. At the last follow-up, the Bostman score was (27.5 ± 3.3), excellent in 32 cases and good in 2 cases, with an excellent rate of 94.4%. The range of motion of the knee joint was (-2.6 ± 2.0)° when the knee was extended and (122 ± 5.0)° when the knee was bent. The muscle strength of quadriceps femoris was grade 5. Double-row anchor suture bridge technique is applied to inferior pole fractures of patella by virtue of its various effects, such as the complete preservation of the inferior pole fragments during the operation, satisfactory fracture reduction, firm fixation, and meeting patients' requirements for early postoperative ambulation. In summary, double-row anchor suture bridge technique is an ideal surgical procedure for the treatment of the inferior pole fracture of patella with safety, reliability and high satisfaction.

Sestrin2 levels in patients with anxiety and depression myocardial infarction was up-regulated and suppressed inflammation and ferroptosis by LKB1-mediated AMPK activation.

Although great progress has been made in the diagnosis and treatment of acute myocardial infarction (AMI) in recent years, its morbidity and mortality are still relatively high. In this study, we explain that the function of Sestrin2 gene in Anxiety and Depression Myocardial infarction and its possible mechanism. 26 patients with Anxiety and Depression Myocardial infarction (ADMI) and 26 normal volunteers were collected from our hospital. All mice anaesthetized using 50 mg/kg of pentobarbital sodium and the left anterior descending arteries (LAD) were ligated to induce myocardial infarction. H9c2 cells were stimulated with 5% oxygen (O2) and 5% carbon dioxide (CO2) and 90% N2 for 24 h. The serum expression of Sestrin2 in patients with ADMI was up-regulated. Sestrin2 gene up-regulation reduced collagen I/II and KEAP1 mRNA expressions, and increased GPX4 and Nrf2 mRNA expressions in vitro model of AMI. Down-regulation of Sestrin2 increased collagen I/II and KEAP1 mRNA expressions, and decreased GPX4 and Nrf2 mRNA expressions in vitro model of AMI. These data confirmed that Sestrin2 reduced inflammation and ferroptosis in model of ADMI by LKB1-mediated AMPK activation. This infers that Sestrin2 is potential target to be used in the treatment of premature AMI.

Predicting recurrent cases of intussusception in children after air enema reduction with machine learning models.

PURPOSE: To develop a model to identify risk factors and predict recurrent cases of intussusception in children. METHODS: Consecutive cases and recurrent cases of intussusception in children from January 2016 to April 2022 were screened. The cohort was divided randomly at a 4:1 ratio to a training dataset and a validation dataset. Three parallel models were developed using extreme gradient boosting (XGBoost), logistic regression (LR), and support vector machine (SVM). Model performance was assessed by the area under the receiver operating characteristic curves (AUC). RESULTS: A total of 2469 cases of intussusception were included, where 225 were recurrent cases. The XGBoost (AUC = 0.718) models showed the best performance in the validation dataset, followed by the LR model (AUC = 0.652), while the SVM model (AUC = 0.613) performed worst among the three models. Based on the Shapley Additive exPlanation values, the most important variables in the XGBoost models were air enema pressure, mass size, age, duration of symptoms, and absence of vomiting. CONCLUSIONS: Machine learning models, especially XGBoost, could be used to predict recurrent cases of intussusception in children. The most important contributing factors to the models are air enema pressure, mass size, age, duration of symptoms and absence of vomiting.

A clinical trial for computed tomography myocardial perfusion based non-invasive index of microcirculatory resistance (MPBIMR): rationale and trial design.

INTRODUCTION: Accurate and rapid assessment of the coronary microcirculation has become an important medical challenge. However, reliable and non-invasive quantitative methods to diagnose coronary microvascular disease (CMVD), select treatments for coronary artery disease (CAD), and therefore improve coronary microcirculation are lacking. Current detection methods have limitations. Therefore, we will assess whether a new detection method, the non-invasive index of microcirculatory resistance (IMR), based on computed tomography (CT) perfusion and hydrodynamics (CT-IMR), can effectively evaluate the function of coronary microvessels. METHODS: We will conduct a multicenter, randomized, open-label study, including a Phase I single-center and Phase II multicenter trial, to assess the accuracy of the non-invasive CT-IMR coronary measurement of microcirculation function. The study will enroll 295 patients who will undergo coronary CT angiography (CCTA), dynamic CT-myocardial perfusion imaging (CT-MPI), invasive coronary angiography (ICA), and invasive IMR. This study will identify the key influencing factors when calculating myocardial microcirculation perfusion and develop an accurate three-dimensional coronary reconstruction method and a non-invasive coronary IMR calculation method based on computational fluid dynamics (CFD). This will facilitate the development of a non-invasive system to detect and measure coronary microcirculation. CONCLUSION: The clinical trial for computed tomography myocardial perfusion based non-invasive index of microcirculatory resistance (MPBIMR) will establish the key influencing factors when calculating myocardial microcirculation perfusion and create a non-invasive CT-IMR calculation method based on CFD. This method may diagnose patients with simple coronary microvascular lesions and those with coronary microvascular lesions combined with coronary vascular lesions.

Music Recognition Using Blockchain Technology and Deep Learning.

The purposes are to recognize and classify different music characteristics and strengthen the copyright protection system for original digital music in the big data era. Deep learning (DL) and blockchain technology are applied and researched herein. Based on CNN (Convolutional Neural Network), a music recognition method combined with hashing learning is proposed. The error generated when outputting the binary hash code is considered, and the semantic similarity of the hash code is ensured. Besides, the application of blockchain technology in the current intellectual property protection in original music is discussed. According to digital music property rights protection needs, the system is divided into modules, and its functions are designed. The system ensures its various functions by applying the application protocol designed in the Algor and network. In the experiments, the MagnaTagATune dataset is selected to verify the performance of the proposed CRNNH (Convolutional Recurrent Neural Network Hashing) algorithm. The algorithm shows the best music recognition performance under different bit numbers. When the number of connections is about 100, the QPS value of the blockchain-based music property rights protection system can be stabilized at about 20,000. At any number of threads, the system pressure will increase dramatically with the increase in the number of analog connections. The music recognition algorithm based on DL and hash method discussed is of great significance in improving the classification accuracy of music recognition. The application of blockchain technology in the copyright protection platform of original music works can protect the copyright of digital music and ensure the operation performance of the system.

Towards fine recognition of orbital angular momentum modes through smoke.

Light beams carrying orbital angular momentum (OAM) have been constantly developing in free-space optical (FSO) communications. However, perturbations in the free space link, such as rain, fog, and atmospheric turbulence, may affect the transmission efficiency of this technique. If the FSO communications procedure takes place in a smoke condition with low visibility, the communication efficiency also will be worse. Here, we use deep learning methods to recognize OAM eigenstates and superposition states in a thick smoke condition. In a smoke transmission link with visibility about 5 m to 6 m, the experimental recognition accuracy reaches 99.73% and 99.21% for OAM eigenstates and superposition states whose Bures distance is 0.05. Two 6 bit/pixel pictures were also successfully transmitted in the extreme smoke conditions. This work offers a robust and generalized proposal for FSO communications based on OAM modes and allows an increase of the communication capacity under the low visibility smoke conditions.

The Genetic Association Between TLR-1, -2, -4, and -6 Gene Polymorphisms and Rheumatoid Arthritis Susceptibility in a Chinese Han Population.

Aims: The toll-like receptor (TLR) genes were shown to be involved in the pathogenesis of rheumatoid arthritis (RA). We aimed to investigate the genetic associations between the TLR-1, -2, -4, and -6 genes polymorphisms with RA susceptibility in a Chinese Han population. Methods: Six polymorphisms [TLR-1 (rs5743610, rs5743618), -2 (rs5743708), -4 (rs4986790, rs4986791), and -6 (rs5743810)] in TLRs genes were genotyped in 360 patients with RA and 560 matched healthy controls by direct sequencing. The odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated using a standard logistic regression analysis. Results: No significant associations were observed under the allelic, dominant, or recessive models for TLR-1 rs5743610, TLR-2 rs5743708, TLR-4 rs4986790 and rs4986791, and TLR-6 rs5743810 polymorphisms and RA risk (all p > 0.05). However, significant associations were detected under the allelic, dominant, and recessive models for TLR-1 rs5743618 and RA risk (allelic: OR [95% CI] = 2.21 [1.73-2.81], p < 0.0001; dominant: OR [95% CI] = 2.33 [1.75-3.09], p < 0.0001; recessive models: OR [95% CI] = 3.70 [1.85-7.41], p = 0.0002). In addition, TLR6 rs5743810 was found to be associated with the rheumatoid factor (RF)- and anticyclic citrullinated peptide (anti-CCP)- antibody in RA group (RF: OR [95% CI] = 2.29 [1.42-3.69], p = 0.0007; anti-CCP: OR [95% CI] = 2.33 [1.39-3.89], p = 0.001). Conclusions: The allelic, dominant, and recessive models of TLR1 rs5743618 might be associated with RA susceptibility. Also, the TLR6 rs5743810 marker may be associated with RF and the anti-CCP antibody of RA in the Chinese Han population.

Genetic association between the PTPN22, IRF5 and TYK2 gene variants and susceptibility to juvenile idiopathic arthritis.

Juvenile idiopathic arthritis (JIA) refers to a group of chronic childhood arthropathies of unknown etiology. In the present study, the genetic association between the variants in PTPN22, IRF5 and TYK2 genes and susceptibility to JIA was investigated. The distributions of 16 variants in PTPN22, IRF5 and TYK2 genes were analyzed by direct sequencing in 378 patients with JIA and 378 healthy controls. Odds ratios and 95% confidence intervals were used to evaluate the association between the gene variants and JIA. The gene-gene interactions were investigated using multifactor dimensionality reduction. All allelic and dominant models of PTPN22 rs1214414, rs1214418, rs1746853, rs3765598 and rs3811021 were significantly associated with JIA risk (P<0.05). IRF5 rs10954213 in both allelic and dominant models, as well as the allelic model of rs2004640, was significantly related to JIA risk (P<0.05). In addition, the allelic, recessive and dominant models of TYK2 rs280500, rs280519, rs2304256 and rs12720270 were significantly related to JIA risk (P<0.05). In addition, three haplotypes (HC A G T C C, HC A G T T C and HC G T T C T ) in PTPN22 gene, three haplotypes (HD T A A, HI T A C and HD T G C) in IRF5 gene and two haplotypes (HA G G A T and HG A G G T) in TYK2 gene were associated with the risk of JIA (P<0.05). Furthermore, a three-way interaction between IRF5 rs10954213, rs2004640 and PTPN22 rs1214414 was shown to be associated with JIA risk. In conclusion, PTPN22 rs1214418, rs1746853, rs3765598, IRF5 rs2004640, TYK2 rs280500, rs2304256 and a three-way interaction between IRF5 rs10954213, rs2004640 and PTPN22 rs1214414 may be risk factors for JIA.

Exploration of machine algorithms based on deep learning model and feature extraction.

The study expects to solve the problems of insufficient labeling, high input dimension, and inconsistent task input distribution in traditional lifelong machine learning. A new deep learning model is proposed by combining feature representation with a deep learning algorithm. First, based on the theoretical basis of the deep learning model and feature extraction. The study analyzes several representative machine learning algorithms, and compares the performance of the optimized deep learning model with other algorithms in a practical application. By explaining the machine learning system, the study introduces two typical algorithms in machine learning, namely ELLA (Efficient lifelong learning algorithm) and HLLA (Hierarchical lifelong learning algorithm). Second, the flow of the genetic algorithm is described, and combined with mutual information feature extraction in a machine algorithm, to form a composite algorithm HLLA (Hierarchical lifelong learning algorithm). Finally, the deep learning model is optimized and a deep learning model based on the HLLA algorithm is constructed. When K = 1200, the classification error rate reaches 0.63%, which reflects the excellent performance of the unsupervised database algorithm based on this model. Adding the feature model to the updating iteration process of lifelong learning deepens the knowledge base ability of lifelong machine learning, which is of great value to reduce the number of labels required for subsequent model learning and improve the efficiency of lifelong learning.

Cranial capacity measurement for modern Chinese adults based on 3D reconstruction.

OBJECTIVES: To determine the average modern adult cranial capacity in China, and assess the gender differences and trends in order to establish normal reference values and provide theoretical basis for individualized treatment in clinical practice. METHODS: We conducted a cross-sectional study between January 2019 to June 2020. Thin-slice (0.9 mm) CT scans of 309 males and 238 females from China were obtained, and classified into the 18-32, 33-47, 48-62, 63-77 and 78-92 years age groups. Three-dimensional reconstruction was performed using mimics software to obtain the cranial capacity for statistical analysis. RESULTS: The average cranial capacity of men was 1497.12±120.70 cm3 and that of women was 1326.24±95.72 cm3. The average cranial capacity of men was larger than that of women in all age groups. In addition, cranial capacity across the different age groups showed significant differences among both men and women. CONCLUSION: The average cranial capacity of modern Chinese male is larger that of females, and both sexes show a tendency to an increase in the intracranial volume over the past few decades. Our findings provide important data for establishing normal reference values for cranial capacity of modern Chinese adults and theoretical basis for individualized treatment of certain cranial diseases with increased intracranial pressure.

Polymorphisms in IRF5 and TYK2 Genes Are Associated with Rheumatoid Arthritis in a Chinese Han Population.

BACKGROUND The IRF5 and TYK2 gene polymorphisms are associated with autoimmune diseases. However, the relationship between the IRF5 and TYK2 gene polymorphisms and RA risk in the Chinese Han population was inconsistent. MATERIAL AND METHODS A total of 578 RA patients (case group) and 578 healthy controls (control group) were assessed in a case-control study. Genotyping of IRF5 (Exon 6 insertion/deletion (in/de), rs2004640, rs2070197, rs10954213) and TYK2 (rs280500, rs280519, rs280521, rs8108236, rs12720253) was performed by direct sequencing method. Data analysis was performed by SHEsis. RESULTS The rs2004640T allele (P=0.0003) and the dominant (P=0.001) and recessive (P=0.01) models of rs2004640 were associated with RA risk after stringent Bonferroni correction (0.05/4). The IRF5 exon 6 (in), rs2070197 and rs10954213 were not associated with RA (P>0.05). Two haplotypes of IRF5 (DTAT and DTGG) were associated with RA susceptibility (P<0.05). In addition, the frequencies of TYK2 rs280500A, rs280521A, and rs8108236A were significantly higher in the RA group compared with the control group (P<0.05). TYK2 rs280500, rs280521, and rs8108236 were associated with RA susceptibility in the dominant model, but the same was not observed for rs280519 and rs12720253 (P<0.05). Furthermore, 3 risk haplotypes (AAAGT, AGGAT, and GAAAT) and a protective haplotype (GAGGT) of TYK2 gene were associated with RA susceptibility (P<0.05). CONCLUSIONS Our results suggest that IRF5 rs2004640, TYK2 rs280500, rs280521, rs8108236, and haplotypes IRF5 (DTAT and DTGG) and TYK2 (AAAGT, AGGAT, GAAAT, and GAGGT) are susceptible factors for RA in a Chinese Han population.

Exploring Quality Evaluation of Innovation and Entrepreneurship Education in Higher Institutions Using Deep Learning Approach and Fuzzy Fault Tree Analysis.

The quality of Innovation and Entrepreneurship Education (IEE) in higher institutions is closely related to the degree to which the undergraduates (UGs) absorb relevant innovation and entrepreneurship knowledge and their entrepreneurial motivation. Thus, an effective Evaluation of Educational Quality (EEQ) is essential. In particular, fault tree analysis (FTA), a common EEQ approach, has some disadvantages, such as fault data reliance and insufficient uncertainties handleability. Thereupon, this article first puts forward a theoretical model based on the deep learning (DL) method to analyze the factors of IEE quality; consequently, based on the traditional FTA, fuzzy fault tree analysis (FFTA) is proposed to evaluate the reliability of IEE classroom teaching for college teachers and students. Finally, based on the top event of entrepreneurial teaching failure, the hyper-ellipsoid model is implemented to restrict the interval probability of basic events and describe the deviation of uncertain events. Furthermore, the model accuracy is verified by a questionnaire survey (QS), based upon which the factors of IEE quality are analyzed. The results show that the designed QS has good reliability, validity, and fitness; the path coefficients of cooperative ability to critical thinking and innovative thinking are 0.9 and 0.66, respectively, indicating that the students' cooperative ability plays a vital role in the classroom teaching. By calculation, the probability of "teaching failure" in entrepreneurial classroom teaching is 0.395, 3, 0.462, and 5. To sum up, the proposed method can effectively and quantitatively evaluate the quality of IEE in higher institutions, thus providing a certain basis for formulating relevant improvement strategies. The purpose is to provide important technical support for improving the IEE quality.

Dangshen Erling Decoction Ameliorates Myocardial Hypertrophy via Inhibiting Myocardial Inflammation.

Myocardial hypertrophy plays an essential role in the structural remodeling of the heart and the progression to heart failure (HF). There is an urgent need to understand the mechanisms underlying cardiac hypertrophy and to develop treatments for early intervention. Dangshen Erling decoction (DSELD) is a clinically used formula in Chinese medicine for treating coronary heart disease in patients with HF. However, the mechanism by which DSELD produces its cardioprotective effects remains largely unknown. This study explored the effects of DSELD on myocardial hypotrophy both in vitro and in vivo. In vitro studies indicated that DSELD significantly (p < 0.05) reduced the cross-sectional area of the myocardium and reduced elevated lactate dehydrogenase (LDH), tumor necrosis factor (TNF)-α, and interleukin (IL)-6 levels in the induced H9C2 cell model to study inflammation. In vivo experiments revealed that DSELD restores cardiac function and significantly reduces myocardial fibrosis in isoproterenol (ISO)-induced HF mouse model (p < 0.05). In addition, DSELD downregulated the expression of several inflammatory cytokines, such as granulocyte-macrophage colony-stimulating factor (GM-CSF), granulocyte CSF (G-CSF), IL-1α, IL-1ß, IL-3, IL-5, IL-7, IL-12, IL-13, and TNF-α in HF (p < 0.05). Further analysis of the cardiac tissue demonstrated that DSELD produces its anti-inflammatory effects via the Toll-like receptor (TLR)4 signaling pathway. The expression of TLR4 downstream proteins such as matrix metalloproteinase-9 (MMP9) and myeloid differentiation factor-88 (MyD88) was among the regulated targets. In conclusion, these observations suggest that DSELD exerts antihypertrophic effects by alleviating the inflammatory injury via the TLR4 signaling pathway in HF and thus holds promising therapeutic potentials.

Ticagrelor inhibits the NLRP3 inflammasome to protect against inflammatory disease independent of the P2Y12 signaling pathway.

Ticagrelor is the first reversibly binding oral P2Y12 receptor antagonist to inhibit platelet activation and has been approved by the Food and Drug Administration for the treatment of coronary artery disease. At present, the other pharmacological functions of ticagrelor remain poorly understood. The NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome plays a critical role in the innate immune system, but its excessive activation also contributes to the pathogenesis of complex diseases. In this study, we systematically examined the effects of ticagrelor on the NLRP3 inflammasome and found that ticagrelor inhibits NLRP3 inflammasome activation in macrophages independent of its classic inhibitory effect on the P2Y12 signaling pathway. Further mechanistic studies demonstrate that ticagrelor attenuates the oligomerization of apoptosis-associated speck-like protein containing a CARD (ASC) by blocking chloride efflux, an effect achieved through the degradation of chloride intracellular channel proteins (CLICs) and blockade of the translocation of CLICs to the plasma membrane. Moreover, experiments on lipopolysaccharide-induced sepsis and alum-induced peritonitis in mice confirmed that ticagrelor mitigates the severity of systemic inflammation independent of P2Y12 receptor antagonism. Importantly, oral administration of ticagrelor rapidly and strongly inhibited NLRP3 inflammasome activation in peripheral blood mononuclear cells from patients with acute coronary syndrome. Overall, our study reveals a novel pharmacological function of ticagrelor in addition to its classic antiplatelet properties, which suggests that ticagrelor may serve as a potential therapeutic agent for use in NLRP3-associated diseases.

The LMP2 CfoI polymorphism is associated with ankylosing spondylitis (AS) risk but not with acute anterior uveitis (AAU): A meta-analysis.

BACKGROUND: Ankylosing spondylitis (AS) is one of the most common chronic inflammatory disorders affecting the sacroiliac joints, spine, and peripheral joints. Apart from HLA-B27, the LMP2 gene has been shown to play a role in the pathogenesis of AS as well as AAU in AS. However, genetic associations between LMP2 CfoI polymorphism and AS and AAU were inconclusive. We aimed to investigate the correlation of LMP2 CfoI polymorphism and AS and AAU using meta-analysis. METHODS: An exhaustive search was conducted using the PubMed, Embase, Cochrane Library, and Chinese National Knowledge Infrastructure (CNKI) electronic databases. The strength association was assessed by crude ORs with 95% CI. RESULTS: Eight eligible records with 449 AS patients and 317 healthy controls were included in the present study. The allelic model of the LMP2 CfoI polymorphism is associated with AS risk (OR = 0.60, 95%CI = [0.32, 1.11], P = .003). A stratified analysis based on ethnicity has shown that the allelic model of LMP2 CfoI was associated with AS in the Caucasian population (OR = 0.72, 95%CI = [0.55, 0.93], P = .01) but not in the Asian population (P > .05). Furthermore, no association was detected between LMP2 CfoI polymorphism and AS complication (AAU). CONCLUSION: Our combined results revealed that the allelic model of LMP2 CfoI might be a protective factor for AS in the Caucasian population. Nevertheless, future studies on different ethnicities with larger sample sizes are needed to obtain a more convincing result.

Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.

The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.