Associations between actigraphy-measured sleep duration, continuity, and timing with mortality in the UK Biobank.

STUDY OBJECTIVES: To examine the associations between sleep duration, continuity, timing, and mortality using actigraphy among adults. METHODS: Data were from a cohort of 88 282 adults (40-69 years) in UK Biobank that wore a wrist-worn triaxial accelerometer for 7 days. Actigraphy data were processed to generate estimates of sleep duration and other sleep characteristics including wake after sleep onset (WASO), number of 5-minute awakenings, and midpoint for sleep onset/wake-up and the least active 5 hours (L5). Data were linked to mortality outcomes with follow-up to October 31, 2021. We implemented Cox models (hazard ratio, confidence intervals [HR, 95% CI]) to quantify sleep associations with mortality. Models were adjusted for demographics, lifestyle factors, and medical conditions. RESULTS: Over an average of 6.8 years 2973 deaths occurred (1700 cancer, 586 CVD deaths). Overall sleep duration was significantly associated with risk for all-cause (p < 0.01), cancer (p < 0.01), and CVD (p = 0.03) mortality. For example, when compared to sleep durations of 7.0 hrs/d, durations of 5 hrs/d were associated with a 29% higher risk for all-cause mortality (HR: 1.29 [1.09, 1.52]). WASO and number of awakenings were not associated with mortality. Individuals with L5 early or late midpoints (<2:30 or ≥ 3:30) had a ~20% higher risk for all-cause mortality, compared to those with intermediate L5 midpoints (3:00-3:29; p ≤ 0.01; e.g. HR ≥ 3:30: 1.19 [1.07, 1.32]). CONCLUSIONS: Shorter sleep duration and both early and late sleep timing were associated with a higher mortality risk. These findings reinforce the importance of public health efforts to promote healthy sleep patterns in adults.

Actigraphy-derived measures of sleep and risk of prostate cancer in the UK Biobank.

BACKGROUND: Studies of sleep and prostate cancer are almost entirely based on self-report, with limited research using actigraphy. Our goal was to evaluate actigraphy-measured sleep and prostate cancer and to expand on findings from prior studies of self-reported sleep. METHODS: We prospectively examined 34 260 men without a history of prostate cancer in the UK Biobank. Sleep characteristics were measured over 7 days using actigraphy. We calculated sleep duration, onset, midpoint, wake-up time, social jetlag (difference in weekend-weekday sleep midpoints), sleep efficiency (percentage of time spent asleep between onset and wake-up time), and wakefulness after sleep onset. Cox proportional hazards models were used to estimate covariate-adjusted hazards ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Over 7.6 years, 1152 men were diagnosed with prostate cancer. Sleep duration was not associated with prostate cancer risk. Sleep midpoint earlier than 4:00 am was not associated with prostate cancer risk, though sleep midpoint of 5:00 am or later was suggestively associated with lower prostate cancer risk but had limited precision (earlier than 4:00 am vs 4:00-4:59 am HR = 1.00, 95% CI = 0.87 to 1.16; 5:00 am or later vs 4:00-4:59 am HR = 0.79, 95% CI = 0.57 to 1.10). Social jetlag was not associated with greater prostate cancer risk (1 to <2 hours vs <1 hour HR = 1.06, 95% CI = 0.89 to 1.25; ≥2 hours vs <1 hour HR = 0.90, 95% CI = 0.65 to 1.26). Compared with men who averaged less than 30 minutes of wakefulness after sleep onset per day, men with 60 minutes or more had a higher risk of prostate cancer (HR = 1.20, 95% CI = 1.00 to 1.43). CONCLUSIONS: Of the sleep characteristics studied, higher wakefulness after sleep onset-a measure of poor sleep quality-was associated with greater prostate cancer risk. Replication of our findings between wakefulness after sleep onset and prostate cancer are warranted.

Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.

Burkitt lymphoma (BL) is an aggressive B-cell lymphoma that significantly contributes to childhood cancer burden in sub-Saharan Africa. Plasmodium falciparum, which causes malaria, is geographically associated with BL, but the evidence remains insufficient for causal inference. Inference could be strengthened by demonstrating that mendelian genes known to protect against malaria-such as the sickle cell trait variant, HBB-rs334(T)-also protect against BL. We investigated this hypothesis among 800 BL cases and 3845 controls in four East African countries using genome-scan data to detect polymorphisms in 22 genes known to affect malaria risk. We fit generalized linear mixed models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), controlling for age, sex, country, and ancestry. The ORs of the loci with BL and P. falciparum infection among controls were correlated (Spearman's ρ = 0.37, p = .039). HBB-rs334(T) was associated with lower P. falciparum infection risk among controls (OR = 0.752, 95% CI 0.628-0.9; p = .00189) and BL risk (OR = 0.687, 95% CI 0.533-0.885; p = .0037). ABO-rs8176703(T) was associated with decreased risk of BL (OR = 0.591, 95% CI 0.379-0.992; p = .00271), but not of P. falciparum infection. Our results increase support for the etiological correlation between P. falciparum and BL risk.

Quantile forward regression for high-dimensional survival data.

Despite the urgent need for an effective prediction model tailored to individual interests, existing models have mainly been developed for the mean outcome, targeting average people. Additionally, the direction and magnitude of covariates' effects on the mean outcome may not hold across different quantiles of the outcome distribution. To accommodate the heterogeneous characteristics of covariates and provide a flexible risk model, we propose a quantile forward regression model for high-dimensional survival data. Our method selects variables by maximizing the likelihood of the asymmetric Laplace distribution (ALD) and derives the final model based on the extended Bayesian Information Criterion (EBIC). We demonstrate that the proposed method enjoys a sure screening property and selection consistency. We apply it to the national health survey dataset to show the advantages of a quantile-specific prediction model. Finally, we discuss potential extensions of our approach, including the nonlinear model and the globally concerned quantile regression coefficients model.

Metabolomic Analysis of Vitamin E Supplement Use in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.

The effects of vitamin E supplementation on cancer and other chronic diseases are not clear. We compared the serum metabolomic profile of differing vitamin E dosages in order to re-examine the previously observed changes in a novel C22 lactone sulfate compound, androgenic steroids, and other metabolites. A total of 3409 women and men previously selected for metabolomics studies in the PLCO Cancer Screening Trial were included in this investigation. Serum metabolites were profiled using ultrahigh-performance liquid and gas chromatography/tandem mass spectrometry. Seventy known metabolites including C22 lactone sulfate and androgens were significantly associated with vitamin E supplementation. In the sex-stratified analysis, 10 cofactors and vitamins (e.g., alpha-CEHC sulfate and alpha-CEHC glucuronide), two carbohydrates (glyceric and oxalic acids), and one lipid (glycocholenate sulfate) were significantly associated with vitamin E dose in both males and females (FDR-adjusted p-value < 0.01). However, the inverse association between C22 lactone sulfate and daily vitamin E supplementation was evident in females only, as were two androgenic steroids, 5-androstenediol and androsterone glucuronide. Our study provides evidence of distinct steroid hormone pathway responses based on vitamin E dosages. Further studies are needed to gain biological insights into vitamin E biochemical effects relevant to cancer and other chronic diseases.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial.

BACKGROUND: Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health. OBJECTIVES: To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification. METHODS: In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs. RESULTS: After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP. CONCLUSIONS: Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

Inference for High-Dimensional Censored Quantile Regression.

With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes. To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression. This paper proposes a novel procedure to draw inference on all predictors within the framework of global censored quantile regression, which investigates covariate-response associations over an interval of quantile levels, instead of a few discrete values. The proposed estimator combines a sequence of low dimensional model estimates that are based on multi-sample splittings and variable selection. We show that, under some regularity conditions, the estimator is consistent and asymptotically follows a Gaussian process indexed by the quantile level. Simulation studies indicate that our procedure can properly quantify the uncertainty of the estimates in high dimensional settings. We apply our method to analyze the heterogeneous effects of SNPs residing in lung cancer pathways on patients' survival, using the Boston Lung Cancer Survivor Cohort, a cancer epidemiology study on the molecular mechanism of lung cancer.

Dietary Quality and Circulating Lipidomic Profiles in 2 Cohorts of Middle-Aged and Older Male Finnish Smokers and American Populations.

BACKGROUND: Higher dietary quality is associated with lower disease risks and has not been examined extensively with lipidomic profiles. OBJECTIVES: Our goal was to examine associations of the Healthy Eating Index (HEI)-2015, Alternate HEI-2010 (AHEI-2010), and alternate Mediterranean Diet Index (aMED) diet quality indices with serum lipidomic profiles. METHODS: We conducted a cross-sectional analysis of HEI-2015, AHEI-2010, and aMED with lipidomic profiles from 2 nested case-control studies within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (n = 627) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n = 711). We used multivariable linear regression to determine associations of the indices, derived from baseline food-frequency questionnaires (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial: 1993-2001, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: 1985-1988) with serum concentrations of 904 lipid species and 252 fatty acids (FAs) across 15 lipid classes and 28 total FAs, within each cohort and meta-analyzed results using fixed-effect models for lipids significant at Bonferroni-corrected threshold in common in both cohorts. RESULTS: Adherence to HEI-2015, AHEI-2010, or aMED was associated positively with 31, 41, and 54 lipid species and 8, 6, and 10 class-specific FAs and inversely with 2, 8, and 34 lipid species and 1, 3, and 5 class-specific FAs, respectively. Twenty-five lipid species and 5 class-specific FAs were common to all indices, predominantly triacylglycerols, FA22:6 [docosahexaenoic acid (DHA)]-containing species, and DHA. All indices were positively associated with total FA22:6. AHEI-2010 and aMED were inversely associated with total FA18:1 (oleic acid) and total FA17:0 (margaric acid), respectively. The identified lipids were most associated with components of seafood and plant proteins and unsaturated:saturated fat ratio in HEI-2015; eicosapentaenoic acid plus DHA in AHEI-2010; and fish and monounsaturated:saturated fat ratio in aMED. CONCLUSIONS: Adherence to HEI-2015, AHEI-2010, and aMED is associated with serum lipidomic profiles, mostly triacylglycerols or FA22:6-containing species, which are related to seafood and plant proteins, eicosapentaenoic acid-DHA, fish, or fat ratio index components.

Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study.

Health outcomes, such as body mass index and cholesterol levels, are known to be dependent on age and exhibit varying effects with their associated risk factors. In this paper, we propose a novel framework for dynamic modeling of the associations between health outcomes and risk factors using varying-coefficients (VC) regional quantile regression via K-nearest neighbors (KNN) fused Lasso, which captures the time-varying effects of age. The proposed method has strong theoretical properties, including a tight estimation error bound and the ability to detect exact clustered patterns under certain regularity conditions. To efficiently solve the resulting optimization problem, we develop an alternating direction method of multipliers (ADMM) algorithm. Our empirical results demonstrate the efficacy of the proposed method in capturing the complex age-dependent associations between health outcomes and their risk factors.

Utilization of Medicare's chronic care management services by primary care providers.

BACKGROUND: Medicare billing codes introduced in 2015 reimburses primary care providers for non-face-to-face, chronic care management (CCM) services rendered by clinical staff. PURPOSE: The purpose of this manuscript was to describe provider trends in billed CCM services and identify factors associated with CCM utilization. METHODS: Observational study using Medicare Public Use Files, 2015 to 2018. General, family, geriatric, and internal medicine physicians, nurse practitioners (NPs), and physician assistants (PAs) with billed primary care services were included. Multivariable analyses modeled associations between the CCM services and type of provider, adjusting for year, primary care services, practice, and patient characteristics. FINDINGS: Among 140,465 physicians and 141,118 NPs/PAs, CCM services increased each year, yet remained underutilized: 2% to 7% of physicians and 0.3% to 1.3% of NPs/PAs billed CCM in 2018. Increases in beneficiaries (p < .0001), percentage of dually enrolled (p = .0134), and primary care services (p < .0001) predicted higher CCM utilization. DISCUSSION: CCM utilization reflects practice-based efforts to improve patient access to care by enhancing care delivery.

Association of Leisure Time Physical Activity Types and Risks of All-Cause, Cardiovascular, and Cancer Mortality Among Older Adults.

Importance: Higher amounts of physical activity are associated with increased longevity. However, whether different leisure time physical activity types are differentially associated with mortality risk is not established. Objectives: To examine whether participation in equivalent amounts of physical activity (7.5 to <15 metabolic equivalent of task [MET] hours per week) through different activity types is associated with mortality risk and to investigate the shape of the dose-response association. Design, Setting, and Participants: Participants in this cohort were respondents from the National Institutes of Health-AARP Diet and Health Study who completed the follow-up questionnaire between 2004 and 2005. This questionnaire collected data on weekly durations of different types of physical activities. Mortality was ascertained through December 31, 2019. Exposures: MET hours per week spent participating in the following activities: running, cycling, swimming, other aerobic exercise, racquet sports, golf, and walking for exercise. Main Outcomes and Measures: All-cause, cardiovascular, and cancer mortality. Separate multivariable-adjusted Cox proportional hazards regression models were fitted to estimate hazard ratios (HRs) and 95% CIs of mortality for each of the 7 types of leisure time physical activities, as well as the sum of these activities. Results: A total of 272 550 participants (157 415 men [58%]; mean [SD] age at baseline, 70.5 [5.4] years [range, 59-82 years]) provided information on types of leisure time activity, and 118 153 (43%) died during a mean (SD) follow-up of 12.4 (3.9) years. In comparison with those who did not participate in each activity, 7.5 to less than 15 MET hours per week of racquet sports (HR, 0.84; 95% CI, 0.75-0.93) and running (HR, 0.85; 95% CI, 0.78-0.92) were associated with the greatest relative risk reductions for all-cause mortality, followed by walking for exercise (HR, 0.91; 95% CI, 0.89-0.93), other aerobic activity (HR, 0.93; 95% CI, 0.90-0.95), golf (HR, 0.93; 95% CI, 0.90-0.97), swimming (HR, 0.95; 95% CI, 0.92-0.98), and cycling (HR, 0.97; 95% CI, 0.95-0.99). Each activity showed a curvilinear dose-response association with mortality risk; low MET hours per week of physical activity for any given activity type were associated with a large reduction in mortality risk, with diminishing returns for each increment in activity thereafter. Associations were similar for cardiovascular and cancer mortality. Conclusions and Relevance: This cohort study of older individuals found differences between different types of leisure time activities and mortality risk, but there were significant associations between participating in 7.5 to less than 15 MET hours per week of any activity and mortality risk.

Rethinking the Digital Divide: Using an Internet Survey in a Flint Water Crisis Medicaid Population.

This project examined the preferred mode of response (internet, phone, mail) to a health services survey. Data were collected via survey responses from a subsample of Flint Water Crisis Medicaid Expansion Waiver enrollees (N=2,584). Analyses were stratified by age, residency, race, and income. Chi-square tests were used to detect categorical differences. The majority of participants responded by internet (55.5%), followed by mail (39.4%), and phone (5.2%). Of those responding by internet, 75% used smartphones for connectivity. Black and White respondents used the internet at a greater rate than Hispanic respondents (p<.01). Respondents at 200% federal poverty level (FPL) or higher used the internet mode at greater rates than those below 200% FPL (p<.01). Our findings suggest greater internet use in a vulnerable population than expected, but the digital divide persists. In the advent of COVID-19, this finding can inform future health programming using digital communication and telehealth.

Paramedic interactions with the packaging of medications and medical supplies: Poor package design has the potential to impact patient outcomes.

BACKGROUND: Settings where Emergency Medical Services (EMS) are provided to stabilize patients and transport them to locations better equipped to provide comprehensive care, "prehospital settings," are not frequently considered when designing packaged products. Packaging design is an understudied area, potentially impacting both healthcare provider behavior and patient outcomes. Our objectives were to: 1) describe difficulties associated with packaging in prehospital settings 2) investigate the coping strategies used by paramedics when difficulties occurred, and 3) assess the potential impacts these difficulties had on patient care. METHODS: An online, cross-sectional survey was distributed via email using the National EMS Certification database maintained by the National Registry of Emergency Medical Technicians (NREMT) to a random sample of nationally-certified paramedics. Eligible respondents were aged 18 and older, employed as paramedics and had administered care in a prehospital setting within the previous 12 months. Survey items explored difficulties experienced and coping strategies used when difficulty was encountered identifying or opening medications and/or medical supplies. Descriptive statistics and logistic regression were calculated to analyse responses for trends. RESULTS: Of the 12,000 emails sent, 1,912 participants responded (response rate = 16%). After removing respondents who had not administered care within the past 12 months and partial surveys, data from 1,702 respondents were analysed. Nearly 20% of all respondents reported that they had experienced difficulties identifying (21.1%) or opening (20.5%) medications and identifying (17.0%) or opening (23.4%) medical supplies within the past year. Between 1.2% (identifying a medication) and 3.0% (opening supplies) of those included in the analysis indicated that reported difficulties had negatively impacted patient care. Common coping strategies reported to deal with difficulty opening included partner assistance, tool use (scissors, pens, and knives), and the use of teeth, all potential pathways for the transmission of microbes, conceivably further impacting outcomes. CONCLUSION: More thoughtfully designed packaging for prehospital settings has the potential to benefit both EMS providers and the patients that they care for.

New Composite Measure for ADL Limitations: Application to Predicting Nursing Home Placement for Michigan MI Choice Clients.

Functional status measured by activities of daily living (ADL) may be used to predict nursing home placement. Scoring of ADL measures is summarized for convenience, yet this is accompanied by losing detail regarding deficits. We sought to determine whether a revised composite measure tailored to Michigan Medicaid beneficiaries would better identify those at risk for nursing home admission. We compared composite ADL measures created by exploratory factor analysis and additive modeling to Medicaid Enrollment, MI Choice Waiver program, and Nursing Facility claims data from 2013 to 2017. There were moderate to high levels of correlation between ADLs (.4-.82). Exploratory factor analysis extracted two factors, corresponding to domains of mobility or self-care tasks. Application of the self-care-based ADL limitations composite measure provided prediction power equivalent to an additive measure incorporating all ADL limitations for nursing home admission. This approach demonstrated improved interpretability with the need for just five measures.

Consistent Estimation of Generalized Linear Models with High Dimensional Predictors via Stepwise Regression.

Predictive models play a central role in decision making. Penalized regression approaches, such as least absolute shrinkage and selection operator (LASSO), have been widely used to construct predictive models and explain the impacts of the selected predictors, but the estimates are typically biased. Moreover, when data are ultrahigh-dimensional, penalized regression is usable only after applying variable screening methods to downsize variables. We propose a stepwise procedure for fitting generalized linear models with ultrahigh dimensional predictors. Our procedure can provide a final model; control both false negatives and false positives; and yield consistent estimates, which are useful to gauge the actual effect size of risk factors. Simulations and applications to two clinical studies verify the utility of the method.

The Efficacy of Neoadjuvant Versus Adjuvant Therapy for Resectable Esophageal Cancer Patients: A Systematic Review and Meta-Analysis.

OBJECTIVE: Inconclusive results are available as to whether chemo/radiotherapy should be administered to resectable esophageal cancer patients before surgery (neoadjuvant therapy) or after surgery (adjuvant therapy). The paper, via a meta-analysis of effects of treatment modalities when administering chemo/radiotherapy, aims to systematically evaluate the effect of timing of chemo/radiotherapy and surgery. METHODS: We performed a systematic literature search for clinical trials of neoadjuvant and adjuvant therapy for patients with esophageal cancer. Using meta-analysis, we conducted direct and adjusted indirect comparisons of overall survival, complete resection rate (R0 resection), perioperative mortality, leakage rate and local recurrence in patients with resectable esophageal cancer. RESULTS: A total of 32 studies involving 7985 patients with esophageal cancer were included in the meta-analysis. Twenty-five randomized controlled studies indirectly compared neoadjuvant/adjuvant therapy with surgery alone, while five non-randomized controlled studies and two randomized controlled studies directly compared neoadjuvant with adjuvant therapy. Neoadjuvant therapy followed by surgery, compared with surgery along with adjuvant therapy, showed a significant overall survival advantage in our pooled analysis (HR 0.88; 95% CI 0.79-0.98). Directly compared with adjuvant therapy, neoadjuvant therapy demonstrated a lower local recurrence rate (OR 0.56; 95% CI 0.43-0.74) with low heterogeneity (I2 = 1%). Neoadjuvant therapy, comparing to surgery with or without adjuvant therapy, showed a significantly higher R0 resection rate (OR 2.86; 95% CI 2.02-4.04) with moderate heterogeneity (I2 = 38%) and no significant differences in postoperative anastomotic leakage (P = 0.50). However, neoadjuvant therapy, compared with surgery adjuvant therapy, significantly increased perioperative mortality in both direct and indirect comparisons (P < 0.01). CONCLUSIONS: We found that neoadjuvant therapy was associated with higher overall survival and R0 resection rate without increasing postoperative anastomotic leakage for patients with resectable esophageal cancer, whereas neoadjuvant therapy was associated with higher perioperative mortality after esophagectomy.

The relationship between gut microbiota and short chain fatty acids in the renal calcium oxalate stones disease.

The relationship of gut microbiota and calcium oxalate stone has been limited investigated, especially with no study of gut microbiota and short chain fatty acids (SCFAs) in nephrolithiasis. We provided Sprague Dawley rats of renal calcium oxalate stones with antibiotics and examined the renal crystals deposition. We also performed a case-control study by analyzing 16S rRNA microbial profiling, shotgun metagenomics and SCFAs in 153 fecal samples from non-kidney stone (NS) controls, patients with occasional renal calcium oxalate stones (OS) and patients with recurrent stones (RS). Antibiotics reduced bacterial load in feces and could promote the formation of renal calcium crystals in model rats. In addition, both OS and RS patients exhibited higher fecal microbial diversity than NS controls. Several SCFAs-producing gut bacteria, as well as metabolic pathways associated with SCFAs production, were considerably lower in the gut microbiota among the kidney stone patients compared with the NS controls. Representation of genes involved in oxalate degradation showed no significance difference among groups. However, fecal acetic acid concentration was the highest in RS patients with high level of urinary oxalate, which was positively correlated with genes involvement in oxalate synthesis. Administration of SCFAs reduced renal crystals. These results shed new light on bacteria and SCFAs, which may promote the development of treatment strategy in nephrolithiasis.

Estimation of time-varying reproduction numbers underlying epidemiological processes: A new statistical tool for the COVID-19 pandemic.

The coronavirus pandemic has rapidly evolved into an unprecedented crisis. The susceptible-infectious-removed (SIR) model and its variants have been used for modeling the pandemic. However, time-independent parameters in the classical models may not capture the dynamic transmission and removal processes, governed by virus containment strategies taken at various phases of the epidemic. Moreover, few models account for possible inaccuracies of the reported cases. We propose a Poisson model with time-dependent transmission and removal rates to account for possible random errors in reporting and estimate a time-dependent disease reproduction number, which may reflect the effectiveness of virus control strategies. We apply our method to study the pandemic in several severely impacted countries, and analyze and forecast the evolving spread of the coronavirus. We have developed an interactive web application to facilitate readers' use of our method.