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Background Liver injuries have been reported in patients with coronavirus disease 2019 (COVID-19). This study aimed to investigate the clinical role played by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods In this multicentre, retrospective study, the parameters of liver function tests in COVID-19 inpatients were compared between various time-points in reference to SARS-CoV-2 shedding, and 3 to 7 days before the first detection of viral shedding was regarded as the reference baseline. Results In total, 70 COVID-19 inpatients were enrolled. Twenty-two (31.4%) patients had a self-medication history after illness. At baseline, 10 (14.3%), 7 (10%), 9 (12.9%), 2 (2.9%), 15 (21.4%), and 4 (5.7%) patients already had abnormal alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), albumin, and total bilirubin (TBIL) values, respectively. ALT and AST abnormal rates and levels did not show any significant dynamic changes during the full period of viral shedding (all p  > 0.05). The GGT abnormal rate ( p  = 0.008) and level ( p  = 0.033) significantly increased on day 10 of viral shedding. Meanwhile, no simultaneous significant increases in abnormal ALP rates and levels were observed. TBIL abnormal rates and levels significantly increased on days 1 and 5 of viral shedding (all p  < 0.05). Albumin abnormal decrease rates increased, and levels decreased consistently from baseline to SARS-CoV-2 clearance day (all p  < 0.05). Thirteen (18.6%) patients had chronic liver disease, two of whom died. The ALT and AST abnormal rates and levels did not increase in patients with chronic liver disease during SARS-CoV-2 shedding. Conclusions SARS-CoV-2 does not directly lead to elevations in ALT and AST but may result in elevations in GGT and TBIL; albumin decreased extraordinarily even when SARS-CoV-2 shedding ended.

INTRODUCTION:The course of maternal antiviral prophylaxis to prevent mother-to-child transmission of hepatitis B virus (HBV-MTCT) varies greatly, and it has not been demonstrated in a randomized controlled study.METHODS:In this multicenter, open-label, randomized controlled trial, eligible pregnant women with HBV DNA of 5.3–9.0 log10 IU/mL who received tenofovir alafenamide fumarate (TAF) from the first day of 33 gestational weeks to delivery (expected 8 week) or to 4 weeks postpartum (expected 12 week) were randomly enrolled at a 1:1 ratio and followed until 6 months postpartum. All infants received standard immunoprophylaxis (hepatitis B immunoglobulin and vaccine). The primary end point was the safety of mothers and infants. The secondary end point was the HBV-MTCT rate of infants at the age of 7 months.RESULTS:Among 119 and 120 intention-to-treat pregnant women, 115 and 116 women were followed until delivery, and 110 and 112 per-protocol mother-infant dyads in 2 groups completed the study. Overall, TAF was well tolerated, no one discontinued the therapy due to adverse events (0/239, 0%, 95% confidence interval [CI] 0%–1.6%), and no infant had congenital defects or malformations at delivery (0/231, 0%, 95% CI 0%–1.6%). The infants' physical development at birth (n = 231) and at 7 months (n = 222) was normal. Furthermore, 97.0% (224/231, 95% CI 93.9%–98.5%) of women achieved HBV DNA <5.3 log10 IU/mL at delivery. The intention-to-treat and per-protocol infants' HBV-MTCT rates were 7.1% (17/239, 95% CI 4.5%–11.1%) and 0% (0/222, 95% CI 0%–1.7%) at the age of 7 months. Comparatively, 15.1% (18/119, 95% CI 9.8%–22.7%) vs 18.3% (22/120, 95% CI 12.4%–26.2%) of women in the 2 groups had mildly elevated alanine aminotransferase levels at 3 months and 6 months postpartum, respectively (P = 0.507); notably, no one experienced alanine aminotransferase flare (0% [0/119, 95% CI 0%–3.1%] vs 0% [0/120, 0%–3.1%]).DISCUSSION:Maternal TAF prophylaxis to prevent HBV-MTCT is generally safe and effective, and expected 8-week prenatal duration is feasible. ClinicalTrials.gov, NCT04850950.

The steel bar connection is an important and inevitable work in civil engineering. The traditional overlapped connection method usually needs to place the transversal rebars in the overlapped splicing area to restrict the splitting cracks in concrete. The steel usage and labor cost are increased. An improved splice, which is the hybrid connection of welding and overlapping, was developed for mid-diameter bars, which is easy to install and has commendable mechanical behavior. A series of reinforcing rebar splice tests with steel-concrete interaction were conducted. The failure model of hybrid connection and the ultimate strength were acquired. Based on the tests, the failure mechanism of hybrid connections was analyzed. The results show that the ultimate load of the new splice is sufficient for the engineering application and the failure model is reasonable. The hybrid connection could be used in the engineering practice.

Commercial grade-70 tire cord steel was microalloyed with V and N to explore the possibility of substitu- ting V for C and the effect of V and N on cementite dissolution during cold drawing process. Tensile strength, elon- gation and torsion laps of cold-drawn wires were determined. Microstructures of secondary phases were studied by transmission electron microscopy （TEM） and energy dispersive spectroscopy （EDS）. Saturation magnetization was measured by using a vibrating sample magnetometer （VSM） to evaluate cementite dissolution during cold drawing process. Experimental results showed that with the increase of V content, tensile strength increased, elongation slightly decreased, and the torsion laps of the cold-drawn wires decreased. Results also showed that with the increase of N content, a peak （increasing first and then decreasing） appeared in the tensile strength graph, and an increase of elongation and a decrease of torsion laps of the cold-drawn wires occured. N is soluble in ferrite when its content is low. The increase in the content of N to 82 × 10^-6 will result in the precipitation of the V-containing secondary pha- ses. Also, cementite tended to be stable during cold drawing process with the increase of V and N contents. Grade-80 tire cord steel can be replaced by grade 70 tire cord steel microalloyed with 0. 086 mass% V.

To identify false-positive SARS-CoV-2 test results caused by novel coronavirus inactivated vaccine contamination, a novel RT-qPCR targeting the ORF1ab and N genes of SARS-CoV-2 and Vero gene was developed. The amplification efficiency, precision, and lower limit of detection (LLOD) of the RT-qPCR assay were determined. A total of 346 clinical samples and 132 environmental samples were assessed, and the diagnostic performance was evaluated. The results showed that the amplification efficiency of the ORF1ab, N, and Vero genes was 95%, 97%, and 93%, respectively. The coefficients of variation of Ct values at a concentration of 3 × 104 copies/mL were lower than 5%. The LLOD for the ORF1ab, N, and Vero genes reached 8.0, 3.3, and 8.2 copies/reaction, respectively. For the 346 clinical samples, our RT-qPCR assay identified SARS-CoV-2-positive and SARS-CoV-2-negative samples with a sensitivity of 100.00% and a specificity of 99.30% and novel coronavirus inactivated vaccine-contaminated samples with a sensitivity of 100% and a specificity of 100%. For the environmental samples, our RT-qPCR assay identified novel coronavirus inactivated vaccine-contaminated samples with a sensitivity of 88.06% and a specificity of 95.38%. In conclusion, the RT-qPCR assay we established can be used to diagnose COVID-19 and, to a certain extent, false-positive results due to vaccine contamination.

Quantum key distribution (QKD) promises theoretically secure communication. However, it encounters challenges in implementation security and performance due to inevitable device imperfections. Since the proposal of measurement-device-independent (MDI) QKD, the critical step toward practical security is to secure QKD with imperfect sources. The source imperfections manifest as state-preparation uncertainty (SPU) in various aspects, e.g., encoding uncertainty, intensity fluctuation, and imperfect vacuum states. Here, we perform an MDI-QKD experiment and achieve both high practical security and superior performance. We address the general form of SPU and guarantee a tight estimation of the secret key rate based on the operator dominance method. We achieve secure key distribution over 303.37 km, which not only represents the farthest distance in experiments involving SPU but also considers the most SPU scenarios. Our experimental results represent a significant step toward promoting practical and secure quantum communication.

The aim of this study was to review the diagnosis and operative management of cases of high-grade pancreatic trauma. A retrospective analysis was performed on 14 patients treated for high-grade pancreatic trauma at our institution between December 2008 and November 2013. The patients were treated for injuries resulting from blunt abdominal trauma. The main clinical data of the patients was analyzed, including time to diagnosis, initial serum amylase level, ultrasonography and abdominal computed tomography (CT) findings, pancreatic injury severity as scored according to the American Association for the Surgery of Trauma Organ Injury Scale, injury to other organs, operative treatment method, postoperative complications, and patient outcome. All 14 patients were diagnosed with severe (≥ grade III) pancreatic trauma. Diagnosis was confirmed in all seven hemodynamically stable patients that underwent CT and in 9/13 patients receiving ultrasound examination. All patients underwent surgical operations, including emergency pancreaticoduodenectomy ( n  = 8), splenectomy with distal pancreatectomy ( n  = 3), spleen-preserving distal pancreatectomy ( n  = 1), medial pancreatectomy with Roux-en-Y pancreaticojejunostomy ( n  = 1), and peripancreatic debridement and drainage ( n  = 1). Diagnosis was delayed beyond 24 h in two patients, both of whom underwent reoperative peripancreatic debridement and drainage, with one death. The complications included pancreatic fistula ( n  = 8), peripancreatic abscess ( n  = 2), hepatic artery hemorrhage ( n  = 1), gastrointestinal bleeding ( n  = 1), and intra-abdominal abscess ( n  = 1). CT is the most reliable method for diagnosing high-grade pancreatic trauma. Aggressive surgical therapy including pancreaticoduodenectomy is acceptable in hemodynamically stable patients.

Mode-pairing quantum key distribution (MP-QKD) is advantageous for long-distance secure communication, leveraging its simple implementation and quadratic scaling capacity. The post-measurement pairing in MP-QKD alleviates the photon-coincidence demands, which is essential for surpassing the fundamental limit to the key-rate transmission. In this work, we propose an improved decoy-state MP-QKD protocol featuring a flexible and efficient pairing strategy. We prove the security of the proposed scheme by presenting an entanglement model for decoy-state MP-QKD. The simulation results show that the secret key rate (SKR) can be enhanced among all distances. Notably, compared with the original scheme [Nature Communication 13, 3903 (2022)], the improvement of SKR is greater than 65\\% within 375 km in the asymptotic case and greater than 50\\% within 400 km in the finite case. And the achievable distance can be extended in the finite case, especially with a small block length. The simulation results demonstrate the high efficiency of the proposed scheme, which is expected to promote the practical applicability of MP-QKD. Furthermore, the entanglement model could provide a theoretical framework for further security and performance analysis of decoy-state MP-QKD.

For the unsorted database quantum search with the unknown fraction \\(\\lambda\\) of target items, there are mainly two kinds of methods, i.e., fixed-point or trail-and-error. (i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett. 113, 210501 (2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder's algorithm is actually in \\(O(1/\\sqrt{\\lambda_0})\\) rather than \\(O(1/\\sqrt{\\lambda})\\), where \\(\\lambda_0\\) is a known lower bound of \\(\\lambda\\). (ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder's algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in \\(\\lambda\\) for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides an new idea for the research on fixed-point and trial-and-error quantum search.

Quantum algorithms can enhance machine learning in different aspects. Here, we study quantum-enhanced least-square support vector machine (LS-SVM). Firstly, a novel quantum algorithm that uses continuous variable to assist matrix inversion is introduced to simplify the algorithm for quantum LS-SVM, while retaining exponential speed-up. Secondly, we propose a hybrid quantum-classical version for sparse solutions of LS-SVM. By encoding a large dataset into a quantum state, a much smaller transformed dataset can be extracted using quantum matrix toolbox, which is further processed in classical SVM. We also incorporate kernel methods into the above quantum algorithms, which uses both exponential growth Hilbert space of qubits and infinite dimensionality of continuous variable for quantum feature maps. The quantum LS-SVM exploits quantum properties to explore important themes for SVM such as sparsity and kernel methods, and stresses its quantum advantages ranging from speed-up to the potential capacity to solve classically difficult machine learning tasks.