Evaluation of a multiplex PCR kit for detection of 17 respiratory pathogens in hospitalized patients

BackgroundRapid pathogen identification is critical for optimizing diagnosis and treatment of infectious diseases. Multiplex polymerase chain reaction (PCR) is a sensitive, broad-spectrum molecular detection technique that is simple and rapid to perform. It is capable of simultaneously screening for multiple pathogens within a short time range. Here, we designed and evaluated a multiplex PCR kit for the identification of 17 common respiratory pathogens in clinical samples from hospitalized patients.MethodsA total of 452 samples from hospitalized patients, including 242 respiratory and 210 non-respiratory samples, were analyzed for 13 bacteria and 4 fungi by a multiplex fluorescent PCR kit. The diagnostic performance of the kit was assessed by considering routine microbiology as the reference standard.ResultsThe overall positivity rate of the multiplex PCR kit was 86.9%, much higher than that noted on routine microbiology (56.9%). Furthermore, the co-infection detection rate was also significantly higher than that noted on routine microbiology (69.5% vs. 15.0%). Compared with routine microbiology, kit sensitivity was >90% for detection of most target bacteria, with a negative predictive value (NPV) of >99%, especially for detection of Pseudomonas aeruginosa, Klebsiella pneumoniae, Acinetobacter baumannii, Stenotrophomonas maltophilia, Enterococcus faecium, Enterococcus faecalis and Escherichia coli. The kit was noted to be particularly superior in identifying Stenotrophomonas maltophilia and Streptococcus pneumoniae as compared to routine microbiology. The multiplex PCR kit was noted to be less sensitive (33.3–59.6%) and more specific (93.9–100.0%) for detection of mycobacteria and fungi.ConclusionsOur multiplex PCR kit offers a rapid and sensitive diagnosis of common bacterial pneumonia, although sensitivity for mycobacteria and fungi warrants enhancement. Further optimization includes minimizing false positivity and increasing relevance to clinical application.     

Applying Deep Learning for Breast Cancer Detection in Radiology

Recent advances in deep learning have enhanced medical imaging research. Breast cancer is the most prevalent cancer among women, and many applications have been developed to improve its early detection. The purpose of this review is to examine how various deep learning methods can be applied to breast cancer screening workflows. We summarize deep learning methods, data availability and different screening methods for breast cancer including mammography, thermography, ultrasound and magnetic resonance imaging. In this review, we will explore deep learning in diagnostic breast imaging and describe the literature review. As a conclusion, we discuss some of the limitations and opportunities of integrating artificial intelligence into breast cancer clinical practice.     

Hemotropic Mycoplasma spp. in Aquatic Mammals,Amazon Basin,Brazil

Hemotropic Mycoplasma spp. (hemoplasmas) are uncultivable bacteria that infect mammals, including humans. We detected a potentially novel hemoplasma species in blood samples from wild river dolphins in the Amazon River Basin, Brazil. Further investigation could determine pathogenicity and zoonotic potential of the detected hemoplasma.     

Osteoporosis Risk in Hemodialysis Patients: The Roles of Gender,Comorbidities, Biochemical Parameters,Health and Diet Literacy

Osteoporosis is a common bone health disorder in hemodialysis patients that is linked with a higher morbidity and mortality rate. While previous studies have explored the associated factors of osteoporosis, there is a lack of studies investigating the impacts of health literacy (HL) and digital healthy diet literacy (DDL) on osteoporosis. Therefore, we aimed to investigate the associations of HL, DDL, and other factors with osteoporosis among hemodialysis patients. From July 2020 to March 2021, a cross-sectional study was conducted on 675 hemodialysis patients in eight hospitals in Vietnam. The data were collected by using the osteoporosis self-assessment tool for Asians (OSTA) and the 12-item short form of the health literacy questionnaire (HLS-SF12) on digital healthy diet literacy (DDL) and hemodialysis dietary knowledge (HDK). In addition, we also collected information about the socio-demographics, the clinical parameters, the biochemical parameters, and physical activity. Unadjusted and adjusted multinomial logistic regression models were utilized in order to investigate the associations. The proportion of patients at low, medium, and high levels of osteoporosis risk was 39.6%, 40.6%, and 19.8%, respectively. In the adjusted models, women had a higher likelihood of osteoporosis risk than men (odds ratio, OR, 3.46; 95% confidence interval, 95% CI, 1.86, 6.44; p < 0.001; and OR, 6.86; 95% CI, 2.96, 15.88; p < 0.001). The patients with rheumatoid arthritis (OR, 4.37; 95% CI, 1.67, 11.52; p = 0.003) and stomach ulcers (OR, 1.95; 95% CI, 1.01, 3.77; p = 0.048) were more likely to have a higher likelihood of osteoporosis risk than those without. The patients who had a higher waist circumference (WC), HL, and DDL were less likely to have a medium level of osteoporosis risk (OR, 0.95; 95% CI, 0.92, 0.98; p = 0.004; OR, 0.92; 95% CI, 0.88, 0.96; p < 0.001; OR, 0.96; 95% CI, 0.93, 0.99; p = 0.017, respectively) and a high level of osteoporosis risk (OR, 0.93; 95% CI, 0.89, 0.97; p = 0.001; OR, 0.89; 95% CI, 0.84, 0.94; p < 0.001; OR, 0.95; 95% CI, 0.91, 0.99; p = 0.008, respectively) compared with a low level of osteoporosis risk and to those with a lower WC, HL, and DDL. In addition, higher levels of hemoglobin (Hb) (OR, 0.79; 95% CI, 0.66, 0.95; p = 0.014), hematocrit (Hct) (OR, 0.95; 95% CI, 0.92, 0.99; p = 0.041), albumin (OR, 0.91; 95% CI, 0.83, 0.99; p = 0.030), and education (OR, 0.37; 95% CI, 0.16, 0.88; p = 0.025) were associated with a lower likelihood of a high level of osteoporosis risk. In conclusion, osteoporosis risk is highly prevalent in hemodialysis patients. Improved HL, DDL, education, WC, albumin, Hb, and Hct levels should be considered in preventing hemodialysis patients from developing osteoporosis.     

Performance comparison of two nucleic acid amplification systems for SARS‐CoV‐2 detection: A multi‐center study

BackgroundMany rapid nucleic acid testing systems have emerged to halt the development and spread of COVID‐19. However, so far relatively few studies have compared the diagnostic performance between these testing systems and conventional detection systems. Here, we performed a retrospective analysis to evaluate the clinical detection performance between SARS‐CoV‐2 rapid and conventional nucleic acid detection system.MethodsClinical detection results of 63,352 oropharyngeal swabs by both systems were finally enrolled in this analysis. Sensitivity (SE), specificity (SP), and positive and negative predictive value (PPV, NPV) of both systems were calculated to evaluate their diagnostic accuracy. Concordance between these two systems were assessed by overall, positive, negative percent agreement (OPA, PPA, NPA) and κ value. Sensitivity of SARS‐CoV‐2 rapid nucleic acid detection system (Daan Gene) was further analyzed with respect to the viral load of clinical specimens.ResultsSensitivity of Daan Gene was slightly lower than that of conventional detection system (0.86 vs. 0.979), but their specificity was equivalent. Daan Gene had ≥98.0% PPV and NPV for SARS‐CoV‐2. Moreover, Daan Gene demonstrated an excellent test agreement with conventional detection system (κ = 0.893, p = 0.000). Daan Gene was 99.31% sensitivity for specimens with high viral load (C _t < 35) and 50% for low viral load (C _t ≥ 35).ConclusionsWhile showing an analytical sensitivity slightly below than that of conventional detection system, rapid nucleic acid detection system may be a diagnostic alternative to rapidly identify SARS‐CoV‐2‐infected individuals with high viral loads and a powerful complement to current detection methods.     

Epigenetic analysis of cell-free DNA by fragmentomic profiling

Cell-free DNA (cfDNA) fragmentation patterns contain important molecular information linked to tissues of origin. We explored the possibility of using fragmentation patterns to predict cytosine-phosphate-guanine (CpG) methylation of cfDNA, obviating the use of bisulfite treatment and associated risks of DNA degradation. This study investigated the cfDNA cleavage profile surrounding a CpG (i.e., within an 11-nucleotide [nt] window) to analyze cfDNA methylation. The cfDNA cleavage proportion across positions within the window appeared nonrandom and exhibited correlation with methylation status. The mean cleavage proportion was ∼twofold higher at the cytosine of methylated CpGs than unmethylated ones in healthy controls. In contrast, the mean cleavage proportion rapidly decreased at the 1-nt position immediately preceding methylated CpGs. Such differential cleavages resulted in a characteristic change in relative presentations of CGN and NCG motifs at 5′ ends, where N represented any nucleotide. CGN/NCG motif ratios were correlated with methylation levels at tissue-specific methylated CpGs (e.g., placenta or liver) (Pearson’s absolute r > 0.86). cfDNA cleavage profiles were thus informative for cfDNA methylation and tissue-of-origin analyses. Using CG-containing end motifs, we achieved an area under a receiver operating characteristic curve (AUC) of 0.98 in differentiating patients with and without hepatocellular carcinoma and enhanced the positive predictive value of nasopharyngeal carcinoma screening (from 19.6 to 26.8%). Furthermore, we elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93. FRAGmentomics-based Methylation Analysis (FRAGMA) presents many possibilities for noninvasive prenatal, cancer, and organ transplantation assessment.

Fragmentation patterns of cell-free DNA (cfDNA) molecules contain a wealth of molecular information related to their tissues of origin (1). For instance, compared with the background DNA molecules that are mainly derived from the hematopoietic system (2, 3), size shortening of fetal and tumoral DNA molecules occurs in the plasma DNA of pregnant women and cancer patients, respectively (4–6). In addition, a series of 10-bp periodicities were present in fetal and tumoral DNA molecules below 146 bp, with a relative reduction in the major peak at 166 bp (1). Such characteristic size profiles suggest that the fragmentation of cfDNA may be associated with nucleosome structures (5, 7). Many important characteristics pertaining to cfDNA fragmentation have been unveiled recently, such as nucleosome footprints (8, 9), fragment end motifs (10), preferred ends (7, 11), and jagged ends (12), which are examples of fragmentomic markers (1).cfDNA fragmentomics is an emergent and actively pursued area, with wide-ranging biological and clinical implications. It has been reported that the use of fragmentation patterns of cfDNA could inform the expression status of genes (13, 14). Using mouse models, DNA nucleases (e.g., DNASE1L3) were found to play important roles in the generation of plasma DNA molecules (15, 16). Fragmentomic features, such as cfDNA end motifs and jagged ends, were further demonstrated to be useful for monitoring DNA nuclease activities, providing biomarkers for autoimmune diseases (e.g., systemic lupus erythematosus) (17, 18). In addition, the deficiencies of nuclease activities in a mouse model resulted in altered DNA methylation profiles of plasma DNA molecules (19). However, how cfDNA fragmentation patterns interplay with DNA methylation in human individuals under different pathophysiological conditions, such as pregnancy and oncogenesis, and in healthy patients without nuclease deficiency, is unknown. It is also not known whether fragmentomic features can be used to deduce cfDNA methylation status.A widely employed way to assess DNA methylation is through bisulfite sequencing (20). A key limitation of this approach is the severe degradation of DNA molecules caused by the bisulfite treatment (21), which greatly increases the sampling variation when analyzing rare target molecules (e.g., tumoral cfDNA at early stages of cancer). Many efforts have been made toward overcoming this issue. For example, Vaisvila et al. developed enzymatic methyl sequencing for which DNA molecules were treated using tet methylcytosine dioxygenase 2 and T4 phage β-glucosyltransferase, followed by the apolipoprotein B mRNA editing enzyme catalytic subunit 3A (APOBEC3A) treatment. Cytosine conversion based on enzymatic processes was reported to be much less destructive (22). Recently, researchers developed approaches making use of third-generation sequencing technologies such as single-molecule real-time sequencing (Pacific Biosciences) (23) and nanopore sequencing (24) to analyze cytosine-phosphate-guanine (CpG) methylation patterns in native DNA molecules, theoretically overcoming the above-mentioned limitation. However, compared with second-generation sequencing (also called next-generation sequencing [NGS]) technologies, the throughput of third-generation sequencing technologies is generally lower and the sequencing cost per nucleotide (nt) is much higher, thus restricting its immediate application in clinical settings. Here, we explore the feasibility of enabling the assessment of DNA methylation using fragmentomic characteristics of cfDNA molecules deduced from NGS results without the use of bisulfite or enzymatic treatment. If successful, such an approach could leverage the high throughput of NGS while obviating the use of chemical/enzymatic conversion and could potentially be readily integrated into currently used NGS-based platforms for cfDNA analysis.In this study, we utilize the fragmentation patterns proximal to a CpG site for deducing its methylation status. The fragmentation pattern is depicted by the frequency of cfDNA fragment ends at each position within a certain nt range relative to a CpG of interest, termed a cleavage profile (Fig. 1). Such a cleavage profile varies according to the methylation status of the CpG site of interest, providing the basis for methylation analysis by using fragmentomic features. We further correlated two types of end motifs (CGN and NCG; N represents any nucleotide of A, C, G, or T) resulting from differential cutting in the measurement window related to DNA methylation, attempting to construct a simplified approach for methylation analysis. Modeling CpG methylation using cfDNA fragmentation may facilitate noninvasive prenatal testing, cancer detection, and tissue-of-origin analysis (Fig. 1). Furthermore, we explore the feasibility of using deep learning to deduce the methylation status at single CpG resolution through the cleavage profile (Fig. 1). We refer to this FRAGmentomics-based Methylation Analysis as FRAGMA in this study.Open in a separate windowFig. 1.Schematic for FRAGMA of cfDNA molecules. cfDNA molecules were sequenced by massively parallel sequencing and aligned to the human reference genome. The cleavage proportion within an 11-nt window (the cleavage measurement window) was used to measure the cutting preference of cfDNA molecules. The patterns of cleavage proportion within a window (the cleavage profile) depended on the methylation status of one or more CpG sites associated with that window. For example, a methylated CpG site might confer a higher probability of cfDNA cutting at the cytosine in the CpG context, but an unmethylated site might not. Such methylation-dependent differential fragmentation within a cleavage measurement window resulted in the change in CGN/NCG motif ratio. Thus, the CGN/NCG motif ratio provided a simplified version for reflecting CpG methylation, allowing cfDNA tissue-of-origin analysis of cfDNA and cancer detection. Furthermore, the great number of cleavage profiles derived from cfDNA molecules might provide an opportunity to train a deep learning model for methylation prediction at the single CpG resolution.     

贵港市急性脑炎及脑膜炎症候群病原体监测

目的 了解华南地区急性脑炎及急性脑膜炎的发病强度、病原谱和流行病学特征,为急性脑炎、脑膜炎的临床诊治和预防控制提供参考依据。方法 在广西贵港市建立涵盖市辖区、桂平市和平南县的急性脑炎、脑膜炎流行病学监测网络,按照筛检标准评估疑似病例,进行流行病学调查和采样,对标本开展细菌学培养和10种常见病毒检测。结果 2007年5月—2008年10月监测期内,共评估急性脑炎及急性脑膜炎症候群病例 883例,死亡 41例,细菌学培养和PCR检测发现存在肺炎链球菌、流脑、Hib、猪链球菌等致病菌,病毒学检测发现肠道病毒、腮腺炎病毒和乙脑病毒是病毒性脑炎脑膜炎的主要病原,贵港市确诊的细菌性、病毒性脑炎脑膜炎年均发病率分别为0.92/10万和6.42/10万,细菌性、病毒性脑炎脑膜炎均以夏秋季多见,10岁以下儿童为主,职业分布细菌性脑炎脑膜炎以散居儿童和农民为主,分别占48.65%和29.73%,病毒性脑炎脑膜炎以散居儿童和学生为主,分别占59.64%和21.08%。结论 广西贵港市急性脑炎脑膜炎病例以病毒性感染占多数,病原诊断的细菌性脑炎脑膜炎发病率处于较低水平。     

VEGFR‐2 expression in carcinoid cancer cells and its role in tumor growth and metastasis

Carcinoid tumors are slow growing and highly vascular neuroendocrine neoplasms that are increasing in incidence. Previously, we showed that carcinoid tumors express vascular endothelial growth factor receptor 2 (VEGFR‐2) in the epithelial compartment of carcinoid tumor sections; yet, its role is not completely understood. The purpose of our study was to: (i) assess the expression of VEGFR‐2 in the novel human carcinoid cell line BON, (ii) to determine the role of PI3K/Akt signaling on VEGFR‐2 expression and (iii) to assess the effect of VEGFR‐2 on BON cell invasion, migration and proliferation. We found that, although VEGFR‐2 is expressed in BON cells, reduction in VEGFR‐2 expression actually enhanced proliferation, invasion, and migration of the BON cell line. Also, expression of VEGFR‐2 was inversely related to PI3K signaling. Carcinoid liver metastases in mice demonstrated decreased VEGFR‐2 expression. Furthermore, the expression of a truncated, soluble form of VEGFR‐2 (sVEGFR‐2), a protein demonstrated to inhibit cell growth, was detected in BON cells. The presence of VEGFR‐2 in the epithelial component of carcinoid tumors and in the BON cell line suggests an alternate role for VEGFR‐2, in addition to its well‐defined role in angiogenesis. The expression of sVEGFR‐2 may explain the inverse relationship between VEGFR‐2 expression and PI3K/Akt signaling and the inhibitory effect VEGFR‐2 has on BON cell proliferation, migration and invasion.     

一种新的循环肿瘤细胞检测平台在膀胱癌诊疗中的初步应用

目的 初步探索一种新的循环肿瘤细胞(CTC)检测平台在膀胱癌诊疗中的应用.方法 选取膀胱癌患者10例为试验组,健康志愿者5例为对照组.10例患者均接受经尿道膀胱肿瘤电切术.术前分别取试验组和对照组的外周全血样本10 ml、尿液样本10 ml,术后再次取试验组的外周全血、尿液样本各10 ml.使用Celsee PREP 400TM循环肿瘤细胞检测平台分别检测所有样本中所含CTC,对比术前试验组与对照组血、尿样本中的CTC,对比试验组术前、术后的CTC.随访12个月,监测患者是否出现复发或进展.结果 试验组术前血样本中均发现CTC,中位数为4个(1~9个);对照组均未发现CTC.试验组术后血样本中,8例(80%)发现CTC,中位数为1.5个(1~4个),2例(20%)未发现CTC.膀胱癌患者术前与术后血样本中的CTC比较,差异有统计学意义(P=0.014).尿液样本因杂质堵塞微通道而无法检测样本中的CTC.随访1年,患者无疾病进展/复发生存率为80%.结论 Celsee PREP 400TM循环肿瘤细胞检测平台可有效检测血样本中的CTC,值得进一步探索其在膀胱癌诊疗中的应用.     

2020年肾移植临床国际前沿热点及新进展荟萃

在浩瀚的肾移植相关文献中, 本文汲取和盘点2020年肾移植临床国际前沿热点和难点, 移植新技术、新方法、新视野及新进展荟萃, 主要内容包括排斥反应, 免疫抑制优化应用与调控, 移植感染, 移植后恶性肿瘤, 无创检测与生物标志物, 供者器官保存、修复及利用, 肾移植术后肾病复发, 多因素影响移植肾长期存活, 计算机与人工智能等。加强对肾移植领域文献的阅读与思考, 站在更高的起点开拓视野, 结合中国肾移植临床实践, 以推动肾移植获得更好的长期效果。