Aproaches To Develop Acyclovir Gastro-Retentive Formulations Using Hot Melt Extrusion Technology

The aim of the current study was to prepare and compare acyclovir (ACV) floating gastro-retentive formulations synthesized via hot-melt extrusion (HME) techniques using P-CO2 and sodium bicarbonate. Physical mixtures of ACV (20%, w/w) and HPC EF (70%, 60%, w/w) with HPC MF (10%, w/w) or HPMCAS-LG (10%, w/w) were prepared using a co-rotating twin-screw extruder with a screw configuration shoin Figure 2. P-CO2 was injected into zone 9 of the extruder or NaHCO3 was added (10% w/w) during the extrusion process. In vitro dissolution studies (0.1 N hydrochloric acid medium) demonstrated that the formulations floated on the medium because of their porosity and low density. Formulations with NaHCO3 (F9, F10) shobetter extended release potential than the counterparts with P-CO2 (F7, F8). The in vitro drug release mechanism of the optimized formulation was found to best fit with the first-order (R2=0.9686) and Higuchi models (R2=0.9614). Accelerated stability studies demonstrated similar release profiles between fresh samples and stability samples after 3 months storage. Altogether, the ACV floating gastro-retentive formulations were successfully developed, which can prolong the gastric residence time to extend therapeutic effects

ChimpCheck: Property-Based Randomized Test Generation for Interactive Apps

We consider the problem of generating relevant execution traces to test rich interactive applications. Rich interactive applications, such as apps on mobile platforms, are complex stateful and often distributed systems where sufficiently exercising the app with user-interaction (UI) event sequences to expose defects is both hard and time-consuming. In particular, there is a fundamental tension between brute-force random UI exercising tools, which are fully-automated but offer low relevance, and UI test scripts, which are manual but offer high relevance. In this paper, we consider a middle way---enabling a seamless fusion of scripted and randomized UI testing. This fusion is prototyped in a testing tool called ChimpCheck for programming, generating, and executing property-based randomized test cases for Android apps. Our approach realizes this fusion by offering a high-level, embedded domain-specific language for defining custom generators of simulated user-interaction event sequences. What follows is a combinator library built on industrial strength frameworks for property-based testing (ScalaCheck) and Android testing (Android JUnit and Espresso) to implement property-based randomized testing for Android development. Driven by real, reported issues in open source Android apps, we show, through case studies, how ChimpCheck enables expressing effective testing patterns in a compact manner.Comment: 20 pages, 21 figures, Symposium on New ideas, New Paradigms, and Reflections on Programming and Software (Onward!2017

Vegetation history and its links to climate change during the last 36 ka in arid Central Asia: Evidence from a loess-paleosol sequence in the Eastern Ili Valley

Detailed vegetation history response to complex influencing factors of arid Central Asia (ACA) is crucial to understanding ecological sustainability. Here, we present the first pollen record in the Ili Valley during the Last Glacial Maximum (LGM) using the Jirentai (JRT) loess-paleosol sequence. Combining the results of multi-climate proxies and optically stimulated luminescence (OSL) dating, we aim to reconstruct the vegetative response to climate change during the last 36 ka. Our results show that rapid loess accumulation in the JRT section began in the Late MIS3 (Marine isotope stage 3), and a thin paleosol layer developed in the Late LGM and Post Glacial. The pollen concentrations in the loess are significantly lower than in the paleosol, but the pollen assemblages are richer. Artemisia and Asteraceae are the dominant non-arboreal types in the loess, and abundant arboreal species are present (e.g., Pinus, Picea, Quercus, Betulaceae). The percentage of Artemisia remains high in the paleosol, and typical drought-tolerant plants are an important component (e.g., Orthomorphic, Ephedra). We suggest that the rich variety of pollen in loess is transported by frequent and intense dust activities, and these pollen may come from regional vegetation. Less diverse pollen assemblages in paleosol respond to the vegetation surrounding the JRT section. The vegetation history obtained from the JRT section shows that the lowlands of the Ili Valley were typical desert or desert-steppe vegetation for the past 36 ka. The surrounding mountains are dominated by Pinus and Picea forests. During the Early LGM, vegetation conditions deteriorated in both of mountainous and lowland. The above phenomena coincide with the pollen records from lakes in the ACA. Our results further suggest that mountain forests reappear and the lowland environment improves in response to increased insolation in the Northern Hemisphere at high latitudes in the Late LGM. This point in time is earlier by about 5–10 ka compared to previous records. We attribute it to the fact that pollen assemblages from the loess-paleosol sequence are more sensitive to vegetation and climate change during the transition from the glacial to interglacial and propose a simple model to characterize them

Leveraging Multimodal Fusion for Enhanced Diagnosis of Multiple Retinal Diseases in Ultra-wide OCTA

Ultra-wide optical coherence tomography angiography (UW-OCTA) is an emerging imaging technique that offers significant advantages over traditional OCTA by providing an exceptionally wide scanning range of up to 24 x 20 $mm^{2}$, covering both the anterior and posterior regions of the retina. However, the currently accessible UW-OCTA datasets suffer from limited comprehensive hierarchical information and corresponding disease annotations. To address this limitation, we have curated the pioneering M3OCTA dataset, which is the first multimodal (i.e., multilayer), multi-disease, and widest field-of-view UW-OCTA dataset. Furthermore, the effective utilization of multi-layer ultra-wide ocular vasculature information from UW-OCTA remains underdeveloped. To tackle this challenge, we propose the first cross-modal fusion framework that leverages multi-modal information for diagnosing multiple diseases. Through extensive experiments conducted on our openly available M3OCTA dataset, we demonstrate the effectiveness and superior performance of our method, both in fixed and varying modalities settings. The construction of the M3OCTA dataset, the first multimodal OCTA dataset encompassing multiple diseases, aims to advance research in the ophthalmic image analysis community

Influence of Free Consultation Services on Patients’ Willingness to Pay in Online Medical Platforms

Online medical platforms have emerged as a popular means for patients to access high-quality medical services efficiently. These platforms offer a variety of services, including paid consultations and free consultations. Given that doctors can increase their revenue through these platforms, researchers should investigate how to improve patients’ willingness to pay for these services. Drawing upon social exchange theory, stimulus-organism-response theory, and the information systems (IS) success model, this study proposes a model and five hypotheses to examine the influence of free medical consultations on patients’ willingness to buy paid services. To test these hypotheses, a questionnaire survey was conducted, and the collected data were analyzed using the structural equation model. The results indicate that the quality of information and services provided by doctors during free consultations positively affects patients’ willingness to pay. By introducing information quality and service quality into the IS success model in the context of free medical consultations, this study contributes to the literature on online medical platforms and expands our understanding of patients’ behavior. The findings of this study can be useful for online medical platforms and doctors to design effective platform functions and individual behavioral strategies

Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model

Multi-target multi-camera tracking (MTMCT), i.e., tracking multiple targets across multiple cameras, is a crucial technique for smart city applications. In this paper, we propose an effective and reliable MTMCT framework for vehicles, which consists of a traffic-aware single camera tracking (TSCT) algorithm, a trajectory-based camera link model (CLM) for vehicle re-identification (ReID), and a hierarchical clustering algorithm to obtain the cross camera vehicle trajectories. First, the TSCT, which jointly considers vehicle appearance, geometric features, and some common traffic scenarios, is proposed to track the vehicles in each camera separately. Second, the trajectory-based CLM is adopted to facilitate the relationship between each pair of adjacently connected cameras and add spatio-temporal constraints for the subsequent vehicle ReID with temporal attention. Third, the hierarchical clustering algorithm is used to merge the vehicle trajectories among all the cameras to obtain the final MTMCT results. Our proposed MTMCT is evaluated on the CityFlow dataset and achieves a new state-of-the-art performance with IDF1 of 74.93%.Comment: Accepted by ACM International Conference on Multimedia 202

Causal association of NAFLD with osteoporosis, fracture and falling risk: a bidirectional Mendelian randomization study

IntroductionThe causal association between non-alcoholic fatty liver disease (NAFLD) and osteoporosis remains controversial in previous epidemiological studies. We employed a bidirectional two-sample Mendelian analysis to explore the causal relationship between NAFLD and osteoporosis.MethodThe NAFLD instrumental variables (IVs) were obtained from a large Genome-wide association study (GWAS) meta-analysis dataset of European descent. Two-sample Mendelian randomization (MR) analyses were used to estimate the causal effect of NAFLD on osteoporosis, fracture, and fall. Reverse Mendelian randomization analysis was conducted to estimate the causal effect of osteoporosis on NAFLD. The inverse-variance weighted (IVW) method was the primary analysis in this analysis. We used the MR-Egger method to determine horizontal pleiotropic. The heterogeneity effect of IVs was detected by MR-Egger and IVW analyses.ResultsFive SNPs (rs2980854, rs429358, rs1040196, rs738409, and rs5764430) were chosen as IVs for NAFLD. In forward MR analysis, the IVW-random effect indicated the causal effect of NAFLD on osteoporosis (OR= 1.0021, 95% CI: 1.0006-1.0037, P= 0.007) but not on fracture (OR= 1.0016, 95% CI: 0.998-1.0053, P= 0.389) and fall (OR= 0.9912, 95% CI: 0.9412-1.0440, P= 0.740). Furthermore, the reverse Mendelian randomization did not support a causal effect of osteoporosis on NAFLD (OR= 1.0002, 95% CI: 0.9997-1.0007, P= 0.231). No horizontal pleiotropic was detected in all MR analyses.ConclusionsThe results of this study indicate a causal association between NAFLD and osteoporosis. NAFLD patients have a higher risk of osteoporosis but not fracture and falling risk. In addition, our results do not support a causal effect of osteoporosis on NAFLD