Technology life cycle (TLC) analysis provides essential support for investment-related strategies and helps to technology trajectory tracing, forecasting, and assessment. The most typical method used ...to identify TLC is the S-curve fitting method. However, doubts about its accuracy and reliability have been raised owing to the single indicator problem and the missing link between TLC and indicators. K-nearest neighbors (KNN) and hidden Markov model (HMM)-based methods are two influential methods that have been developed. However, something could be improved with these methods. The emerging order of stages is not under control, and the impact of early technology development on the later stages has yet to be addressed. These issues led us to propose a new method to identify TLC using multiple indicators based on machine learning techniques. We extracted ten indicators from the incoPat patent database and utilized a long short-term memory (LSTM) network–conditional random field (CRF) to identify TLC stages with the probability of technology being in a particular stage at a point of the year and changing to other stages during the following year. Moreover, this study investigates the theoretical meaning and empirical performance of indicators. 3-Dimensional print technology was selected as a case study, and its TLC was analyzed and prospects discussed. Comparison of this method and other methods are made as well. The results of our method that fit with the actual progression of technology are relatively accurate. Our analysis showed that the proposed method could offer a smooth and stationary TLC pattern that is accurate and easily understood.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Cancer is a leading public health problem worldwide. Its treatment remains a daunting challenge, although significant progress has been made in existing treatments in recent years. A large concern is ...the poor therapeutic effect due to lack of specificity and low bioavailability. Gene therapy has recently emerged as a powerful tool for cancer therapy. However, delivery methods limit its therapeutic effects. Exosomes, a subset of extracellular vesicles secreted by most cells, have the characteristics of good biocompatibility, low toxicity and immunogenicity, and great designability. In the past decades, as therapeutic carriers and diagnostic markers, they have caught extensive attention. This review introduced the characteristics of exosomes, and focused on their applications as delivery carriers in DNA, messenger RNA (mRNA), microRNA (miRNA), small interfering RNA (siRNA), circular RNA (circRNA) and other nucleic acids. Meanwhile, their application in cancer therapy and exosome-based clinical trials were presented and discussed. Through systematic summarization and analysis, the recent advances and current challenges of exosome-mediated nucleic acid delivery for cancer therapy are introduced, which will provide a theoretical basis for the development of nucleic acid drugs.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
•An optimal method was proposed to estimate chromium (Cr) concentration in arable soil.•The Savitzky-Golay (SG) spectral pretreatment can be used as a good pretreatment method for estimating Cr ...concentration.•The Principal Component Analysis (PCA) could effectively reduce the dimensionality of the hyperspectral data.•The optimal principal components (PCs) were obtained by comparing the influence of the different PCs on the estimation performance of the hyperspectral models.
The heavy metal pollution in arable soil poses a significant threat to human health. Thus, it is of great significance to investigate the contamination of heavy metal elements in the soil. As the soil polluted by heavy metal is sensitive to spectral reflectance, thus the hyperspectral remote sensing technology could be a valuable tool for retrieving heavy metal components in the soil. This study, taking chromium (Cr) concentration as an example, proposes an optimal model for estimating heavy metal components in the soil by comprehensively taking account of the spectral pretreatment, dimensionality reduction with optimal parameters, and hyperspectral model. To this end, both the linear model, i.e., partial least squares regression (PLSR), and the nonlinear model, i.e., the gradient boosting decision tree (GBDT), are applied in this study. It is found in the study area, the Savitzky-Golay (SG) method can be regarded as an excellent spectral pretreatment for the hyperspectral data regardless of the applied model. By contrast, the dimensionality reduction in terms of the Principal Component Analysis (PCA) is closely related to hyperspectral model: the optimal principal components (PCs) in the estimation of Cr concentration are the first 9 PCs for the GBDT (nonlinear model), while that for the PLSR (linear model) become the first 8 PCs. Moreover, the examination of hyperspectral model shows the GBDT model has slightly better performance than the PLSR model for the Cr concentration estimation under most conditions. Finally, when the spectral pretreatment, dimensionality reduction, and hyperspectral model are fully considered, the best retrieval model for the Cr concentration in the study area is the SG-PCA-GBDT model. Numeric measures of model accuracy show the proposed model has a determination coefficient of 0.80 and a residual prediction deviation of 2.04, which provides a potentially new method for estimating Cr concentration in the polluted soil.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The thoracic small biopsy sampling procedure including transbronchial forceps lung biopsy (TBLB) and endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) can be accompanied by rapid ...on-site evaluation (ROSE) of sample material to provide immediate feedback for the proceduralist. The present study aims to investigate the supplemental effect of ROSE smear samples for lung cancer molecular test.
In a retrospective study, 308 patients admitted to our hospital from August 2020 to December 2022 undergoing diagnostic TBLB and EBUS-TBNA with ROSE and subsequently diagnosed as non-small cell lung cancer (NSCLC) were analyzed. The matched formalin-fixed paraffin-embedding (FFPE) tissue section and ROSE smears for tumor cellularity were compared. DNA yields of smears were determined. Real-time polymerase chain reaction (PCR) and next-generation sequencing (NGS) were performed on adequate smear samples.
ROSE smear samples were enriched in tumor cells. Among 308 biopsy samples, 78 cases (25.3%) exhibited
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FFLJ, NUK, ODKLJ, UL, UM, UPUK, VSZLJ
Abstract
Objective
To investigate the association of the MTHFR C677T gene polymorphism with metabolic syndrome (MetS) in people in Hubei Province, China.
Methods
A case–control study was conducted ...with 651 subjects with MetS (MetS group) and 727 healthy controls (control group) at Renmin Hospital of Wuhan University between January and December 2016. The MTHFR C677T genotype was detected by the gene chip technique and clinical data were collected.
Results
Body mass index, waist circumference, the waist-hip-ratio, systolic and diastolic blood pressure, fasting blood glucose, fasting insulin, triglyceride, total cholesterol, low-density lipoprotein-cholesterol, and homocysteine levels, and the homeostasis model assessment of insulin resistance were higher in the MetS group than in controls. The risk of MetS was higher for the TT genotype and T allele carriers than for the CC genotype and C allele carriers. With MetS, the TT genotype increased the risk of elevated blood pressure, fasting glucose levels, and triglyceride levels. Patients with MetS and the TT genotype showed more severe abdominal obesity, dyslipidaemia, insulin resistance, elevated blood pressure, elevated fasting glucose levels, and hyperhomocysteinaemia compared with those with the CC genotype.
Conclusions
In this population, MTHFR C677T gene polymorphism may be a risk factor for MetS.
This study aimed to evaluate the infection rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among different populations in Wuhan, China. This cross-sectional survey-based study ...examined the results of SARS-CoV-2-specific serological tests and RT-PCR tests for 4,454 community residents and 4,614 healthcare workers performed from May 15 to May 29, 2020. The healthcare workers were classified as administrative and logistical staff (n = 1,378), non-first-line healthcare workers (n = 2,630), or first-line healthcare workers (n = 606) according to their frequency of contact with coronavirus disease (COVID-19) patients. The positive rates of SARS-CoV-2-specific IgG, IgM, and RNA were 2.9%, 0.4%, and 0.1% for the community residents and 3.3%, 0.6%, and 0.2% for the healthcare workers, respectively. There were no statistically significant differences between the rates of the two groups. Spearman’s correlation analysis showed that the frequency of contact with COVID-19 patients negatively correlated with the positive rates of RT-PCR (rs = -0.036, P = 0.016), but did not significantly correlate with the positive rates of IgM (rs = -0.006, P = 0.698) or IgG (rs = 0.017, P = 0.239). There was no statistically significant difference between the SARS-CoV-2-specific IgG, IgM, or RNA positive rates of the community residents and those of the healthcare workers. The positive rate of SARS-CoV-2 RNA was lower for the first-line healthcare workers than for the non-first-line healthcare workers and the administrative and logistical staff.
Environmental contamination by heavy metals is a public health concern. However, understandings of sources and pathways of heavy metal accumulation in crops, especially in major agricultural areas, ...is insufficient. In this study, atmospheric dust, coal, vehicle exhaust particles, maize and corresponding soils were collected from a major agricultural area in Northeast China and analyzed for heavy metal (Cd, Hg, Pb, As, Cu, Zn, Ni, Cr) contents and Pb isotopic compositions. Compared to the risk screening values for soil contamination of agricultural land in China, the soils in the study area have relatively low heavy metal concentrations. However, the contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo) indicated a slight degree of heavy metal (particularly Cd) accumulation during the past few decades. The concentrations of Cd, Cu, Hg and Pb decreased from leaves, roots, stalks to grains, whereas it decreased from roots, grains, leaves to stalks for Zn and from roots, leaves, stalks to grains for As, Cr and Ni. The calculated bioconcentration factor (BCF) values indicated that Cd had a high possibility of entering maize roots from soil, while it was relatively difficult for Cr and Pb to accumulate in maize roots. The order of the mean translocation factor (TF) values was Zn (1.41) > Cu (0.31) > Hg (0.27) > Cd (0.15) > Pb (0.11) > Cr (0.11) > As (0.11) > Ni (0.08), suggesting that Zn had the highest mobility from root to grain, while >90% of absorbed Ni was sequestered in roots. Based on a simple binary model, the approximate contributions of Pb in vehicle emissions and coal to atmospheric dust were 78.1% and 21.9%, respectively, suggesting that Pb in atmospheric dust was mainly from vehicle emissions. For maize organs, airborne Pb was the dominant source contributor to maize stalks and grains, with approximate contributions of 78.3% and 15.1% to leaves and roots, respectively. Our study suggested that Pb accumulation in maize plants might be mainly derived from atmospheric deposition related to vehicle emissions. Hence, more efficient managerial strategies should be adopted to protect food safety and human health.
•Cd and As in cropland soils of Jilin Province show a slight degree of accumulation.•Cd has a higher possibility of entering the maize root from soil than Cr and Pb.•Zn has highest mobility from root to grain, >90% of Ni was sequestered in the root.•Airborne Pb is the dominant source contributor to maize stalks, leaves and grains.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We described a challenge named “Diabetic Retinopathy (DR)—Grading and Image Quality Estimation Challenge” in conjunction with ISBI 2020 to hold three sub-challenges and develop deep learning models ...for DR image assessment and grading. The scientific community responded positively to the challenge, with 34 submissions from 574 registrations. In the challenge, we provided the DeepDRiD dataset containing 2,000 regular DR images (500 patients) and 256 ultra-widefield images (128 patients), both having DR quality and grading annotations. We discussed details of the top 3 algorithms in each sub-challenges. The weighted kappa for DR grading ranged from 0.93 to 0.82, and the accuracy for image quality evaluation ranged from 0.70 to 0.65. The results showed that image quality assessment can be used as a further target for exploration. We also have released the DeepDRiD dataset on GitHub to help develop automatic systems and improve human judgment in DR screening and diagnosis.
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•Provides the DeepDRiD dataset, performance evaluation, top methods and results•Presents deep learning approaches in DR image quality assessment and grading•Discusses the future work of DR automatic screening
Diabetic retinopathy (DR) is the most common disease caused by diabetes. Challenges are held to address real-world issues encountered in the design of DR automated screening systems to advance the technology in this area. Thus, we described a challenge named "Diabetic Retinopathy (DR)—Grading and Image Quality Estimation Challenge" in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI 2020) for fundus image assessment and DR grading. The scientific community responded positively to the challenge. In the challenge, we provided a deep DR image dataset (DeepDRiD) containing regular DR images and ultra-widefield (UWF) DR images, both having image quality and DR grading diagnosis. We discussed details of the three best algorithms in each sub-challenges. The results by the top algorithms showed that image quality assessment can be used as a target for further exploration.
In DeepDRiD challenge, organizers hold a real-world exploration in diabetic retinopathy (DR) auto-screening systems using regular fundus images from 500 participants and ultra-widefield fundus images from 128 participants. Among the 34 participating teams, we summarized the top 3 teams in the three sub-challenges involved in DR grading and image quality assessment. In addition to providing new insights into image quality assessment strategy, these models can enhance the judgment of healthcare workers in DR screening and bring precise screening results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The ER Ca2+ channel ryanodine receptor 2 (RyR2) is required for maintenance of insulin content and glucose-stimulated insulin secretion, in part, via regulation of the protein IRBIT in the insulinoma ...cell line INS-1. Here, we examined store-operated and depolarization-dependent Ca2+entry using INS-1 cells in which either RyR2 or IRBIT were deleted. Store-operated Ca2+ entry (SOCE) stimulated with thapsigargin was reduced in RyR2KO cells compared to controls, but was unchanged in IRBITKO cells. STIM1 protein levels were not different between the three cell lines. Basal and stimulated (500 μM carbachol) phospholipase C (PLC) activity was also reduced specifically in RyR2KO cells. Insulin secretion stimulated by tolbutamide was reduced in RyR2KO and IRBITKO cells compared to controls, but was potentiated by an EPAC-selective cAMP analog in all three cell lines. Cellular PIP2 levels were increased and cortical f-actin levels were reduced in RyR2KO cells compared to controls. Whole-cell Cav channel current density was increased in RyR2KO cells compared to controls, and barium current was reduced by acute activation of the lipid phosphatase pseudojanin preferentially in RyR2KO cells over control INS-1 cells. Action potentials stimulated by 18 mM glucose were more frequent in RyR2KO cells compared to controls, and insensitive to the SK channel inhibitor apamin. Taken together, these results suggest that RyR2 plays a critical role in regulating PLC activity and PIP2 levels via regulation of SOCE. RyR2 also regulates β-cell electrical activity by controlling Cav current density and SK channel activation.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The colonization of bacterial pathogens is a major concern in wound infection and becoming a public health issue. Herein, a core-shell structured Ag@MSN (silver core embedded with mesoporous silica, ...AM)-based nanoplatform was elaborately fabricated to co-load ciprofloxacin (CFL) and tumor necrosis factor-alpha (TNF-alpha) small interfering RNA (siTNF-alpha) (AMPC@siTNF-alpha) for treating the bacterial-infected wound. The growth of bacterial pathogens was mostly inhibited by released silver ions (Ag.sup.+) and CFL from AMPC@siTNF-alpha. Meanwhile, the loaded siTNF-alpha was internalized by macrophage cells, which silenced the expression of TNF-alpha (a pro-inflammatory cytokine) in macrophage cells and accelerated the wound healing process by reducing inflammation response. In the in vivo wound model, the Escherichia coli (E. coli)-infected wound in mice almost completely disappeared after treatment with AMPC@siTNF-alpha, and no suppuration symptom was observed during the course of the treatment. Importantly, this nanoplatform had negligible side effects both in vitro and in vivo. Taken together, this study strongly demonstrates the promising potential of AMPC@siTNF-alpha as a synergistic therapeutic agent for clinical wound infections.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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