Excess non-COVID-19-related mortality among inflammatory bowel disease decedents during the COVID-19 pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare in the United States. AIM: To investigate COVID-19-related and non-COVID-19-related death and characteristics associated with excess death among inflammatory bowel disease (IBD) decedents. METHODS: We performed a register-based study using data from the National Vital Statistics System, which reports death data from over 99% of the United States population, from January 1, 2006 through December 31, 2021. IBD-related deaths among adults 25 years and older were stratified by age, sex, race/ethnicity, place of death, and primary cause of death. Predicted and actual age-standardized mortality rates (ASMRs) per 100000 persons were compared. RESULTS: 49782 IBD-related deaths occurred during the study period. Non-COVID-19-related deaths increased by 13.14% in 2020 and 18.12% in 2021 [2020 ASMR: 1.55 actual vs 1.37 predicted, 95% confidence interval (CI): 1.26-1.49; 2021 ASMR: 1.63 actual vs 1.38 predicted, 95%CI: 1.26-1.49]. In 2020, non-COVID-19-related mortality increased by 17.65% in ulcerative colitis (UC) patients between the ages of 25 and 65 and 36.36% in non-Hispanic black (NHB) Crohn's disease (CD) patients. During the pandemic, deaths at home or on arrival and at medical facilities as well as deaths due to neoplasms also increased. CONCLUSION: IBD patients suffered excess non-COVID-19-related death during the pandemic. Excess death was associated with younger age among UC patients, and with NHB race among CD patients. Increased death at home or on arrival and due to neoplasms suggests that delayed presentation and difficulty accessing healthcare may have led to increased IBD mortality.

The Effects of Different Zn Forms on Sintering Basic Characteristics of Iron Ore.

The micro-sintering method was used to determine the sintering basic characteristics of iron ore with Zn contents from 0 to 4%, the influence mechanism of Zn on sintering basic characteristics of iron ore was clarified by means of thermodynamic analysis and first-principles calculations. The results showed that (1) increasing the ZnO and ZnFe2O4 content increased the lowest assimilation temperature (LAT) but decreased the index of liquid phase fluidity (ILF) of iron ore. The addition of ZnS had no obvious effect on LAT but increased the LIF of iron ore. (2) ZnO and ZnFe2O4 reacted with Fe2O3 and CaO, respectively, during sintering, which inhibited the formation of silico-ferrite of calcium and aluminum (SFCA). The addition of ZnS accelerated the decomposition of Fe2O3 in the N2 atmosphere; however, the high decomposition temperature limited the oxidation of ZnS, so the presence of ZnS had a slight inhibitory effect on the formation of SFCA. (3) The Zn concentrated in hematite or silicate and less distributed in SFCA and magnetite in the form of solid solution; meanwhile, the microhardness of the mineral phase decreased with the increase in Zn-containing solid solution content. As the adsorption of Zn on the SFCA crystal surface was more stable, the microhardness of SFCA decreased more. The decrease in microhardness and content of the SFCA bonding phase resulted in a decrease in the compressive strength of the sinter.

Age and urban-rural disparities in cutaneous melanoma mortality rates in the United States during the COVID-19 pandemic.

Most recent studies on the coronavirus disease 2019 (COVID-19) pandemic and cutaneous melanoma (CM) focused more on delayed diagnosis or advanced presentation. We aimed to ascertain mortality trends of CM between 2012 and 2022, focusing on the effects of the COVID-19 pandemic. In this serial population-based study, the National Vital Statistics System dataset was queried for mortality data. Excess CM-related mortality rates were estimated by calculating the difference between observed and projected mortality rates during the pandemic. Totally there were 108,853 CM-associated deaths in 2012-2022. CM-associated mortality saw a declining trend from 2012 to 2019 overall. However, it increased sharply in 2020 (ASMR 3.73 per 100,000 persons, 5.95% excess mortality), and remained high in 2021 and 2022, with the ASMRs of 3.82 and 3.81, corresponding to 11.17% and 13.20% excess mortality, respectively. The nonmetro areas had the most pronounced rise in mortality with 12.20% excess death in 2020, 15.33% in 2021 and 20.52% in 2022, corresponding to a 4-6 times excess mortality risk compared to large metro areas during the pandemic. The elderly had the most pronounced rise in mortality, but the mortality in the younger population was reduced.

Investigation of causal relationships between cortical structure and osteoporosis using two-sample Mendelian randomization.

The mutual interaction between bone characteristics and brain had been reported previously, yet whether the cortical structure has any relevance to osteoporosis is questionable. Therefore, we applied a two-sample bidirectional Mendelian randomization analysis to investigate this relationship. We utilized the bone mineral density measurements of femoral neck (n = 32,735) and lumbar spine (n = 28,498) and data on osteoporosis (7300 cases and 358,014 controls). The global surficial area and thickness and 34 specific functional regions of 51,665 patients were screened by magnetic resonance imaging. For the primary estimate, we utilized the inverse-variance weighted method. The Mendelian randomization-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis were conducted to assess heterogeneity and pleiotropy. We observed suggestive associations between decreased thickness in the precentral region (OR = 0.034, P = 0.003) and increased chance of having osteoporosis. The results also revealed suggestive causality of decreased bone mineral density in femoral neck to declined total cortical surface area (ß = 1400.230 mm2, P = 0.003), as well as the vulnerability to osteoporosis and reduced thickness in the Parstriangularis region (ß = -0.006 mm, P = 0.002). Our study supports that the brain and skeleton exhibit bidirectional crosstalk, indicating the presence of a mutual brain-bone interaction.

Adsorption of Zn(II) from aqueous solution and separation of zinc isotopes by displacement chromatography using chelating adsorbent.

The removal of zinc ions (Zn(II)) in water and the separation of zinc isotopes were fully investigated in this study. Imidodiacetic acid (IDA) type adsorbent (named PSGI) based on polystyrene spheres (PS) was synthesized by simultaneous irradiation grafting. By adsorption method, the removal of Zn(II) from water by the chelating adsorbent was studied in batch experiments. Under optimized condition, PSGI showed the removal efficiency of more than 98 % for Zn(II) and the adsorption capacity of 70.1 mg/g. Langmuir isothermal and pseudo-second-order kinetic model fitted the experimental results better, indicating that the adsorption is dominated by chemical adsorption. The spent adsorbent (PSGI-Zn) was used for further zinc isotope separation by displacement chromatography using EDTA-NH4 solution as eluent. Due to the mass effect of isotopes, 70Zn was found to preferentially fractionated into the front-end effluents with the highest front enrichment values of 70Zn/64Zn. By extending the migration distance to 20 m, we obtained the best isotope enrichment with the front maximum enrichment values as 1.0949, 1.0739 and separation coefficient values as 1.977 × 10-3, 8.33 × 10-3 corresponding to the isotope pairs 66Zn/64Zn, 68Zn/64Zn.

Fusang: a framework for phylogenetic tree inference via deep learning.

Phylogenetic tree inference is a classic fundamental task in evolutionary biology that entails inferring the evolutionary relationship of targets based on multiple sequence alignment (MSA). Maximum likelihood (ML) and Bayesian inference (BI) methods have dominated phylogenetic tree inference for many years, but BI is too slow to handle a large number of sequences. Recently, deep learning (DL) has been successfully applied to quartet phylogenetic tree inference and tentatively extended into more sequences with the quartet puzzling algorithm. However, no DL-based tools are immediately available for practical real-world applications. In this paper, we propose Fusang (http://fusang.cibr.ac.cn), a DL-based framework that achieves comparable performance to that of ML-based tools with both simulated and real datasets. More importantly, with continuous optimization, e.g. through the use of customized training datasets for real-world scenarios, Fusang has great potential to outperform ML-based tools.

HIV-related mortality in the United States during the COVID-19 pandemic: A population-based study.

BACKGROUND: US progress toward ending the HIV epidemic was disrupted during the COVID-19 pandemic. OBJECTIVES: To determine the impact of the pandemic on HIV-related mortality and potential disparities. METHODS: Using data from the Centers for Disease Control and Prevention and the United States (US) Census Bureau, HIV-related mortality data of decedents aged ≥25 years between 2012 and 2021 were analyzed. Excess HIV-related mortality rates were estimated by determining the difference between observed and projected mortality rates during the pandemic. The trends of mortality were quantified with joinpoint regression analysis. RESULTS: Of the 79,725 deaths documented in adults aged 25 years and older between 2012 and 2021, a significant downward trend was noted in HIV-related mortality rates before the pandemic, followed by a surge during the pandemic. The observed mortality rates were 18.8% (95% confidence interval [CI]: 13.1%-25.5%) and 25.4% (95%CI: 19.9%-30.4%) higher than the projected values in 2020 and 2021, respectively. Both of these percentages were higher than that in the general population in 2020 (16.4%, 95%CI: 14.9%-17.9%) and 2021 (19.8%, 95%CI: 18.0%-21.6%), respectively. Increased HIV-related mortality was observed across all age subgroups, but those aged 25-44 years demonstrated the greatest relative increase and the lowest COVID-19-related deaths when compared to middle- and old-aged decedents. Disparities were observed across racial/ethnic subgroups and geographic regions. CONCLUSIONS: The pandemic led to a reversal in the attainments made to reduce the prevalence of HIV. Individuals living with HIV were disproportionately affected during the pandemic. Thoughtful policies are needed to address the disparity in excess HIV-related mortality.

Trends of Cirrhosis-related Mortality in the USA during the COVID-19 Pandemic.

Immunocompromised status and interrupted routine care may render patients with cirrhosis vulnerable to the coronavirus disease 2019 (COVID-19) pandemic. A nationwide dataset that includes more than 99% of the decedents in the U.S. between April 2012 and September 2021 was used. Projected age-standardized mortality during the pandemic were estimated according to prepandemic mortality rates, stratified by season. Excess deaths were determined by estimating the difference between observed and projected mortality rates. A temporal trend analysis of observed mortality rates was also performed in 0.83 million decedents with cirrhosis between April 2012 and September 2021 was included. Following an increasing trend of cirrhosis-related mortality before the pandemic, with a semiannual percentage change (SAPC) of 0.54% [95% confidence interval (CI): (0.0-1.0%), p=0.036], a precipitous increase with seasonal variation occurred during the pandemic (SAPC 5.35, 95% CI: 1.9-8.9, p=0.005). Significantly increased mortality rates were observed in those with alcohol-associated liver disease (ALD), with a SAPC of 8.44 (95% CI: 4.3-12.8, p=0.001) during the pandemic. All-cause mortality of nonalcoholic fatty liver disease rose steadily across the entire study period with a SAPC of 6.79 (95% CI: 6.3-7.3, p<0.001). The decreasing trend of HCV-related mortality was reversed during the pandemic, while there was no significant change in HBV-related deaths. While there was significant increase in COVID-19-related deaths, more than 55% of the excess deaths were the indirect impact of the pandemic. We observed an alarming increase in cirrhosis-related deaths during the pandemic especially for ALD, with evidence in both direct and indirect impact. Our findings have implications on formulating policies for patients with cirrhosis.

Excess risk for acute myocardial infarction mortality during the COVID-19 pandemic.

The COVID-19 pandemic has had a detrimental impact on the healthcare system. Our study armed to assess the extent and the disparity in excess acute myocardial infarction (AMI)-associated mortality during the pandemic, through the recent Omicron outbreak. Using data from the CDC's National Vital Statistics System, we identified 1 522 669 AMI-associated deaths occurring between 4/1/2012 and 3/31/2022. Accounting for seasonality, we compared age-standardized mortality rate (ASMR) for AMI-associated deaths between prepandemic and pandemic periods, including observed versus predicted ASMR, and examined temporal trends by demographic groups and region. Before the pandemic, AMI-associated mortality rates decreased across all subgroups. These trends reversed during the pandemic, with significant rises seen for the youngest-aged females and males even through the most recent period of the Omicron surge (10/2021-3/2022). The SAPC in the youngest and middle-age group in AMI-associated mortality increased by 5.3% (95% confidence interval [CI]: 1.6%-9.1%) and 3.4% (95% CI: 0.1%-6.8%), respectively. The excess death, defined as the difference between the observed and the predicted mortality rates, was most pronounced for the youngest (25-44 years) aged decedents, ranging from 23% to 34% for the youngest compared to 13%-18% for the oldest age groups. The trend of mortality suggests that age and sex disparities have persisted even through the recent Omicron surge, with excess AMI-associated mortality being most pronounced in younger-aged adults.

Impact of the COVID-19 pandemic on liver disease-related mortality rates in the United States.

BACKGROUND & AIMS: The pandemic has resulted in an increase of deaths not directly related to COVID-19 infection. We aimed to use a national death dataset to determine the impact of the pandemic on people with liver disease in the USA, focusing on alcohol-associated liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD). METHODS: Using data from the National Vital Statistic System from the Center for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) platform and ICD-10 codes, we identified deaths associated with liver disease. We evaluated observed vs. predicted mortality for 2020-2021 based on trends from 2010-2019 with joinpoint and prediction modelling analysis. RESULTS: Among 626,090 chronic liver disease-related deaths between 2010 and 2021, Age-standardised mortality rates (ASMRs) for ALD dramatically increased between 2010-2019 and 2020-2021 (annual percentage change [APC] 3.5% to 17.6%, p <0.01), leading to a higher observed ASMR (per 100,000 persons) than predicted for 2020 (15.67 vs. 13.04) and 2021 (17.42 vs. 13.41). ASMR for NAFLD also increased during the pandemic (APC: 14.5%), whereas the rates for hepatitis B and C decreased. Notably, the ASMR rise for ALD was most pronounced in non-Hispanic Whites, Blacks, and Alaska Indians/Native Americans (APC: 11.7%, 10.8%, 18.0%, all p <0.05), with similar but less critical findings for NAFLD, whereas rates were steady for non-Hispanic Asians throughout 2010-2021 (APC: 4.9%). The ASMR rise for ALD was particularly severe for the 25-44 age group (APC: 34.6%, vs. 13.7% and 12.6% for 45-64 and ≥65, all p <0.01), which were also all higher than pre-COVID-19 rates (all p <0.01). CONCLUSIONS: ASMRs for ALD and NAFLD increased at an alarming rate during the COVID-19 pandemic with the largest disparities among the young, non-Hispanic White, and Alaska Indian/Native American populations. IMPACT AND IMPLICATIONS: The pandemic has led to an increase of deaths directly and indirectly related to SARS-CoV-2 infection. As shown in this study, age-standardised mortality rates for alcohol-associated liver disease and non-alcoholic fatty liver disease substantially increased during the COVID-19 pandemic in the USA and far exceeded expected levels predicted from past trends, especially among the young, non-Hispanic White, and Alaska Indian/Native American populations. However, much of this increase was not directly related to COVID-19. Therefore, for the ongoing pandemic as well as its recovery phase, adherence to regular monitoring and care for people with chronic liver disease should be prioritised and awareness should be raised among patients, care providers, healthcare systems, and public health policy makers.

Forced convection of non-darcy flow of ethylene glycol conveying copper(II) oxide and titanium dioxide nanoparticles subject to lorentz force on wedges: Non-newtonian casson model.

The topic of two-dimensional steady laminar MHD boundary layer flow across a wedge with non-Newtonian hybrid nanoliquid (CuO-TiO2/C2H6O2) with viscous dissipation and radiation is taken into consideration. The controlling partial differential equations have been converted to non-linear higher-order ordinary differential equations using the appropriate similarity transformations. It is demonstrated that a number of thermo-physical characteristics govern the transmuted model. The issue is then mathematically resolved. When the method's accuracy is compared to results that have already been published, an excellent agreement is found. While the thermal distribution increases with an increase in Eckert number, radiation and porosity parameters, the velocity distribution decreases as porosity increases.

Excess diabetes mellitus-related deaths during the COVID-19 pandemic in the United States.

Background: Diabetes mellitus (DM) is a critical risk factor for severe SARS-CoV-2 infection, and SARS-CoV-2 infection contributes to worsening glycemic control. The COVID-19 pandemic profoundly disrupted the delivery of care for patients with diabetes. We aimed to determine the trend of DM-related deaths during the pandemic. Methods: In this serial population-based study between January 1, 2006 and December 31, 2021, mortality data of decedents aged ≥25 years from the National Vital Statistics System dataset was analyzed. Decedents with DM as the underlying or contributing cause of death on the death certificate were defined as DM-related deaths. Excess deaths were estimated by comparing observed versus expected age-standardized mortality rates derived from mortality during 2006-2019 with linear and polynomial regression models. The trends of mortality were quantified with joinpoint regression analysis. Subgroup analyses were performed by age, sex, race/ethnicity, and state. Findings: Among 4·25 million DM-related deaths during 2006-2021, there was a significant surge of more than 30% in mortality during the pandemic, from 106·8 (per 100,000 persons) in 2019 to 144·1 in 2020 and 148·3 in 2021. Adults aged 25-44 years had the most pronounced rise in mortality. Widened racial/ethnic disparity was observed, with Hispanics demonstrating the highest excess deaths (67·5%; 95% CI 60·9-74·7%), almost three times that of non-Hispanic whites (23·9%; 95% CI 21·2-26·7%). Interpretation: The United States saw an increase in DM-related mortality during the pandemic. The disproportionate rise in young adults and the widened racial/ethnic disparity warrant urgent preventative interventions from diverse stakeholders. Funding: National Natural Science Foundation of China.

Critical Quantum Metrology in the Non-Linear Quantum Rabi Model.

The quantum Rabi model (QRM) with linear coupling between light mode and qubit exhibits the analog of a second-order phase transition for vanishing mode frequency which allows for criticality-enhanced quantum metrology in a few-body system. We show that the QRM including a nonlinear coupling term exhibits much higher measurement precisions due to its first-order-like phase transition at finite frequency, avoiding the detrimental slowing-down effect close to the critical point of the linear QRM. When a bias term is added to the Hamiltonian, the system can be used as a fluxmeter or magnetometer if implemented in circuit QED platforms.

Coevolutionary dynamics of host-pathogen interaction with density-dependent mortality.

This study explores the coevolutionary dynamics of host-pathogen interaction based on a susceptible-infected population model with density-dependent mortality. We assume that both the host's resistance and the pathogen's virulence will adaptively evolve, but there are inevitable costs in terms of host birth rate and disease-related mortality rate. Particularly, it is assumed that both the host resistance and pathogen virulence can affect the transmission rate. By using the approach of adaptive dynamics and numerical simulation, we find that the finally coevolutionary outcome depends on the strength of host-pathogen asymmetric interaction, the curvature of trade-off functions, and the intensity of density-dependent natural mortality. To be specific, firstly, we find that if the strengths of host-pathogen asymmetric interaction and disease-related mortality are relatively weak, or the density-dependent natural mortality is relatively strong, then the host resistance and pathogen virulence will evolve to a continuously stable strategy. However, if the strength of host-pathogen asymmetric interaction and disease-related mortality becomes stronger, then the host resistance and pathogen virulence will evolve periodically. Secondly, we find that if the intensities of both the birth rate trade-off function and the density-dependent natural mortality are relatively weak, but the strength of host-pathogen asymmetric interaction becomes relatively strong, then the evolution of host resistance will have a relatively strongly accelerating benefit, the evolutionary branching of host resistance will first arise. However, if the strength of host-pathogen asymmetric interaction is relatively weak, but the intensity of the trade-off function of disease-related mortality becomes relatively strong, then the evolution of pathogen virulence will have a relatively strongly decelerating cost, and the evolutionary branching of pathogen virulence will first arise. Thirdly, after the evolutionary branching of host resistance and pathogen virulence, we further study the coevolutionary dynamics of two-hosts-one-pathogen interaction and one-host-two-pathogens interaction. We find that if the evolutionary branching of host resistance arises firstly, then the finally evolutionary outcome contains a dimorphic host and a monomorphic pathogen population. If the evolutionary branching of pathogen virulence arises firstly, then the finally evolutionary outcome may contain a monomorphic host and a dimorphic pathogen population.

COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies.

BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. OBJECTIVE: Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. METHODS: We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. RESULTS: Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75-100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65-100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0-17 and 75-100 age groups as of June 1, 2021, then the allocation of 80% to the 0-17 age group and 20% to the 75-100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. CONCLUSIONS: The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections.

Clinical Analysis of Pyocele of Tunica Vaginalis in 56 Newborns.

OBJECTIVE: This study aimed to explore the clinical characteristics, treatment methods, and prognosis of neonatal pyocele of tunica vaginalis and to provide a reference for the clinical treatment. METHODS: A total of 56 newborns with pyocele of tunica vaginalis were admitted to our hospital due to the scrotal emergency from January 2015 to January 2020. Our study retrospectively analyzed these 56 cases. Of the 56 cases, including 32 full-term infants and 24 premature infants, age ranged from 1 to 27 days. Initially, conservative treatment (intravenous antibiotic treatment) was applied to 42 cases, and surgery to 14 cases. Then, 7 underwent surgical exploration during the conservative treatment, and 2 cases with initial surgical treatment experienced orchiectomy because of complete necrosis. For 56 cases, the average follow-up time was 18 months. RESULTS: The clinical recovery time of cases with conservative treatment ranged from 8 to 17 days, with an average of 11.02 ± 2.31 days. The clinical recovery time of cases with surgery ranged from 6 to 15 days, with an average of 9.28 ± 2.78 days. During the follow-up, for 56 cases, except for the 2 cases with orchiectomy, the testicular position and Doppler flow both went back to normal, of the 42 cases with initial conservative treatment, 1 case experienced testicular retardation, of the 14 cases with initial surgical treatment, 2 cases experienced testicular retardation, and hydrocele of 42 cases were self-healed. CONCLUSIONS: Neonatal pyocele of tunica vaginalis is mostly secondary to intra-abdominal infection. Color Doppler ultrasound is helpful for the diagnosis. The percutaneous aspiration is a way of collecting pathogenic bacteria during the conservative treatment. If the color Doppler suggests testicular involvement, surgical exploration should be performed.

Effect of exposure to antibiotics on the gut microbiome and biochemical indexes of pregnant women.

INTRODUCTION: Exposure to antibiotics (ABX) during pregnancy can have a systematic effect on both fetal and maternal health. Although previous biomonitoring studies have indicated the effects on children of extensive exposure to ABX, studies on pregnant women remain scarce. To explore the effect on pregnant women of environmental exposure to ABX through accidental ingestion and identify potential health risks, the present study investigated 122 pregnant women in East China between 2019 and 2020. RESEARCH DESIGN AND METHODS: The presence of six categories of ABX (quinolones, sulfonamides, lincosamides, tetracyclines, amide alcohol ABX, and ß-lactams) in plasma samples taken from the pregnant women was investigated using an ABX kit and a time-resolved fluorescence immunoassay. RESULTS: All six ABX were detected in the plasma, with a detection rate of 17.2%. It was discovered that the composition of intestinal flora in pregnant women exposed to ABX was different from that of pregnant women who had not been exposed to ABX. The intestinal flora of pregnant women exposed to ABX also changed at both the phylum and genus levels, and several genera almost disappeared. Furthermore, the metabolic levels of glucose and insulin and the alpha diversity of pregnant women exposed to ABX were higher than those of pregnant women not exposed to ABX. CONCLUSION: Pregnant women are potentially at higher risk of adverse microbial effects. Glucose metabolism and insulin levels were generally higher in pregnant women exposed to ABX than in unexposed women. Also, the composition and color of the gut microbiome changed.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures-such as face mask use and social distancing-may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely. STUDY DESIGN: This was a mathematical modeling study. METHODS: We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic. RESULTS: The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge. CONCLUSIONS: Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study.

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently. Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19. Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method. Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0-17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0-17 and 18-44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.