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As a dense instance segmentation problem, rebar counting in a complex environment such as rebar yard and rebar transpotation has received significant attention in both academic and industrial contexts. Traditional counting approaches, such as manual counting and machine vision-based algorithms, are often inefficient or inaccurate since rebars with varied sizes and shapes are stacked overlapping, rebar image is not clear for complex light condition such as dawn, night and strong light, and other environmental noises exist in rebar image; thus, they no longer fulfil the requirements of modern automation. This paper proposes MaskID, an innovative counting method based on deep learning and heuristic strategies. First, an improved version of the Mask region-based convolutional neural network (Mask R-CNN) was designed to obtain the segmentation results through splitting and rescaling so as to capture more detail in a large-scale rebar image. Then, a series of intelligent denoising strategies corresponding to aspect ratio of recognized box, overlapping recognized objects, object distribution and environmental noise, were applied to improve the segmentation results. The performance of the proposed method was evaluated on open-competition and test-platform datasets. The F1-score was found to be over 0.99 on all datasets. The experimental results demonstrate that the proposed method is effective for dense rebar counting and significantly outperforms existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Background: Laparoscopic hepatectomy (LH) has achieved rapid progress over the last decade. However, it is still challenging to apply laparoscopy to lesions located in segments I, VII, VIII, and IVa and the hepatic hilar region due to difficulty operating around complex anatomical structures. In this study, we applied three-dimensional printing (3DP) and indocyanine green (ICG) fluorescence imaging technology to complex laparoscopic hepatectomy (CLH) to explore the effects and value of the modified procedure. Materials and methods: From January 2019 to January 2021, 54 patients with complex hepatobiliary diseases underwent LH at our center. Clinical data were collected from these patients and retrospectively analyzed. Results: A total of 30 patients underwent CLH using the conventional approach, whereas 24 cases received CLH with 3DP technology and ICG fluorescent navigation. Preoperative data were compared between the two groups. In the 3DP group, we modified the surgical strategy of four patients (4/24, 16.7%) due to real-time intraoperative navigation with 3DP and ICG fluorescent imaging technology. We did not modify the surgical strategy for any patient in the non-3DP group (P = 0.02). There were no significant differences between the non-3DP and 3DP groups regarding operating time (297.7±104.1 min vs. 328.8±110.9 min, P = 0.15), estimated blood loss (400±263.8 ml vs. 345.8±356.1 ml, P = 0.52), rate of conversion to laparotomy (3/30 vs. 2/24, P = 0.79), or pathological outcomes including the incidence of microscopical R0 margins (28/30 vs. 24/24, P = 0.57). Additionally, there were no significant differences in postoperative complications or recovery conditions between the two groups. No instances of 30- or 90-day mortality were observed. Conclusion: The optimal surgical strategy for CLH can be chosen with the help of 3DP technology and ICG fluorescent navigation. This modified procedure is both safe and effective, but without improvement of intraoperative and short-term outcomes. [ABSTRACT FROM AUTHOR]

Background: Many studies have shown associations between rising temperatures, El Niño events and dengue incidence, but the effect of sustained periods of extreme high temperatures (i.e., heatwaves) on dengue outbreaks has not yet been investigated. This study aimed to compare the short-term temperature-dengue associations during different dengue outbreak periods, estimate the dengue cases attributable to temperature, and ascertain if there was an association between heatwaves and dengue outbreaks in Hanoi, Vietnam. Methodology/Principal findings: Dengue outbreaks were assigned to one of three categories (small, medium and large) based on the 50th, 75th, and 90th percentiles of distribution of weekly dengue cases during 2008–2016. Using a generalised linear regression model with a negative binomial link that controlled for temporal trends, temperature variation, rainfall and population size over time, we examined and compared associations between weekly average temperature and weekly dengue incidence for different outbreak categories. The same model using weeks with or without heatwaves as binary variables was applied to examine the potential effects of extreme heatwaves, defined as seven or more days with temperatures above the 95th percentile of daily temperature distribution during the study period. This study included 55,801 dengue cases, with an average of 119 (range: 0 to 1454) cases per week. The exposure-response relationship between temperature and dengue risk was non-linear and differed with dengue category. After considering the delayed effects of temperature (one week lag), we estimated that 4.6%, 11.6%, and 21.9% of incident cases during small, medium, and large outbreaks were attributable to temperature. We found evidence of an association between heatwaves and dengue outbreaks, with longer delayed effects on large outbreaks (around 14 weeks later) than small and medium outbreaks (4 to 9 weeks later). Compared with non-heatwave years, dengue outbreaks (i.e., small, moderate and large outbreaks combined) in heatwave years had higher weekly number of dengue cases (p<0.05). Findings were robust under different sensitivity analyses. Conclusions: The short-term association between temperature and dengue risk varied by the level of outbreaks and temperature seems more likely affect large outbreaks. Moreover, heatwaves may delay the timing and increase the magnitude of dengue outbreaks. Author summary: Dengue fever is one of the most common mosquito-borne viral diseases. Weather extremes such as El Niño event and extreme hot summer can affect dengue incidence rate and dengue outbreaks. More frequent, more intensive and longer lasting heatwaves in the 21st century is anticipated because of global warming, making it necessary to investigate the association between heatwaves and dengue outbreaks. In this study, we estimated 4.6%, 11.6%, and 21.9% of incident dengue cases during small, medium, and large outbreaks attributable to temperature in Hanoi, Vietnam. We also found evidence of an association between heatwaves and dengue outbreaks, with longer delayed effects on large outbreaks than small and medium outbreaks. Compared with non-heatwave years, dengue outbreaks in heatwave years had higher number of dengue cases. Heatwave weather may represent an emerging risk factor or predicator of dengue outbreaks in tropical regions. Future dengue prediction models incorporating heatwaves may help increase the accuracy of predictability. [ABSTRACT FROM AUTHOR]

Exploring the evolutionary patterns of mitochondrial genomes is important for our understanding of the Saccharomyces sensu stricto (SSS) group, which is a model system for genomic evolution and ecological analysis. In this study, we first obtained the complete mitochondrial sequences of two important species, Saccharomyces mikatae and Saccharomyces kudriavzevii. We then compared the mitochondrial genomes in the SSS group with those of close relatives, and found that the non-coding regions evolved rapidly, including dramatic expansion of intergenic regions, fast evolution of introns and almost 20-fold higher rearrangement rates than those of the nuclear genomes. However, the coding regions, and especially the protein-coding genes, are more conserved than those in the nuclear genomes of the SSS group. The different evolutionary patterns of coding and non-coding regions in the mitochondrial and nuclear genomes may be related to the origin of the aerobic fermentation lifestyle in this group. Our analysis thus provides novel insights into the evolution of mitochondrial genomes. [ABSTRACT FROM AUTHOR]

Various computational models have been developed to transfer annotations of gene essentiality between organisms. However, despite the increasing number of microorganisms with well-characterized sets of essential genes, selection of appropriate training sets for predicting the essential genes of poorly-studied or newly sequenced organisms remains challenging. In this study, a machine learning approach was applied reciprocally to predict the essential genes in 21 microorganisms. Results showed that training set selection greatly influenced predictive accuracy. We determined four criteria for training set selection: (1) essential genes in the selected training set should be reliable; (2) the growth conditions in which essential genes are defined should be consistent in training and prediction sets; (3) species used as training set should be closely related to the target organism; and (4) organisms used as training and prediction sets should exhibit similar phenotypes or lifestyles. We then analyzed the performance of an incomplete training set and an integrated training set with multiple organisms. We found that the size of the training set should be at least 10% of the total genes to yield accurate predictions. Additionally, the integrated training sets exhibited remarkable increase in stability and accuracy compared with single sets. Finally, we compared the performance of the integrated training sets with the four criteria and with random selection. The results revealed that a rational selection of training sets based on our criteria yields better performance than random selection. Thus, our results provide empirical guidance on training set selection for the identification of essential genes on a genome-wide scale. [ABSTRACT FROM AUTHOR]

The canonical glycolysis pathway is responsible for converting glucose into 2 molecules of acetyl-coenzyme A (acetyl-CoA) through a cascade of 11 biochemical reactions. Here, we have designed and constructed an artificial phosphoketolase (APK) pathway, which consists of only 3 types of biochemical reactions. The core enzyme in this pathway is phosphoketolase, while phosphatase and isomerase act as auxiliary enzymes. The APK pathway has the potential to achieve a 100% carbon yield to acetyl-CoA from any monosaccharide by integrating a one-carbon condensation reaction. We tested the APK pathway in vitro, demonstrating that it could efficiently catabolize typical C1-C6 carbohydrates to acetyl-CoA with yields ranging from 83% to 95%. Furthermore, we engineered Escherichia coli stain capable of growth utilizing APK pathway when glycerol act as a carbon source. This novel catabolic pathway holds promising route for future biomanufacturing and offering a stoichiometric production platform using multiple carbon sources. The canonical glycolysis pathway converts glucose into two molecules of acetyl-CoA via a cascade of eleven biochemical reactions. This study repurposes phosphoketolase to construct an artificial pathway which comprises only three reactions and could theoretically achieve a 100% carbon yield of acetyl-CoA from any sugar. [ABSTRACT FROM AUTHOR]

Orcinol glucoside (OG), mainly found in the rhizome of the traditional Chinese herb Curculigo orchioides Gaertn, is noted for its antidepressant effects. In this study, an efficient screening pipeline was established for identifying the highly active orcinol synthase (ORS) and UDP-dependent glycosyltransferase (UGT) involved in the biosynthesis of OG by combining transcriptome analysis, structure-based virtual screening, and in vitro enzyme activity assays. By enhancing the downstream pathway, metabolic engineering and fermentation optimization, the OG production in Yarrowia lipolytica was improved 100-fold, resulting in a final yield of 43.46 g/L (0.84 g/g DCW), which is almost 6,400-fold higher than the extraction yield from C. orchioides roots. This study provides a reference for rapid identification of functional genes and high-yield production of natural products. This study deciphers the biosynthetic pathway of the antidepressant orcinol glucoside from Curculigo orchioides and engineers the production of orcinol glucoside in Yarrowia lipolytica with yields over 6,400-fold higher than that extracted from its natural plant source. [ABSTRACT FROM AUTHOR]

The antituberculosis vaccine Bacillus Calmette–Guérin (BCG) induces nonspecific protection against heterologous infections, at least partly through induction of innate immune memory (trained immunity). The amplitude of the response to BCG is variable, but the factors that influence this response are poorly understood. Metabolites, either released by cells or absorbed from the gut, are known to influence immune responses, but whether they impact BCG responses is not known. We vaccinated 325 healthy individuals with BCG, and collected blood before, 2 weeks and 3 months after vaccination, to assess the influence of circulating metabolites on the immune responses induced by BCG. Circulating metabolite concentrations after BCG vaccination were found to have a more pronounced impact on trained immunity responses, such as the increase in IL-1β and TNF-α production upon Staphylococcus aureus stimulation, than on specific adaptive immune memory, assessed as IFN-γ production in response to Mycobacterium tuberculosis. Circulating metabolites at baseline were able to predict trained immunity responses at 3 months after vaccination and enrichment analysis based on the metabolites positively associated with trained immunity revealed enrichment of the tricarboxylic acid (TCA) cycle and glutamine metabolism, both of which were previously found to be important for trained immunity. Several new metabolic pathways that influence trained immunity were identified, among which taurine metabolism associated with BCG-induced trained immunity, a finding validated in functional experiments. In conclusion, circulating metabolites are important factors influencing BCG-induced trained immunity in humans. Modulation of metabolic pathways may be a novel strategy to improve vaccine and trained immunity responses. The response to the BCG vaccine, which provides protection against tuberculosis as well as unrelated pathogens, is variable. This study shows that the baseline plasma metabolome is able to partially predict trained immunity upon BCG vaccination, identifying the metabolome as a potential source of this heterogeneity. [ABSTRACT FROM AUTHOR]

Three dimensional multicellular aggregate, also referred to as cell spheroid or microtissue, is an indispensable tool for in vitro evaluating antitumor activity and drug efficacy. Compared with classical cellular monolayer, multicellular tumor spheroid (MCTS) offers a more rational platform to predict in vivo drug efficacy and toxicity. Nevertheless, traditional processing methods such as plastic dish culture with nonadhesive surfaces are regularly time-consuming, laborious and difficult to provide uniform-sized spheroids, thus causing poor reproducibility of experimental data and impeding high-throughput drug screening. In order to provide a robust and effective platform for in vitro drug evaluation, we present an agarose scaffold prepared with the template containing uniform-sized micro-wells in commercially available cell culture plates. The agarose scaffold allows for good adjustment of MCTS size and large-scale production of MCTS. Transparent agarose scaffold also allows for monitoring of spheroid formation under an optical microscopy. The formation of MCTS from MCF-7 cells was prepared using different-size-well templates and systematically investigated in terms of spheroid growth curve, circularity, and cell viability. The doxorubicin cytotoxicity against MCF-7 spheroid and MCF-7 monolayer cells was compared. The drug penetration behavior, cell cycle distribution, cell apoptosis, and gene expression were also evaluated in MCF-7 spheroid. The findings of this study indicate that, compared with cellular monolayer, MCTS provides a valuable platform for the assessment of therapeutic candidates in an in vivo-mimic microenvironment, and thus has great potential for use in drug discovery and tumor biology research. [ABSTRACT FROM AUTHOR]

Non-specific protective effects of certain vaccines have been reported, and long-term boosting of innate immunity, termed trained immunity, has been proposed as one of the mechanisms mediating these effects. Several epidemiological studies suggested cross-protection between influenza vaccination and COVID-19. In a large academic Dutch hospital, we found that SARS-CoV-2 infection was less common among employees who had received a previous influenza vaccination: relative risk reductions of 37% and 49% were observed following influenza vaccination during the first and second COVID-19 waves, respectively. The quadrivalent inactivated influenza vaccine induced a trained immunity program that boosted innate immune responses against various viral stimuli and fine-tuned the anti-SARS-CoV-2 response, which may result in better protection against COVID-19. Influenza vaccination led to transcriptional reprogramming of monocytes and reduced systemic inflammation. These epidemiological and immunological data argue for potential benefits of influenza vaccination against COVID-19, and future randomized trials are warranted to test this possibility. Author summary: COVID-19, caused by the virus SARS-CoV-2, has claimed millions of lives and affected many more since its emergence. A number of studies have previously suggested that influenza vaccination can provide protection against COVID-19. Although multiple COVID-19 vaccines are currently available, emergence of new variants and inequity in vaccine distribution around the world make it crucial to identify alternative ways that can help in the fight against this pandemic. With this in mind, we investigated if seasonal influenza vaccination had any effect on COVID-19 incidence. Dutch healthcare workers who received the influenza vaccine in the previous flu season had 37% and 49% lower risk of SARS-CoV-2 infection in the first two waves of the pandemic, respectively. We also explored the mechanisms underlying this observation, using various techniques such as single-cell RNA sequencing, proteomics, and stimulation assays. The influenza vaccine reduced systemic inflammation and reprogrammed the immune cells to fine-tune the response against SARS-CoV-2. This study reveals influenza vaccination as a safe and helpful tool to decrease COVID-19 burden. [ABSTRACT FROM AUTHOR]

The rheological properties parameters of paddy soil affect the interaction between the tillage tools and soil, thus influencing the operation quality and power consumption. In order to study the effects of tillage methods and moisture content on the rheological properties parameters of paddy soil in the middle and lower reaches of the Yangtze River, uniaxial compression creep tests of paddy soils with four moisture contents under no tillage (moisture contents: 26.71%, 24.52%, 23.26%, 21.28%) and plough tillage (moisture contents: 26.77%, 25.55%, 23.40%, 20.56%) were carried out using a TMS-PRO texture analyzer. The creep properties curves obtained from the tests, and the rheological constitutive equation of paddy soil under compression was established by Burgers viscoelastic model. Respectively, the quantitative change rules of creep properties of paddy soil with different moisture contents under different tillage methods and the correlation between these parameters were explored. The results showed that the moisture content under the three-year plough tillage and no tillage methods had significant influence on the rheological properties parameters of paddy soil (P < 0.05). The instantaneous elastic modulus, delay elastic modulus, and viscosity coefficient of the two paddy soils (no tillage and plough tillage soils) decreased with the increase of moisture content. However, the variation rules of relaxation time and delay viscosity coefficient with moisture content differed between these two paddy soils. Specifically, the strain rate of the two paddy soils decreased as moisture content decreased, where the total strain combines elastic strain, viscous strain, and viscoelastic strain. The initial strain rate and steady strain rate of the plough tillage paddy soils were lower than that of the no tillage paddy soils. The established creep model equation could be used to obtain viscoelastic rheological parameters of paddy soil in a wide range. The fitting equations between rheological parameters and moisture content were introduced into Burgers model, and the coupling equations between creep deformation and moisture content and time were derived, which could be used to predict the creep properties and deformation behavior of paddy soil in a certain range of no tillage and ploughed field. Overall, this study has a certain theoretical significance for the development and improvement of paddy soil rheology theory, and can also provide theoretical basis and technical support for the research of agricultural machinery design optimization, field water, soil conservation, soil tillage and compaction related simulation analysis in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

The KBI (kissing balloon inflation) technique is considered the default strategy for the two-stent approach in real world practice. Studies comparing KBI and No-KBI in patients undergoing the one-stent approach have reported conflicting results. The meta-analysis was performed to compare the clinical outcomes of the KBI strategy and the No-KBI strategy for coronary bifurcation lesions in the one-stent approach. Five randomized studies were included, and a total of 1264 patients were involved in the meta-analysis. The primary outcome was cardiac death. The secondary end points were stent thrombosis, MI (myocardial infarction), target lesion revascularization (TLR), target vessel revascularization (TVR), and main vessel and side branch restenosis. Compared with the No-KBI strategy, the KBI strategy was associated with a significant reduction in side branch restenosis (OR: 0.44, 95% CI: 0.30–0.64, p<0.001). A high risk of main vessel restenosis was found in the KBI group (OR: 2.96, 95% CI: 1.74–5.01, p<0.001). There were no significant differences in rates of cardiac death (OR: 1.89, 95% CI: 0.60–5.95, p = 0.28), stent thrombosis (OR: 0.98, 95% CI: 0.19–4.94, p = 0.98), MI (OR: 0.68, 95% CI: 0.33–1.44, p = 0.30), TLR (OR 1.14, 95% CI 0.68–1.90, p = 0.62), or TVR (OR 1.27, 95% CI 0.75–2.16, p = 0.38). Compared with the No-KBI strategy, the KBI strategy reduced the incidence of side branch restenosis and increased the risk of main branch restenosis in the one-stent approach. However, the clinical outcomes were similar between the KBI and No-KBI groups. [ABSTRACT FROM AUTHOR]

Purpose: Develop and evaluate an electrochemical method to identify healthy individuals, malignant hematopathic patients and solid tumor patients by detecting the leukocytes in whole-blood. Methods: A total of 114 individual blood samples obtained from our affiliated hospital in China (June 2015- August 2015) were divided into three groups: healthy individuals (n = 35), hematologic malignancies (n = 41) and solid tumors (n = 38). An electrochemical workstation system was used to measure differential pulse voltammetry due to the different electrochemical behaviors of leukocytes in blood samples. Then, one-way analysis of variance (ANOVA) was applied to analyze the scanning curves and to compare the peak potential and peak current. Results: The scanning curve demonstrated the specific electrochemical behaviors of the blank potassium ferricyanide solution and that mixed with blood samples in different groups. Significant differences in mean peak potentials of mixture and shifts (ΔEp (mV)) were observed of the three groups (P< = 0.001). 106.00±9.00 and 3.14±7.48 for Group healthy individuals, 120.90±11.18 and 18.10±8.81 for Group hematologic malignancies, 136.84±11.53 and 32.89±10.50 for Group solid tumors, respectively. In contrast, there were no significant differences in the peak currents and shifts. Conclusions: The newly developed method to apply the electrochemical workstation system to identify hematologic malignancies and solid tumors with good sensitivity and specificity might be effective, suggesting a potential utility in clinical application. [ABSTRACT FROM AUTHOR]

The first genome-wide association study for coronary artery disease (CAD) in the Han Chinese population, we reported recently, had identified rs6903956 in gene ADTRP on chromosome 6p24.1 as a novel susceptibility locus for CAD. The risk allele of rs6903956 was associated with decreased mRNA expression of ADTRP. To further study the correlation of ADTRP expression and CAD, in this study we evaluated the associations of eight common variants in the expression-regulating regions of ADTRP with CAD in the Southern Han Chinese population. Rs169790 in 3’UTR, rs2076189 in 5’UTR, four SNPs (rs2076188, rs7753407, rs11966356 and rs1018383) in promoter, and two SNPs (rs3734273, rs80355771) in the last intron of ADTRP were genotyped in 1716 CAD patients and 1572 controls. The correlations between these loci and total or early-onset CAD were investigated. None of these loci was discovered to associate with total CAD (P > 0.05). However, with early-onset CAD, significant both allelic and genotypic associations of rs7753407, rs11966356 and rs1018383 were identified, after adjustment for risk factors of age, gender, hypertension, diabetes, lipid profiles and smoking (adjusted P < 0.05). A haplotype AGCG (constructed by rs2076188, rs7753407, rs11966356 and rs1018383) was identified to protect subjects from early-onset CAD (OR = 0.332, 95% CI = 0.105–0.879, adjusted P = 0.010). Real-time quantitative reverse transcription polymerase chain reaction assay showed that the risk alleles of the associated loci were significantly associated with decreased expression of ADTRP mRNA. Moreover, the average level of ADTRP mRNA expression in early-onset CAD cases was significantly lower than that in controls. Our results provide new evidence supporting the association of ADTRP with the pathogenesis of early-onset CAD. [ABSTRACT FROM AUTHOR]

Background: Previous studies have reported that natriuretic peptides in the blood and pleural fluid (PF) are effective diagnostic markers for heart failure (HF). These natriuretic peptides include N-terminal pro-brain natriuretic peptide (NT-proBNP), brain natriuretic peptide (BNP), and midregion pro-atrial natriuretic peptide (MR-proANP). This systematic review and meta-analysis evaluates the diagnostic accuracy of blood and PF natriuretic peptides for HF in patients with pleural effusion. Methods: PubMed and EMBASE databases were searched to identify articles published in English that investigated the diagnostic accuracy of BNP, NT-proBNP, and MR-proANP for HF. The last search was performed on 9 October 2014. The quality of the eligible studies was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies tool. The diagnostic performance characteristics (sensitivity, specificity, and other measures of accuracy) were pooled and examined using a bivariate model. Results: In total, 14 studies were included in the meta-analysis, including 12 studies reporting the diagnostic accuracy of PF NT-proBNP and 4 studies evaluating blood NT-proBNP. The summary estimates of PF NT-proBNP for HF had a diagnostic sensitivity of 0.94 (95% confidence interval [CI]: 0.90–0.96), specificity of 0.91 (95% CI: 0.86–0.95), positive likelihood ratio of 10.9 (95% CI: 6.4–18.6), negative likelihood ratio of 0.07 (95% CI: 0.04–0.12), and diagnostic odds ratio of 157 (95% CI: 57–430). The overall sensitivity of blood NT-proBNP for diagnosis of HF was 0.92 (95% CI: 0.86–0.95), with a specificity of 0.88 (95% CI: 0.77–0.94), positive likelihood ratio of 7.8 (95% CI: 3.7–16.3), negative likelihood ratio of 0.10 (95% CI: 0.06–0.16), and diagnostic odds ratio of 81 (95% CI: 27–241). The diagnostic accuracy of PF MR-proANP and blood and PF BNP was not analyzed due to the small number of related studies. Conclusions: BNP, NT-proBNP, and MR-proANP, either in blood or PF, are effective tools for diagnosis of HF. Additional studies are needed to rigorously evaluate the diagnostic accuracy of PF and blood MR-proANP and BNP for the diagnosis of HF. [ABSTRACT FROM AUTHOR]