Effect of mobile health reminders on tuberculosis treatment outcomes in Shanghai, China: A prospective cohort study

BackgroundPoor adherence increases the risk of unfavorable outcomes for tuberculosis (TB) patients. Mobile health (mHealth) reminders become promising approaches to support TB patients’ treatment. But their effects on TB treatment outcomes remain controversial. In this prospective cohort study, we evaluated the effect of the reminder application (app) and the smart pillbox on TB treatment outcomes compared with the standard care in Shanghai, China.MethodsWe recruited new pulmonary TB (PTB) patients diagnosed between April and November 2019 who were aged 18 or above, treated with the first-line regimen (2HREZ/4HR), and registered at Songjiang CDC (Shanghai). All eligible patients were invited to choose the standard care, the reminder app, or the smart pillbox to support their treatment. Cox proportional hazard model was fitted to assess the effect of mHealth reminders on treatment success.Results260 of 324 eligible patients enrolled with 88 using standard care, 82 the reminder app, and 90 the smart pillbox, followed for a total of 77,430 days. 175 (67.3%) participants were male. The median age was 32 (interquartile range [IQR] 25 to 50) years. A total of 44,785 doses were scheduled for 172 patients in the mHealth reminder groups during the study period. 44,604 (99.6%) doses were taken with 39,280 (87.7%) monitored by the mHealth reminders. A significant time-dependent downward linear trend was observed in the monthly proportion of dose intake (p < 0.001). 247 (95%) patients were successfully treated. The median treatment duration of successfully treated patients in the standard care group was 360 (IQR 283–369) days, significantly longer than those in the reminder app group (296, IQR 204–365, days) and the smart pillbox group (280, IQR 198–365, days) (both p < 0.01). Using the reminder app and the smart pillbox was associated with 1.58 times and 1.63 times increase in the possibility of treatment success compared with the standard care, respectively (both p < 0.01).ConclusionThe reminder app and the smart pillbox interventions were acceptable and improved the treatment outcomes compared with the standard care under the programmatic setting in Shanghai, China. More high-level evidence is expected to confirm the effect of mHealth reminders on TB treatment outcomes

Assessing the spatial heterogeneity of tuberculosis in a population with internal migration in China: a retrospective population-based study

BackgroundInternal migrants pose a critical threat to eliminating Tuberculosis (TB) in many high-burden countries. Understanding the influential pattern of the internal migrant population in the incidence of tuberculosis is crucial for controlling and preventing the disease. We used epidemiological and spatial data to analyze the spatial distribution of tuberculosis and identify potential risk factors for spatial heterogeneity.MethodsWe conducted a population-based, retrospective study and identified all incident bacterially-positive TB cases between January 1st, 2009, and December 31st, 2016, in Shanghai, China. We used Getis-Ord Gi* statistics and spatial relative risk methods to explore spatial heterogeneity and identify regions with spatial clusters of TB cases, and then used logistic regression method to estimate individual-level risk factors for notified migrant TB and spatial clusters. A hierarchical Bayesian spatial model was used to identify the attributable location-specific factors.ResultsOverall, 27,383 bacterially-positive tuberculosis patients were notified for analysis, with 42.54% (11,649) of them being migrants. The age-adjusted notification rate of TB among migrants was much higher than among residents. Migrants (aOR, 1.85; 95%CI, 1.65-2.08) and active screening (aOR, 3.13; 95%CI, 2.60-3.77) contributed significantly to the formation of TB high-spatial clusters. With the hierarchical Bayesian modeling, the presence of industrial parks (RR, 1.420; 95%CI, 1.023-1.974) and migrants (RR, 1.121; 95%CI, 1.007-1.247) were the risk factors for increased TB disease at the county level.ConclusionWe identified a significant spatial heterogeneity of tuberculosis in Shanghai, one of the typical megacities with massive migration. Internal migrants play an essential role in the disease burden and the spatial heterogeneity of TB in urban settings. Optimized disease control and prevention strategies, including targeted interventions based on the current epidemiological heterogeneity, warrant further evaluation to fuel the TB eradication process in urban China

A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3

The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the potential to provide additional options for drug development. This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. These techniques were used to identify inhibitors of JAK3 with a novel sketch from a specific “In-house” database. Using molecular docking with varying precision, MM/GBSA, geometric deep learning scoring, and manual selection, 10 compounds were obtained for subsequent biological evaluation. One of these 10 compounds, compound 8, was found to have inhibitory potency against JAK3 and the MOLM-16 cell line, providing a valuable lead compound for further development of JAK3 inhibitors. To gain a better understanding of the interaction between compound 8 and JAK3, molecular dynamics (MD) simulations were conducted to provide more details on the binding conformation of compound 8 with JAK3 to guide the subsequent structure optimization. In this article, we achieved compound 8 with a novel sketch possessing inhibitory bioactivity against JAK3, and it would provide an acceptable “hit” for further structure optimization and modification to develop JAK3 inhibitors

Numerical Investigation of Non-Newtonian Flow and Heat Transfer Characteristics in Rectangular Tubes with Protrusions

Flow characteristics and heat transfer performances in rectangular tubes with protrusions are numerically investigated in this paper. The thermal heat transfer enhancement of composite structures and flow resistance reduction of non-Newtonian fluid are taken advantage of to obtain a better thermal performance. Protrusion channels coupled with different CMC concentration solutions are studied, and the results are compared with that of smooth channels with water flow. The comprehensive influence of turbulence effects, structural effects, and secondary flow effects on the CMC’s flow in protrusion tubes is extensively investigated. The results indicate that the variation of flow resistance parameters of shear-thinning power-law fluid often shows a nonmonotonic trend, which is different from that of water. It can be concluded that protrusion structure can effectively enhance the heat transfer of CMC solution with low pressure penalty in specific cases. Moreover, for a specific protrusion structure and a fixed flow velocity, there exists an optimal solution concentration showing the best thermal performance

Study on treatment outcome and risk factors of multidrug-resistant pulmonary tuberculosis patients in Shanghai

ObjectiveTo describe the characteristics of treatment outcomes of multidrug-resistant tuberculosis （MDR-TB） patients enrolled in second-line treatment in Shanghai from 2017 to 2018， and to analyze the influencing factors of treatment outcomes.MethodsTotally 182 MDR-TB patients were analyzed by using data collected from the China tuberculosis management information system， the hospital's electronic medical record information system， whole genome sequencing results and a questionnaire survey， and logistic regression analysis was used to analyze the factors affecting the success of treatment.ResultsIn 182 MDR-TB patients， the success rate of treatment was 65.4%， the loss to follow-up rate was 8.2%， the mortality rate was 4.9%， the unassessable rate was 13.7%， and the drug withdrawal rate was 7.7%. The factors affecting the success of treatment in MDR-TB patients included age （35‒ years old， OR=5.28， 95%CI： 1.58‒17.59， P=0.007； 55‒ years old， OR=16.30， 95%CI： 4.36‒60.92， P<0.001） and compliance to medication （OR=0.55， 95%CI： 0.42‒0.72， P<0.001）.ConclusionThe treatment success rate of MDR-TB patients in Shanghai from 2017 to 2018 is significantly higher than the average level in China. Older patients and patients with less compliant are at higher risk of adverse treatment outcomes

Data_Sheet_1_A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3.pdf

The JAKs protein family is composed of four isoforms, and JAK3 has been regarded as a druggable target for the development of drugs to treat various diseases, including hematologic tumors, cancer, and neuronal death. Therefore, the discovery of JAK3 inhibitors with novel scaffolds possesses the potential to provide additional options for drug development. This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. These techniques were used to identify inhibitors of JAK3 with a novel sketch from a specific “In-house” database. Using molecular docking with varying precision, MM/GBSA, geometric deep learning scoring, and manual selection, 10 compounds were obtained for subsequent biological evaluation. One of these 10 compounds, compound 8, was found to have inhibitory potency against JAK3 and the MOLM-16 cell line, providing a valuable lead compound for further development of JAK3 inhibitors. To gain a better understanding of the interaction between compound 8 and JAK3, molecular dynamics (MD) simulations were conducted to provide more details on the binding conformation of compound 8 with JAK3 to guide the subsequent structure optimization. In this article, we achieved compound 8 with a novel sketch possessing inhibitory bioactivity against JAK3, and it would provide an acceptable “hit” for further structure optimization and modification to develop JAK3 inhibitors.</p

Latent tuberculosis infection status and its risk factors among tuberculosis-related health-care workers in Shanghai

ObjectiveTo obtain the status of latent tuberculosis infection （LTBI） among tuberculosis （TB）-related health-care workers （HCWs） in Shanghai， and to explore the risk factors related to TB infection.MethodsA multi-center cross-sectional study was conducted by recruiting medical workers from multiple designated TB hospitals， centers for disease control and prevention， and community health service centers in Shanghai. Each subject was required to complete a questionnaire and to provide a blood sample for TB infection test. Univariate and multivariate analysis ware made in order to find risk factors relating to TB infection.ResultsA total of 165 medical workers were recruited， and the proportion of TB infection was 16.36% （95%CI： 11.49%‒22.76%）. Multivariate logistic analysis showed that clinical doctors and nurses （adjusted OR=9.756， 95%CI： 1.790‒53.188）， laboratory staffs （adjusted OR=78.975， 95%CI： 8.749‒712.918）， and nursing and cleaning workers （adjusted OR=89.920， 95%CI： 3.111‒2 598.930） had higher risk of TB infection.ConclusionThe overall LTBI prevalence among TB-related HCWs is low. However， working as doctors， nurses， laboratory staffs， nursing workers and cleaning workers are risk factors of TB infection. TB-related HCWs who work at hospitals are at risk of TB infection comparing to medical staffs who work outside hospitals

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China

BackgroundsThe diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels.MethodThe study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors.ResultsOverall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3–26), 9 days (IQR: 4–18), and 27 days (IQR: 15–43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays.ConclusionDespite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting

AnyOpt: Predicting and optimizing IP Anycast performance

The key to optimizing the performance of an anycast-based system (e.g., the root DNS or a CDN) is choosing the right set of sites to announce the anycast prefix. One challenge here is predicting catchments. A naïve approach is to advertise the prefix from all subsets of available sites and choose the best-performing subset, but this does not scale well. We demonstrate that by conducting pairwise experiments between sites peering with tier-1 networks, we can predict the catchments that would result if we announce to any subset of the sites. We prove that our method is effective in a simplified model of BGP, consistent with common BGP routing policies, and evaluate it in a real-world testbed. We then present AnyOpt, a system that predicts anycast catchments. Using AnyOpt, a network operator can find a subset of anycast sites that minimizes client latency without using the naïve approach. In an experiment using 15 sites, each peering with one of six transit providers, AnyOpt predicted site catchments of 15,300 clients with 94.7% accuracy and client RTTs with a mean error of 4.6%. AnyOpt identified a subset of 12 sites, announcing to which lowers the mean RTT to clients by 33ms compared to a greedy approach that enables the same number of sites with the lowest average unicast latency