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COVID-19 due to SARS-CoV-2 infection has had an enormous adverse impact on global public health. As the COVID-19 pandemic evolves, the WHO declared several variants of concern (VOCs), including Alpha, Beta, Gamma, Delta, and Omicron. Compared with earlier variants, Omicron, now a dominant lineage, exhibits characteristics of enhanced transmissibility, tropism shift toward the upper respiratory tract, and attenuated disease severity. The robust transmission of Omicron despite attenuated disease severity still poses a great challenge for pandemic control. Under this circumstance, its tropism shift may be utilized for discovering effective preventive approaches.This review aims to estimate the potential of green tea epigallocatechin gallate (EGCG), the most potent antiviral catechin, in neutralizing SARS-CoV-2 Omicron variant, based on current knowledge concerning EGCG distribution in tissues and Omicron tropism.EGCG has a low bioavailability. Plasma EGCG levels are in the range of submicromolar concentrations following green tea drinking, or reach at most low μM concentrations after pharmacological intervention. Nonetheless, its levels in the upper respiratory tract could reach concentrations as high as tens or even hundreds of μM following green tea consumption or pharmacological intervention. An approach for delivering sufficiently high concentrations of EGCG in the pharynx has been developed. Convincing data have demonstrated that EGCG at tens to hundreds of μM can dramatically neutralize SARS-CoV-2 and effectively eliminate SARS-CoV-2-induced cytopathic effects and plaque formation. Thus, EGCG, which exhibits hyperaccumulation in the upper respiratory tract, deserves closer investigation as an antiviral in the current global battle against COVID-19, given Omicron's greater tropism toward the upper respiratory tract.

High-performance all-solid-state fiber supercapacitors assembled with MXene/RGO/PEDOT:PSS hybrid fiber electrodes with radially oriented channels and an anti-freezing electrolyte exhibit excellent capacitance retention at ultralow temperatures.

Panonychus citri is a major citrus pest worldwide. The short life cycle and high reproductive potential of P. citri, combined with heavy acaricide use, have led to high levels of resistance to acaricides, posing a threat to global resistance management programs. Here, resistance monitoring was established to determine the pyridaben resistance status of ten P. citri populations in China from 2014 to 2021 using a leaf-dipping assay. Four characterized strains-the susceptible strain (Lab_S), the resistant strain (Pyr_R), as well as the segregated resistant strain (Pyr_Rs) and the segregated susceptible strain (Pyr_Control) derived from the crossing of the Lab_S and Pyr_R strains, were used to evaluate the life-history characteristics using age-stage, two-sex life tables.Most P. citri populations developed high resistance to pyridaben. Resistance levels exceeded 1000-fold in Yuxi, Anyue, Nanning, and Ganzhou populations compared with the Lab_S strain. Compared with Pyr_Control, two key fitness cost criteria, developmental period and fecundity, showed significant differences in Pyr_Rs under consistent conditions. The intrinsic rate of increase, net reproductive rate and gross reproductive rate were lower in the resistant strain compared with the Pyr_Control strain. The Pyr_Rs strain had a lower relative fitness of 0.934 compared with the Pyr_Control. Moreover, the life-history traits and population parameters of the Pyr_R strain also showed significant differences compared with the Lab_S strain.The resistance levels to pyridaben varied greatly among the different P. citri populations and showed regional differences. Substantial fitness costs are associated with pyridaben resistance. This study provides potential implications for developing strategies for resistance management in P. citri. © 2022 Society of Chemical Industry.

A decreased estimated glomerular filtration rate (eGFR) is associated with frailty, but the association between kidney function and frailty using multidimensional assessments has not been entirely examined. We aimed to investigate whether albuminuria and the eGFR using different biomarkers were associated with frailty.A total of 1830 older adults were included. Kidney function was assessed by the eGFR (based on combined creatinine-cystatin C [eGFRAt baseline, kidney function was associated with prevalent frailty. During the 2-year follow-up, a decreased eGFR (per 10 units) was associated with an increased risk of incident frailty using the FP (eGFRKidney function decline and CKD were associated with an increased risk of prevalent and incident frailty in older adults. Physicians should pay more attention to monitoring frailty status in older adults with CKD, even in those with kidney function decline.

Leather manual inspection is common in many industries, these methods are low efficiency and cannot be in line with automated manufacturing. In this paper, we propose a leather automated defect inspection (LADI) method based on machine learning and establish a practical LADI system composed of four modules: image acquisition, image preprocessing, image segmentation, and post-processing. The LADI method which forms the image segmentation module is a combination of multi-layer perceptron (MLP) and principal component analysis (PCA), namely MLPPCA. We propose two new algorithms that image preprocessing and post-processing to enhance the image quality and enrich details of the segmentation result. In the result analysis, compare MLPPCA, MLP, KNN, SVMRBF, GMM, show that MLPPCA has strong competitiveness in performance and execution time. The LADI system has been used in a China leather factory, the feedback shows that it combines the advantages of high inspection accuracy and short execution time. &nbsp

This study analyzed data from the National COVID Cohort Collaborative (N3C) database to investigate whether high-density lipoprotein (HDL) and its major protein component, apolipoprotein A1 (apoA1), are associated with severe COVID-19 sequelae, specifically acute kidney injury (AKI) and severe COVID-19 disease as defined by the infection resulting in hospitalization, extracorporeal membrane oxygenation (ECMO), invasive ventilation, or death. Our study included a total of 1,415,302 subjects with HDL values and 3589 subjects with apoA1 values. Higher levels of both HDL and apoA1 were associated with a lower incidence of infection as well as a lower incidence of severe disease. Higher HDL levels were also associated with a lower incidence of developing AKI. Most comorbidities were negatively correlated with SARS-CoV-2 infection, presumably due to the behavioral changes that occurred as a result of the precautions taken by individuals with underlying comorbidities. The presence of comorbidities, however, was associated with developing severe COVID-19 disease and AKI. African American and Hispanic populations experienced worse outcomes, including a higher incidence of infection and the development of severe disease, as well as AKI. Smoking and being male were associated with a lower incidence of infection, while they were risk factors for the development of severe disease and AKI. The results on cholesterol and diabetes drugs warrant further research, given that the database included multiple drugs in each category impeding for analysis of specific medications. Despite the current limitations in the N3C data, this study is the first to investigate the roles of HDL and apoA1 on the outcomes of COVID-19 using the US population data.

Background Psychiatric illnesses affect outcomes in trauma. Studies have examined the relationship between depression, schizophrenia, post-traumatic stress disorder, and other mental disorders with trauma, yet few have examined attention-deficit-hyperactivity disorder (ADHD). Attention-deficit-hyperactivity disorder has been suggested to increase the risk of injury, but severity and outcomes of the injury are not frequently studied. The relationship of additional psychiatric disorders in patients with ADHD to traumatic injury was also examined in this study. Methods A 5-year retrospective analysis was performed using the trauma registry of an urban ACS verified level 1 trauma center. Patients with ADHD were separated into ADHD Only and ADHD+ (having additional psychiatric comorbidities) and compared to a matched population of non-ADHD patients and patients with non-ADHD psychiatric disorders to analyze their demographics and outcomes. Descriptive statistics were used to analyze the data as appropriate. Results Seventy-three patients with ADHD were identified, with over half having additional psychiatric comorbidities (58.9%). The majority of ADHD patients were White (54.8%) vs Black (61.6%) at admission. At admission non-ADHD patients had significantly fewer psychiatric comorbidities (11%) compared to ADHD patients (58.9%). ADHD with psychiatric comorbidities patients had significantly higher ISS and longer hospital LOS. However, GCS and ICU LOS were not different between the two groups. Conclusions Patients with ADHD were significantly more likely to have psychiatric comorbidities and experience worse outcomes compared to patients without ADHD.

Ipsilateral axillary lymphadenopathy is a well-documented finding associated with COVID-19 vaccination. Varying guidelines have been published for the management of asymptomatic patients who have a history of recent vaccination and present with incidental lymphadenopathy at screening mammography. Some experts recommend follow-up imaging, and others suggest that clinical management, rather than repeat imaging or biopsy, is appropriate. Symptomatic patients with lymphadenopathy and/or additional abnormal imaging findings should be treated differently depending on risk factors and clinical scenarios. Although ipsilateral lymphadenopathy is well documented, ipsilateral breast edema after COVID-19 vaccination has been rarely reported. The combination of ipsilateral lymphadenopathy and diffuse breast edema after COVID-19 vaccination presents a clinical management challenge because edema can obscure underlying abnormalities at imaging. For symptomatic patients with lymphadenopathy and associated breast parenchymal abnormality, prompt action is appropriate, including diagnostic evaluation and consideration of tissue sampling. This approach may prevent delays in diagnosis and treatment of patients with malignancy masked by symptoms from the vaccination.

Purpose: This study investigates the association between body composition change during concurrent chemoradiotherapy (CCRT) and outcome in patients with locally advanced cervical cancer (LACC).Experimental Design: Pre- and posttreatment CT images of 245 patients with LACC who were treated between 2004 and 2015 were analyzed. Skeletal muscle index (SMI) and density (SMD), subcutaneous adipose tissue index (SATI), and visceral adipose tissue index (VATI) were measured from two sets of CT images at the level of the L3 vertebra. Sarcopenia and a low SMD were defined using published cut-off points. Predictors of overall survival (OS) and cancer-specific survival (CSS) were analyzed using Cox regression models.Results: The median follow-up was 62.7 (range, 7.3–152.3) months. Among the 245 patients, 127 (51.8%) had pretreatment sarcopenia, and 154 (62.9%) had a low SMD. SMI did not decrease significantly during CCRT, 0.6%/150 days [95% confidence interval (CI), −1.8–0.6; P = 0.35]. However, SMI loss during CCRT of >10.0%/150 days was independently associated with poorer OS (HR, 6.02; 95% CI, 3.04–11.93; P < 0.001) and CSS (HR, 3.49; 95% CI, 1.44–8.42; P = 0.006) when adjusted for FIGO stage, pathology, and treatment. Pretreatment sarcopenia and change of SMD, SATI, and VATI during CCRT were not associated with survival.Conclusions: Skeletal muscle measurements could be imaging biomarkers to predict outcomes for patients with LACC in clinical practice. Further studies are needed to determine whether multimodal interventions can preserve skeletal muscle mass and thereby improve survival. Clin Cancer Res; 24(20); 5028–36. ©2018 AACR.

Supplementary Table S1 Patient and tumour characteristics according to muscle change (n = 245); Supplementary Table S2 Univariable Cox proportional hazards model for overall survival and cancer-specific survival (n = 245); Supplementary Table S3 Univariable and multivariable Cox proportional hazards model for overall survival and cancer-specific survival for patients with squamous cell carcinoma (n = 215); Supplementary Table S4 Acute toxicities by SATI and VATI groups (n = 245).

Kaplan-Meier curve demonstrating overall survival and cancer-specific survival for overall patients (n = 245) according to (A, B) pre-treatment skeletal muscle index, (C, D) pre-treatment skeletal muscle density , (E, F) subcutaneous adipose tissue index, (G, H) visceral adipose tissue index groups. SMD, skeletal muscle density; SMI, skeletal muscle index; SATI, subcutaneous adipose tissue index; VATI visceral adipose tissue index.

Kaplan-Meier curve demonstrating overall survival and cancer-specific survival for patients with squamous cell carcinoma (n = 215) according to (A, B) pre-treatment skeletal muscle index, (C, D) pre-treatment skeletal muscle density, (E, F) skeletal muscle change, (G, H) subcutaneous adipose tissue index, (I, J) visceral adipose tissue index groups. SMD, skeletal muscle density; SMI, skeletal muscle index; SATI, subcutaneous adipose tissue index; VATI visceral adipose tissue index.

The intraobserver reproducibility was tested by analysing data from 80 subjects randomly selected from this cohort. The measurements were repeated at two time points at least 1 month apart. ICC, intraclass correlation coefficients; CI, confidence interval.

During the COVID-19 pandemic, the value of palliative care has become more evident than ever. The current study quantitatively investigated the perceptions of palliative care emerging from the pandemic experience by analyzing a total of 26,494 English Tweets collected between 1 January 2020 and 1 January 2022. Such an investigation was considered invaluable in the era of more people sharing and seeking healthcare information on social media, as well as the emerging roles of palliative care. Using a web scraping method, we reviewed 6000 randomly selected Tweets and identified four themes in the extracted Tweets: (1) Negative Impact of the Pandemic on Palliative Care; (2) Positive Impact of the Pandemic on Palliative Care; (3) Recognized Benefits of Palliative Care; (4) Myth of Palliative Care. Although a large volume of Tweets focused on the negative impact of COVID-19 on palliative care as expected, we found almost the same volume of Tweets that were focused on the positive impact of COVID-19 on palliative care. We also found a smaller volume of Tweets associated with myths about palliative care. Using these manually classified Tweets, we trained machine learning (ML) algorithms to automatically classify the remaining tweets. The automatic classification of Tweets was found to be effective in classifying the negative impact of the COVID-19.

Power and energy is the first-class design constraint for multi-core processors and is a limiting factor for future-generation supercomputers. While modern processor design provides a wide range of mechanisms for power and energy optimization, it remains unclear how software can make the best use of them. This article presents a novel approach for runtime power optimization on modern multi-core systems. Our policy combines power capping and uncore frequency scaling to match the hardware power profile to the dynamically changing program behavior at runtime. We achieve this by employing reinforcement learning (RL) to automatically explore the energy-performance optimization space from training programs, learning the subtle relationships between the hardware power profile, the program characteristics, power consumption and program running times. Our RL framework then uses the learned knowledge to adapt the chip's power budget and uncore frequency to match the changing program phases for any new, previously unseen program. We evaluate our approach on two computing clusters by applying our techniques to 11 parallel programs that were not seen by our RL framework at the training stage. Experimental results show that our approach can reduce the system-level energy consumption by 12 percent, on average, with less than 3 percent of slowdown on the application performance. By lowering the uncore frequency to leave more energy budget to allow the processor cores to run at a higher frequency, our approach can reduce the energy consumption by up to 17 percent while improving the application performance by 5 percent for specific workloads.

A series of dithioalkylated methylidenyl cyclopentadithiophene-based quinoidal small molecules (CDTSQs) with different side chain lengths were designed for n-type OFETs, reaching electron mobility of 0.14 cm2 V−1 s−1 with good ambient stability.

Although wood-derived carbon (WC) and its derivatives are promising electrodes for supercapacitors because of their hierarchically porous architecture, superior mechanical flexibility, and environmental friendliness, pure WC electrodes usually exhibit poor wettability, inferior areal capacitance, and unsatisfactory electronic conduction. Herein, hierarchically porous graphene/wood-derived carbon (GWC) aerogels are fabricated for high-performance supercapacitor electrodes by chemical reduction of graphene oxide/wood hydrogels followed by directional-freezing, freeze-drying, and carbonization at 1000 oC. An activated GWC (AGWC) anode is prepared by activating the GWC with ZnCl2 to create more mass transport paths and increase wettability; while the cathode is synthesized by in situ growth of NiCo2O4 (NCO) in the channels of the GWC to bring about pseudocapacitance and increase energy storage sites. The resultant NCO@GWC cathode and AGWC anode exhibit superior capacitances of 8540 and 10965 mF cm-2 (854 and 183 F g-1) at 1 mA cm-2, respectively. An assembled NCO@GWC//AGWC asymmetric supercapacitor exhibits a superior areal capacitance of 7116 mF cm-2 at 1 mA cm-2, a high energy density of 2.2 mWh cm-2 (5.6 mWh cm-3), a power density of 45.1 mW cm-2 (112.8 mW cm-3), and an excellent cyclic stability of 100% capacitance retention over 1000 cycles at 10 mA cm-2.

Instruction: Rift valley fever virus (RVFV) is a mosquito-transmitted bunyavirus that causes severe disease in animals and humans. Nevertheless, there are no vaccines applied to prevent RVFV infection for human at present. Therefore, it is necessary to develop a safe and effective RVFV vaccine.Methods: We generated Ad5-GnGcopt, a replication-deficient recombinant Ad5 vector (human adenovirus serotype 5) expressing codon-optimized RVFV glycoproteins Gn and Gc, and evaluated its immunogenicity and protective efficacy in mice.Results and Discussion: Intramuscular immunization of Ad5-GnGcopt in mice induces strong and durable antibody production and robust cellular immune responses. Additionally, a single vaccination with Ad5-GnGcopt vaccination can completely protect interferon-α/β receptor-deficient A129 mice from lethal RVFV infection. Our work indicates that Ad5-GnGcopt might represent a potential vaccine candidate against RVFV. However, further research is needed, first to confirm its efficacy in a natural animal host, and ultimately escalate as a potential vaccine candidate for humans.

The primary goal of this retrospective study is to understand how the COVID-19 pandemic differentially impacted transplant status across race, sex, age, primary insurance, and geographic regions by examining which candidates: (i) remained on the waitlist, (ii) received transplants, or (iii) were removed from the waitlist due to severe sickness or death on a national level. Methods: The trend analysis aggregated by monthly transplant data from 1 December 2019 to 31 May 2021 (18 months) at the transplant center level. Ten variables about every transplant candidate were extracted from UNOS standard transplant analysis and research (STAR) data and analyzed. Characteristics of demographical groups were analyzed bivariately using t-test or Mann–Whitney U test for continuous variables and using Chi-sq/Fishers exact tests for categorical variables. Results: The trend analysis with the study period of 18 months included 31,336 transplants across 327 transplant centers. Patients experienced a longer waiting time when their registration centers in a county where high numbers of COVID-19 deaths were observed (SHR < 0.9999, p < 0.01). White candidates had a more significant transplant rate reduction than minority candidates (−32.19% vs. −20.15%) while minority candidates were found to have a higher waitlist removal rate than White candidates (9.23% vs. 9.45%). Compared to minority patients, White candidates’ sub-distribution hazard ratio of the transplant waiting time was reduced by 55% during the pandemic period. Candidates in the Northwest United States had a more significant reduction in the transplant rate and a greater increase in the removal rate during the pandemic period. Conclusions: Based on this study, waitlist status and disposition varied significantly based on patient sociodemographic factors. During the pandemic period, minority patients, those with public insurance, older patients, and those in counties with high numbers of COVID-19 deaths experienced longer wait times. In contrast, older, White, male, Medicare, and high CPRA patients had a statistically significant higher risk of waitlist removal due to severe sickness or death. The results of this study should be considered carefully as we approach a reopening world post-COVID-19, and further studies should be conducted to elucidate the relationship between transplant candidate sociodemographic status and medical outcomes during this era.

Gaussian boson sampling (GBS) is not only a feasible protocol for demonstrating quantum computational advantage, but also mathematically associated with certain graph-related and quantum chemistry problems. In particular, it is proposed that the generated samples from the GBS could be harnessed to enhance the classical stochastic algorithms in searching some graph features. Here, we use Jiuzhang, a noisy intermediate-scale quantum computer, to solve graph problems. The samples are generated from a 144-mode fully-connected photonic processor, with photon-click up to 80 in the quantum computational advantage regime. We investigate the open question of whether the GBS enhancement over the classical stochastic algorithms persists -- and how it scales -- with an increasing system size on noisy quantum devices in the computationally interesting regime. We experimentally observe the presence of GBS enhancement with large photon-click number and a robustness of the enhancement under certain noise. Our work is a step toward testing real-world problems using the existing noisy intermediate-scale quantum computers, and hopes to stimulate the development of more efficient classical and quantum-inspired algorithms.

Lichens are important sources of versatile bioactive compounds. Two new dibenzofurans (1–2), a multi-substituted single benzene ring (3), and two organic acid compounds (4–5) along with 25 known compounds (6–30) were isolated from the lichen Usnea diffracta Vain. Their structures were identified by physicochemical properties and spectral analyses. Compounds 1–30 were tested for inhibitory activities against Staphylococcus aureus, Escherichia coli, and Candida albicans by the disk diffusion method and microdilution assay respectively. Compound 3 showed moderate inhibitory activities against S. aureus and E. coli with the inhibition zone (IZ) of 6.2 mm and 6.3 mm, respectively. Depside 10 exhibited good activity against S.aureus and C. albicans with 6.6 mm and 32 μg/ml, respectively. The acetylcholinesterase inhibitory activities of compounds 1, 2, and 6–8 with the characteristic dibenzofuran scaffold were evaluated var anti-AChE assay and a molecular docking study. Compound 2 could better inhibit AChE at the concentration of 0.3 μmol/ml with a value of 61.07 ± 0.85%. The molecular docking study also demonstrated that compound 2 had the strongest binding affinity among the five dibenzofurans, and the “-CDOCKER Energy” value was 14.4513 kcal/mol.

Additional file 1: Table S1. Information of volunteers. Table S2. Information for antibodies. Table S3. Table of materials for western blotting. Table S4. Primers used in this study. Table S5. The parameters of radiography images. Table S6. Information of assays/instruments/software used in this study.

Inspired by the success of recent vision transformers and large kernel design in convolutional neural networks (CNNs), in this paper, we analyze and explore essential reasons for their success. We claim two factors that are critical for 3D large-scale scene understanding: a larger receptive field and operations with greater non-linearity. The former is responsible for providing long range contexts and the latter can enhance the capacity of the network. To achieve the above properties, we propose a simple yet effective long range pooling (LRP) module using dilation max pooling, which provides a network with a large adaptive receptive field. LRP has few parameters, and can be readily added to current CNNs. Also, based on LRP, we present an entire network architecture, LRPNet, for 3D understanding. Ablation studies are presented to support our claims, and show that the LRP module achieves better results than large kernel convolution yet with reduced computation, due to its nonlinearity. We also demonstrate the superiority of LRPNet on various benchmarks: LRPNet performs the best on ScanNet and surpasses other CNN-based methods on S3DIS and Matterport3D. Code will be made publicly available.

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ~ 600 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years., submitted on 10 April

Additional file 2: Figure S1. The immunofluorescence images and quantitative analysis of fluorescence intensity of TLR9 and NF-κB. Figure S2. The immunofluorescence images and quantitative analysis of fluorescence intensity of PLA (mtDNA-TLR9). Figure S3. The immunofluorescence images and quantitative analysis of fluorescence intensity of dsDNA.

In terms of ocean tide visualization, to meet the requirement of both display range and operational efficiency, an advanced method is proposed, in which the tide height is rapidly computed with global tide model EOT10a, and dynamically displayed by OpenGL. Aiming at the large amounts of calculation of global tide height, the feature of multicore processor is integrated into the method. The experiment shows that, compared to a single-core processor, when using a 6-core processor, the speedup ratio is about 5.4, parallel efficiency reaches 90%, and 880 000 tide heights can be calculated per second. Eventually, the result would be output as a tide height graph by OpenGL. This method could be a useful tool for marine cartography due to the large display range and the high efficiency.