Numerical Simulation and Parameter Optimization for Water-to-CO2 Flooding in a Strongly Water-Sensitive Reservoir.

Carbon dioxide flooding can accelerate the development of low-permeability reservoirs of the Kexia group in the K region of the T oil field, thus resolving the issue of inadequate water drive effects. This study was focused on the well group 80513 in the K region, and based on the reservoir and fluid parameters, a simulation model of water-sensitive post-CO2 flooding was constructed to refine the gas injection strategy gradually. The injection rate of the continuous gas injection stage was preferred based on the degree of recovery. Multiindicator and multifactor injection and extraction schemes were established to optimize and analyze the key controlling factors, including the gas injection rate, gas injection period, gas-to-water ratio, and bottom-hole flow pressure, in the carbon dioxide gas-to-water alternation process. Recovery efficiency, oil exchange rate, formation pressure, and carbon dioxide storage rate were used as indicators. After 5 years of continuous CO2 flooding, the results indicated that switching to CO2 gas-water alternating flooding was more appropriate for the target block's environment. The best development plan was achieved when the gas injection rates were 1.0 and 1.25 × 104 m3·d-1 for continuous gas injection and CO2 gas-water alternating flooding, respectively, with a gas-water ratio of 1:1, a gas injection cycle of 90 days, and a bottom-hole flow pressure of 25 MPa in the production wells. A comparison between the results revealed that the formation pressure and oil recovery efficiency of this well group significantly increased upon CO2 flooding, and the parameter optimization results were well suited for controlling the gas flurry, offering a versatile model for future development of the block.

TGF-ß1 and TGF-ßR1 variants are associated with clinical outcomes in smoking-related head and neck cancer patients treated with chemoradiation through modulating microRNA-mediated regulation.

TGF-ß1 and TGF-ßR1 play important roles in immune and inflammatory responses. Genetic variants of TGF-ß1 rs1800470 and TGF-ßR1 rs334348 have emerged as potentially prognostic biomarkers for HPV-related head and neck cancer, while their prognostic effect on survival of smoking-related head and neck cancer remains unknown. This study included 1403 patients with smoking-related head and neck cancer, and all these patients were genotyped for TGF-ß1 rs1800470 and TGF-ßR1 rs334348. Both univariate and multivariate analyses were performed to evaluate associations between the two functional genetic variants in microRNA binding sites of TGF-ß1 and TGF-ßR1 and survivals. Patients with TGF-ß1 rs1800470 CT or CC genotype had 30-35% risk reductions for OS, DSS, and DFS compared to patients with TT genotype among overall patients, ever smokers, and patients administered chemoradiation. Furthermore, patients with TGF-ßR1 rs334348 GA or GG genotype had significant 50-60% risk reductions for OS, DSS, and DFS compared to patients with AA genotype among overall patients and patients administered chemoradiation; among ever smokers, the risk reductions even reached 60-70%. The TCGA dataset was used for validation. These findings suggest that TGF-ß1 rs1800470 and TGF-ßR1 rs334348 significantly affect survival outcomes in patients with smoking-related head and neck cancer, especially in the subgroups of ever smokers and patients treated with chemoradiation. These genetic variants may serve as prognostic indicators for patients with smoking-related head and neck cancer and could play a role in advancing the field of personalized chemoradiation, thereby improving patient survival and quality of life.

Highly efficient clustering of long-read transcriptomic data with GeLuster.

MOTIVATION: The advancement of long-read RNA sequencing technologies leads to a bright future for transcriptome analysis, in which clustering long reads according to their gene family of origin is of great importance. However, existing de novo clustering algorithms require plenty of computing resources. RESULTS: We developed a new algorithm GeLuster for clustering long RNA-seq reads. Based on our tests on one simulated dataset and nine real datasets, GeLuster exhibited superior performance. On the tested Nanopore datasets it ran 2.9-17.5 times as fast as the second-fastest method with less than one-seventh of memory consumption, while achieving higher clustering accuracy. And on the PacBio data, GeLuster also had a similar performance. It sets the stage for large-scale transcriptome study in future. AVAILABILITY AND IMPLEMENTATION: GeLuster is freely available at https://github.com/yutingsdu/GeLuster.

Cocaine use and head and neck cancer risk: A pooled analysis in the International Head and Neck Cancer Epidemiology Consortium.

BACKGROUND: Cocaine is an illegal recreational drug used worldwide, yet little is known about whether cocaine inhalation (smoking/snorting) increases the risk of head and neck cancer (HNC). METHODS: The analyses were conducted by pooling data from three case-control studies with 1639 cases and 2506 controls from the International Head and Neck Cancer Epidemiology Consortium. Epidemiologic data, including cocaine use histories, were obtained in face-to-face interviews. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were estimated using hierarchical logistic regression models. RESULTS: Controlling for cumulative tobacco and alcohol use, we observed a weak positive association between cocaine use and HNC (ORever vs. never = 1.35, 95% CI: 0.96, 1.90). In stratified analysis, while we did not detect associations among never tobacco or alcohol users due to the limited sample size, the association with cocaine use was observed among tobacco users and alcohol drinkers. ORs for ever and high cumulative use (>18 times) versus never use were 1.40 (95% CI: 0.98, 2.00) and 1.66 (95% CI: 1.03, 2.69) among tobacco users, and 1.34 (95% CI: 0.93, 1.92) and 1.59 (95% CI: 1.00, 2.51) among alcohol drinkers, respectively. CONCLUSION: In this pooled analysis, we observed a weak positive association between cocaine inhalation and HNC risk. Our findings provide preliminary evidence of the potential carcinogenic effect of cocaine on HNC. Because of study limitations, including limited number of cocaine users, confounding, and heterogeneity across studies, future investigations will require larger studies with more detailed information on cocaine use history.

Long non-coding RNA ACTA2-AS1 suppresses metastasis of papillary thyroid cancer via regulation of miR-4428/KLF9 axis.

BACKGROUND: Metastasis is the primary cause of recurrence and death in patients with papillary thyroid carcinoma (PTC). LncRNA ACTA2-AS1, a long non-coding RNA, acts as a tumor suppressor in multiple types of human malignancies, while the role of ACTA2-AS1 in PTC metastasis remains unclear. METHODS: The ACTA2-AS1 expression in PTC tissues was analyzed. The sponged roles of ACTA2-AS1 via miR-4428/KLF9 axis were identified using starBase tool. The function of ACTA2-AS1 in PTC was performed with in vitro and in vivo experiments. The correlation between DNA methylation and mRNA expressions of these gene in the TCGA dataset was explored. RESULTS: ACTA2-AS1 expression was downregulated in PTC tissues without metastasis and further decreased in PTC tissues with lymph node metastasis compared with that in normal tissues. Functionally, the overexpression of ACTA2-AS1 inhibited the growth, proliferation, and invasion of PTC cells, whereas its depletion exerted opposite effect. In vivo, ACTA2-AS1 expression inhibited PTC metastasis. Furthermore, ACTA2-AS1 acted as a competing endogenous RNA for miR-4428, thereby positively regulating the expression of miR-4428 target gene, KLF9. Finally, miR-4428 overexpression enhanced invasive potential of PTC cells and significantly weakened the effects of ACTA2-AS1 on promotion and inhibition of KLF9 expression as well as invasive ability of PTC cells, respectively. In the TCGA dataset, the methylation level of ACTA2-AS1 was significantly correlated with its mRNA expression (r = 0.21, p = 2.1 × e-6). CONCLUSIONS: Our findings demonstrate that ACTA2-AS1 functions as a tumor suppressor in PTC progression at least partly by regulating the miR-4428-dependent expression of KLF9.

scQA: A dual-perspective cell type identification model for single cell transcriptome data.

Single-cell RNA sequencing technologies have been pivotal in advancing the development of algorithms for clustering heterogeneous cell populations. Existing methods for utilizing scRNA-seq data to identify cell types tend to neglect the beneficial impact of dropout events and perform clustering focusing solely on quantitative perspective. Here, we introduce a novel method named scQA, notable for its ability to concurrently identify cell types and cell type-specific key genes from both qualitative and quantitative perspectives. In contrast to other methods, scQA not only identifies cell types but also extracts key genes associated with these cell types, enabling bidirectional clustering for scRNA-seq data. Through an iterative process, our approach aims to minimize the number of landmarks to approximately a dozen while maximizing the inclusion of quasi-trend-preserved genes with dropouts both qualitatively and quantitatively. It then clusters cells by employing an ingenious label propagation strategy, obviating the requirement for a predetermined number of cell types. Validated on 20 publicly available scRNA-seq datasets, scQA consistently outperforms other salient tools. Furthermore, we confirm the effectiveness and potential biological significance of the identified key genes through both external and internal validation. In conclusion, scQA emerges as a valuable tool for investigating cell heterogeneity due to its distinctive fusion of qualitative and quantitative facets, along with bidirectional clustering capabilities. Furthermore, it can be seamlessly integrated into border scRNA-seq analyses. The source codes are publicly available at https://github.com/LD-Lyndee/scQA.

Impact of pretreatment body mass index on the survival of head and neck cancer patients.

BACKGROUND: Differences in pretreatment body mass index (BMI) have been associated with survival in squamous cell carcinoma of head and neck (SCCHN). We examined effects of BMI on survival in SCCHN patients after stratifying patients by tumor human papillomavirus (HPV) status and subsite. METHODS: Totally 2204 SCCHN patients in a prospective study were included in this secondary analysis. Multivariable Cox models were used to evaluate associations between pretreatment BMI and overall survival, disease-specific survival, and disease-free survival. RESULTS: BMI was significantly higher among patients with HPV-positive tumors than HPV-negative tumors. BMI >25 kg/m2 was associated with improved survival, while BMI <18.5 kg/m2 was associated with reduced survival, particularly in patients with HPV-positive oropharyngeal cancer tumors. CONCLUSIONS: This exploratory analysis suggests that pretreatment BMI could be an independent prognostic factor of survival outcomes in SCCHN patients, particularly in patients with HPV-positive oropharyngeal cancer tumors. Further prospective investigations are warranted.

A survey of methods for handling initial state shifts in iterative learning control.

This paper introduces three types of controllers: a PID-type iterative learning controller, an adaptive iterative learning controller, and an optimal iterative learning controller, and reviews the history and research status of initial shifts rectifying algorithms. Initial state shifts have attracted research attention because they affect both the tracking performance and system stability. This study focuses on the current common initial shifts rectifying methods and analyzes the underlying mechanism in detail. To verify the effectiveness of the presented initial shifts rectifying algorithms, we simulated those using ideal first- and second-order systems. Finally, directions for the future development of iterative learning control (ILC) and some challenging topics related to initial shifts rectifying for ILC are presented. This article aims to introduce recent developments and advances in initial shifts rectifying algorithms and discuss the directions for their further exploration.

Flexible Platform Composed of T-Shaped Micropyramid Patterns toward a Waterproof Sensing Interface.

Antifouling is essential to guaranteeing the sensitivity and precision of flexible sensing interfaces. Materials and structures are the two primary strategies. However, optimizing the inherent microstructures to integrate waterproofing and sensing is rarely reported. To improve the liquid repellency of micropyramid structures, this work presents a study of the design and fabrication of T-shaped micropyramid structures. These structures are patterned uniformly and largely on polydimethylsiloxane (PDMS) skin by the new process of two-step magnetic induction. The waterproofing is related to the breakthrough pressure and the liquid repellency, both of which are a function of structural characteristics, D, and material properties, θY. At the breakthrough transition, two failure models distinguished by θY appear: the depinning transition and the sagging transition. Meanwhile, when considering D in practice, some models will shift and occur early. The D value regulates the transition of the material's wettability to the liquid repellency. The influence of the material's inherent nonwettability on liquid repellency diminishes as D decreases, and the transition from completely wetting liquids to super-repellents can be achieved. Experiments demonstrate that for D = 0.3 under water the resistance is approximately 142 times larger than the depth of the structure, considerably facilitating the waterproofing of conventional micropyramid arrays. This work provides a novel method for fabricating flexible T-shaped micropyramid array structures and opens a new window on flexible sensing interfaces with excellent waterproofing.

Solar-driven thermochemical conversion of H2O and CO2 into sustainable fuels.

Solar-driven thermochemical conversion of H2O and CO2 into sustainable fuels, based on redox cycle, provides a promising path for alternative energy, as it employs the solar energy as high-temperature heat supply and adopts H2O and CO2 as initial feedstock. This review describes the sustainable fuels production system, including a series of physical and chemical processes for converting solar energy into chemical energy in the form of sustainable fuels. Detailed working principles, redox materials, and key devices are reviewed and discussed to provide systematic and in-depth understanding of thermochemical fuels production with the aid of concentrated solar power technology. In addition, limiting factors affecting the solar-to-fuel efficiency are analyzed; meanwhile, the improvement technologies (heat recovery concepts and designs) are summarized. This study therefore sets a pathway for future research works based on the current status and demand for further development of such technologies on a commercial scale.

HycDemux: a hybrid unsupervised approach for accurate barcoded sample demultiplexing in nanopore sequencing.

DNA barcodes enable Oxford Nanopore sequencing to sequence multiple barcoded DNA samples on a single flow cell. DNA sequences with the same barcode need to be grouped together through demultiplexing. As the number of samples increases, accurate demultiplexing becomes difficult. We introduce HycDemux, which incorporates a GPU-parallelized hybrid clustering algorithm that uses nanopore signals and DNA sequences for accurate data clustering, alongside a voting-based module to finalize the demultiplexing results. Comprehensive experiments demonstrate that our approach outperforms unsupervised tools in short sequence fragment clustering and performs more robustly than current state-of-the-art demultiplexing tools for complex multi-sample sequencing data.

Performance of CT-based deep learning in diagnostic assessment of suspicious lateral lymph nodes in papillary thyroid cancer: a prospective diagnostic study.

BACKGROUND: Preoperative evaluation of the metastasis status of lateral lymph nodes (LNs) in papillary thyroid cancer is challenging. Strategies for using deep learning to diagnosis of lateral LN metastasis require additional development and testing. This study aimed to build a deep learning-based model to distinguish benign lateral LNs from metastatic lateral LNs in papillary thyroid cancer and test the model's diagnostic performance in a real-world clinical setting. METHODS: This was a prospective diagnostic study. An ensemble model integrating a three-dimensional residual network algorithm with clinical risk factors available before surgery was developed based on computed tomography images of lateral LNs in an internal dataset and validated in two external datasets. The diagnostic performance of the ensemble model was tested and compared with the results of fine-needle aspiration (FNA) (used as the standard reference method) and the diagnoses made by two senior radiologists in 113 suspicious lateral LNs in patients enrolled prospectively. RESULTS: The area under the receiver operating characteristic curve of the ensemble model for diagnosing suspicious lateral LNs was 0.829 (95% CI: 0.732-0.927). The sensitivity and specificity of the ensemble model were 0.839 (95% CI: 0.762-0.916) and 0.769 (95% CI: 0.607-0.931), respectively. The diagnostic accuracy of the ensemble model was 82.3%. With FNA results as the criterion standard, the ensemble model had excellent diagnostic performance ( P =0.115), similar to that of the two senior radiologists ( P =1.000 and P =0.392, respectively). CONCLUSION: A three-dimensional residual network-based ensemble model was successfully developed for the diagnostic assessment of suspicious lateral LNs and achieved diagnostic performance similar to that of FNA and senior radiologists. The model appears promising for clinical application.

GWAS-identified telomere length associated genetic variants predict risk of recurrence of HPV-positive oropharyngeal cancer after definitive radiotherapy.

BACKGROUND: Lymphocyte telomere length (LTL)-related genetic variants may modulate LTL and affect recurrence of squamous cell carcinoma of the oropharynx (SCCOP). METHODS: A total of 1013 patients with incident SCCOP were recruited and genotyped for 16 genome-wide association study (GWAS)-identified TL-related polymorphisms. Of these patients, 489 had tumour HPV16 status determination. Univariate and multivariate analyses were performed to evaluate associations. FINDINGS: Of the 16 TL-related polymorphisms, four were significantly associated with LTL: rs1920116, rs3027234, rs6772228, and rs11125529, and the patients with putatively favourable genotypes had approximately 1.5-3 times the likelihood of shorter LTL compared with patients with the corresponding risk genotypes. Moreover, patients with one to four favourable genotypes of the four combined polymorphisms had approximately 3-11 times the likelihood of shorter LTL compared with patients with no favourable genotype. The four LTL-related polymorphisms were significantly associated with approximately 40% reduced risk (for favourable genotypes) or doubled risk (for risk genotypes) of recurrence, and similar but more pronounced associations were observed in patients with tumour HPV16-positive SCCOP. Similarly, patients with one to four risk genotypes had significantly approximately 2.5-4 times increased recurrence risk compared with patients with no risk genotype, and similar but more pronounced associations were observed in patients with tumour HPV16-positive SCCOP. INTERPRETATION: Four LTL-related polymorphisms individually or jointly modify LTL and risk of recurrence of SCCOP, particularly HPV-positive SCCOP. These LTL-related polymorphisms could have potential to further stratify patients with HPV-positive SCCOP for individualized treatment and better survival. FUNDING: Not applicable.

Functional Genetic Variants in TGFß1 and TGFßR1 in miRNA-Binding Sites Predict Outcomes in Patients with HPV-positive Oropharyngeal Squamous Cell Carcinoma.

PURPOSE: TGFß1 and TGFß receptor 1 (TGFßR1) participate in regulation of the host's immune system and inflammatory responses and may serve as prognostic biomarkers for human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). EXPERIMENTAL DESIGN: This study included 1,013 patients with incident OPSCC, of whom 489 had tumor HPV16 status determined. All patients were genotyped for two functional polymorphisms: TGFß1 rs1800470 and TGFßR1 rs334348. Univariate and multivariate Cox regression models were performed to evaluate associations between the polymorphisms and overall survival (OS), disease-specific survival (DSS), and disease-free survival (DFS). RESULTS: Patients with TGFß1 rs1800470 CT or CC genotype had 70%-80% reduced risks of OS, DSS, and DFS compared with patients with TT genotype, and patients with TGFßR1 rs334348 GA or GG genotype had 30%-40% reduced risk of OS, DSS, and DFS compared with patients with AA genotype. Furthermore, among patients with HPV-positive (HPV+) OPSCC, the same patterns were observed but the risk reductions were greater: up to 80%-90% for TGFß1 rs1800470 CT or CC genotype and 70%-85% for TGFßR1 rs334348 GA or GG genotype. The risk reductions were still greater (up to 17 to 25 times reduced) for patients with both TGFß1 rs1800470 CT or CC genotype and TGFßR1 rs334348 GA or GG genotype compared with patients with both TGFß1 rs1800470 TT genotype and TGFßR1 rs334348 AA genotype among patients with HPV+ OPSCC. CONCLUSIONS: Our findings indicate that TGFß1 rs1800470 and TGFßR1 rs334348 may individually or jointly modify risks of death and recurrence in patients with OPSCC, particularly those with HPV+ OPSCC undergoing definitive radiotherapy, and may serve as prognostic biomarkers, which could lead to better personalized treatment and improved prognosis.

Joint effect of human papillomavirus exposure, smoking and alcohol on risk of oral squamous cell carcinoma.

BACKGROUND: Smoking, alcohol consumption, and human papillomavirus (HPV) infection are known risk factors for oral squamous cell carcinoma (OSCC) including SCC of oropharynx (SCCOP) and SCC of oral cavity (SCCOC). Researchers have examined each of these risk factors independently, but few have observed the potential risk of their interaction. This study investigated the interactions among these risk factors and risk of OSCC. METHODS: Totally 377 patients with newly diagnosed SCCOP and SCCOC and 433 frequency-matched cancer-free controls by age and sex were included. Multivariable logistic regression was performed to calculate ORs and 95% CIs. RESULTS: We found that overall OSCC risk was independently associated with smoking (adjusted OR(aOR), 1.4; 95%CI, 1.0-2.0), alcohol consumption (aOR, 1.6; 95%CI, 1.1-2.2), and HPV16 seropositivity (aOR, 3.3; 95%CI, 2.2-4.9), respectively. Additionally, we found that HPV16 seropositivity increased the risk of overall OSCC in ever-smokers (aOR, 6.8; 95%CI, 3.4-13.4) and ever-drinkers (aOR, 4.8; 95%CI, 2.9-8.0), while HPV16-seronegative ever-smokers and ever-drinkers had less than a twofold increase in risk of overall OSCC (aORs, 1.2; 95%CI, 0.8-1.7 and 1.8; 95%CI, 1.2-2.7, respectively). Furthermore, the increased risk was particularly high for SCCOP in HPV16-seropositive ever-smokers (aOR, 13.0; 95%CI, 6.0-27.7) and in HPV16-seropositive ever-drinkers (aOR, 10.8; 95%CI, 5.8-20.1), while the similar increased risk was not found in SCCOC. CONCLUSION: These results suggest a strong combined effect of HPV16 exposure, smoking, and alcohol on overall OSCC, which may indicate a strong interaction between HPV16 infection and smoking and alcohol consumption, particularly for SCCOP.

Characterization of the oral microbiota among middle-aged men with and without human papillomavirus infection.

OBJECTIVES: To characterize the oral microbiota among middle-aged men and identify differences between men with a prevalent oral high-risk (oncogenic) HPV infection and those without. MATERIALS AND METHODS: This was a case-control study nested within a prospective screening study for HPV-related cancers among middle-aged men. 16S rRNA sequencing was used to characterize the oral microbiota and the cobas HPV Test was used to detect presence of oral high-risk HPV types. We determined the overall composition of the oral microbiota and assessed differences in relative abundance of bacterial taxa as well as alpha and beta diversity among men with a prevalent oral high-risk HPV infection compared to men who were HPV-negative. RESULTS: Among 13 high-risk HPV-positive and 30 HPV-negative men, we found significant differences in beta diversity but not alpha diversity. Fretibacterium, F0058, Kingella, Treponema, and Prevotella were more abundant among the high-risk HPV-positive men while Neisseria and Lactobacillus were more abundant among the HPV-negative men. CONCLUSION: This study adds to the evidence that the oral microbiota varies according to oral HPV infection status and may be associated with the natural history of oral HPV infection.

Expression Pattern of Cytokines in Patients with Chronic Hepatitis B Receiving PEGinterferon Therapy.

Purpose: Chronic hepatitis B virus (CHB) infection is a worldwide health problem. Polyethylene glycol (PEG)ylated interferon (PEG-IFN) is an available therapy for CHB that has antiviral and immunomodulatory effects. However, PEG-IFN therapy is limited by the fact that only a subset of patients show a sustained response, its severe side effects, and high cost. The aim of this study was to explore novel biomarkers for the early prediction of PEG-IFN treatment response and to uncover its underlying mechanism. Patients and Methods: We enrolled 10 paired patients with Hepatitis B e antigen (HBeAg)-positive CHB who received PEG-IFN-α2a monotherapy. Patient serum samples were collected at 0, 4, 12, 24, and 48 weeks and serum samples were collected from eight healthy people as healthy controls. For confirmation, we enrolled 27 patients with HBeAg-positive CHB receiving PEG-IFN therapy and serum samples at 0 and 12 weeks were obtained. Serum samples were analyzed using Luminex technology. Results: Among 27 assessed cytokines, 10 cytokines were identified to have high expression levels. Among them, six cytokines had significant differences in their levels between the patients with HBeAg-positive CHB and the healthy controls (P < 0.05). Potentially, treatment response could be predicted using the early time points of 4, 12, and 24 weeks. Moreover, after 12 weeks of PEG-IFN treatment, increased levels of pro-inflammatory cytokines and decreased levels of anti-inflammatory cytokines were observed. The fold change of IP-10 between 12 weeks and 0 weeks correlated with the decrease in ALT levels from 0 to 12 weeks (r = 0.2675, P = 0.0024). Conclusion: In patients with CHB, we observed a certain pattern in the levels of cytokines during treatment with PEG-IFN, and the cytokine IP-10 might be a potential biomarker for treatment response.

Quantifying the partial ionization effect of gold in the transition region between condensed matter and warm dense matter.

It is now well known that solids under ultra-high-pressure shock compression will enter the warm dense matter (WDM) regime which connects condensed matter and hot plasma. How condensed matter turns into the WDM, however, remains largely unexplored due to the lack of data in the transition pressure range. In this letter, by employing the unique high-Z three-stage gas gun launcher technique developed recently, we compress gold into TPa shock pressure to fill the gap inaccessible by the two-stage gas gun and laser shock experiments. With the aid of high-precision Hugoniot data obtained experimentally, we observe a clear softening behavior beyond ~560 GPa. The state-of-the-art ab-initio molecular dynamics calculations reveal that the softening is caused by the ionization of 5d electrons in gold. This work quantifies the partial ionization effect of electrons under extreme conditions, which is critical to model the transition region between condensed matter and WDM.

An automatic recognition method of nematode survival rate based on bright field and dark field experimental images.

BACKGROUND: The survival rate of experimental animals is a very important index in chemical toxicity evaluation experiments. The calculation of nematode survival rate is used in many experiments. OBJECTIVE: Traditional survival rate quantification methods require manual counting. This is a time-consuming and laborious work when using 384-well plate for high-throughput chemical toxicity assessment experiments. At present, there is a great need for an automatic method to identify the survival rate of nematodes in the experiment of chemical toxicity evaluation. METHODS: We designed an automatic nematode survival rate recognition method by combining the bright field experimental image of nematodes and the dark field image of nematodes which is captured after adding Propidium Iodide dye, and used it to calculate the nematode survival rate in different chemical environments. Experiment results show that the survival rate obtained by our automatic counting method is very similar to the survival rate obtained by manual counting. RESULTS: Through several different chemical experiments, we can see that chemicals with different toxicity have different effects on the survival rate of nematodes. And the survival rate of nematodes under different chemical concentrations has an obvious gradient trend from high concentration to low concentration. In addition, our method can quantify the motility of nematodes. There are also significant differences in the motility of nematodes cultured in different chemical environments. Moreover, the nematode motility under different chemical concentrations showed an obvious gradient change trend from high concentration to low concentration. CONCLUSION: Our study provides an accurate and efficient nematode survival rate recognition method for chemical toxicology research.