Discrete Time Periods Research Articles

The impact of COVID-19 restrictions on HIV prevention and treatment services for key populations in South Africa: an interrupted time series analysis

BackgroundKey populations (KP), including men who have sex with men (MSM), female sex workers (FSW), and transgender women (TGW), experience a disproportionate burden of HIV, even in generalized epidemics like South Africa. Given this disproportionate burden and unique barriers to accessing health services, sustained provision of care is particularly relevant. It is unclear how the COVID-19 pandemic and its associated restrictions may have impacted this delivery. In this study, we aimed to describe patterns of engagement in HIV prevention and treatment services among KP in South Africa and assess the impact of different COVID-19 restriction levels on service delivery.MethodsWe leveraged programmatic data collected by the US President’s Emergency Plan for AIDS Relief (PEPFAR)-supported KP partners in South Africa. We divided data into three discrete time periods based on national COVID-19 restriction periods: (i) Pre-restriction period, (ii) High-level restriction period, and (iii) After-high level restriction period. Primary outcomes included monthly total HIV tests, new HIV cases identified, new initiations of pre-exposure prophylaxis (PrEP), and new enrollments in antiretroviral therapy (ART). We conducted interrupted time series segmented regression analyses to estimate the impact of COVID-19 restrictions on HIV prevention and treatment service utilization.ResultsBetween January 2018 and June 2022, there were a total of 231,086 HIV tests, 27,051 HIV positive cases, 27,656 pre-exposure prophylaxis (PrEP) initiations, and 15,949 antiretroviral therapy initiations among MSM, FSW and TGW in PEPFAR-supported KP programs in South Africa. We recorded 90,457 total HIV tests during the ‘pre-restriction’ period, with 13,593 confirmed new HIV diagnoses; 26,134 total HIV tests with 2,771 new diagnoses during the ‘high-level restriction’ period; and 114,495 HIV tests with 10,687 new diagnoses during the after high-level restriction period. Our Poisson regression model estimates indicate an immediate and significant decrease in service engagement at the onset of COVID-19 restrictions, including declines in HIV testing, treatment, and PrEP use, which persisted. As programs adjusted to the new restrictions, there was a gradual rebound in service engagement, particularly among MSM and FSW. Towards the end of the high-level restriction period, with some aspects of daily life returning to normal but others still restricted, there was more variability. Some indicators continued to improve, while others stagnated or decreased.ConclusionService provision rebounded from the initial shock created by pandemic-related restrictions, and HIV services were largely maintained for KP in South Africa. These results suggest that HIV service delivery among programs designed for KP was able to be flexible and resilient to the evolving restrictions. The results of this study can inform plans for future pandemics and large-scale disruptions to the delivery of HIV services.

3D Chaotic Nonlinear Dynamic Population-Growing Mathematical System Modeling with Multiple Controllers

Modeling, stabilization, and identification processes are significant stages in the process of developing knowledge about chaotic dynamical systems which entail the effective prediction depending on the degree of uncertainty toleration in the forecast, accuracy of the current state to be measured as well as a time scale resting on the dynamics of the system. Control of under-activated dynamical systems has been considered substantially, and it is for periods and is currently developing in various domains such as biology, data analysis, computing systems, and so forth. Dynamic systems of growing population signifies a model describing the way a population evolves over time during which population goes through major life events, split into discrete time periods. The size of the population at a given time period is determined by the rate of growth as well as other related factors. Most progress has been made in model-based control theory, which has drawbacks when the system under consideration is exceedingly complicated, and no model can be constructed. Accordingly, a 3D-discrete and dynamic human population growth system with many controllers is proposed by examining the stability and symmetry of controller system clarifications. The symmetric stability control results are presented by considering a special parametric dynamic system in its coefficients besides suggesting periodic functional coefficients in terms of sin and cos functions. The controllers have the ability to reduce population growth rate unpredictability or enhance system stability under various external conditions. The unique and very effective strategies in relevant domains could provide a deeper understanding of their impact as well as the theoretical or technological innovations thereof. These controllers are capable of reducing population growth rate unpredictability or improving system stability under various external conditions, and applicable strategies in the relevant domains can provide profound comprehension over the impact along with the theoretical as well as technological advancements.

Emergency Department Referral of Patients With Chest Pain for Noninvasive Cardiac Testing and 2-Year Clinical Outcomes.

Noninvasive cardiac testing (NICT) has been associated with decreased long-term risks of major adverse cardiac events (MACEs) among emergency department patients at high coronary risk. It is unclear whether this association extends to patients without evidence of myocardial injury on initial ECG and cardiac troponin testing. A retrospective cohort study was conducted of patients presenting with chest pain between 2013 and 2019 to 21 emergency departments within an integrated health care system in Northern California, excluding patients with ST-segment-elevation myocardial infarction or myocardial injury by serum troponin testing. To account for confounding by indication, we grouped patient encounters by the NICT referral rate of the initially assigned emergency physician relative to local peers within discrete time periods. The primary outcome was MACE within 2 years. Secondary outcomes were coronary revascularization and MACE, inclusive of all-cause mortality. Associations between the NICT referral group (low, intermediate, or high) and outcomes were assessed using risk-adjusted proportional hazards methods with censoring for competing events. Among 144 577 eligible patient encounters, the median age was 58 years (interquartile range, 48-68) and 57% were female. Thirty-day NICT referral was 13.0%, 19.9%, and 27.8% in low, intermediate, and high NICT referral groups, respectively, with a good balance of baseline covariates between groups. Compared with the low NICT referral group, there was no significant decrease in the adjusted hazard ratio of MACE within the intermediate (adjusted hazard ratio, 1.08 [95% CI, 1.02-1.14]) or high (adjusted hazard ratio, 1.05 [95% CI, 0.99-1.11]) NICT referral groups. Results were similar for MACE, inclusive of all-cause mortality, and coronary revascularization, as well as subgroup analyses stratified by estimated risk (history, electrocardiogram, age, risk factors, troponin [HEART] score: percent classified as low risk, 48.2%; moderate risk, 49.2%; and high risk, 2.7%). Increases in NICT referrals were not associated with changes in the hazard of MACE within 2 years following emergency department visits for chest pain without evidence of acute myocardial injury. These findings further highlight the need for evidence-based guidance regarding the appropriate use of NICT in this population.

Why is the Cobb-Douglas production function so popular?

It is well known that, in continuous time, the Cobb-Douglas function can be derived from the underlying, data governing, accounting identity under some reasonable assumptions (factor shares are constant, and the weighted growth of the labour input price and the capital input price is constant). In this article these results are generalized in three ways: (1) the accounting identity contains a (pure) profit term; (2) continuous time is replaced by discrete time periods; (3) additional assumptions appear to be superfluous. The article also discusses extensions: from two to multiple inputs, from value added to gross output, and from a single production unit to an ensemble of those units.

Call and response: Ethnomusicological methods to awaken specific memories with targeted songs encoded in neuronal populations of a dementia patient

AbstractThis study collaborates with a fellow expert ethnomusicologist Sean Williams to trigger specific contextual memories associated with songs of her mother Julian Williams, born in 1932, and currently struggling with the early stages of dementia. The goal was to ascertain the success rate of a one‐to‐one correspondence type: The use of targeted, known songs of the dementia patient as a means to trigger the patient’s contextual memories.By adopting a methodology in Ethnomusicology involving the autobiography of one’s music history and their corresponding memories of the patient Julian Williams, I set up the experiment for Sean Williams to conduct. Dividing the study into discrete music time periods (infancy, childhood, teenager, young adult, older adult), I asked Sean Williams to choose specific songs with specific memories to the patient to be sung. The memory responses of the patient on video were then recorded.Each of those songs had deep levels of recognition by the Alzheimer’s patient, as evidenced in her singing with some memories (lyrics and contextual environment) stronger than than others. The fact that there is some autobiographical recall, despite a weakened sense of time and space after the onset of Alzheimer’s, suggests there may be use for this technique in dementia care. Of note, is the fun‐filled disposition of the participants during the recording of the singing. That speaks to a higher quality of life one could expect by using music as a memory‐recall and time‐ travel companion.This single case study needs to be broadened into a larger‐scale experiment involving many participants from different cultures to ascertain the use of individualized targeted songs to awaken specific memories of the dementia patients. In the area of dementia care, this approach also makes it possible for families to participate actively since the songs will probably be known to them as well.

Impact of food-related conflicts on self-reported food insecurity

Food security is recognized as an inherent human right, enshrined within the principles of the Agenda 2030. The Global Report of Food Crises 2022 points out 193 million people facing severe food insecurity across 53 countries, posing challenges to decision-makers and institutions. Among the many causes of food crises, violent conflict, economic shocks, and environmental pressures are the most influential. In this work, we focus primarily on the conflict-related domain. Finding a stable relationship between conflict and food insecurity is complex for several reasons: first, the relationship is mutually reinforcing; second, the full impact of conflict on food insecurity may take time to have an effect; and third, conflict itself is a multidimensional phenomenon and can include multiple types of violent events. This research set out to comparatively assess the impact of different types of violence on self-reported food insecurity in three prominent food crisis contexts: Burkina Faso, Syria, and Yemen. A measure of food-related classifying events was developed using a rules-based approach. The analysis showed that this approach can effectively code and classify food-related conflict in diverse contexts. By refining the search string, it becomes possible to capture food-related conflict in various food systems. Our findings point out that the new-build measure of food-related conflict is more strongly correlated to subsequent self-reported insufficient food consumption than other forms of violence. The results demonstrate that this relationship is robust across a range of data collection windows and across discrete time periods of analysis. In summary, the research suggests that focusing on the use of food and food systems as tactics in conflict can be highly valuable for understanding and addressing food insecurity.

Rates of John Cunningham virus seroconversion greatly reduced in natalizumab-treated patients during COVID-19-related lockdowns.

This study was undertaken to retrospectively compare rates of John Cunningham virus (JCV) seroconversion in natalizumab-treated patients before and during COVID-19-related community restrictions. Natalizumab is highly effective therapy for relapsing-remitting multiple sclerosis. Prolonged exposure to natalizumab in JCV-positive patients can cause progressive multifocal leukoencephalopathy, a potentially fatal brain infection. Serial assessment of JCV status is required for patients receiving natalizumab. Patients receiving natalizumab at the Royal Melbourne Hospital were assessed for change in JCV serostatus and duration of exposure to natalizumab in two discrete time periods: from 1 February 2012 until 1 February 2017 ("pre-COVID"; n = 128) and from 1 April 2020 until 12 October 2022 ("COVID"; n = 214). A Poisson regression model adjusted for age at natalizumab commencement and sex was used to model seroconversion rate between the two time periods. The pre-COVID JCV seroconversion rate among natalizumab-treated patients at the Royal Melbourne Hospital was 9.08%. Conversely, we found a precipitous decline in JCV seroconversion during COVID lockdown. Annualized seroconversion during COVID-19-related restrictions was 2.01%. The annualized seroconversion rate was 4.7 times higher during the pre-COVID-19 period (95% confidence interval = 2.96-7.45, p < 0.0001) compared to the annualized seroconversion rate during COVID lockdown. Males had a 2× higher rate of seroconversion compared to females. JCV seroconversion among natalizumab-treated patients was markedly lower during COVID-19-related community restrictions. Restrictions observed in Melbourne were among the longest and most comprehensive implemented worldwide. This suggests the presence of modifiable risk factors that could lower rates of JCV seroconversion among natalizumab-treated patients.

Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer.

When utilities are analyzed by time to death (TTD), this has historically been implemented by 'grouping' observations as discrete time periods to create health state utilities. We extended the approach to use continuous functions, avoiding assumptions around groupings. The resulting models were used to test the concept with data from different regions and different country tariffs. Five-year follow-up in advanced non-small cell lung cancer (NSCLC) was used to fit six continuous TTD models using generalized estimating equations, which were compared with progression-based utilities and previously published TTD groupings. Sensitivity analyses were performed using only patients with a confirmed death, the last year of life only, and artificially censoring data at 24 months. The statistically best-fitting model was then applied to data subsets by region and different EQ-5D-3L country tariffs. Continuous (natural) [Formula: see text] and [Formula: see text] models outperformed other continuous models, grouped TTD, and progression-based models in statistical fit (mean absolute error and Quasi Information Criterion). This held through sensitivity and scenario analyses. The pattern of reduced utility as a patient approaches death was consistent across regions and EQ-5D tariffs using the preferred [Formula: see text] model. The use of continuous models provides a statistically better fit than TTD groupings, without the need for strong assumptions about the health states experienced by patients. Where a TTD approach is merited for use in modelling, continuous functions should be considered, with the scope for further improvements in statistical fit by both widening the number of candidate models tested and the therapeutic areas investigated.

TSM: Temporal segmentation and modules-based computation offloading using predictive analytics and NR-V2X

Recent increases in the usage of applications dependent on distributed computing have persuaded designers and entrepreneurs to utilize these solutions for diverse purposes, especially latency-constrained computation-intensive applications. Vehicular fog computing (VFC) is the innovative paradigm of distributed computing techniques, and therefore, a number of VFC offloading frameworks have been developed using AI-based advanced optimization procedures, with support from standards maintenance organizations like IEEE, 3rd Generation Partnership Project (3GPP), and some others. However, many of these strategies have not been adapted to specific application data and types, therefore these frameworks may function poorly despite their comprehensive offloading principles. Moreover, most computation offloading frameworks ignore the use of updated V2X protocols. We designed a temporal segmentation and modules (TSM)-based method specific for computation-intensive V2X applications that uses a four-tier hierarchy of resource-rich nodes and works in discrete time periods. TSM relies on status updates from previous time periods and uses predictive analytics to address the stochastic nature of vehicular networks using the latest 3GPP 5G V2X standards. Using an online modular computation offloading structure that heuristically manages the whole process, we were able to successfully and timely execute the latency-sensitive advanced vehicular applications. TSM supports computation-deficient devices in under a hundred milliseconds, makes use of smart vehicles’ processing units as fog nodes, and solves the optimization problem in short, discrete stages. We utilized Monte Carlo analysis, which confirmed that TSM outperformed the three other baseline methods.

Interrupting prolonged sitting with frequent short bouts of light-intensity activity in people with type 1 diabetes improves glycaemic control without increasing hypoglycaemia: The SIT-LESS randomised controlled trial.

To examine the impact of interrupting prolonged sitting with frequent short bouts of light-intensity activity on glycaemic control in people with type 1 diabetes (T1D). In total, 32 inactive adults with T1D [aged 27.9 ± 4.7 years, 15 men, diabetes duration 16.0 ± 6.9 years and glycated haemoglobin 8.4 ± 1.4% (68 ± 2.3 mmol/mol)] underwent two 7-h experimental conditions in a randomised crossover fashion with >7-day washout consisting of: uninterrupted sitting (SIT), or, interrupted sitting with 3-min bouts of self-paced walking at 30-min intervals (SIT-LESS). Standardised mixed-macronutrient meals were administered 3.5 h apart during each condition. Blinded continuous glucose monitoring captured interstitial glucose responses during the 7-h experimental period and for a further 48-h under free-living conditions. SIT-LESS reduced total mean glucose (SIT 8.2 ± 2.6 vs. SIT-LESS 6.9 ± 1.7 mmol/L, p = .001) and increased time in range (3.9-10.0 mmol/L) by 13.7% (SIT 71.5 ± 9.5 vs. SIT-LESS 85.1 ± 7.1%, p = .002). Hyperglycaemia (>10.0 mmol/L) was reduced by 15.0% under SIT-LESS (SIT 24.2 ± 10.8 vs. SIT-LESS 9.2 ± 6.4%, p = .002), whereas hypoglycaemia exposure (<3.9 mmol/L) (SIT 4.6 ± 3.0 vs. SIT-LESS 6.0 ± 6.0%, p = .583) was comparable across conditions. SIT-LESS reduced glycaemic variability (coefficient of variation %) by 7.8% across the observation window (p = .021). These findings were consistent when assessing discrete time periods, with SIT-LESS improving experimental and free-living postprandial, whole-day and night-time glycaemic outcomes (p < .05). Interrupting prolonged sitting with frequent short bouts of light-intensity activity improves acute postprandial and 48-h glycaemia in adults with T1D. This pragmatic strategy is an efficacious approach to reducing sedentariness and increasing physical activity levels without increasing risk of hypoglycaemia in T1D.

Defining and reporting activity patterns: a modified Delphi study

BackgroundDespite significant interest in assessing activity patterns in different populations, there has been no consensus concerning the definition and operationalisation of this term. This has limited the comparability, interpretability, and synthesis of study findings to date. The aim of this study was to establish a consensus regarding the way in which activity patterns and activity pattern components are defined and reported.MethodsThe activity patterns literature was searched to identify experts to be invited to participate and to develop a proposed definition of activity patterns and activity pattern components. A three-round modified Delphi survey was conducted online (November 2021 to May 2022). In Round 1, participants were asked to rate their agreement with a proposed activity patterns definition, which also included six activity pattern components (e.g., activity intensity, activity bout, transitions), six examples of activity patterns (e.g., frequency of postural transitions in discrete time periods) and eight items for reporting activity patterns in future research (n = 21 items). Open-ended questions enabled participants to provide further comments and suggestions for additional items. Consensus was defined a priori as ≥ 80% participants rating their agreement with an item. In Round 2, participants were asked to rate their agreement with 25 items (13 original items, eight amended, and four new). In Round 3, participants rated their agreement with 10 items (five original items, four amended, and one new).ResultsTwenty experts in activity patterns research participated in Round 1, with response rates of 80% and 60% in Rounds 2 and 3, respectively. The proposed activity pattern definition, all activity pattern components definitions, four of the six activity pattern examples, and 10 items in the activity patterns reporting framework achieved consensus. The removal of one activity component item between Rounds 1 and 2 achieved consensus.ConclusionThis modified Delphi study achieved consensus for defining and reporting activity patterns for the first time. This consensus definition enables standardisation of activity patterns terminology, which is important given the significant interest in quantifying how individuals accumulate their physical activity and sedentary behaviour across the lifespan to inform the development of future public health guidelines and interventions efforts.

Music as a trigger for specific memories

AbstractBackgroundThis study uses the expertise of an ethnomusicologist who uses preexisting music in the brain music as the cue to trigger the autobiographical memories of her own mother struggling with dementia.MethodBy adapting a methodology in Ethnomusicology involving the autobiography of one’s music history, I set up the experiment for another ethnomusicologist to conduct. Dividing the study into discrete music time periods (infancy, childhood, teenager, young adult, older adult), I delineated specific songs or pieces of music with powerful meanings to the patient in those time periods to be played. The responses of the patient on video was then recorded.ResultEach of those pieces of music had some level of recognition by the Alzheimer’s patient, some stronger than others. Other attendant contextual memories surfaced during the experiment, suggesting autobiographical recall, despite a weakened sense of time and space after the onset of Alzheimer’s.ConclusionThis single case study needs to be broadened into a larger scale experiment involving many participants to assess the efficacy of this ethnomusicological‐derived approach to improve autobiographical recall abilities among the Alzheimer’s patients. This approach also makes it possible for families to engage in the autobiographical recall process using the preexisting music in the patients’ neural pathways. This study also offers collaborative efforts between Ethnomusicology and Neurology in running clinical trials to develop autobiographical memory recall processes for therapy.

Spatiotemporal changes in largemouth bass mercury concentrations from Connecticut waterbodies, 1995-2021.

We evaluated spatiotemporal changes in the mean and variation in largemouth bass (Micropterus salmoides) mercury concentrations over three discrete time periods (1995, 2005-2006, and 2019-2021) across 56 Connecticut waterbodies. We detected largemouth bass raw mercury concentrations that exceeded the US Environmental Protection Agency (USEPA) Fish Tissue Residue Criterion (≥ 0.30µgg-1 ww) in 75.1%, 63.3%, and 47.7% of all fish sampled during 1995, 2005-2006, and 2019-2021, respectively. Total length (TL)-adjusted largemouth bass mercury concentrations declined across all ecoregions in Connecticut between subsequent sampling periods but increased between 2005-2006 and 2019-2021 in the Northwest Hills/Uplands ecoregion. The coefficient of variation (CV) of largemouth bass TL-adjusted mercury concentrations increased through time, increasing from 25.78% during 1995 to 36.47% during 2019-2021. The probability of a largemouth bass having a raw mercury concentration > 0.30µgg-1 ww increased with total length (TL), but the TL with a 50% probability varied across ecoregions and periods. The variation in largemouth bass mercury concentrations highlights the roles that changes to individual behaviors, food web structure, lake properties, and legacy mercury may play in shaping broad patterns and trends in mercury consumption risks.

Modeling the spatiotemporal spread of beneficial alleles using ancient genomes.

Ancient genome sequencing technologies now provide the opportunity to study natural selection in unprecedented detail. Rather than making inferences from indirect footprints left by selection in present-day genomes, we can directly observe whether a given allele was present or absent in a particular region of the world at almost any period of human history within the last 10,000 years. Methods for studying selection using ancient genomes often rely on partitioning individuals into discrete time periods or regions of the world. However, a complete understanding of natural selection requires more nuanced statistical methods which can explicitly model allele frequency changes in a continuum across space and time. Here we introduce a method for inferring the spread of a beneficial allele across a landscape using two-dimensional partial differential equations. Unlike previous approaches, our framework can handle time-stamped ancient samples, as well as genotype likelihoods and pseudohaploid sequences from low-coverage genomes. We apply the method to a panel of published ancient West Eurasian genomes to produce dynamic maps showcasing the inferred spread of candidate beneficial alleles over time and space. We also provide estimates for the strength of selection and diffusion rate for each of these alleles. Finally, we highlight possible avenues of improvement for accurately tracing the spread of beneficial alleles in more complex scenarios.

Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing

Briefing: In the construction of Metaverses, sensors that are referred to as the “bridge of information transmission”, play a key role. The functionality and efficiency of today's sensors, which operate in a manner similar to physical sensing, are frequently constrained by their hardware and software. In this research, we proposed the Parallel Sensing framework, which includes background, concept, basic methods and typical application of parallel sensing. In our formulation, sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence, in order to boost the performance of the sensors. Each sensor will have a parallel counterpart in the virtual world within the framework of parallel sensing. Digital sensors serve as the brain of sensors and maintain the same properties as physical sensors. Parallel sensing allows physical sensors to operate in discrete time periods to conserve energy, while cloud-based descriptive, predictive, and prescriptive sensors operate continuously to offer compensation data and serve as guardians. To better illustrate parallel sensing concept, we show some example applications of parallel sensing such as parallel vision, parallel point cloud and parallel light fields, both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception models. Experimental results demonstrate the effective of parallel sensing framework. The interaction between the real and virtual worlds enables sensors to operate actively, allowing them to intelligently adapt to various scenarios and ultimately attain the goal of “Cognitive, Parallel, Crypto, Federated, Social and Ecologic” 6S sensing.

Statewide Examination of Access to Cancer Surgery During the COVID-19 Pandemic

IntroductionThe COVID-19 pandemic caused interruptions in the delivery of medical care across a wide range of conditions including cancer. Trends in surgical treatment for cancer during the pandemic have not been well described. We sought to characterize associations between the pandemic and access to surgical treatment for breast, colorectal, and lung cancer in Illinois. MethodsWe performed a retrospective cohort study evaluating inpatient admissions at Illinois hospitals providing surgical care for lung cancer (n = 1913 cases, n = 64 hospitals), breast cancer (n = 910 cases, n = 108 hospitals), and colorectal cancer (n = 5339 cases, n = 144 hospitals). Using discharge data from the Illinois Health and Hospital Association's Comparative Health Care and Hospital Data Reporting Services database, average monthly surgical case volumes were compared from 2019 to 2020. We also compared rates of cancer surgery for each cancer type, by patient characteristics, and hospital type across the three time periods using Pearson chi-squared and ANOVA testing as appropriate. Three discrete time periods were considered: prepandemic (7-12/2019), primary pandemic (4-6/2020), and pandemic recovery (7-12/2020). Hospital characteristics evaluated included hospital type (academic, community, safety net), COVID-19 burden, and baseline cancer surgery volume. ResultsThere were 2096 fewer operations performed for breast, colorectal, and lung cancer in 2020 than 2019 in Illinois, with the greatest reductions in cancer surgery volume occurring at the onset of the pandemic in April (colorectal, −48.3%; lung, −13.1%) and May (breast, −45.2%) of 2020. During the pandemic, breast (−14.6%) and colorectal (−13.8%) cancer surgery experienced reductions in volume whereas lung cancer operations were more common (+26.4%) compared to 2019. There were no significant differences noted in gender, race, ethnicity, or insurance status among patients receiving oncologic surgery during the primary pandemic or pandemic recovery periods. Academic hospitals, hospitals with larger numbers of COVID-19 admissions, and those with greater baseline cancer surgery volumes were associated with the greatest reduction in cancer surgery during the primary pandemic period (all cancer types, P < 0.01). During the recovery period, hospitals with greater baseline breast and lung cancer surgery volumes remained at reduced surgery volumes compared to their counterparts (P < 0.01). ConclusionsThe COVID-19 pandemic was associated with significant reductions in breast and colorectal cancer operations in Illinois, while lung cancer operations remained relatively consistent. Overall, there was a net reduction in cancer surgery that was not made up during the recovery period. Academic hospitals, those caring for more COVID-19 patients, and those with greater baseline surgery volumes were most vulnerable to reduced surgery rates during peaks of the pandemic and to delays in addressing the backlog of cases.

Association of the Timing of Postpartum Intrauterine Device Insertion and Breastfeeding With Risks of Intrauterine Device Expulsion

Intrauterine device (IUD) expulsion increases the risk of unintended pregnancy; how timing of postpartum IUD insertion and breastfeeding are associated with risk of expulsion is relevant to the benefit-risk profile. To evaluate the association of postpartum timing of IUD insertion and breastfeeding status with incidence and risk of IUD expulsion. The Association of Perforation and Expulsion of Intrauterine Devices (APEX-IUD) cohort study included women aged 50 years or younger with an IUD insertion between 2001 and 2018. The breastfeeding analysis focused on a subcohort of women at 52 or fewer weeks post partum with known breastfeeding status. The study was conducted using data from electronic health records (EHRs) at 4 research sites with access to EHR: 3 Kaiser Permanente sites (Northern California, Southern California, Washington) and the Regenstrief Institute (Indiana). Data analysis was conducted from June to November 2019. Timing of IUD insertion post partum was categorized into discrete time periods: 0 to 3 days, 4 days to 6 or fewer weeks, more than 6 weeks to 14 or fewer weeks, more than 14 weeks to 52 or fewer weeks, and non-post partum (>52 weeks or no evidence of delivery). Breastfeeding status at the time of insertion was determined from clinical records, diagnostic codes, or questionnaires from well-baby visits. Incidence rates and adjusted hazard ratios (aHRs) were estimated using propensity scores to adjust for confounding. The full cohort included 326 658 women (mean [SD] age, 32.0 [8.3] years; 38 911 [11.9%] Asian or Pacific Islander; 696 [0.2%] Hispanic Black; 56 180 [17.2%] Hispanic other; 42 501 [13.0%] Hispanic White; 28 323 [8.7%] non-Hispanic Black; 137 102 [42.0%] non-Hispanic White), and the subcohort included 94 817 women. Most IUDs were levonorgestrel-releasing (259 234 [79.4%]). There were 8943 expulsions. The 5-year cumulative incidence of IUD expulsion was highest for insertions 0 to 3 days post partum (10.73%; 95% CI, 9.12%-12.61%) and lowest for insertions more than 6 weeks to 14 or fewer weeks post partum (3.18%; 95% CI, 2.95%-3.42%). Adjusted HRs using women with non-post partum IUD insertion as the referent were 5.34 (95% CI, 4.47-6.39) for those with postpartum insertion at 0 to 3 days; 1.22 (95% CI, 1.05-1.41) for those with postpartum insertion at 4 days to 6 or fewer weeks; 1.06 (95% CI, 0.95-1.18) for those with postpartum insertion at more than 6 to 14 or fewer weeks; and 1.43 (95% CI, 1.29-1.60) for those with postpartum insertion at more than 14 to 52 or fewer weeks. In the subcohort, 5-year cumulative incidence was 3.49% (95% CI, 3.25%-3.73%) for breastfeeding women and 4.57% (95% CI, 4.22%-4.95%) for nonbreastfeeding women; the adjusted HR for breastfeeding vs not breastfeeding was 0.71 (95% CI, 0.64-0.78). In this study of real-world data, IUD expulsion was rare but more common with immediate postpartum insertion. Breastfeeding was associated with lower expulsion risk.

Higher intensity of 72-h noninvasive cardiac test referral does not improve short-term outcomes among emergency department patients with chest pain.

It is unclear whether referral for cardiac noninvasive testing (NIT) following emergency department (ED) chest pain encounters improves short-term outcomes. This was a retrospective cohort study of patients presenting with chest pain, without ST-elevation myocardial infarction or myocardial injury by serum troponin testing, between 2013 and 2019 to 21 EDs within an integrated health care system. We examined the association between NIT referral (within 72h of the ED encounter) and a primary outcome of 60-day major adverse cardiac events (MACE). Secondary outcomes were 60-day MACE without coronary revascularization (MACE-CR) and 60-day all-cause mortality. To account for confounding by indication for NIT, we grouped patient encounters into ranked tertiles of NIT referral intensity based on the likelihood of 72-h NIT referral associated with the initially assigned emergency physician, relative to local peers and within discrete time periods. Associations between NIT referral-intensity tertile and outcomes were assessed using risk-adjusted multivariable logistic regression. Among 210,948 eligible patient encounters, 72-h NIT referral frequency was 11.9%, 18.3%, and 25.9% in low, intermediate, and high NIT referral-intensity encounters, respectively. Compared with the low referral-intensity tertile, there was a higher risk of 60-day MACE within the high referral-intensity tertile (odds ratio [OR]= 1.11, 95% confidence interval [CI]= 1.04 to 1.17) due to more coronary revascularizations without corresponding differences in MACE-CR or all-cause mortality. In analyses stratified by patients' estimated risk (HEART score; 50.5% lower risk, 38.7% moderate risk, 10.8% higher risk), the difference in 60-day MACE was primarily attributable to moderate-risk encounters (OR= 1.15, 95% CI= 1.08 to 1.24), with no differences among either lower- (OR= 1.10, 95% CI= 0.92 to 1.31) or higher- (OR= 1.01, 95% CI= 0.90 to 1.14) risk encounters. Higher referral intensity for 72-h NIT was associated with higher risk of coronary revascularization but no difference in adverse events within 60days. These findings further call into question the urgency of NIT among ED patients without objective evidence of myocardial injury.

Reconstruction of dynamic regulatory networks reveals signaling-induced topology changes associated with germ layer specification.

SummaryElucidating regulatory relationships between transcription factors (TFs) and target genes is fundamental to understanding how cells control their identity and behavior. Unfortunately, existing computational gene regulatory network (GRN) reconstruction methods are imprecise, computationally burdensome, and fail to reveal dynamic regulatory topologies. Here, we present Epoch, a reconstruction tool that uses single-cell transcriptomics to accurately infer dynamic networks. We apply Epoch to identify the dynamic networks underpinning directed differentiation of mouse embryonic stem cells (ESCs) guided by multiple signaling pathways, and we demonstrate that modulating these pathways drives topological changes that bias cell fate potential. We also find that Peg3 rewires the pluripotency network to favor mesoderm specification. By integrating signaling pathways with GRNs, we trace how Wnt activation and PI3K suppression govern mesoderm and endoderm specification, respectively. Finally, we identify regulatory circuits of patterning and axis formation that distinguish in vitro and in vivo mesoderm specification.

Model and solution for the traveling salesman problem with multiple time windows

This paper applies the multi-time window traveling salesman problem to not only optimize the logistics cost, but also effectively endow users with multiple discrete idle optional time periods to meet the time requirements of just-in-time production. In the process of problem solving, firstly, the dynamic penalty factor is introduced into the objective function and the penalty function is added to relax the constraints of multi-time window in order to construct the relaxation model. Secondly, while in solving the model, the compressed annealing algorithm, which has the property of probability convergence, is proposed on the basis of the simulated annealing algorithm with only temperature parameter. The dynamic penalty factor is added as a pressure parameter to control the probability of the transition to an infeasible route regarding the time windows. Finally, comparison through data experiments between multi-time windows and single-time windows verifies the practicability of the former and comparison between the solution algorithm and simulated annealing algorithm verifies the stability of compressed annealing algorithm. The result shows that the compressed annealing algorithm is a comparatively better method to solve multi-time window traveling salesman problem.