[Component identification and analysis in vivo of Sanhan Huashi formula].

Sanhan Huashi formula(SHF) is the intermediate of a newly approved traditional Chinese medicine(TCM) Sanhan Huashi Granules for the treatment of COVID-19 infection. The chemical composition of SHF is complex since it contains 20 single herbal medicines. In this study, UHPLC-Orbitrap Exploris 240 was used to identify the chemical components in SHF and in rat plasma, lung and feces after oral administration of SHF, and heat map was plotted for characterizing the distribution of the chemical components. Chromatographic separation was conducted on a Waters ACQUITY UPLC BEH C_(18)(2.1 mm×100 mm, 1.7 µm) using 0.1% formic acid(A)-acetonitrile(B) as mobile phases in a gradient elution. Electrospray ionization(ESI) source was used to acquire data in positive and negative mode. By reference to quasi-molecular ions and MS/MS fragment ions and in combination with MS spectra of reference substances and compound information in literature reports, 80 components were identified in SHF, including 14 flavonoids, 13 coumarins, 5 lignans, 12 amino-compounds, 6 terpenes and 30 other compounds; 40 chemical components were identified in rat plasma, 27 in lung and 56 in feces. Component identification and characterization of SHF in vitro and in vivo lay foundations for disclosure of its pharmacodynamic substances and elucidation of the scientific connotation.

Optimization of multistage timeliness transit consolidation problem using adaptive-weighted genetic algorithm.

Cargo consolidation is becoming a crucial part of international transportation and changing the customer consumption patterns of the international community. Poor connections between different operations and the delay of international express have motivated sellers and logistics organizers to put timeliness first in international multimodal transport, especially during the COVID-19 epidemic. However, for cargo with small quality and multiple batches, designing an efficient consolidation network presents a set of unique challenges, including the coupling of multiple origins and destinations (ODs), and fully utilizing the capacity of the container. We defined a multistage timeliness transit consolidation problem to decouple the multiple ODs of the logistics resource. By solving this problem, we can increase the connectivity between different phases and make full use of the container. To make this systematic multistage transit consolidation more flexible, we proposed a two-stage adaptive-weighted genetic algorithm that mainly focuses on the edge area of the Pareto front space and the diversity of the population. Computational experiments indicate that the correlation between parameters has certain regular trends, and appropriate parameter settings can lead to more satisfactory results. We also confirm that the pandemic has a giant influence on the market share of different transportation modes. Moreover, the comparison with other approaches demonstrates the feasibility and effectiveness of the proposed method.

A Randomized, Double-Blind, Placebo-Controlled Phase II Study to Evaluate the Efficacy and Safety of Ivarmacitinib (SHR0302) in Adult Patients with Moderate to Severe Alopecia Areata.

BACKGROUND: Alopecia areata (AA) is a CD8+ T cell mediated autoimmune disease characterized by non-scarring hair loss. Ivarmacitinib, a selective oral Janus kinase 1 (JAK1) inhibitor, may interrupt certain cytokine signaling implicated in the pathogenesis of AA. OBJECTIVE: To evaluate the efficacy and safety of ivarmacitinib in adult AA patients who have ≥25% scalp hair loss. METHODS: Eligible patients were randomized 1:1:1:1 to receive ivarmacitinib 2 mg, 4 mg, or 8 mg QD or placebo for 24 weeks. The primary endpoint was percentage change from baseline in Severity of Alopecia Tool (SALT) score at week 24. RESULTS: A total of 94 patients were randomized. At week 24, the least squares mean (LSM) difference in percentage change from baseline in SALT score for ivarmacitinib 2 mg,4 mg, 8 mg, and placebo groups were -30.51% (90% confidence interval [CI]: -45.25, -15.76), -56.11% (90% CI: -70.28, -41.95), -51.01% (90% CI: -65.20, -36.82) and -19.87% (90% CI: -33.99, -5.75), respectively. Two SAEs, follicular lymphoma, and COVID-19 pneumonia were reported. LIMITATIONS: Small sample size limits the generalizability of the results. CONCLUSION: Treatment with ivarmacitinib 4 mg and 8 mg doses in moderate and severe AA patients for 24 weeks was efficacious and generally tolerated.

Real-Time Monitoring and Early Warning of a Cytokine Storm In Vivo Using a Wearable Noninvasive Skin Microneedle Patch.

A cytokine storm may be the last attack of various diseases, such as sepsis, cancer, and coronavirus disease 2019, that can be life threatening. Real-time monitoring of cytokines in vivo is helpful for assessing the immune status of patients and providing an early warning of a cytokine storm. In this study, a functional carbon nanotube biointerface-based wearable microneedle patches for real-time monitoring of a cytokine storm in vivo via electrochemical analysis are reported. This wearable system has sensitivity with a detection limit of 0.54 pg mL-1 , high specificity, and 5 days of stability with a coefficient of variation of 4.0%. The system also has a quick response of several hours (1-4 h) to increasing cytokines. This wearable microneedle patch may offer a promising route for real-time biomolecule wearables construction. The patch is also the first reported integrated capture and monitoring system that is capable of real-time measurement of protein markers in interstitial fluid.

Boronic acid-modified bacterial cellulose microspheres as packing materials for enveloped virus removal.

Viruses are the most abundant microorganisms on the earth, their existence in contaminated waters possesses a significant threat to humans. Waterborne viral infections could be fatal to sensitive population including young child, the elderly, and the immune-compromised. It is imperative to remove viruses during water treatment to better protect public health, especially in the light of evidence of detection of coronaviruses genetic fragments in raw sewage. We reported bench-scale experiments evaluating the extent and mechanisms of removal of a model virus (spring viremia of carp virus, SVCV) in water by adsorption. Microspheres made by boronic acid-modified bacterial cellulose with excellent mechanical strength were successfully fabricated as packing materials for the column to remove glycoproteins and enveloped viruses from water. The synthesized adsorbent was characterized by attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Brunauer Emmett Teller (BET) measurement. The adsorption efficiency of glycoproteins was investigated by SDS-PAGE and the Broadford protein assay, while the binding capacity with the virus (spring viremia of carp virus) was monitored by cell culture to calculate the viral cytopathic effect and viral titer caused by the virus. The data obtained from the above experiments showed that ∼3-log removal of SVCV in 3 h, which significantly reduced the virus concentration from microspheres packed column. The present study provides substantial evidence to prove beyond doubt that material based on bacterial cellulose seems to have the potential for virus removal from water which can be extended to systems of significant importance.

Disease-related compound identification based on deeping learning method.

Acute lung injury (ALI) is a serious respiratory disease, which can lead to acute respiratory failure or death. It is closely related to the pathogenesis of New Coronavirus pneumonia (COVID-19). Many researches showed that traditional Chinese medicine (TCM) had a good effect on its intervention, and network pharmacology could play a very important role. In order to construct "disease-gene-target-drug" interaction network more accurately, deep learning algorithm is utilized in this paper. Two ALI-related target genes (REAL and SATA3) are considered, and the active and inactive compounds of the two corresponding target genes are collected as training data, respectively. Molecular descriptors and molecular fingerprints are utilized to characterize each compound. Forest graph embedded deep feed forward network (forgeNet) is proposed to train. The experimental results show that forgeNet performs better than support vector machines (SVM), random forest (RF), logical regression (LR), Naive Bayes (NB), XGBoost, LightGBM and gcForest. forgeNet could identify 19 compounds in Erhuang decoction (EhD) and Dexamethasone (DXMS) more accurately.

Economic value and characteristics of cloud pharmacy for children based on internet hospital in western China during the COVID-19 pandemic: Cross-sectional survey study.

Background: Online health care services have been encouraged by the Chinese government in recent years, and the COVID-19 pandemic catalyzed the rapid growing of internet hospitals. As an integral part of online health care services, little is known about the economic value and characteristics of cloud pharmacy especially for children. This study aimed to reveal the economic value and comprehensive characteristics of pediatric cloud pharmacy during the COVID-19 pandemic in a tertiary children's hospital in western China. Methods: A total of 33,254 online prescriptions over the course of February 2020 through December 2021 were analyzed with respect to the user profiles, diseases, consulting behaviors, distribution of departments, delivery region and distance, drug information and degree of satisfaction. The cost savings for patients calculated lost wages and the high-speed railway fees for transport to and from hospital. Results: A total of 33,254 prescriptions, including 56,216 drugs were delivered to 27 provinces and municipalities of China. The internet cloud pharmacy saved a total of more than RMB 11.17 million in financial costs for patients. Of the 33,254 delivered prescriptions, 50.40% were sent to Chongqing Province, the top 5 provinces for out-of-province prescription deliveries were Sichuan (37.77%), Guizhou (8.00%), Yunnan (1.18%), Hubei (0.66%) and Guangdong (0.42%). In terms of department distribution, neurology (31.7%), respiratory (15.0%) and endocrinology (14.6%) were the top three departments. Epilepsy (16.2%), precocious puberty (10.3%) and asthma (8.7%) were the top three frequently consulted diseases. The peak times of day for online prescriptions occurred at 9 AM and 8 PM. 99.67% of users gave full marks for their internet counseling. Conclusion: The pediatric cloud pharmacy is efficient, cost-saving and convenient for children with chronic disease or mild symptoms during the COVID-19 pandemic. The widespread use of this pediatric cloud pharmacy can help alleviating pressure on offline hospitals and facilitated people's lives beyond geographical and time-related limitations. Further efforts are needed to be made to improve the quality and acceptance of pediatric cloud pharmacy, as well as to regulate and standardize the management of this novel online health care service.

Computed tomography-aided diagnosis of COVID-19

Coronavirus disease (COVID-19) is highly infectious, has spread worldwide, and has a relatively high mortality rate. Early diagnosis and timely isolation are essential to control the spread of COVID-19. Computed tomography (CT) is considered to be an effective tool for the rapid diagnosis of COVID-19 and plays a key role in diagnosis, clinical course monitoring, and the evaluation of treatment outcomes. Artificial intelligence (AI) has emerged as a useful technology for early diagnosis, lesion quantification, and prognosis evaluation in patients with COVID-19. In this review, we discuss the role of CT in the diagnosis of COVID-19, typical CT manifestations of COVID-19 throughout the disease course, differential diagnoses, and the application of AI as a diagnostic and therapeutic tool in this patient population.

COVID-19 in orthotopic heart transplant recipients and association with donor specific antibodies.

De novo donor-specific antibodies (DSAs) are associated with increased risk of antibody-mediated rejection and worse clinical outcomes after orthotopic heart transplant (OHT). No study has reported the production of DSAs after infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in an OHT population. In this retrospective study, we described coronavirus disease 2019 (COVID-19) incidence and clinical course in a large, contemporary OHT cohort. We showed that the case-fatality rate has significantly decreased since the early days of the pandemic, although remains higher than that of the general population. In addition, we found that 10% of OHT recipients developed de novo DSAs or experienced an increase in pre-existing DSAs after COVID-19, with the majority occurring in unvaccinated patients (15% vs 2%). Further studies are necessary to substantiate our findings in an external cohort.

Disease-Ligand Identification Based on Flexible Neural Tree.

In order to screen the disease-related compounds of a traditional Chinese medicine prescription in network pharmacology research accurately, a new virtual screening method based on flexible neural tree (FNT) model, hybrid evolutionary method and negative sample selection algorithm is proposed. A novel hybrid evolutionary algorithm based on the Grammar-guided genetic programming and salp swarm algorithm is proposed to infer the optimal FNT. According to hypertension, diabetes, and Corona Virus Disease 2019, disease-related compounds are collected from the up-to-date literatures. The unrelated compounds are chosen by negative sample selection algorithm. ECFP6, MACCS, Macrocycle, and RDKit are utilized to numerically characterize the chemical structure of each compound collected, respectively. The experiment results show that our proposed method performs better than classical classifiers [Support Vector Machine (SVM), random forest (RF), AdaBoost, decision tree (DT), Gradient Boosting Decision Tree (GBDT), KNN, logic regression (LR), and Naive Bayes (NB)], up-to-date classifier (gcForest), and deep learning method (forgeNet) in terms of AUC, ROC, TPR, FPR, Precision, Specificity, and F1. MACCS method is suitable for the maximum number of classifiers. All methods perform poorly with ECFP6 molecular descriptor.

COVID-19 vaccination for patients with benign childhood epilepsy with centrotemporal spikes.

AIM: There is a high demand for information on COVID-19 vaccination for patients with childhood epilepsy with centrotemporal spikes (BECTS). Patients with this condition need a stable, daily life; unfortunately, the decision of vaccination is not easy for their parents. We evaluated patients with BECTS for symptoms and seizure control after COVID-19 vaccination. METHODS: We asked the caregivers of all patients who visited our hospital to report their vaccination status, and if vaccinated, their experience in terms of adverse effects and seizure control after the second dose of the four Chinese-approved COVID-19 vaccines. RESULTS: Seventy-seven children had received their second COVID-19 vaccine dose: 58 of 77 (75.3%) received Sinopharm (Beijing): BBIBP-CorV (Vero cells) and 16 (20.8%) received CanSino: Ad5-nCoV. Twenty of seventy-seven (25.97%) patients with BECTS reported having side effects; all effects were mild that could be relieved themselves. For Sinopharm (Beijing): BBIBP-CorV (Vero cells), the most frequent local side effect reported by the parents was pain at the site of injection (17.24%) and systematic side effect was fatigue (15.52%). For CanSino: Ad5-nCoV, the most reported local side effect was pain at the site of injection (6.25%). All parents reported that their child's side effects could be relieved by themselves. No patient reported status epilepticus or exacerbation of a pre-existing condition. If non-vaccinated, the cause of hesitation was explored: 40% of parents worried about inducing seizures, 19% of parents worried about vaccine side effects, 32% of parents worried about the vaccine-antiepileptic drug interactions, and 9% of parents feared for their child's physical condition. More than 34.1% of parents accepted that the decision to get the vaccine for their child was difficult. Over 90% of parents believe that research on the safety and tolerability of vaccination would help them to make the decision. CONCLUSION: Our data suggest that COVID-19 vaccination is well tolerated and safe in patients below 18 years of age having BECTS, thereby supporting the recommendation of vaccination.

Accurate identification of SARS-CoV-2 variant delta using graphene/CRISPR-dCas9 electrochemical biosensor.

Delta (B.1.617.2), a highly infectious variant of SARS-CoV-2, has been sweeping the world, and threatening the safety of human life seriously. It is urgent to develop a highly selective and sensitive assay to accurately identify the SARS-CoV-2 variant Delta. In this work, we constructed a graphene/CRISPR-dCas9 electrochemical biosensor to accurately identify SARS-CoV-2 variant Delta, where the signal was further amplified by embedded electrochemical probe [Ru(phen)2dppz]BF4. This detection assay could be finished within 47 min totally, with the detection limit of 1.2 pM and good reproducibility with a C·V.% of 2.48% (n = 5). And the biosensor could selectively identify Delta among SARS-CoV-2 and other variants, including Alpha, Beta, Gamma. This assay was further validated by 26 real clinical samples, showing 100% clinical sensitivity and 100% clinical specificity, which provides a new direction for identifying other SARS-CoV-2 variants in the future.

IgG antibody titers against SARS-CoV-2 nucleocapsid protein correlate with the severity of COVID-19 patients.

BACKGROUND: The 2019 novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) is a current worldwide threat for which the immunological features after infection need to be investigated. The aim of this study was to establish a highly sensitive and quantitative detection method for SARS-CoV-2 IgG antibody and to compare the antibody reaction difference in patients with different disease severity. RESULTS: Recombinant SARS-CoV-2 nucleocapsid protein was expressed in Escherichia coli and purified to establish an indirect IgG ELISA detection system. The sensitivity of the ELISA was 100% with a specificity of 96.8% and a 98.3% concordance when compared to a colloidal gold kit, in addition, the sensitivity of the ELISA was 100% with a specificity of 98.9% and a 99.4% concordance when compared to a SARS-CoV-2 spike S1 protein IgG antibody ELISA kit. The increased sensitivity resulted in a higher rate of IgG antibody detection for COVID-19 patients. Moreover, the quantitative detection can be conducted with a much higher serum dilution (1:400 vs 1:10, 1:400 vs 1:100). The antibody titers of 88 patients with differing COVID-19 severity at their early convalescence ranged from 800 to 102,400, and the geometric mean titer for severe and critical cases, moderate cases, asymptomatic and mild cases was 51,203, 20,912, and 9590 respectively. CONCLUSION: The development of a highly sensitive ELISA system for the detection of SARS-CoV-2 IgG antibodies is described herein. This system enabled a quantitative study of rSARS-CoV-2-N IgG antibody titers in COVID-19 patients, the occurrence of higher IgG antibody titers were found to be correlated with more severe cases.

Expanding syphilis test uptake using rapid dual self-testing for syphilis and HIV among men who have sex with men in China: A multiarm randomized controlled trial.

BACKGROUND: Low syphilis testing uptake is a major public health issue among men who have sex with men (MSM) in many low- and middle-income countries. Syphilis self-testing (SST) may complement and extend facility-based testing. We aimed to evaluate the effectiveness and costs of providing SST on increasing syphilis testing uptake among MSM in China. METHODS AND FINDINGS: An open-label, parallel 3-arm randomized controlled trial (RCT) was conducted between January 7, 2020 and July 17, 2020. Men who were at least 18 years of age, had condomless anal sex with men in the past year, reported not testing for syphilis in the last 6 months, and had a stable residence with mailing addresses were recruited from 124 cities in 26 Chinese provinces. Using block randomization with blocks of size 12, enrolled participants were randomly assigned (1:1:1) into 3 arms: standard of care arm, standard SST arm, and lottery incentivized SST arm (1 in 10 chance to win US$15 if they had a syphilis test). The primary outcome was the proportion of participants who tested for syphilis during the trial period and confirmed with photo verification and between arm comparisons were estimated with risk differences (RDs). Analyses were performed on a modified intention-to-treat basis: Participants were included in the complete case analysis if they had initiated at least 1 follow-up survey. The Syphilis/HIV Duo rapid test kit was used. A total of 451 men were enrolled. In total, 136 (90·7%, 136/150) in the standard of care arm, 142 (94·0%, 142/151) in the standard of SST arm, and 137 (91·3%, 137/150) in the lottery incentivized SST arm were included in the final analysis. The proportion of men who had at least 1 syphilis test during the trial period was 63.4% (95% confidence interval [CI]: 55.5% to 71.3%, p = 0.001) in the standard SST arm, 65.7% (95% CI: 57.7% to 73.6%, p = 0.0002) in the lottery incentivized SST arm, and 14.7% (95% CI: 8.8% to 20.7%, p < 0.001) in the standard of care arm. The estimated RD between the standard SST and standard of care arm was 48.7% (95% CI: 37.8% to 58.4%, p < 0.001). The majority (78.5%, 95% CI: 72.7% to 84.4%, p < 0.001) of syphilis self-testers reported never testing for syphilis. The cost per person tested was US$26.55 for standard SST, US$28.09 for the lottery incentivized SST, and US$66.19 for the standard of care. No study-related adverse events were reported during the study duration. Limitation was that the impact of the Coronavirus Disease 2019 (COVID-19) restrictions may have accentuated demand for decentralized testing. CONCLUSIONS: Compared to standard of care, providing SST significantly increased the proportion of MSM testing for syphilis in China and was cheaper (per person tested). TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR1900022409.

Monetary incentives and peer referral in promoting secondary distribution of HIV self-testing among men who have sex with men in China: A randomized controlled trial.

BACKGROUND: Digital network-based methods may enhance peer distribution of HIV self-testing (HIVST) kits, but interventions that can optimize this approach are needed. We aimed to assess whether monetary incentives and peer referral could improve a secondary distribution program for HIVST among men who have sex with men (MSM) in China. METHODS AND FINDINGS: Between October 21, 2019 and September 14, 2020, a 3-arm randomized controlled, single-blinded trial was conducted online among 309 individuals (defined as index participants) who were assigned male at birth, aged 18 years or older, ever had male-to-male sex, willing to order HIVST kits online, and consented to take surveys online. We randomly assigned index participants into one of the 3 arms: (1) standard secondary distribution (control) group (n = 102); (2) secondary distribution with monetary incentives (SD-M) group (n = 103); and (3) secondary distribution with monetary incentives plus peer referral (SD-M-PR) group (n = 104). Index participants in 3 groups were encouraged to order HIVST kits online and distribute to members within their social networks. Members who received kits directly from index participants or through peer referral links from index MSM were defined as alters. Index participants in the 2 intervention groups could receive a fixed incentive ($3 USD) online for the verified test result uploaded to the digital platform by each unique alter. Index participants in the SD-M-PR group could additionally have a personalized peer referral link for alters to order kits online. Both index participants and alters needed to pay a refundable deposit ($15 USD) for ordering a kit. All index participants were assigned an online 3-month follow-up survey after ordering kits. The primary outcomes were the mean number of alters motivated by index participants in each arm and the mean number of newly tested alters motivated by index participants in each arm. These were assessed using zero-inflated negative binomial regression to determine the group differences in the mean number of alters and the mean number of newly tested alters motivated by index participants. Analyses were performed on an intention-to-treat basis. We also conducted an economic evaluation using microcosting from a health provider perspective with a 3-month time horizon. The mean number of unique tested alters motivated by index participants was 0.57 ± 0.96 (mean ± standard deviation [SD]) in the control group, compared with 0.98 ± 1.38 in the SD-M group (mean difference [MD] = 0.41),and 1.78 ± 2.05 in the SD-M-PR group (MD = 1.21). The mean number of newly tested alters motivated by index participants was 0.16 ± 0.39 (mean ± SD) in the control group, compared with 0.41 ± 0.73 in the SD-M group (MD = 0.25) and 0.57 ± 0.91 in the SD-M-PR group (MD = 0.41), respectively. Results indicated that index participants in intervention arms were more likely to motivate unique tested alters (control versus SD-M: incidence rate ratio [IRR = 2.98, 95% CI = 1.82 to 4.89, p-value < 0.001; control versus SD-M-PR: IRR = 3.26, 95% CI = 2.29 to 4.63, p-value < 0.001) and newly tested alters (control versus SD-M: IRR = 4.22, 95% CI = 1.93 to 9.23, p-value < 0.001; control versus SD-M-PR: IRR = 3.49, 95% CI = 1.92 to 6.37, p-value < 0.001) to conduct HIVST. The proportion of newly tested testers among alters was 28% in the control group, 42% in the SD-M group, and 32% in the SD-M-PR group. A total of 18 testers (3 index participants and 15 alters) tested as HIV positive, and the HIV reactive rates for alters were similar between the 3 groups. The total costs were $19,485.97 for 794 testers, including 450 index participants and 344 alter testers. Overall, the average cost per tester was $24.54, and the average cost per alter tester was $56.65. Monetary incentives alone (SD-M group) were more cost-effective than monetary incentives with peer referral (SD-M-PR group) on average in terms of alters tested and newly tested alters, despite SD-M-PR having larger effects. Compared to the control group, the cost for one more alter tester in the SD-M group was $14.90 and $16.61 in the SD-M-PR group. For newly tested alters, the cost of one more alter in the SD-M group was $24.65 and $49.07 in the SD-M-PR group. No study-related adverse events were reported during the study. Limitations include the digital network approach might neglect individuals who lack internet access. CONCLUSIONS: Monetary incentives alone and the combined intervention of monetary incentives and peer referral can promote the secondary distribution of HIVST among MSM. Monetary incentives can also expand HIV testing by encouraging first-time testing through secondary distribution by MSM. This social network-based digital approach can be expanded to other public health research, especially in the era of the Coronavirus Disease 2019 (COVID-19). TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR) ChiCTR1900025433.

Active disease-related compound identification based on capsule network.

Pneumonia, especially corona virus disease 2019 (COVID-19), can lead to serious acute lung injury, acute respiratory distress syndrome, multiple organ failure and even death. Thus it is an urgent task for developing high-efficiency, low-toxicity and targeted drugs according to pathogenesis of coronavirus. In this paper, a novel disease-related compound identification model-based capsule network (CapsNet) is proposed. According to pneumonia-related keywords, the prescriptions and active components related to the pharmacological mechanism of disease are collected and extracted in order to construct training set. The features of each component are extracted as the input layer of capsule network. CapsNet is trained and utilized to identify the pneumonia-related compounds in Qingre Jiedu injection. The experiment results show that CapsNet can identify disease-related compounds more accurately than SVM, RF, gcForest and forgeNet.

Swarm Robots Cooperative and Persistent Distribution Modeling and Optimization Based on the Smart Community Logistics Service Framework

The high efficiency, flexibility, and low cost of robots provide huge opportunities for the application and development of intelligent logistics. Especially during the COVID-19 pandemic, the non-contact nature of robots effectively helped with preventing the spread of the epidemic. Task allocation and path planning according to actual problems is one of the most important problems faced by robots in intelligent logistics. In the distribution, the robots have the fundamental characteristics of battery capacity limitation, limited load capacity, and load affecting transportation capacity. So, a smart community logistics service framework is proposed based on control system, automatic replenishment platform, network communication method, and coordinated distribution optimization technology, and a Mixed Integer Linear Programming (MILP) model is developed for the collaborative and persistent delivery of a multiple-depot vehicle routing problem with time window (MDVRPTW) of swarm robots. In order to solve this problem, a hybrid algorithm of genetically improved set-based particle swarm optimization (S-GAIPSO) is designed and tested with numerical cases. Experimental results show that, Compared to CPLEX, S-GAIPSO has achieved gaps of 0.157%, 1.097%, and 2.077% on average, respectively, when there are 5, 10, and 20 tasks. S-GAIPSO can obtain the optimal or near-optimal solution in less than 0.35 s, and the required CPU time slowly increases as the scale increases. Thus, it provides utility for real-time use by handling a large-scale problem in a short time.

Impact of chemotherapy and immunotherapy on the composition and function of immune cells in COVID-19 convalescent with gynecological tumors.

Ongoing pandemic and potential resurgence of Coronavirus disease 2019 (COVID-19) has prompted urgent efforts to investigate the immunological memory of convalescent patients, especially in patients with active cancers. Here we performed single-cell RNA sequencing in peripheral blood samples of 3 healthy donors (HDs), 4 COVID-19 patients (Covs) and 4 COVID-19 patients with active gynecological tumor (TCs) pre- and post- anti-tumor treatment. All Covs patients had recovered from their acute infection. Interestingly, the molecular features of PBMCs in TCs are similar to that in Covs, suggesting that convalescent COVID-19 with gynecologic tumors do not have major immunological changes and may be protected against reinfection similar to COVID-19 patients without tumors. Moreover, the chemotherapy given to these patients mainly caused neutropenia, while having little effect on the proportion and functional phenotype of T and B cells, and T cell clonal expansion. Notably, anti-PD-L1 treatment massively increased cytotoxic scores of NK cells, and T cells, and facilitated clonal expansion of T cells in these patients. It is likely that T cells could protect patients from SARS-CoV-2 virus reinfection and anti-PD-L1 treatment can enhance the anti-viral activity of the T cells.