With the current accumulation of metagenome data, it is possible to build an integrated platform for processing of rigorously selected metagenomic samples (also referred as "metagenomic communities" here) of interests. Any metagenomic samples could then be searched against this database to find the most similar sample(s). However, on one hand, current databases with a large number of metagenomic samples mostly serve as data repositories but not well annotated database, and only offer few functions for analysis. On the other hand, the few available methods to measure the similarity of metagenomic data could only compare a few pre-defined set of metagenome. It has long been intriguing scientists to effectively calculate similarities between microbial communities in a large repository, to examine how similar these samples are and to find the correlation of the meta-information of these samples. In this work we propose a novel system, Meta-Mesh, which includes a metagenomic database and its companion analysis platform that could systematically and efficiently analyze, compare and search similar metagenomic samples. In the database part, we have collected more than 7 000 high quality and well annotated metagenomic samples from the public domain and in-house facilities. The analysis platform supplies a list of online tools which could accept metagenomic samples, build taxonomical annotations, compare sample in multiple angle, and then search for similar samples against its database by a fast indexing strategy and scoring function. We also used case studies of "database search for identification" and "samples clustering based on similarity matrix" using human-associated habitat samples to demonstrate the performance of Meta-Mesh in metagenomic analysis. Therefore, Meta-Mesh would serve as a database and data analysis system to quickly parse and identify similar
Cluster Analysis ; Computational Biology ; methods ; Databases, Genetic ; Humans ; Metagenome ; Metagenomics ; methods

A novel method for accurate,fast and sensitive detection of pesticides such as imidacloprid,isocarbophos,phoxim,dursban,imidacloprid,pyridaben and avermectin in environmental water samples has been developed by using ultrasound-assisted dispersive liquid-liquid microextraction (UA-DLLME) coupled with high performance liquid chromatography with ultraviolet detection (HPLC-UV).The UA-DLLME parameters such as types/volumes of extraction/dispersion solvents,ultrasonic time,ionic strength and extraction time were investigated.Under the optimized extraction conditions,the linearity for the detection of six pesticides in the concentration range of 10-600 μg/L was obtained with limits of detections (LODs) of 0.8-3.1 μg/L and relative standard deviations (RSDs) of 4.7％-11.3％.UA-DLLME method exhibited strong enrichment ability for the six pesticides,and the enrichment factor (EFs) were ranged from 58 to 187.This method had perfect linearity,precision and recovery results,and showed obvious advantages and practicality comparing the previously reported methods.

Objective To evaluate the role of conventional and functional MR in the diagnosis of orbital mucosa-associated lymphoid tissue lymphoma (MALToma).Methods Twenty-two patients with pathologically confirmed orbital MALToma were enrolled in our study.The number,location,morphology,involvement of surrounding structure and imaging features were evaluated.Apparent diffusion coefficient (ADC) values derived from diffusion weighted imaging and time-intensity curve (TIC)pattern derived from dynamic contrast enhanced MRI were assessed. Results Orbital MALToma occurred unilaterally in 1 7 cases and bilaterally in 5 cases.Anterior orbit preseptal region was involved most frequently (20 cases),followed by intraconal(19 cases),extraxonal (17 cases)and lacrimal fossa (12 cases)regions.Most cases showed as homogeneously iso-intensity on both T1 and T2 weighted images.Mean ADC value of the lesions was (0.61 ± 0.08)× 10 -3 mm2/s.A washout-type TIC pattern was observed in 1 5 cases,while plateau pattern was found in 7 cases.Conclusion Conventional MRI can assist in describing the extent,while the functional MRI can quantitatively reflect the histo-pathological features of orbital MALToma.Combination of conventional and functional MRI can help the diagnosis of orbital MALToma.

Objective To evaluate the correlation between the gray-white matter ratio (GWR) and the outcomes of comatose adult survivors from cardiac arrest (CA) in Chinese.Methods Sixty-one CA patients checked with CT scans within 72 hours of resuscitation from January 2011 to January 2016 were included in this single-center retrospective study.Gray and white matter density (Hounsfield units) were measured,and the GWRs were calculated according to previous studies.The prognostic values of the GWRs in predicting poor outcomes (Cerebral Performance Category 3-5) were analyzed.Results The density values of gray matter were significantly higher in the good outcome group than those in the poor one.All GWRs were significantly higher in the good outcome group (P ＜ 0.05).A GWR (basal ganglia) ＜ 1.18 predicted poor outcomes with a sensitivity and specificity of 50.0％ and 88.2％,respectively (P =0.012).Conclusions Low GWRs,determined from brain CT scans in comatose CA patients after resuscitation,were associated with poor neurological outcomes.GWR determination from brain CT can be a useful indicator for outcome prediction aiding in an optimal clinical decision process in comatose survivors from CA.

Objective To evaluate the value of quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion weighted imaging (DWI) for differentiating malignant from benign orbital lymphoproliferative disorder(OLPD). Methods Forty-three patients with OLPDs(20 patients with benign OLPDs and 23 patients with orbital lymphoma) confirmed by histopathology or clinical follow-up were enrolled in this retrospective study.Quantitative parameters of DCE-MRI including volume transfer constant (Ktrans), flux rate constant (Kep), and extravascular extracellular volume fraction (Ve) and mean apparent diffusion coefficient(ADC)values were obtained. χ2test and t test were used to compare the differences of qualitative and quantitative parameters between two groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic ability of each parameter and its combination. Results Malignant group showed significantly lower mean ADC values and higher Kepvalues than benign group [ADC:(0.674±0.126)×10-3mm2/s vs(1.030±0.304)×10-3mm2/s,P<0.001;Kep:(1.299±0.566)/min vs(0.787± 0.311)/min, P= 0.001], while no significant differences was found on Ktrans(P= 0.637) and Ve(P= 0.023). ROC analyses results indicated that,a sensitivity of 95.7%,specificity of 80.0% and area under curve(AUC) of 0.896 could be obtained,when using ADC=0.809×10-3mm2/s as the cut-off value.Setting the Kepvalue of 0.863/min as the cut-off value, a sensitivity of 91.3%, specificity of 75.0% and AUC of 0.848 could be obtained. When combination of mean ADC and Kepwas used, optimal diagnostic performance could be obtained (AUC, 0.926;sensitivity, 91.3%;specificity, 90.0%). Conclusion Mean ADC values and Kepare significant variables in predicting malignant OLPDs. Combination of DWI and DCE-MRI can further improve the diagnostic capability in differentiating malignant from benign OLPDs.

Objective Toinvestigatetheclinicalvalueofreadoutsegmentationoflongvariableecho-trainsdiffusion-weightedimaging (RESOLVE-DWI)inthediagnosisandstagingofthyroid-associatedophthalmopathy(TAO).Methods Atotalof30consecutivepatientswith TAOand30healthycontrols(HCs)whounderwentRESOLVE-DWIwereenrolledinourstudy.ADCvaluesofextraocularmuscles (superiorrectus,inferiorrectus,medialrectusandlateralrectus)were measuredandcomparedbetween TAOsand HCs,active TAOsandinactiveTAOs,orinactiveTAOsandHCs.ROCanalysiswasperformedtoevaluatethediagnosticvalueofsignificantparametersfor discriminatingactivefrominactiveTAOs.Results TheADCvaluesofallextraocularmusclesinTAOsweresignificantlyhigherthan thoseinHCs(P<0.05).Meanwhile,alltheextraocularmusclesinactiveTAOsshowedsignificantlyhigherADCvaluesthanthose ininactiveTAOs(P<0.05),exceptlateralrectus(P=0.267).WhilstnosignificantdifferenceswerefoundontheADCvaluesofall extraocularmusclesbetweeninactiveTAOsandHCs(P>0.05).ROCanalysisresultsindicatedthattheADCvalueofmedialrectus showedtheoptimalstagingefficacy(cutoffvalue,1.40×10-3 mm2/s;AUC,0.766;sensitivity,92.1%;specificity,59.1%).Conclusion RESOLVE-DWIanditsderivedADCvaluesofextraocularmusclescanassistinthediagnosisofTAO.TheADCvalueofmedial rectushastheoptimalefficacyontheevaluationofitsclinicalactivity.

Objective:To investigate the value of multi-parametric analysis based on dual-layer detector spectral CT (DLCT) in predicting the initial recurrence risk for papillary thyroid carcinoma (PTC).Methods:From November 2021 to October 2022, 102 PTC patients confirmed by pathology were retrospectively collected at the First Affiliated Hospital of Nanjing Medical University in this cross-sectional study. There were 25 males and 77 females, with an age of (42±13) years old. The initial recurrence risk assessment for PTC patients was categorized into a low-risk group (75 cases) and an intermediate-high-risk group (27 cases). Clinical data, including age, gender, body mass index, history of nodular goiter, history of Hashimoto thyroiditis, and preoperative thyroid function, were collected. Tumor morphological features, including size, location, shape, aspect ratio, the degree of thyroid capsule contact, calcification, and cystic change, were evaluated. Quantitative DLCT parameters, including iodine concentration (IC), standardized iodine concentration (NIC), effective atomic number (Z eff), standardized effective atomic number (NZ eff), electronic density (ED), CT values under different energy levels (40-200 keV, 30 keV intervals) and slope of energy spectrum curve (λ HU) both in the arterial and venous phase were measured. The differences in clinical, morphological features, and spectral CT quantitative parameters between the two groups were compared using independent sample ttest, Mann-Whitney U test, or χ2 test. Multivariate logistic regression analyses were used to construct three models based on clinical and morphological features, quantitative DLCT parameters and their combination, respectively. The receiver operating characteristic curve was used to evaluate the predictive performance of these models for the initial recurrence risk of PTC patients, and the area under the curve (AUC) was compared using the DeLong test. Results:Significant differences were found in gender, lesion long diameter, lesion short diameter and calcification between the low-risk group and intermediate-high-risk groups ( P<0.05). The arterial phase IC, arterial phase Z eff, arterial phase λ HU, arterial phase CT 40 keV, venous phase NIC and venous phase NZ eff in intermediate-high-risk group were significantly lower than those in the low-risk group ( P<0.05). The logistic regression analysis revealed that the clinical model included gender ( OR=2.895, 95% CI 1.047-8.002, P=0.040) and lesion long diameter ( OR=1.142, 95% CI 1.042-1.251, P=0.004), with an AUC of 0.720, sensitivity of 63.0%, and specificity of 78.7% in predicting the initial recurrence risk of PTC patients. The DLCT quantitative parameter model included arterial phase IC ( OR=0.580, 95% CI 0.370-0.908, P=0.017), venous phase NIC ( OR=0.077, 95% CI 0.011-0.536, P=0.010), and venous phase NZ eff ( OR=0.002, 95% CI 0.001-0.103, P=0.009), with an AUC of 0.774, sensitivity of 71.9%, and specificity of 70.0%. The AUC of the combined model was 0.857, with a sensitivity of 74.1%, and specificity of 88.0%, outperforming the clinical model ( Z=2.92, P=0.004) and the DLCT quantitative parameter model ( Z=2.07, P=0.046). Conclusion:Multi-parametric analysis based on DLCT can help predict the initial recurrence risk for PTC, and combining it with clinical and morphological features, the predictive accuracy can be improved.

Objective:To explore the diagnostic value of radiomics based on arterial-venous mixed images derived from dual-energy CT (DECT) data in diagnosis of cervical lymph nodes (LNs) metastasis of papillary thyroid cancer (PTC).Methods:From June 2017 to December 2018, eighty-four patients with preoperatively DECT scanning and pathologically confirmed PTC (129 non-metastatic LNs and 97 metastatic LNs) in the First Affiliated Hospital of Nanjing Medical University were included in this study. The clinical and imaging data of all patients were retrospectively analyzed. The training cohort consisted of 62 PTC cases with 156 LNs (91 non-metastatic LNs and 65 metastatic LNs). An independent validation cohort consisted of 22 PTC patients with 70 LNs (38 non-metastatic LNs and 32 metastatic LNs). Semi-automatic LNs segmentation was conducted on arterial-venous mixed images derived from DECT using Syngo.via Frontier Radiomics software. Totally 1 226 radiomics features were extracted from arterial-venous mixed images for each LN. The least absolute shrinkage and selection operator (LASSO) regression was applied for radiomics features selection and signature building. The logistic regression modeling was used to construct diagnostic models based on the CT image features of LNs (model 1), the radiomics signature (model 2) and the combination of the CT image features and radiomics signature (model 3). An intuitive nomogram was plotted for model 3. The ROC curve analyses and area under the curve (AUC) were performed to evaluate the diagnostic efficiency of the three models, with the performances compared using the Delong test.Results:Model 1 was developed with LNs shape, degree of enhancement, pattern of enhancement, calcification and extra nodal extension. Three arterial phase radiomics features were selected and used to establish radiomics signature using LASSO regression (model 2). Model 3 was developed with LNs size, shape, degree of enhancement and radiomics signature. In both the training and validation cohort, model 3 showed the best diagnostic performance (AUC=0.965, 0.933), followed by model 2 (AUC=0.947, 0.910), and both these two models significantly outperformed model 1 (AUC=0.850, 0.846) (training cohort, Z=4.066 and 3.758, P both<0.001; validation cohort, Z=2.871 and 1.998, P=0.017 and 0.042) respectively. Conclusion:The radiomics model based on arterial-venous mixed images derived from DECT data can realize effective diagnosis of LNs metastasis in patients with PTC; and the combination model of radiomics signature with CT image features can further improve the diagnostic accuracy.

The human microbiome project (HMP) promoted further understanding of human oral microbes. However, research on the human oral microbiota has not made as much progress as research on the gut microbiota. Currently, the causal relationship between the oral microbiota and oral diseases remains unclear, and little is known about the link between the oral microbiota and human systemic diseases. To further understand the contribution of the oral microbiota in oral diseases and systemic diseases, a Human Oral Microbiome Database (HOMD) was established in the US. The HOMD includes 619 taxa in 13 phyla, and most of the microorganisms are from American populations. Due to individual differences in the microbiome, the HOMD does not reflect the Chinese oral microbial status. Herein, we established a new oral microbiome database-the Oral Microbiome Bank of China (OMBC, http://www.sklod.org/ombc ). Currently, the OMBC includes information on 289 bacterial strains and 720 clinical samples from the Chinese population, along with lab and clinical information. The OMBC is the first curated description of a Chinese-associated microbiome; it provides tools for use in investigating the role of the oral microbiome in health and diseases, and will give the community abundant data and strain information for future oral microbial studies.
China ; Humans ; Microbiota ; Mouth ; microbiology