Self-partitioning SlipChip for slip-induced droplet formation and human papillomavirus viral load quantification with digital LAMP

Human papillomavirus (HPV) is one of the most common sexually transmitted infections worldwide, and persistent HPV infection can cause warts and even cancer. Nucleic acid analysis of HPV viral DNA can be very informative for the diagnosis and monitoring of HPV. Digital nucleic acid analysis, such as digital PCR and digital isothermal amplification, can provide sensitive detection and precise quantification of target nucleic acids, and its utility has been demonstrated in many biological research and medical diagnostic applications. A variety of methods have been developed for the generation of a large number of individual reaction partitions, a key requirement for digital nucleic acid analysis. However, an easily assembled and operated device for robust droplet formation without preprocessing devices, auxiliary instrumentation or control systems is still highly desired. In this paper, we present a self-partitioning SlipChip (sp-SlipChip) microfluidic device for the slip-induced generation of droplets to perform digital loop-mediated isothermal amplification (LAMP) for the detection and quantification of HPV DNA. In contrast to traditional SlipChip methods, which require the precise alignment of microfeatures, this sp-SlipChip utilized a design of “chain-of-pearls” continuous microfluidic channel that is independent of the overlapping of microfeatures on different plates to establish the fluidic path for reagent loading. Initiated by a simple slipping step, the aqueous solution can robustly self-partition into individual droplets by capillary pressure-driven flow. This advantage makes the sp-SlipChip very appealing for the point-of-care quantitative analysis of viral load. As a proof of concept, we performed digital LAMP on an sp-SlipChip to quantify human papillomaviruses (HPVs) 16 and 18 and tested this method with fifteen anonymous clinical samples

cDNA-AFLP analysis of gene expression differences between the flower bud and sprout-shoot apical meristem of Angelica sinensis (Oliv.) Diels

Angelica sinensis (Oliv.) Diels (Umbelliferae) is a well-known medicinal plant mainly distributed in Gansu Province of China. Its local and global demand is significant because of its food and medicinal applications. However, the early bolting rate of Angelica sinensis (Oliv.) Diels reaches 20%–60%, which seriously affects its food and medicinal qualities. Thus, differences in gene expression between the flower bud and sprout-shoot apical meristem underwent analysis, by means of cDNA-amplified restriction fragment length polymorphism, to better understand the flowering mechanism. 64 primer sets, each of which amplified to 60 transcript-derived fragments (TDFs), were used. Among these TDFs, 26 were expressed specifically in the flower bud. After cloning and sequencing, 32 distinct sequences were obtained from these 26 TDFs, and 25 were found with homologous sequences in databases. Confirmation of differential expression of 13 sequences was obtained by semi-quantitative RT-PCR, their showing higher expression levels in flower buds. These homologous sequences encode transposable elements, pentatricopeptide repeat-containing proteins, DNA-binding transcription factors, zinc finger (B-box type) family proteins, NADP-dependent sorbitol 6-phosphate dehydrogenase (S6PDH), amongst others

Human Health Indicator Prediction from Gait Video

Body Mass Index (BMI), age, height and weight are important indicators of human health conditions, which can provide useful information for plenty of practical purposes, such as health care, monitoring and re-identification. Most existing methods of health indicator prediction mainly use front-view body or face images. These inputs are hard to be obtained in daily life and often lead to the lack of robustness for the models, considering their strict requirements on view and pose. In this paper, we propose to employ gait videos to predict health indicators, which are more prevalent in surveillance and home monitoring scenarios. However, the study of health indicator prediction from gait videos using deep learning was hindered due to the small amount of open-sourced data. To address this issue, we analyse the similarity and relationship between pose estimation and health indicator prediction tasks, and then propose a paradigm enabling deep learning for small health indicator datasets by pre-training on the pose estimation task. Furthermore, to better suit the health indicator prediction task, we bring forward Global-Local Aware aNd Centrosymmetric Encoder (GLANCE) module. It first extracts local and global features by progressive convolutions and then fuses multi-level features by a centrosymmetric double-path hourglass structure in two different ways. Experiments demonstrate that the proposed paradigm achieves state-of-the-art results for predicting health indicators on MoVi, and that the GLANCE module is also beneficial for pose estimation on 3DPW

THERMAL AND MECHANICAL RESPONSES OF FIBER REINFORCED POLYMER COMPOSITES UNDER ONE-SIDED FIRE EXPOSURE

This research investigated the thermal and mechanical responses of fiber reinforced polymer (FRP) composites in fire. The research focused on thermal decomposition and heat transfer, deformation, delamination, and structural integrity of FRP composites. The research was undertaken by thermal and fire testing, and fire dynamics and finite element modeling. To simplify the modeling of the decomposition of FRP composites, an infinite-rate pyrolysis model was incorporated into heat transfer modeling to predict the thermal response of the composite panels under one sided heating. The thermal prediction by the infinite-rate model was compared to the finite-rate model, in which the decomposition was described by Arrhenius equation, and was validated with both bench and intermediate scale fire tests. A concept of shift temperature was introduced into the heat transfer to account for the effect of heating rate on the decomposition temperature. With temperature results given by the heat transfer model, a simplified plane strain model was proposed to predict the mechanical response of FRP composites. Based on a bilinear traction-separation law, cohesive elements in commercial finite element software ABAQUS were incorporated in the mechanical model to consider the effect of delamination for sandwich panels. In order to evaluate the effect of heat flux of a composite's own flame on its thermal response and fire properties, two-layer flame geometry was proposed to predict the effect of flame heat flux on the thermal response of char-forming materials. The total flame heat flux in a typical cone test was estimated based on general turbulent flame temperature and combustible gas temperature. All prediction results were validated with experimental data. It was demonstrated that (1) the modeling of decomposition reaction using the infinite-rate model required less input parameters, (2) a material's own flame had significant influent on its fire reaction properties at the beginning of flaming combustion, (3) the plane-strain model was capable of predicting deformation and time-to-failure with a good accuracy, and (4) cohesive elements can be used to model the delamination of sandwich FRP panels in fire

On the two-distance embedding in real Euclidean space of coherent configuration of type (2,2;3)

Finding the maximum cardinality of a $2$-distance set in Euclidean space is a classical problem in geometry. Lison\v{e}k in 1997 constructed a maximum $2$-distance set in $\mathbb R^8$ with $45$ points. That $2$-distance set constructed by Lison\v{e}k has a distinguished structure of a coherent configuration of type $(2,2;3)$ and is embedded in two concentric spheres in $\mathbb R^8$. In this paper we study whether there exists any other similar embedding of a coherent configuration of type $(2,2;3)$ as a $2$-distance set in $\mathbb R^n$, without assuming any restriction on the size of the set. We prove that there exists no such example other than that of Lison\v{e}k. The key ideas of our proof are as follows: (i) study the geometry of the embedding of the coherent configuration in Euclidean spaces and to drive diophantine equations coming from this embedding. (ii) solve diophantine equations with certain additional conditions of integrality of some parameters of the combinatorial structure by using the method of auxiliary equations

Self-partitioning SlipChip for slip-induced droplet formation and human papillomavirus viral load quantification with digital LAMP

Human papillomavirus (HPV) is one of the most common sexually transmitted infections worldwide, and persistent HPV infection can cause warts and even cancer. Nucleic acid analysis of HPV viral DNA can be very informative for the diagnosis and monitoring of HPV. Digital nucleic acid analysis, such as digital PCR and digital isothermal amplification, can provide sensitive detection and precise quantification of target nucleic acids, and its utility has been demonstrated in many biological research and medical diagnostic applications. A variety of methods have been developed for the generation of a large number of individual reaction partitions, a key requirement for digital nucleic acid analysis. However, an easily assembled and operated device for robust droplet formation without preprocessing devices, auxiliary instrumentation or control systems is still highly desired. In this paper, we present a self-partitioning SlipChip (sp-SlipChip) microfluidic device for the slip-induced generation of droplets to perform digital loop-mediated isothermal amplification (LAMP) for the detection and quantification of HPV DNA. In contrast to traditional SlipChip methods, which require the precise alignment of microfeatures, this sp-SlipChip utilized a design of “chain-of-pearls” continuous microfluidic channel that is independent of the overlapping of microfeatures on different plates to establish the fluidic path for reagent loading. Initiated by a simple slipping step, the aqueous solution can robustly self-partition into individual droplets by capillary pressure-driven flow. This advantage makes the sp-SlipChip very appealing for the point-of-care quantitative analysis of viral load. As a proof of concept, we performed digital LAMP on an sp-SlipChip to quantify human papillomaviruses (HPVs) 16 and 18 and tested this method with fifteen anonymous clinical samples

PD-1/PD-L1 Axis, Rather Than High-Mobility Group Alarmins or CD8+ Tumor-Infiltrating Lymphocytes, Is Associated With Survival in Head and Neck Squamous Cell Carcinoma Patients Who Received Surgical Resection

In current studies, the influence of tumor immune microenvironment on tumorigenesis and tumor progression has been widely explored. In the present study, we investigated the expression and significance of high mobility group box 1 (HMGB1), HMG nucleosome-binding protein 1 (HMGN1), the receptor programmed cell death 1 (PD-1) and its ligand programmed cell death ligand 1 (PD-L1) in head and neck squamous cell carcinoma (HNSCC). We explored whether HMGB1 and HMGN1 take part in recruiting T cells to HNSCC microenvironment. Furthermore, we assessed the prognostic value of HMG proteins, TILs, and PD-1/PD-L1 in postoperative patients. Tumor tissue sections were collected from 81 cases of patients with resectable HNSCC. All patients' information was integrated with clinical and pathological records, as well as follow-up data. We used immunohistochemistry to examine the subcellular localization and expression levels of HMGB1 and HMGN1, as well as tumor CD3+, CD8+, FOXP3+ lymphocyte infiltration, and the expression of immune inhibiting molecules PD-1/PD-L1. Results showed that there was no significant difference in the number of CD8+ and FOXP3+ T cells between the two groups with or without HMGB1 cytoplasmic expression in tumor tissues. The number of CD3+ T cells in HMGB1 cytoplasmic expression group (339.39 ± 230.76) was more than that in group without HMGB1 cytoplasmic expression (233.30 ± 230.91, P < 0.05). The number of CD3+, CD8+, and FOXP3+ T cells in HMGN1 cytoplasmic expression group [400.74 ± 224.04, 158.10 ± 112.10, 36.00(15.00, 69.00)] was more than that in group without HMGN1-cytoplasmic expression [222.84 ± 217.78, P < 0.01; 105.10 ± 108.25, P < 0.05; 13.00(6.75, 32.25), P < 0.01]. The positive rates of PD-1 and PD-L1 in tumor tissues were 29.6 and 67.9%, respectively. Multivariate analysis suggested that tumor expression of PD-L1 was an independent prognostic factor and PD-L1 overexpression indicated a poor overall survival (OS) and disease-free survival (DFS). Taken together, we concluded that HMGB1 and HMGN1 secreted by cancer cells may relate to recruitment of tumor infiltrating lymphocytes (TILs) in HNSCC. PD-1/PD-L1 axis, rather than HMG proteins or CD8+ tumor-infiltrating lymphocytes, has a critical role in tumor immune microenvironment and could predict the outcome of HNSCC patients who received surgical resection

Knowledge, Attitudes, and Social Responsiveness Toward Corona Virus Disease 2019 (COVID-19) Among Chinese Medical Students—Thoughts on Medical Education

Purpose: To assess knowledge, attitudes, and social responsiveness toward COVID-19 among Chinese medical students.Methods: Self-administered questionnaires were used to collect data from 889 medical students in three well-known Chinese medical universities. The questionnaire was comprised of three domains which consisted of demographic characteristic collection, seven items for knowledge, and eight items for attitudes and social responsiveness toward COVID-19. Data from different universities were lumped together and were divided into different groups to compare the differences, including (1) students at the clinical learning stage (Group A) or those at the basic-medicine stage (Group B) and (2) students who have graduated and worked (Group C) or those newly enrolled (Group D).Results: Medical students at group B had a weaker knowledge toward COVID-19 than did students at group A, especially in the question of clinical manifestations (p < 0.001). The percentage of totally correct answers of COVID-19 knowledge in group C was higher than that in Group D (p < 0.001). There were significant differences between groups C and D in the attitudes and social responsiveness toward COVID-19. Surprisingly, we found that the idea of newly enrolled medical students could be easily affected by interventions.Conclusions: In light of this information, medical education should pay attention not only to the cultivation of professional knowledge and clinical skills but also to the positive interventions to better the comprehensive qualities including communicative abilities and empathy

RITA: Boost Autonomous Driving Simulators with Realistic Interactive Traffic Flow

High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating traffic patterns that accurately reflect the various features of real-world data while also simulating human-like reactive responses to the tested autopilot driving strategies. Taking one step forward to addressing such a problem, we propose Realistic Interactive TrAffic flow (RITA) as an integrated component of existing driving simulators to provide high-quality traffic flow for the evaluation and optimization of the tested driving strategies. RITA is developed with consideration of three key features, i.e., fidelity, diversity, and controllability, and consists of two core modules called RITABackend and RITAKit. RITABackend is built to support vehicle-wise control and provide traffic generation models from real-world datasets, while RITAKit is developed with easy-to-use interfaces for controllable traffic generation via RITABackend. We demonstrate RITA's capacity to create diversified and high-fidelity traffic simulations in several highly interactive highway scenarios. The experimental findings demonstrate that our produced RITA traffic flows exhibit all three key features, hence enhancing the completeness of driving strategy evaluation. Moreover, we showcase the possibility for further improvement of baseline strategies through online fine-tuning with RITA traffic flows.Comment: 8 pages, 5 figures, 3 table