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The implementation of AI assisted cancer detection systems in clinical environments has faced numerous hurdles, mainly because of the restricted explainability of their elemental mechanisms, even though such detection systems have proven to be highly effective. Medical practitioners are skeptical about adopting AI assisted diagnoses as due to the latter's inability to be transparent about decision making processes. In this respect, explainable artificial intelligence (XAI) has emerged to provide explanations for model predictions, thereby overcoming the computational black box problem associated with AI systems. In this particular research, the focal point has been the exploration of the Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) approaches which enable model prediction explanations. This study used an ensemble model consisting of three convolutional neural networks(CNN): InceptionV3, InceptionResNetV2 and VGG16, which was based on averaging techniques and by combining their respective predictions. These models were trained on the Kvasir dataset, which consists of pathological findings related to gastrointestinal cancer. An accuracy of 96.89% and F1-scores of 96.877% were attained by our ensemble model. Following the training of the ensemble model, we employed SHAP and LIME to analyze images from the three classes, aiming to provide explanations regarding the deterministic features influencing the model's predictions. The results obtained from this analysis demonstrated a positive and encouraging advancement in the exploration of XAI approaches, specifically in the context of gastrointestinal cancer detection within the healthcare domain.
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Inteligencia Artificial , Neoplasias Gastrointestinales , Redes Neurales de la Computación , Humanos , Neoplasias Gastrointestinales/patología , Neoplasias Gastrointestinales/diagnóstico , Neoplasias Gastrointestinales/clasificación , Diagnóstico por Computador/métodosRESUMEN
Background: Surgical nursing is a high-risk, high-pressure, and complex field. Nurses need extensive knowledge, skills, and abilities. Problem-Based Learning (PBL) and Simulation-Based Learning (SBL) are effective student-centered methods. Which method is better for surgical nurse training? More research is needed to determine the best approach for undergraduate surgical nurse education. Purpose: To compare the impact of PBL and SBL on undergraduate nursing students' performance and improve learning outcomes in surgical nursing education. Methods: We used a pretest/post-test design with 318 nursing undergraduates randomly assigned to two groups. Participants completed three progressive scenarios focused on surgical nursing cases. Experts blindly reviewed video recordings using the 70-item Korean Nurses' Core Competence Scale (KNCCS) to assess performance. The 13-item Satisfaction and Self-confidence in learning Scale (SSS) measured learning confidence and satisfaction. SBL participants also completed the 16-item Educational Practices in Simulation Scale (EPSS) and 20-item Simulation Design Scale (SDS). Results: The study found significant positive effects on both groups, with noticeable improvements in post-test, retention, and follow-up test results (P < 0.001). The SBL group showed higher competency levels in nurses (P < 0.001). The Cohen's d and effect size (r) for various skills were as follows: clinical performance (0.84767 and 6.39023), critical thinking (0.31017 and 0.15325), professional attitude (0.85868 and 0.39452), and communication skills (1.55149 and 0.61294). The satisfaction and self-confidence of nurses were higher in the SBL group (4.53±0.596; 4.47±0.611) compared to the PBL group (4.32±0.689; 4.25±0.632) in all dimensions of SSS (all P < 0.05). The SBL group also scored high in simulation design and EPSS. However, improvements are needed in fidelity, objectives, information, and students' expectations. Conclusion: SBL and PBL improve nurses' core competence, satisfaction, and self-confidence. SBL is superior. This study promotes student-centered education, enhancing surgical nursing professionals' quality and ensuring future patient safety.
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Quantitative analysis of the process of urban expansion and evolution is of great practical significance for the future planning and development potential of valley cities. Based on GEE cloud platform and Landsat satellite data, this paper analyzed the spatio-temporal change characteristics and transfer rules of land cover in Xining City and its surrounding areas in the past 33 years by using random forest algorithm, spatio-temporal consistency test, land use dynamic attitude, transfer matrix and transfer hot spot analysis methods. The results show that the accuracy range of the preliminary classification of construction land is improved by 1.57%-3.53 % by using the spatio-temporal consistency test algorithm. The characteristics of land cover change in the study area are mainly the increase of construction land and forest area, the decrease of cultivated land and grassland area, the small change of water body and unused land, and the change of land cover type from cultivated land to urban construction land is prominent. The hot areas of construction land have gradually shifted from the central and eastern districts of the city in 1987 to the hot areas dominated by the Haihu New District of the West of the city, the Biological Park and the higher education base of the North District of the city, the South New District of the city, Duoba Town and the Ganhe Industrial Park in 2019.
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A method for spectral reflectance factor reconstruction based on wideband multi-illuminant imaging was proposed, using a programmable LED lighting system and modified Bare Bones Particle Swarm Optimization algorithms. From a set of 16 LEDs with different spectral power distributions, nine light sources with correlated color temperatures in the range of 1924 K - 15746 K, most of them daylight simulators, were generated. Samples from three color charts (X-Rite ColorChecker Digital SG, SCOCIE ScoColor paint chart, and SCOCIE ScoColor textile chart), were captured by a color industrial camera under the nine light sources, and used in sequence as training and/or testing colors. The spectral reconstruction models achieved under multi-illuminant imaging were trained and tested using the canonical Bare Bones Particle Swarm Optimization and its proposed modifications, along with six additional and commonly used algorithms. The impacts of different illuminants, illuminant combinations, algorithms, and training colors on reconstruction accuracy were studied comprehensively. The results indicated that training colors covering larger regions of color space give more accurate reconstructions of spectral reflectance factors, and combinations of two illuminants with a large difference of correlated color temperature achieve more than twice the accuracy of that under a single illuminant. Specifically, the average reconstruction error by the method proposed in this paper for patches from two color charts under A + D90 light sources was 0.94 and 1.08 CIEDE2000 color difference units. The results of the experiment also confirmed that some reconstruction algorithms are unsuitable for predicting spectral reflectance factors from multi-illuminant images due to the complexity of optimization problems and insufficient accuracy. The proposed reconstruction method has many advantages, such as being simple in operation, with no requirement of prior knowledge, and easy to implement in non-contact color measurement and color reproduction devices.
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Mesothelioma is classified into three histological subtypes, epithelioid, sarcomatoid, and biphasic, according to the relative proportions of epithelioid and sarcomatoid tumor cells present. Current guidelines recommend that the sarcomatoid component of each mesothelioma is quantified, as a higher percentage of sarcomatoid pattern in biphasic mesothelioma shows poorer prognosis. In this work, we develop a dual-task graph neural network (GNN) architecture with ranking loss to learn a model capable of scoring regions of tissue down to cellular resolution. This allows quantitative profiling of a tumor sample according to the aggregate sarcomatoid association score. Tissue is represented by a cell graph with both cell-level morphological and regional features. We use an external multicentric test set from Mesobank, on which we demonstrate the predictive performance of our model. We additionally validate our model predictions through an analysis of the typical morphological features of cells according to their predicted score.
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Neoplasias Pulmonares , Mesotelioma Maligno , Mesotelioma , Neoplasias de los Tejidos Blandos , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Mesotelioma/patología , Redes Neurales de la ComputaciónRESUMEN
Malignant Mesothelioma is a difficult to diagnose and highly lethal cancer usually associated with asbestos exposure. It can be broadly classified into three subtypes: Epithelioid, Sarcomatoid, and a hybrid Biphasic subtype in which significant components of both of the previous subtypes are present. Early diagnosis and identification of the subtype informs treatment and can help improve patient outcome. However, the subtyping of malignant mesothelioma, and specifically the recognition of transitional features from routine histology slides has a high level of inter-observer variability. In this work, we propose an end-to-end multiple instance learning (MIL) approach for malignant mesothelioma subtyping. This uses an adaptive instance-based sampling scheme for training deep convolutional neural networks on bags of image patches that allows learning on a wider range of relevant instances compared to max or top-N based MIL approaches. We also investigate augmenting the instance representation to include aggregate cellular morphology features from cell segmentation. The proposed MIL approach enables identification of malignant mesothelial subtypes of specific tissue regions. From this a continuous characterisation of a sample according to predominance of sarcomatoid vs epithelioid regions is possible, thus avoiding the arbitrary and highly subjective categorisation by currently used subtypes. Instance scoring also enables studying tumor heterogeneity and identifying patterns associated with different subtypes. We have evaluated the proposed method on a dataset of 234 tissue micro-array cores with an AUROC of 0.89±0.05 for this task. The dataset and developed methodology is available for the community at: https://github.com/measty/PINS.
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Mesotelioma Maligno , Humanos , Redes Neurales de la Computación , Reconocimiento en PsicologíaRESUMEN
Soil texture is one of the important physical and natural properties of soil. Much of the current research focuses on soil texture monitoring using non-imaging geophysical spectrometers. However there are fewer studies utilizing unmanned aerial vehicle (UAV) hyperspectral data for soil texture monitoring. UAV mounted hyperspectral cameras can be used for quickly and accurately obtaining high-resolution spatial information of soil texture. A foundation has been laid for the realization of rapid soil texture surveys using unmanned airborne hyperspectral data without field sampling. This study selected three typical farmland areas in Huangshui Basin of Qinghai as the study area, and a total of 296 soil samples were collected. Data calibration of UAV spectra using laboratory spectra and field in situ spectra to explore the feasibility of applying laboratory soil texture models directly to field conditions. This results show that UAV hyperspectral imagery combined with machine learning can obtain a set of ideal processing methods. The pre-processing of the spectral data can obtain high accuracy of soil texture estimation and good mapping effect. The results of this study can provide effective technical support and decision-making assistance for future agricultural land planning on the Tibetan Plateau. The main innovation of this study is to establish a set of processing procedures and methods applicable to UAV hyperspectral imagery to provide data reference for monitoring soil texture in agricultural fields on the Tibetan Plateau.
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Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Since it is difficult to obtain multiple spatial resolution remote sensing images of the same area at the same time, the main current method to study the scale effect of land cover classification is to use the same image resampled to different resolutions, however errors in the resampling process lead to uncertainty in the accuracy of land cover classification. To study the land cover classification scale effect of different spatial resolutions of multi-source remote sensing data, we selected 1 m and 4 m of GF-2, 6 m of SPOT-6, 10 m of Sentinel-2, and 30 m of Landsat-8 multi-sensor data, and explored the scale effect of image spatial resolution on land cover classification from two aspects of mixed image element decomposition and spatial heterogeneity. For the study area, we compared the classification obtained from GF-2, SPOT-6, Sentinel-2, and Landsat-8 images at different spatial resolutions based on GBDT and RF. The results show that (1) GF-2 and SPOT-6 had the best classification results, and the optimal scale based on this classification accuracy was 4-6 m; (2) the optimal scale based on linear decomposition depended on the study area; (3) the optimal scale of land cover was related to spatial heterogeneity, i.e., the more fragmented and complex was the space, the smaller the scale needed; and (4) the resampled images were not sensitive to scale and increased the uncertainty of the classification. These findings have implications for land cover classification and optimal scale selection, scale effects, and landscape ecology uncertainty studies.
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Monitoreo del Ambiente , Tecnología de Sensores Remotos , Imágenes Satelitales , Monitoreo del Ambiente/métodos , Procesamiento de Imagen Asistido por ComputadorRESUMEN
Objective: Single-pill amlodipine besylate (AML) plus losartan (LOS) has been used to treat inadequately controlled hypertension after antihypertensive monotherapy; however, relevant data in China are limited. This study aimed to compare the efficacy and safety of single-pill AML/LOS and LOS alone in Chinese patients with inadequately controlled hypertension after LOS treatment. Methods: In this multicenter, double-blind, randomized, controlled phase III clinical trial, patients with inadequately controlled hypertension after 4 weeks of LOS treatment were randomized to receive daily single-pill AML/LOS (5/100â mg, AML/LOS group, N = 154) or LOS (100â mg, LOS group, N = 153) tablets for 8 weeks. At weeks 4 and 8 of treatment, sitting diastolic and systolic blood pressure (sitDBP and sitSBP, respectively) and the BP target achievement rate were assessed. Results: At week 8, the sitDBP change from baseline was greater in the AML/LOS group than in the LOS group (-8.84 ± 6.86 vs. -2.65 ± 7.62â mmHg, P < 0.001). In addition, the AML/LOS group also showed greater sitDBP change from baseline to week 4 (-8.77 ± 6.60 vs. -2.99 ± 7.05â mmHg) and sitSBP change from baseline to week 4 (-12.54 ± 11.65 vs. -2.36 ± 10.33â mmHg) and 8 (-13.93 ± 10.90 vs. -2.38 ± 12.71â mmHg) (all P < 0.001). Moreover, the BP target achievement rates at weeks 4 (57.1% vs. 25.3%, P < 0.001) and 8 (58.4% vs. 28.1%, P < 0.001) were higher in the AML/LOS group than those in the LOS group. Both treatments were safe and tolerable. Conclusion: Single-pill AML/LOS is superior to LOS monotherapy for controlling BP and is safe and well tolerated in Chinese patients with inadequately controlled hypertension after LOS treatment.
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Ischemic stroke (IS) is a leading cause of morbidity and mortality worldwide. Immunity and inflammation are key factors in the pathophysiology of IS. The inflammatory response is involved in all stages of stroke, and microglia are the predominant cells involved in the post-stroke inflammatory response. Resident microglia are the main immune cells of the brain and the first line of defense of the nervous system. After IS, activated microglia can be both advantageous and detrimental to surrounding tissue; they can be divided into the harmful M1 types or the neuro-protective M2 type. Currently, with the latest progress of transcriptomics analysis, different and more complex phenotypes of microglia activation have been described, such as disease-related microglia (DAM) associated with Alzheimer's disease (AD), white matter associated microglia (WAMs) in aging, and stroke-related microglia (SAM) etc. The triggering receptor expressed on myeloid cell 2 (TREM2) is an immune-related receptor on the surface of microglia. Its expression increases after IS, which is related to microglial inflammation and phagocytosis, however, its relationship with the microglia phenotype is not clear. This paper reviews the following: 1) the phenotypic changes of microglia in various pathological stages after IS and its relationship with inflammatory factors; 2) the relationship between the expression of the TREM2 receptor and inflammatory factors; 3) the relationship between phenotypic changes of microglia and its surface receptor TREM2; 4) the TREM2-related signalling pathway of microglia after IS and treatment for TREM2 receptor; and finally 5) To clarify the relationship among TREM2, inflammation, and microglia phenotype after IS, as well as the mechanism among them and the some possible treatment of IS targeting TREM2. Moreover, the relationship between the new phenotype of microglia such as SAM and TREM2 has also been systematically summarized, but there are no relevant research reports on the relationship between TREM2 and SAM after IS.
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Enfermedad de Alzheimer , Accidente Cerebrovascular Isquémico , Accidente Cerebrovascular , Humanos , Microglía/metabolismo , Encéfalo/metabolismo , Inflamación/metabolismo , Enfermedad de Alzheimer/metabolismo , Glicoproteínas de Membrana/genética , Glicoproteínas de Membrana/metabolismo , Receptores Inmunológicos/genética , Receptores Inmunológicos/metabolismoRESUMEN
Lumpy skin disease virus (LSDV) is a rapidly emerging pathogen in Asia, including China. Improving the propagation of LSDV is important for diagnostics and vaccine production. Our study identified and compared the LSDV susceptibility of eleven standard cells using western blot, indirect immune-fluorescence assay, quantitative PCR, and 50 % tissue culture infectious dose. Our finding revealed that the LSDV strain could infect five cell lines and show a cytopathic effect. Furthermore, the hTERT-CSF cell line had the highest level of virus in the five cell models, followed by BHK-21, MDBK, Vero, and hTERT-ST. Hence, hTERT-CSF could be used as a candidate cell line for basic and applied research, clinical application, and LSDV vaccine development, providing a vital reference in LSDV and other viruses.
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Dermatosis Nodular Contagiosa , Virus de la Dermatosis Nodular Contagiosa , Animales , Bovinos , Asia , Línea Celular , China , Virus de la Dermatosis Nodular Contagiosa/genética , Reacción en Cadena de la PolimerasaRESUMEN
The present study aims to quantitatively assess soil erosion intensity (SEI) and amounts in the Qinghai Lake Basin (QLB) over the 1990-2020 period using the Integrated Valuation Ecosystem Services and Tradeoffs (InVEST) model based on multi-source data. In addition, the changing trends and driving factors of soil erosion (SE) in the study area were systematically analyzed. The result showed: (1) An increasing-decreasing trend in the total soil erosion amount (SEA) in the QLB over the 1990-2020 period, with an average SEI of 579.52 t/km2. In addition, very low and low erosion classes covered 94.49% of the total surface area, while areas with high SEI were mainly distributed in alpine areas with low vegetation coverage (VC). (2) The highest average SEI was observed in bare land, while grassland and unused land were the main land use (LU) types where SE mainly occurred, with the ratio of the two being 95.78%. (3) The average value of SEI was positively correlated with altitude values below 4800 m. In addition, areas with altitude ranges of 4000-4400 m, 3600-4000 m, and 4400-4800 m were the main areas where SE occurred, with an average total soil erosion ratio (SER) value of 88.73%. (4) The average SEI was directly proportional to the slope degrees. SE occurred mainly in the areas with slope degree ranges of 15-25°, 25-35°, 8-15°, and >35°, accounting for 93.16% of the average total SER value. (5) The q value of the two-factor interaction was greater than that of the single-factor interaction. In addition, the areas with a high SE risk were mainly those with 1220-2510 m rainfall, <0.104 VC, the land use/land cover (LULC) type bare land, the altitude range 4400-4800 m, and a slope of >35°. The interaction between rainfall, VC, LULC, elevation, and slope had a significant impact on the spatial distribution of SEI.
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Ecosistema , Erosión del Suelo , Suelo , Lagos , Monitoreo del Ambiente , Conservación de los Recursos Naturales , ChinaRESUMEN
Objective: To investigate anatomical and visual outcomes of macular hole (MH) after inverted internal limiting membrane (ILM) flap technique for idiopathic macular hole (IMH). Methods: A total of 13 IMH cases diagnosed in Shanxi Eye Hospital between January 2015 and June 2016 were included in the study. All patients underwent vitrectomy combined with indocyanine green-assisted inverted ILM flap technique. The MH closure rate, best-corrected visual acuity (BCVA), changes of ellipsoid zone (EZ), and external limiting membrane (ELM) were examined before operation and one, three, and six months after operation. Furthermore, 488 nm fundus autofluorescence (FAF) and spectral domain optical coherence tomography (SD-OCT) were used to observe the dynamic changes in function of macular area after surgery. Results: One month after the surgery, the MH closure rate was 100% and the visual acuity (VA) was stable, with no recurrence. Additionally, the average logMAR BCVA before operation was 1.208 ± 0.158, and this value became 0.877 ± 0.105 one month after the operation, showing a significant decrease. Three months after surgery, the average logMAR BCVA was 0.792 ± 0.103, which was significantly lower than the level one month after the surgery but much higher than that six months after surgery (0.708 ± 0.131). Besides, the diameter of the EZ defect of the postoperative one month, three months, and six months was (1377.46 ± 198.65) µm, (964.62 ± 336.26) µm, and (817.08 ± 442.99) µm, respectively. In postoperative one month, three months, and six months, the diameter of the ELM defect diameter was (969.62 ± 189.92) µm, (649.92 ± 413.15) µm, and (557.62 ± 412.50) µm, respectively. The diameter of both EZ and ELM defects was significantly reduced with the passage of time after surgery. Conclusion: Inverted ILM flap technique can reconstruct macular anatomical structure and improve VA. This technique is effective for the treatment of IMH with large MH minimum diameter and base diameter.
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Perforaciones de la Retina , Humanos , Perforaciones de la Retina/cirugía , Perforaciones de la Retina/diagnóstico , Estudios Retrospectivos , Retina/diagnóstico por imagen , Retina/cirugía , Agudeza Visual , Colgajos QuirúrgicosRESUMEN
In this work, a protonated graphitic carbon nitride (P-g-C3N4)-coated graphene oxide (GO) composite (GO/P-g-C3N4) was prepared via wet-chemistry exfoliation, followed by a freeze-drying process. The GO/P-g-C3N4 composite was found to have an outstanding photodegradation performance effect on the reactive red 195 (RR195) dye and very strong antibacterial properties. Both the GO structure and the dispersed state of P-g-C3N4 were found to play a significant role in enhancing the photocatalytic activity of GO/P-g-C3N4. The GO/P-g-C3N4 obtained via freeze-drying retained a large number of oxygen-containing groups and showed higher catalytic activity and reusability than the reduced GO (rGO)/g-C3N4 obtained via thermal reduction. Characterization of the samples indicates that GO/P-g-C3N4 has a higher specific surface area and photocurrent density than rGO/g-C3N4; it is likely that these properties lead to the superior photocatalytic activity observed in GO/P-g-C3N4. Adsorption energy calculations indicate that O2 can be readily adsorbed onto the GO surface, which results in stronger oxidizing superoxide anion radicals (â¢O2-) and holes (h+); these active radicals can rapidly degrade RR195 dyes. Moreover, broad-spectrum antibacterial activity (demonstrated against Staphylococcus aureus and Escherichia coli) was observed in the case of the GO/P-g-C3N4 composite irradiated with visible light. This work offers new insights into the design of cost-effective g-C3N4-based photocatalysts for environmental remediation.
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Antibacterianos , Antibacterianos/farmacología , Antibacterianos/química , Catálisis , Escherichia coli , Fotólisis , Oxidantes FotoquímicosRESUMEN
Recent reports have suggested that abnormal miR-29c expression in hippocampus have been implicated in the pathophysiology of some neurodegenerative and neuropsychiatric diseases. However, the underlying effect of miR-29c in regulating hippocampal neuronal function is not clear. In this study, HT22 cells were infected with lentivirus containing miR-29c or miR-29c sponge. Cell counting kit-8 (CCK8) and lactate dehydrogenase (LDH) assay kit were applied to evaluate cell viability and toxicity before and after TNF-α administration. Reactive oxygen species (ROS) generation and mitochondrial membrane potential (MMP) were measured with fluorescent probes. Hoechst 33258 staining and TUNEL assay were used to evaluate cell apoptosis. The expression of key mRNA/proteins (TNFR1, Bcl-2, Bax, TRADD, FADD, caspase-3, -8 and -9) in the apoptosis pathway was detected by PCR or WB. In addition, the protein expression of microtubule-associated protein-2 (MAP-2), nerve growth-associated protein 43 (GAP-43) and synapsin-1 (SYN-1) was detected by WB. As a result, we found that miR-29c overexpression could improve cell viability, attenuate LDH release, reduce ROS production and inhibit MMP depolarization in TNF-α-treated HT22 cells. Furthermore, miR-29c overexpression was found to decrease apoptotic rate, along with decreased expression of Bax, cleaved caspase-3, cleaved caspase-9, and increased expression of Bcl-2 in TNF-α-treated HT22 cells. However, miR-29c sponge exhibited an opposite effects. In addition, in TNF-α-treated HT22 cells, miR-29c overexpression could decrease the expressions of TNFR1, TRADD, FADD and cleaved caspase-8. However, in HT22 cells transfected with miR-29c sponge, TNF-α-induced the expressions of TNFR1, TRADD, FADD and cleaved caspase-8 was significantly exacerbated. At last, TNF-α-induced the decreased expression of MAP-2, GAP-43 and SYN-1 was reversed by miR-29c but exacerbated by miR-29c sponge. Overall, our study demonstrated that miR-29c protects against TNF-α-induced HT22 cells injury through alleviating ROS production and reduce neuronal apoptosis. Therefore, miR-29c might be a potential therapeutic agent for TNF-α accumulation and toxicity-related brain diseases.
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MicroARNs , Factor de Necrosis Tumoral alfa , Ratones , Animales , Especies Reactivas de Oxígeno/metabolismo , Caspasa 3/metabolismo , Factor de Necrosis Tumoral alfa/farmacología , Factor de Necrosis Tumoral alfa/metabolismo , Caspasa 8/metabolismo , Caspasa 8/farmacología , Receptores Tipo I de Factores de Necrosis Tumoral , Proteína X Asociada a bcl-2/metabolismo , Proteína GAP-43/metabolismo , Línea Celular , Apoptosis , Proteínas Proto-Oncogénicas c-bcl-2/metabolismo , MicroARNs/metabolismo , Hipocampo/metabolismoRESUMEN
@#Abstract: Objective To explore the threshold of ALT for initiating antiviral therapy in HBV infected patients, and to provide a basis for initiating antiviral therapy in chronic HBV-infected patients. Methods This retrospective cohort study recruited 707 consecutive treatment-naïve chronic hepatitis B (CHB) patients undergoing diagnostic liver biopsy in the department of infectious diseases of the Affiliated Hospital of Yan′an University from October 2013 to August 2018. Liver biopsy specimens were obtained under ultrasound guidance using Menghini 16G disposable needles. The METAVIR scoring system, which is commonly used internationally, was used to divide the patients into the group with mild liver tissue injury and the group with significant liver tissue injury, and the alanine aminotransferase (ALT) levels were measured separately. Receiver operating characteristic (ROC) curve and Mann-Whitney U test were used to evaluate the diagnostic value of ALT for significant liver tissue injury under different demographic characteristics. Results Of 707 patients, 292 (41.30%) had significant liver tissue injury confirmed by liver biopsy (METAVIR ≥A2 and/or F2). When the ULN of ALT was set to NICE criteria (30 U/L for males, 19 U/L for females), AASLD criteria (35 U/L for males, 25 U/L for females) and EASL or APASL criteria (40 U/L for males and females), CHB patients with <ULN accounted for 32.38%, 35.03% and 36.07% of significant liver tissue injury, respectively. And significant liver tissue injury in CHB patients with 1-2×ULN accounted for 41.99%, 41.85% and 50.30%, respectively. The optimal ALT critical values were 33 U/L for overall patients, 25 U/L for females, 45 U/L for males, 45 U/L for ≤30 years olds, 33 U/L for>30 years olds, 22 U/L for HBeAg negative and 31 U/L for HBeAg positive patients. Conclusions The threshold of ALT for initiating antiviral therapy in chronic HBV patients should be individualized, especially should be down-regulated for the females, olders and HBeAg-negative patients.
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The effective monitoring and early warning capability of metal mine tailings ponds can improve the associated safety risk management level. The infiltration line is an important core index of tailings pond stability. In this paper, a tailings pond monitoring and early warning system, which provides technical support for the design and daily management of tailings reservoir early warning systems, is constructed. Based on a deep learning bidirectional recurrent long and short memory network, an infiltration line prediction model with univariate input and an infiltration line prediction model with multivariate input are proposed. The data adopted are those from four monitoring points of the same cross-section at different positions and data from one adjacent internal lateral displacement and internal vertical displacement monitoring point. Using the adaptive moment estimation (Adam) optimization algorithm and the root mean square error (RMSE) model evaluation metric, the multilayer perceptron model, univariate input model, and multivariate input model are compared. This work shows that their RMSEs are 0.10611, 0.09966, and 0.11955, respectively.
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Aprendizaje Profundo , Estanques , Monitoreo del Ambiente , MetalesRESUMEN
As the COVID-19 pandemic continues, countries around the world are switching toward vaccinations and boosters to combat the pandemic. However, waning immunity against SARS-CoV-2 wild-type (WT) and variants have been widely reported. Booster vaccinations have shown to be able to increase immunological protection against new variants; however, the protection observed appears to decrease quickly over time suggesting a second booster shot may be appropriate. Moreover, heterogeneity and waning of the immune response at the individual level was observed suggesting a more personalized vaccination approach should be considered. To evaluate such a personalized strategy, it is important to have the ability to rapidly evaluate the level of neutralizing antibody (nAbs) response against variants at the individual level and ideally at a point of care setting. Here, we applied the recently developed cellulose pulled-down virus neutralization test (cpVNT) to rapidly assess individual nAb levels to WT and variants of concerns in response to booster vaccination. Our findings confirmed significant heterogeneity of nAb responses against a panel of SARS-CoV-2 variants, and indicated a strong increase in nAb response against variants of concern (VOCs) upon booster vaccination. For instance, the nAb response against current predominant omicron variant was observed with medians of 88.1% (n = 6, 95% CI = 73.2% to 96.2%) within 1-month postbooster and 70.7% (n = 22, 95% CI = 66.4% to 81.8%) 3 months postbooster. Our data show a point of care (POC) test focusing on nAb response levels against VOCs can guide decisions on the potential need for booster vaccinations at individual level. Importantly, it also suggests the current booster vaccines only give a transient protective response against some VOC and new more targeted formulations of a booster vaccine against specific VOC may need to be developed in the future. IMPORTANCE Vaccination against SARS-CoV-2 induces protection through production of neutralization antibodies (nAb). The level of nAb is a major indicator of immunity against SARS-CoV-2 infection. We developed a rapid point-of-care test that can monitor the nAb level from a drop of finger stick blood. Here, we have implemented the test to monitor individual nAb level against wild-type and variants of SARS-CoV-2 at various time points of vaccination, including post-second-dose vaccination and postbooster vaccination. Huge diversity of nAb levels were observed among individuals as well as increment in nAb levels especially against Omicron variant after booster vaccination. This study evaluated the performance of this point-of-care test for personalized nAb response tracking. It verifies the potential of using a rapid nAb test to guide future vaccination regimens at both the individual and population level.
Asunto(s)
COVID-19 , Vacunas , Humanos , SARS-CoV-2/genética , Anticuerpos Antivirales , Pandemias , COVID-19/prevención & control , Anticuerpos Neutralizantes , VacunaciónRESUMEN
The Huangshui River Basin is one of the most densely populated areas on the Qinghai-Tibet Plateau and is characterized by a high level of human activity. The contradiction between ecological protection and socioeconomic development has become increasingly prominent; determining how to achieve the balanced and coordinated development of the Huangshui River Basin is an important task. Thus, this study used the Google Earth Engine (GEE) cloud-computing platform and Sentinel-1/2 data, supplemented with an ALOS digital elevation model (ALOS DEM) and field survey data, and combined a remote sensing classification method, grid method, and ecosystem service value (ESV) evaluation method to study the spatial correlation and interaction between land use (LU) and ESV in the Huangshui River Basin. The following results were obtained: (1) on the GEE platform, Sentinel-1/2 active and passive remote sensing data, combined with the gradient tree-boosting algorithm, can efficiently produce highly accurate LU data with a spatial resolution of 10 m in the Huangshui River Basin; the overall accuracy (OA) reached 88%. (2) The total ESV in the Huangshui River Basin in 2020 was CNY 33.18 billion (USD 4867.2 million), of which woodland and grassland were the main contributors to ESV. In the Huangshui River Basin, the LU type, LU degree, and ESV have significant positive spatial correlations, with urban and agricultural areas showing an H-H agglomeration in terms of LU degree, with woodlands, grasslands, reservoirs, and wetlands showing an H-H agglomeration in terms of ESV. (3) There is a significant negative spatial correlation between the LU degree and ESV in the Huangshui River Basin, indicating that the enhancement of the LU degree in the basin could have a negative spatial spillover effect on the ESV of surrounding areas. Thus, green development should be the future direction of progress in the Huangshui River Basin, i.e., while maintaining and expanding the land for ecological protection and restoration, and the LU structure should be actively adjusted to ensure ecological security and coordinated and sustainable socioeconomic development in the Basin.