Supramolecular Enzyme-Peptide Gels for Localized Therapeutic Biocatalysis.

Enzyme therapeutics are often compromised by poor accumulation within target tissues, necessitating high doses that can exacerbate off-target effects. We report an injectable supramolecular enzyme-peptide gel platform for prolonged local enzyme retention in vivo . The gel is based on CATCH(+/-) ( C o- A ssembling T ags based on CH arge-complementarity), cationic and anionic peptide pairs that form ß-sheet fibrils upon mixing 1 . Enzymes recombinantly fused to CATCH(-) peptide integrate into CATCH(+/-) ß-sheet fibrils during assembly, resulting in an enzyme-peptide gel. Catalytically-active gels were fabricated with four disparate enzymes: CATCH(-)-NanoLuc luciferase, CATCH(-)-cutinase, CATCH(-)-uricase, and CATCH(-)-adenosine synthase A. CATCH(-)-cutinase gels demonstrated tunability of the platform, while CATCH(-)-NanoLuc gels demonstrated prolonged tissue retention relative to soluble enzyme. CATCH(-)-uricase gels resolved localized inflammation in a gout model, while CATCH(-)-adenosine synthase A gels suppressed localized lipopolysaccharide-induced inflammation. Modular and tunable enzyme content, coupled with prolonged tissue retention, establish CATCH enzyme-peptide gels as a generalizable vehicle for effective local therapeutic biocatalysis.

Highly sensitive detection of Salmonella typhimurium via gold and magnetic nanoparticle-mediated sandwich hybridization coupled with ICP-MS.

Foodborne pathogens including Salmonella typhimurium (S. typhimurium) are responsible for over 600 million global incidences of illness annually, posing a significant threat to public health. Inductively coupled plasma mass spectrometry (ICP-MS), coupled with element labeling strategies, has emerged as a promising platform for multivariate and accurate pathogen detection. However, achieving high specificity and sensitivity remains a critical challenge. Herein, we synthesize clustered magnetic nanoparticles (MNPs) and popcorn-shaped gold nanoparticles (AuNPs) to conjugate capture and report DNA probes for S. typhimurium, respectively. These engineered nanoparticles facilitate the identification of S. typhimurium DNA through a sandwich hybridization technique. ICP-MS quantification of Au within the sandwich-structure complexes allows for precise S. typhimurium detection. The unique morphology of the AuNPs and MNPs increases the available sites for probe attachment, enhancing the efficiency of S. typhimurium DNA capture, broadening the detection range to 101-1010 copies mL-1, and achieving a low detection limit of 1 copy mL-1, and the overall assay time is 70 min. The high specificity of this method is verified by anti-interference assays against ten other pathogens. The recovery was 96.8-102.8% for detecting S. typhimurium DNA in biological samples. As these specially designed nanoparticles may facilitate the attachment of various proteins and nucleic acid probes, they may become an effective platform for detecting multiple pathogens.

Sweet corn phytoglycogen dendrimers as a lyoprotectant for dry-state protein storage.

Protein biotherapeutics typically require expensive cold-chain storage to maintain their fold and function. Packaging proteins in the dry state via lyophilization can reduce these cold-chain requirements. However, formulating proteins for lyophilization often requires extensive optimization of excipients that both maintain the protein folded state during freezing and drying (i.e., "cryoprotection" and "lyoprotection"), and form a cake to carry the dehydrated protein. Here we show that sweet corn phytoglycogens, which are glucose dendrimers, can act as both a protein lyoprotectant and a cake-forming agent. Phytoglycogen (PG) dendrimers from 16 different maize sources (PG1-16) were extracted via ethanol precipitation. PG size was generally consistent at ~70-100 nm for all variants, whereas the colloidal stability in water, protein contaminant level, and maximum density of cytocompatibility varied for PG1-16. 10 mg/mL PG1, 2, 9, 13, 15, and 16 maintained the activity of various proteins, including green fluorescent protein, lysozyme, ß-galactosidase, and horseradish peroxidase, over a broad range of concentrations, through multiple rounds of lyophilization. PG13 was identified as the lead excipient candidate as it demonstrated narrow dispersity, colloidal stability in phosphate-buffered saline, low protein contaminants, and cytocompatibility up to 10 mg/mL in NIH3T3 cell cultures. All dry protein-PG13 mixtures had a cake-like appearance and all frozen protein-PG13 mixtures had a Tg' of ~ -26°C. The lyoprotection and cake-forming properties of PG13 were density-dependent, requiring a minimum density of 5 mg/mL for maximum activity. Collectively these data establish PG dendrimers as a new class of excipient to formulate proteins in the dry state.

A novel nomogram model to predict in-hospital mortality in patients with acute type A aortic dissection after surgery.

BACKGROUND: Acute type A aortic dissection is a dangerous disease that threatens public health. In recent years, with the progress of medical technology, the mortality rate of patients after surgery has been gradually reduced, leading that previous prediction models may not be suitable for nowadays. Therefore, the present study aims to find new independent risk factors for predicting in-hospital mortality and construct a nomogram prediction model. METHODS: The clinical data of 341 consecutive patients in our center from 2019 to 2023 were collected, and they were divided into two groups according to the death during hospitalization. The independent risk factors were analyzed by univariate and multivariate logistic regression, and the nomogram was constructed and verified based on these factors. RESULTS: age, preoperative lower limb ischemia, preoperative activated partial thromboplastin time (APTT), preoperative platelet count, Cardiopulmonary bypass (CPB) time and postoperative acute kidney injury (AKI) independently predicted in-hospital mortality of patients with acute type A aortic dissection after surgery. The area under the receiver operating characteristic curve (AUC) for the nomogram was 0.844. The calibration curve and decision curve analysis verified that the model had good quality. CONCLUSION: The new nomogram model has a good ability to predict the in-hospital mortality of patients with acute type A aortic dissection after surgery.

The health benefits of dietary polyphenols on pediatric intestinal diseases: Mechanism of action, clinical evidence and future research progress.

Pediatric intestinal development is immature, vulnerable to external influences and produce a variety of intestinal diseases. At present, breakthroughs have been made in the treatment of pediatric intestinal diseases, but there are still many challenges, such as toxic side effects, drug resistance, and the lack of more effective treatments and specific drugs. In recent years, dietary polyphenols derived from plants have become a research hotspot in the treatment of pediatric intestinal diseases due to their outstanding pharmacological activities such, as anti-inflammatory, antibacterial, antioxidant and regulation of intestinal flora. This article reviewed the mechanism of action and clinical evidence of dietary polyphenols in the treatment of pediatric intestinal diseases, and discussed the influence of physiological characteristics of children on the efficacy of polyphenols, and finally prospected the new dosage forms of polyphenols in pediatrics.

Structural Elucidation of Glycosaminoglycans in the Tissue of Flounder and Isolation of Chondroitin Sulfate C.

Glycosaminoglycans (GAGs) are valuable bioactive polysaccharides with promising biomedical and pharmaceutical applications. In this study, we analyzed GAGs using HPLC-MS/MS from the bone (B), muscle (M), skin (S), and viscera (V) of Scophthalmus maximus (SM), Paralichthysi (P), Limanda ferruginea (LF), Cleisthenes herzensteini (G), Platichthys bicoloratus (PB), Pleuronichthys cornutus (PC), and Cleisthenes herzensteini (CH). Unsaturated disaccharide products were obtained by enzymatic hydrolysis of the GAGs and subjected to compositional analysis of chondroitin sulfate (CS), heparin sulfate (HS), and hyaluronic acid (HA), including the sulfation degree of CS and HS, as well as the content of each GAG. The contents of GAGs in the tissues and the sulfation degree differed significantly among the fish. The bone of S. maximus contained more than 12 µg of CS per mg of dry tissue. Although the fish typically contained high levels of CSA (CS-4S), some fish bone tissue exhibited elevated levels of CSC (CS-6S). The HS content was found to range from 10-150 ug/g, primarily distributed in viscera, with a predominant non-sulfated structure (HS-0S). The structure of HA is well-defined without sulfation modification. These analytical results are independent of biological classification. We provide a high-throughput rapid detection method for tissue samples using HPLC-MS/MS to rapidly screen ideal sources of GAG. On this basis, four kinds of CS were prepared and purified from flounder bone, and their molecular weight was determined to be 23-28 kDa by HPGPC-MALLS, and the disaccharide component unit was dominated by CS-6S, which is a potential substitute for CSC derived from shark cartilage.

Parallel ß-Sheet Structure and Structural Heterogeneity Detected within Q11 Self-Assembling Peptide Nanofibers.

Q11 peptide nanofibers are used as a biomaterial for applications such as antigen presentation and tissue engineering, yet detailed knowledge of molecular-level structure has not been reported. The Q11 peptide sequence was designed using heuristics-based patterning of hydrophobic and polar amino acids with oppositely charged amino acids placed at opposite ends of the sequence to promote antiparallel ß-sheet formation. In this work, we employed solid-state nuclear magnetic resonance spectroscopy (NMR) to evaluate whether the molecular organization within Q11 self-assembled peptide nanofibers is consistent with the expectations of the peptide designers. We discovered that Q11 forms a distribution of molecular structures. NMR data from two-dimensional (2D) 13C-13C dipolar-assisted rotational resonance indicate that the K3 and E9 residues between Q11 ß-strands are spatially proximate (within ∼0.6 nm). Frequency-selective rotational echo double resonance (fsREDOR) on K3 Nζ and E9 Cδ-labeled sites showed that approximately 9% of the sites are close enough for salt bridge formation to occur. Surprisingly, dipolar recoupling measurements revealed that Q11 peptides do not assemble into antiparallel ß-sheets as expected, and structural analysis using Fourier-transform infrared spectroscopy and 2D NMR alone can be misleading. 13C PITHIRDS-CT dipolar recoupling measurements showed that the most abundant structure consists of parallel ß-sheets, in contrast to the expected antiparallel ß-sheet structure. Structural heterogeneity was detected from 15N{13C} REDOR measurements, with approximately 22% of ß-strands having antiparallel nearest neighbors. We cannot propose a complete structural model of Q11 nanofibers because of the complexity involved when examining structurally heterogeneous samples using NMR. Altogether, our results show that while heuristics-based patterning is effective in promoting ß-sheet formation, designing a peptide sequence to form a targeted ß-strand arrangement remains challenging.

Myocardial ischemia simulation based on a multi-scale heart electrophysiology model.

BACKGROUND: Myocardial ischemia, caused by insufficient myocardial blood supply, is a leading cause of human death worldwide. Therefore, it is crucial to prioritize the prevention and treatment of this condition. Mathematical modeling is a powerful technique for studying heart diseases. OBJECTIVE: The aim of this study was to discuss the quantitative relationship between extracellular potassium concentration and the degree of myocardial ischemia directly related to it. METHODS: A human cardiac electrophysiological multiscale model was developed to calculate action potentials of all cells simultaneously, enhancing efficiency over traditional reaction-diffusion models. RESULTS: Contrary to the commonly held view that myocardial ischemia is caused by an increase in extracellular potassium concentration, our simulation results indicate that level 1 ischemia is associated with a decrease in extracellular potassium concentration. CONCLUSION: This unusual finding provides a new perspective on the mechanisms underlying myocardial ischemia and has the potential to lead to the development of new diagnostic and treatment strategies.

Gastrodin ameliorates neuroinflammation in Alzheimer's disease mice by inhibiting NF-κB signaling activation via PPARγ stimulation.

AIM: We investigated the effects and targets of gastrodin (GAS) for improving cognitive ability in Alzheimer's disease (AD). METHODS: The targets and mechanisms of GAS were analyzed by network pharmacology. Morris water and eight-arm radial mazes were used to detect the behaviors of 7-months-old APP/PS1 mice. The levels of IBA-1 and PPARγ were examined by histochemical staining, nerve cells were detected by Nissl staining, inflammatory cytokines were measured by ELISA, and protein expressions were monitored by Western blotting. The neurobehavioral effects of GAS on mice were detected after siRNA silencing of PPARγ. Microglia were cultured in vitro and Aß1-42 was used to simulate the pathology of AD. After treatment with GAS, the levels of inflammatory cytokines and proteins were assayed. RESULTS: Network pharmacological analysis revealed that PPARγ was the action target of GAS. By stimulating PPARγ, GAS inhibited NF-κB signaling activation and decreased neuroinflammation and microglial activation, thereby ameliorating the cognitive ability of AD mice. After silencing PPARγ, GAS could not further improve such cognitive ability. Cellular-level results demonstrated that GAS inhibited microglial injury, reduced tissue inflammation, and activated PPARγ. CONCLUSIONS: GAS can regulate microglia-mediated inflammatory response by stimulating PPARγ and inhibiting NF-κB activation, representing a mechanism whereby it improves the cognitive behavior of AD.

Visual Tracking in Amblyopia: A Continuous Psychophysical Approach.

Purpose: This study aimed to explore the underlying mechanisms of the observed visuomotor deficit in amblyopia. Methods: Twenty-four amblyopic (25.8 ± 3.8 years; 15 males) and 22 normal participants (25.8 ± 2.1 years; 8 males) took part in the study. The participants were instructed to continuously track a randomly moving Gaussian target on a computer screen using a mouse. In experiment 1, the participants performed the tracking task at six different target sizes. In experiments 2 and 3, they were asked to track a target with the contrast adjusted to individual's threshold. The tracking performance was represented by the kernel function calculated as the cross-correlation between the target and mouse displacements. The peak, latency, and width of the kernel were extracted and compared between the two groups. Results: In experiment 1, target size had a significant effect on the kernel peak (F(1.649, 46.170) = 200.958, P = 4.420 × 10-22). At the smallest target size, the peak in the amblyopic group was significantly lower than that in the normal group (0.089 ± 0.023 vs. 0.107 ± 0.020, t(28) = -2.390, P = 0.024) and correlated with the contrast sensitivity function (r = 0.739, P = 0.002) in the amblyopic eyes. In experiments 2 and 3, with equally visible stimuli, there were still differences in the kernel between the two groups (all Ps < 0.05). Conclusions: When stimulus visibility was compensated, amblyopic participants still showed significantly poorer tracking performance.

Effects of Indocyanine Green (ICG) Imaging-Assisted Cholecystectomy on Intraoperative and Postoperative Complications: A meta-Analysis.

BACKGROUND: Accurate recognition of Calot's triangle during cholecystectomy is important in preventing intraoperative and postoperative complications. The use of indocyanine green (ICG) fluorescence imaging has become increasingly prevalent in cholecystectomy procedures. Our study aimed to evaluate the specific effects of ICG-assisted imaging in reducing complications. MATERIALS AND METHODS: A comprehensive search of databases including PubMed, Web of Science, Europe PMC, and WANFANGH DATA was conducted to identify relevant articles up to July 5, 2023. Review Manager 5.3 software was applied to statistical analysis. RESULTS: Our meta-analysis of 14 studies involving 3576 patients compared the ICG group (1351 patients) to the control group (2225 patients). The ICG group had a lower incidence of postoperative complications (4.78% vs 7.25%; RR .71; 95%CI: .54-.95; P = .02). Bile leakage was significantly reduced in the ICG group (.43% vs 2.02%; RR = .27; 95%CI: .12-.62; I2 = 0; P = .002), and they also had a lower bile duct drainage rate (24.8% vs 31.8% RR = .64, 95% CI: .44-.91, P = .01). Intraoperative complexes showed no statistically significant difference between the 2 groups (1.16% vs 9.24%; RR .17; 95%CI .03-1.02), but the incidence of intraoperative bleeding is lower in the ICG group. CONCLUSION: ICG fluorescence imaging-assisted cholecystectomy was associated with a range of benefits, including a lower incidence of postoperative complications, decreased rates of bile leakage, reduced bile duct drainage, fewer intraoperative complications, and reduced intraoperative bleeding.

TRIM5 as a promising diagnostic biomarker of hepatocellular carcinoma: integrated analysis and experimental validation.

The TRIM family is associated with the membrane, and its involvement in the progression, growth, and development of various cancer types has been researched extensively. However, the role played by the TRIM5 gene within this family has yet to be explored to a great extent in terms of hepatocellular carcinoma (HCC). The data of patients relating to mRNA expression and the survival rate of individuals diagnosed with HCC were extracted from The Cancer Genome Atlas (TCGA) database. UALCAN was employed to examine the potential link between TRIM5 expression and clinicopathological characteristics. In addition, enrichment analysis of differentially expressed genes (DEGs) was conducted as a means of deciphering the function and mechanism of TRIM5 in HCC. The data in the TCGA and TIMER2.0 databases was utilized to explore the correlation between TRIM5 and immune infiltration in HCC. WGCNA was performed as a means of assessing TRIM5-related co-expressed genes. The "OncoPredict" R package was also used for investigating the association between TRIM5 and drug sensitivity. Finally, qRT-PCR, Western blotting (WB) and immunohistochemistry (IHC) were employed for exploring the differential expression of TRIM5 and its clinical relevance in HCC. According to the results that were obtained from the vitro experiments, mRNA and protein levels of TRIM5 demonstrated a significant upregulation in HCC tissues. It is notable that TRIM5 expression levels were found to have a strong association with the infiltration of diverse immune cells and displayed a positive correlation with several immune checkpoint inhibitors. The TRIM5 expression also displayed promising clinical prognostic value for HCC patients.

Perceptual learning changes the amplitude not the shape of the temporal window of visual processing.

Perceptual learning (PL) can significantly improve human performance in perceptual tasks primarily through template reweighting. Previous studies have documented how PL changes perceptual template in stimulus feature space. We investigated how PL reweights visual information in time. With a dynamic external noise paradigm and the elaborated perceptual template model (ePTM) analysis, we found that training with an orientation identification task in the zero external noise condition reduced contrast thresholds in both zero and high external noise conditions, whereas training in the high external noise condition only reduced contrast thresholds in high external noise conditions. The ePTM analysis showed that training in both zero and high external noise changed the overall amplitude, but not the shape of the temporal window of the perceptual template to exclude external noise across time, and training in zero external noise additionally reduced additive internal noise. Our results provided additional constraints for models of PL. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Programming co-assembled peptide nanofiber morphology via anionic amino acid type: Insights from molecular dynamics simulations.

Co-assembling peptides can be crafted into supramolecular biomaterials for use in biotechnological applications, such as cell culture scaffolds, drug delivery, biosensors, and tissue engineering. Peptide co-assembly refers to the spontaneous organization of two different peptides into a supramolecular architecture. Here we use molecular dynamics simulations to quantify the effect of anionic amino acid type on co-assembly dynamics and nanofiber structure in binary CATCH(+/-) peptide systems. CATCH peptide sequences follow a general pattern: CQCFCFCFCQC, where all C's are either a positively charged or a negatively charged amino acid. Specifically, we investigate the effect of substituting aspartic acid residues for the glutamic acid residues in the established CATCH(6E-) molecule, while keeping CATCH(6K+) unchanged. Our results show that structures consisting of CATCH(6K+) and CATCH(6D-) form flatter ß-sheets, have stronger interactions between charged residues on opposing ß-sheet faces, and have slower co-assembly kinetics than structures consisting of CATCH(6K+) and CATCH(6E-). Knowledge of the effect of sidechain type on assembly dynamics and fibrillar structure can help guide the development of advanced biomaterials and grant insight into sequence-to-structure relationships.

Side-Chain Chemistry Governs Hierarchical Order of Charge-Complementary ß-sheet Peptide Coassemblies.

Self-assembly of proteinaceous biomolecules into functional materials with ordered structures that span length scales is common in nature yet remains a challenge with designer peptides under ambient conditions. This report demonstrates how charged side-chain chemistry affects the hierarchical co-assembly of a family of charge-complementary ß-sheet-forming peptide pairs known as CATCH(X+/Y-) at physiologic pH and ionic strength in water. In a concentration-dependent manner, the CATCH(6K+) (Ac-KQKFKFKFKQK-Am) and CATCH(6D-) (Ac-DQDFDFDFDQD-Am) pair formed either ß-sheet-rich microspheres or ß-sheet-rich gels with a micron-scale plate-like morphology, which were not observed with other CATCH(X+/Y-) pairs. This hierarchical order was disrupted by replacing D with E, which increased fibril twisting. Replacing K with R, or mutating the N- and C-terminal amino acids in CATCH(6K+) and CATCH(6D-) to Qs, increased observed co-assembly kinetics, which also disrupted hierarchical order. Due to the ambient assembly conditions, active CATCH(6K+)-green fluorescent protein fusions could be incorporated into the ß-sheet plates and microspheres formed by the CATCH(6K+/6D-) pair, demonstrating the potential to endow functionality.

Effects of Lianhuaqingwen Capsules in adults with mild-to-moderate coronavirus disease 2019: an international, multicenter, double-blind, randomized controlled trial.

BACKGROUND: In a randomized trial, Lianhuaqingwen (LHQW) capsule was effective for accelerating symptom recovery among patients with coronavirus disease 2019 (COVID-19). However, the lack of blinding and limited sample sizes decreased the level of clinical evidence. OBJECTIVES: To evaluate the efficacy and safety of LHQW capsule in adults with mild-to-moderate COVID-19. METHODS: We conducted a double-blind randomized controlled trial in adults with mild-to-moderate COVID-19 (17 sites from China, Thailand, Philippine and Vietnam). Patients received standard-of-care alone or plus LHQW capsules (4 capsules, thrice daily) for 14 days. The primary endpoint was the median time to sustained clinical improvement or resolution of nine major symptoms. RESULTS: The full-analysis set consisted of 410 patients in LHQW capsules and 405 in placebo group. LHQW significantly shortened the primary endpoint in the full-analysis set (4.0 vs. 6.7 days, hazards ratio: 1.63, 95% confidence interval: 1.39-1.90). LHQW capsules shortened the median time to sustained clinical improvement or resolution of stuffy or runny nose (2.8 vs. 3.7 days), sore throat (2.0 vs. 2.6 days), cough (3.2 vs. 4.9 days), feeling hot or feverish (1.0 vs. 1.3 days), low energy or tiredness (1.3 vs. 1.9 days), and myalgia (1.5 vs. 2.0 days). The duration to sustained clinical improvement or resolution of shortness of breath, headache, and chills or shivering did not differ significantly between the two groups. Safety was comparable between the two groups. No serious adverse events were reported. INTERPRETATION: LHQW capsules promote recovery of mild-to-moderate COVID-19 via accelerating symptom resolution and were well tolerated. Trial registration ChiCTR2200056727 .

Assigning channel weights using an attention mechanism: an EEG interpolation algorithm.

During the acquisition of electroencephalographic (EEG) signals, various factors can influence the data and lead to the presence of one or multiple bad channels. Bad channel interpolation is the use of good channels data to reconstruct bad channel, thereby maintaining the original dimensions of the data for subsequent analysis tasks. The mainstream interpolation algorithm assigns weights to channels based on the physical distance of the electrodes and does not take into account the effect of physiological factors on the EEG signal. The algorithm proposed in this study utilizes an attention mechanism to allocate channel weights (AMACW). The model gets the correlation among channels by learning from good channel data. Interpolation assigns weights based on learned correlations without the need for electrode location information, solving the difficulty that traditional methods cannot interpolate bad channels at unknown locations. To avoid an overly concentrated weight distribution of the model when generating data, we designed the channel masking (CM). This method spreads attention and allows the model to utilize data from multiple channels. We evaluate the reconstruction performance of the model using EEG data with 1 to 5 bad channels. With EEGLAB's interpolation method as a performance reference, tests have shown that the AMACW models can effectively reconstruct bad channels.

Neural Correlation of EEG and Eye Movement in Natural Grasping Intention Estimation.

Decoding the user's natural grasp intent enhances the application of wearable robots, improving the daily lives of individuals with disabilities. Electroencephalogram (EEG) and eye movements are two natural representations when users generate grasp intent in their minds, with current studies decoding human intent by fusing EEG and eye movement signals. However, the neural correlation between these two signals remains unclear. Thus, this paper aims to explore the consistency between EEG and eye movement in natural grasping intention estimation. Specifically, six grasp intent pairs are decoded by combining feature vectors and utilizing the optimal classifier. Extensive experimental results indicate that the coupling between the EEG and eye movements intent patterns remains intact when the user generates a natural grasp intent, and concurrently, the EEG pattern is consistent with the eye movements pattern across the task pairs. Moreover, the findings reveal a solid connection between EEG and eye movements even when taking into account cortical EEG (originating from the visual cortex or motor cortex) and the presence of a suboptimal classifier. Overall, this work uncovers the coupling correlation between EEG and eye movements and provides a reference for intention estimation.

Clinical characteristics and outcomes of patients with COVID-19 and tuberculosis coinfection.

BACKGROUND: Data on the coincidence of Tuberculosis (TB) and Coronavirus disease 2019 (COVID-19) are limited. We sought to investigate the clinical characteristics and outcomes of coinfected patients in Henan and identify whether TB disease is associated with an increased risk of intensive care unit (ICU) admission and mortality. METHOD: We conducted a retrospective matched cohort study of COVID-19 inpatients involving 41 TB-positive patients with 82 patients without TB. Leveraging data was collected from electronic medical records. RESULTS: There were no significant differences in clinical manifestations, the need for mechanical ventilation and vasopressors, ICU admission, or in-hospital mortality between 2 groups. TB-positive patients had a lower lymphocyte counts (1.24 ± 0.54 vs. 1.59 ± 0.58, p = 0.01), B cells (99/µl vs. 201/µl, p < 0.01), CD4+ T cells (382/µl vs. 667/µl, p < 0.01), CD8+ T cells (243/µl vs. 423/µl, p < 0.01), NK cells (145/µl vs. 216/µl, p = 0.01), IL-2 (14.18 ± 11.23 vs. 31.86 ± 34.55, p < 0.01) and TNF-α (3.42 ± 2.93 vs. 5.62 ± 3.69, p < 0.01). Notably, the TB-positive group had a longer duration of SARS-CoV-2 shedding (67 days vs. 22 days, p < 0.01). CONCLUSIONS: Concomitant TB does not significantly impact clinical outcomes of hospitalised patients with acute COVID-19. However, TB-positive patients had longer duration of SARS-COV-2-RNA positivity.

Suppression of Crosstalk in Quantum Circuit Based on Instruction Exchange Rules and Duration.

Crosstalk is the primary source of noise in quantum computing equipment. The parallel execution of multiple instructions in quantum computation causes crosstalk, which causes coupling between signal lines and mutual inductance and capacitance between signal lines, destroying the quantum state and causing the program to fail to execute correctly. Overcoming crosstalk is a critical prerequisite for quantum error correction and large-scale fault-tolerant quantum computing. This paper provides an approach for suppressing crosstalk in quantum computers based on multiple instruction exchange rules and duration. Firstly, for the majority of the quantum gates that can be executed on quantum computing devices, a multiple instruction exchange rule is proposed. The multiple instruction exchange rule reorders quantum gates in quantum circuits and separates double quantum gates with high crosstalk on quantum circuits. Then, time stakes are inserted based on the duration of different quantum gates, and quantum gates with high crosstalk are carefully separated in the process of quantum circuit execution by quantum computing equipment to reduce the influence of crosstalk on circuit fidelity. Several benchmark experiments verify the proposed method's effectiveness. In comparison to previous techniques, the proposed method improves fidelity by 15.97% on average.