Preoperative Three-Dimensional Morphological Tumor Features Predict Microvascular Invasion in Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: The study was designed to evaluate microvascular invasion (MVI) using three-dimensional (3D) morphological indicators prior to surgery. MATERIALS AND METHODS: This retrospective study included 156 patients with hepatocellular carcinoma (HCC) at our hospital from 2017 to 2018. Through thin-layer CT scanning and 3D reconstruction, the tumor surface inclination angles can be quantitatively analyzed to determine the surface irregularity rate (SIR), which serves as a comprehensive assessment method for tumor irregularity based on preoperative 3D morphological evaluation. Univariate and multivariate logistic regression analyses were employed to investigate the correlation with MVI. RESULTS: The SIR was related to MVI (OR: 10.667, P < 0.001). Multivariate logistic regression analysis showed that the SIR was an independent risk factor for MVI. The area under the receiver operating characteristic curve (ROC) of prediction model composed of the morphological indicator SIR was 0.831 (95% confidence interval: 0.759-0.895). CONCLUSION: The preoperative 3D morphological indicator SIR of a tumor is an accurate predictor of MVI, providing a valuable tool in clinical decision-making.

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning.

Significance: Rapid diagnosis and analysis of human keloid scar tissues in an automated manner are essential for understanding pathogenesis and formulating treatment solutions. Aim: Our aim is to resolve the features of the extracellular matrix in human keloid scar tissues automatically for accurate diagnosis with the aid of machine learning. Approach: Multiphoton microscopy was utilized to acquire images of collagen and elastin fibers. Morphological features, histogram, and gray-level co-occurrence matrix-based texture features were obtained to produce a total of 28 features. The minimum redundancy maximum relevancy feature selection approach was implemented to rank these features and establish feature subsets, each of which was employed to build a machine learning model through the tree-based pipeline optimization tool (TPOT). Results: The feature importance ranking was obtained, and 28 feature subsets were acquired by incremental feature selection. The subset with the top 23 features was identified as the most accurate. Then stochastic gradient descent classifier optimized by the TPOT was generated with an accuracy of 96.15% in classifying normal, scar, and adjacent tissues. The area under curve of the classification results (scar versus normal and adjacent, normal versus scar and adjacent, and adjacent versus normal and scar) was 1.0, 1.0, and 0.99, respectively. Conclusions: The proposed approach has great potential for future dermatological clinical diagnosis and analysis and holds promise for the development of computer-aided systems to assist dermatologists in diagnosis and treatment.

Placental morphological features of small for gestational age preterm neonates born to mothers with pregnancy-induced hypertension.

Introduction: Small for gestational age (SGA) neonates are often born to mothers with pregnancy-induced hypertension (PIH). Here, we aimed to explore the morphometric characteristics of the placenta during the perinatal period associated with SGA risk in mothers with PIH and identify the risk factors related to SGA. Methods: The medical records of 134 neonates born between 28- and 32-weeks' gestation to PIH mothers were retrospectively analyzed. Placental morphology and umbilical cord (UC) length were compared between the SGA and appropriate for gestational age (AGA) groups. Results: The placenta of the SGA group had a shorter major (15.00 vs. 18.00 cm; z = -6.04, p < 0.01) and minor placenta axes (13.00 vs. 15.00 cm; z = -4.59, p < 0.01), lower weight (300.00 vs. 420.00 g; z = -7.21, p < 0.01), smaller volume (282.00 vs. 396.00 cm3; z = -5.00, p < 0.01), and smaller area (141.00 vs. 212.00 cm2; z = -5.96, p < 0.01) than the AGA group. The UC was significantly shorter (39.00 vs. 44.00 cm; z = -3.68, p < 0.01). Short placental major axis [p = 0.03; odds ratio (OR): 2.16; 95% confidence interval (CI): 1.84 - 2.63] and low placental weight (p < 0.01; OR: 2.68; 95% CI: 2.66 - 2.70) were independent risk factors for SGA in premature newborns of PIH mothers. Discussion: A major axis shorter than 15.5 cm or placental weight lower than 347.50 g at birth was related to a greater risk of SGA infants born to PIH mothers. As a predictor in prenatal ultrasound, the major axis is more helpful for precise prenatal pre-evaluation of vulnerable SGA preterm neonates with PIH mothers.

Deep learning-based morphological feature analysis and the prognostic association study in colon adenocarcinoma histopathological images.

Colorectal cancer (CRC) is now the third most common malignancy to cause mortality worldwide, and its prognosis is of great importance. Recent CRC prognostic prediction studies mainly focused on biomarkers, radiometric images, and end-to-end deep learning methods, while only a few works paid attention to exploring the relationship between the quantitative morphological features of patients' tissue slides and their prognosis. However, existing few works in this area suffered from the drawback of choosing the cells randomly from the whole slides, which contain the non-tumor region that lakes information about prognosis. In addition, the existing works, which tried to demonstrate their biological interpretability using patients' transcriptome data, failed to show the biological meaning closely related to cancer. In this study, we proposed and evaluated a prognostic model using morphological features of cells in the tumor region. The features were first extracted by the software CellProfiler from the tumor region selected by Eff-Unet deep learning model. Features from different regions were then averaged for each patient as their representative, and the Lasso-Cox model was used to select the prognosis-related features. The prognostic prediction model was at last constructed using the selected prognosis-related features and was evaluated through KM estimate and cross-validation. In terms of biological meaning, Gene Ontology (GO) enrichment analysis of the expressed genes that correlated with the prognostically significant features was performed to show the biological interpretability of our model.With the help of tumor segmentation, our model achieved better statistical significance and better biological interpretability compared to the results without tumor segmentation. Statistically, the Kaplan Meier (KM) estimate of our model showed that the model using features in the tumor region has a higher C-index, a lower p-value, and a better performance on cross-validation than the model without tumor segmentation. In addition, revealing the pathway of the immune escape and the spread of the tumor, the model with tumor segmentation demonstrated a biological meaning much more related to cancer immunobiology than the model without tumor segmentation. Our prognostic prediction model using quantitive morphological features from tumor regions was almost as good as the TNM tumor staging system as they had a close C-index, and our model can be combined with the TNM tumor stage system to make a better prognostic prediction. And to the best of our knowledge, the biological mechanisms in our study were the most relevant to the immune mechanism of cancer compared to the previous studies.

Automatically recognize and segment morphological features of the 3D vertebra based on topological data analysis.

BACKGROUND: For spinal surgery, exact knowledge about the shape of individual vertebra is of great importance. However, due to the complex morphological features of human vertebrae and spine, it is challenging to locate, segment automatically, and recognize the morphological features in vertebral images. Significantly, pedicle recognition is more challenging because of the particular structure. METHODS: Topological structures such as the Reeb graph could facilitate effective visualization and interactive exploration of feature-rich data. In this paper, we conducted topological data analysis on the 3D vertebra, whereby some principal morphological features of the 3D vertebra are recognized and segmented. First, a scalar field of the 3D vertebra is created in a vertebra coordinate system (VCS). Then, the Reeb graph is adopted for topological data analysis on the scalar field. Morphological features of the 3D vertebra are separated using a cycle-detect-based algorithm in the Reeb graph, and the valid pedicle region is finally generated. Pedicle morphometry is measured for surgical references. RESULTS: Experiments on the dataset from the CSI 2014 Workshop with our method show that the spinous process and vertebral body are 100% (255/255) recognized, the pedicle is 99.8% (509/510) recognized, the transverse process is 94.1% (240/255) recognized. The parameters incl. chord length and diameter of pedicle morphometry are measured and verify the efficiency of the valid pedicle region deduced from the recognized pedicle. CONCLUSION: Topological data analysis is an effective and promising automatic tool for segmenting and recognizing morphological features on the 3D vertebra. The final extracted valid pedicle region and its pedicle morphometry can provide good references for pedicle screw placement.

[Measurement of morphological features of Oncomelania hupensis shells in Yunnan Province].

OBJECTIVE: To investigate the morphological variation of Oncomelania hupensis shells in Yunnan Province, so as to provide insights into the understanding of O. hupensis genetic evolution and control. METHODS: According to the O. hupensis density, geographical location, altitude, water system and environmental type, 12 administrative villages were sampled from 10 schistosomiasis-endemic counties (districts) in 3 prefectures (cities) of Yunnan Province as snail collection sites. From December 2021 to January 2022, about 200 snails were collected from each collection site, among which thirty adult snails (6 to 7 spirals) were randomly selected from each site, and the 11 morphological indexes of snail shells were measured and subjected to cluster analysis and principal component analysis. RESULTS: Of O. hupensis snails from 12 localities of Yunnan Province, the longest shell (7.33 mm) was detected in snails from Yongle Village, Eryuan County, with the shortest (4.68 mm) in Dongyuan Village, Gucheng District, and the largest angle of apex (59.47°) was measured in snails from Caizhuang Village, Midu County, with the smallest (41.40°) in Qiandian Village, Eryuan County. The mean coefficient of variation was 9.075% among O. hupensis snails from 12 localities of Yunnan Province, with the largest coefficient of variation seen in the thickness of the labra brim (29.809%). Among O. hupensis snails from 12 localities of Yunnan Province, the mean Euclidean distance was 2.26, with the shortest Euclidean distance seen between O. hupensis snails from Qiandian Village of Eryuan County and Wuxing Village of Dali City (0.26), and the largest found between O. hupensis snails from Caizhuang Village of Midu County and Cangling Village of Chuxiong County (8.17). Cluster analysis and principal component analysis classified O. hupensis snails from 12 localities of Yunnan Province into three categories, including the O. hupensis snail samples from Caizhuang Village of Midu County, O. hupensis snail samples from Cangling Village of Chuxiong County, and O. hupensis snail samples from Qiandian Village of Eryuan County, Wuxing Village of Dali City, Yangwu Village of Yongsheng County, Xiaoqiao Village of Xiangyun County, Yongle Village of Eryuan County, Xiaocen Village of Dali City, Anding Village of Nanjian County, Dongyuan Village of Gucheng District, Lianyi Village of Heqing County, and Dianzhong Village of Weishan County. The variations in these three categories of snail samples were mainly measured in the principal component 2 related to the angle of apex and the thickness of the labra brim. CONCLUSIONS: The variations in the Euclidean distance and morphological features of shells of O. hupensis from 12 localities of Yunnan Province gradually rise with the decrease in the latitude of the collection sites. The angle of apex is an indicator for the growth of O. hupensis whorl.

Morphological features of 52 cases of breast phyllodes tumours with local recurrence.

Typical phyllodes tumours (PTs) of the breast are fibroepithelial neoplasms characterised histologically by stromal hypercellularity and leaf-like structures. However, morphological changes may be atypical in some cases, increasing the difficulty of diagnosis and the likelihood of misdiagnosis. To provide more morphological clues for pathological diagnosis of PTs, we retrospectively analysed 52 PT cases with typical morphological features after recurrence, and summarized the clinicopathological characteristics of the paired primary tumours. We found five special histological features in the primary tumours distinct from classic PTs, namely (1) PTs with epithelioid feature (three cases); (2) PTs with gland-rich feature (eight cases); (3) PTs with fibroadenoma-like feature (20 cases); (4) PTs with myxoid fibroadenoma-like feature (five cases); and (5) PTs with pseudohemangiomatoid stromal hyperplasia-like feature (four cases). All the features can exist independently, and a few cases displayed more than two distinctive features at the same time. In this cohort of recurrent PTs, all the primary tumours were absent of recognisable stromal hypercellularity and leaf-like structures that are the critical diagnostic criteria of PTs; however, they showed some other non-classic characteristics which may provide significant clues for the diagnosis of PTs. Particularly, tumours with epithelioid feature displayed high grade at earlier stages, tumours with fibroadenoma-like feature were most likely to be confused with classical fibroadenomas, and tumours with myxoid feature were prone to be neglected because of their hypocellularity.

Structural characterization and biological evaluation of a new O-acetyl-1,4-linked-ß-d-mannan possessed potential application in hydrophilic polymer materials from Dendrobium devonianum.

To explore the active polysaccharides from Dendrobium devonianum, a novel O-acetylmannan (DDP-1) with molecular weight of 117 kDa was isolated from D. devonianum. The chemical and instrumental analysis indicated that the DDP-1 was a homopolysaccharide containing a backbone chain composed of →4)-ß-d-Manp-(1 â†’ (71.4%) residue with internal →4)-2-O-acetyl-ß-d-Manp-(1 â†’ (14.2%), →4)-3-O-acetyl-ß-d-Manp-(1 â†’ (7.1%), and non-reducing end ß-d-Manp-(1 â†’ (7.3%) residues. Anticancer assay in vitro revealed that DDP-1 had anticancer activity against the growth of HepG2 and MCF-7 cancer cells. Moreover, cytokine secretion assays also presented that DDP-1 can promote cytokine production of TNF-α and IL-6 in THP-1 macrophage stimulated by PMA. Finally, the effects of isolation and purification on the microstructure of DDP-1 was studied by scanning electron microscope. The morphological features of DDP-1 indicated that DDP-1 hold high potential application in hydrophilic polymer materials.

In vitrobreast cancer model with patient-specific morphological features for personalized medicine.

In vitrocancer models that can simulate patient-specific drug responses for personalized medicine have attracted significant attention. However, the technologies used to produce such models can only recapitulate the morphological heterogeneity of human cancer tissue. Here, we developed a novel 3D technique to bioprint anin vitrobreast cancer model with patient-specific morphological features. This model can precisely mimic the cellular microstructures of heterogeneous cancer tissues and produce drug responses similar to those of human cancers. We established a bioprinting process for generating cancer cell aggregates with ductal and solid tissue microstructures that reflected the morphology of breast cancer tissues, and applied it to develop breast cancer models. The genotypic and phenotypic characteristics of the ductal and solid cancer aggregates bioprinted with human breast cancer cells (MCF7, SKBR3, MDA-MB-231) were respectively similar to those of early and advanced cancers. The bioprinted solid cancer cell aggregates showed significantly higher hypoxia (>8 times) and mesenchymal (>2-4 times) marker expressions, invasion activity (>15 times), and drug resistance than the bioprinted ductal aggregates. Co-printing the ductal and solid aggregates produced heterogeneous breast cancer tissue models that recapitulated three different stages of breast cancer tissue morphology. The bioprinted cancer tissue models representing advanced cancer were more and less resistant, respectively, to the anthracycline antibiotic doxorubicin and the hypoxia-activated prodrug tirapazamine; these were analogous to the results in human cancer. The present findings showed that cancer cell aggregates can mimic the pathological micromorphology of human breast cancer tissue and they can be bioprinted to produce breast cancer tissuein vitrothat can morphologically represent the clinical stage of cancer in individual patients.

[Morphological and molecular identification of trematode isloates from laying ducks in Nanchang City].

OBJECTIVE: To identify the species of trematodes isolated from laying ducks in Nanchang City using morphological and molecular approaches. METHODS: Trematodes were isolated from the hepatobiliary duct, gallbladder and large intestine of market-sold laying ducks in Nanchang City. Following morphological characterization, total DNA was extracted from all trematode specimens, and internal transcribed spacer region (ITS) and cytochrome C oxidase subunit 1 (Cox1) genes were amplified using PCR assay and sequenced. Sequence alignment was performed using the Blast software, and homology and phylogenetic analyses were done in the trematode isolates based on ITS and Cox1 gene sequences. RESULTS: The morphological characteristics of two trematode isolates from the large intestine of laying ducks were similar to those of Echinostoma revolutum and E. miyagawai, and the morphological characteristics of eight trematode samples isolated from the hepatobiliary duct and gallbladder of laying ducks were similar to those of Amphimerus anatis. The ITS and Cox1 gene sequences of the two trematode isolates from the large intestine of laying ducks had 99.3% and 98.9%-99.4% homology with E. miyagawai, and the phylogenetic analysis showed that two trematode isolates had the closest genetic relationship with E. miyagawai based on ITS and Cox1 gene sequences. The ITS gene sequences of eight trematode isolates from the hepatobiliary duct and gallbladder of laying ducks shared 95.1%-95.5% with Opisthorchis sudarikovi and Clonorchis sinensis, while the Cox1 gene sequences of eight trematode isolates from the hepatobiliary duct and gallbladder of laying ducks shared 86.3%-86.4% and 85.5%-85.7% with O. viverrini and O. sudarikovi. ITS gene sequence-based phylogenetic analysis showed that the duck-derived trematode isolates had the closest genetic relationship with C. sinensis, and Cox1 gene sequence-based phylogenetic analysis showed that the duck-derived trematode isolates had the closest genetic relationship with Metorchis orientalis and O. viverrini. CONCLUSIONS: The trematode isolates from the large intestine of laying ducts in Nanchang City may be E. miyagawai, and the trematode isolates from the hepatobiliary duct and gallbladder may be an unidentified trematode species of the family Opisthorchiidae.

Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study.

OBJECTIVES: To investigate the value of morphological feature and signal intensity ratio (SIR) derived from conventional magnetic resonance imaging (MRI) in distinguishing primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (aGBM). METHODS: Pathology-confirmed PCNSLs (n = 93) or aGBMs (n = 48) from three institutions were retrospectively enrolled and divided into training cohort (n = 98) and test cohort (n = 43). Morphological features and SIRs were compared between PCNSL and aGBM. Using linear discriminant analysis, multiple models were constructed with SIRs and morphological features alone or jointly, and the diagnostic performances were evaluated via receiver operating characteristic (ROC) analysis. Areas under the curves (AUCs) and accuracies (ACCs) of the models were compared with the radiologists' assessment. RESULTS: Incision sign, T2 pseudonecrosis sign, reef sign and peritumoral leukomalacia sign were associated with PCNSL (training and overall cohorts, P < 0.05). Increased T1 ratio, decreased T2 ratio and T2/T1 ratio were predictive of PCNSL (all P < 0.05). ROC analysis showed that combination of morphological features and SIRs achieved the best diagnostic performance for differentiation of PCNSL and aGBM with AUC/ACC of 0.899/0.929 for the training cohort, AUC/ACC of 0.794/0.837 for the test cohort and AUC/ACC of 0.869/0.901 for the overall cohort, respectively. Based on the overall cohort, two radiologists could distinguish PCNSL from aGBM with AUC/ACC of 0.732/0.724 for radiologist A and AUC/ACC of 0.811/0.829 for radiologist B. CONCLUSION: MRI morphological features can help differentiate PCNSL from aGBM. When combined with SIRs, the diagnostic performance was better than that of radiologists' assessment.

Morphological features of smile attractiveness and related factors influence perception and gingival aesthetic parameters.

INTRODUCTION: In addition to understanding the basic standards of a smile and patient's opinion, dentists should take into account smile aesthetics, an essential factor for optimal outcomes. This study aimed to evaluate the factors that affect the perception of an aesthetic smile and determine its morphological characteristics and measure the gingival aesthetic parameters. METHODS: In all, 200 Vietnamese aged 18-35 years were recruited to have their spontaneous smiles captured. These smile images were assessed by 50 laypersons and 50 dentists using a visual analogue scale measurement. The images were analysed to evaluate perceptions of evaluators, determine smile attractiveness, and measure gingival aesthetics. RESULTS: The difference in the judgements of laypersons and dentists, males and females, and laypersons aged 18-25 and 26-35 years were nonsignificant. High or average anterior smile line, parallel smile arc, upward upper lip curvature, second premolars as the posterior-most teeth displayed, smile index of 5.23-5.63, and dynamic smile symmetry of 1 were scored highly on smile attractiveness. The following maxillary gingival aesthetic parameters were preferred: gingival zenith (GZ) of the canine 0.72-0.75 mm apical to the GZ of the central incisor; GZ of the lateral incisor 0.66 mm coronal to the gingival line; gingival line angle of ∼87°; for the central incisor, lateral incisor, and canines, distance from the GZ to the long axis of 1, 0.4, and 0 mm, respectively; interdental papilla height of 4.25, 3.60, and 3.85 mm, respectively; ratio of the distance from the GZ and the interdental papilla tip to the incisal edge of ∼1.74-1.77 mm. CONCLUSIONS: Factors including profession, gender, and age of evaluators had almost no impact on their perception of aesthetics. Smile attractiveness characteristics and gingival aesthetic parameters have clinical applicability for patient care.

Aortic arch type, a novel morphological indicator and the risk for acute type B aortic dissection.

OBJECTIVES: Aortic arch type is a readily recognizable and obtainable morphological feature of the aorta that does not require complex measurements. The goal of this study was to evaluate whether aortic arch type is a comparable and alternative morphological parameter for predicting acute type B aortic dissection (aTBAD) by comparing the prognostic value of the aortic arch type with that of other morphological parameters such as aortic length, angulation and tortuosity index. METHODS: The patients with aTBAD (n = 216) were matched 1:1 with a control group (n = 263) by propensity score matching. The morphological data of the ascending aorta and the aortic arch, which included diameter, length, angulation and tortuosity index, were collected on a three-dimensional aortic model using 3mensio Vascular software. The aortic arch type was identified by the vertical distance from the origin of the brachiocephalic trunk to the top of the arch. The binary logistic regression models were analysed to determine the independent geometric variables related to the aTBAD. The nonparametric approach was performed to assess whether there were statistical differences between the area under the receiver operating characteristic curves (AUC) of the models. RESULTS: After propensity score matching, 151 matched pairs of patients were selected. The diameters at the sinotubular junction and the mid-ascending aorta, the ascending aorta length and the ascending aorta angulation in the aTBAD group were significantly greater than those of the controls. Compared with the control group, the diameters at the proximal aortic arch, mid-aortic arch and distal aortic arch, the angulation and the tortuosity index of the aortic arch were significantly greater in the aTBAD group. The proportion of the type III arch in the patients with aTBAD is higher than that of the type I arch and the type II arch (χ2 = 70.187; P < 0.001). Binary logistic regression analysis showed that the diameter at the mid-aortic arch, the ascending aorta length, the aortic arch angulation and the tortuosity index were independently related to the aTBAD with an AUC value of 0.887. Another binary logistic regression analysis indicated that the diameter at the mid-aortic arch and the aortic arch type were independent correlative variables associated with the aTBAD with an AUC of 0.874. No significant difference was observed in the prognostic value of receiver operating characteristic curves between the 2 models (P = 0.716). CONCLUSIONS: The type III arch, which has the characteristics of aortic elongation, incremental angulation and tortuosity index, is a comparable and alternative identifier for patients at high risk for aTBAD.

Measurement of morphological features of Oncomelania hupensis shells in Yunnan Province / 中国血吸虫病防治杂志

Objective To investigate the morphological variation of Oncomelania hupensis shells in Yunnan Province, so as to provide insights into the understanding of O. hupensis genetic evolution and control. Methods According to the O. hupensis density, geographical location, altitude, water system and environmental type, 12 administrative villages were sampled from 10 schistosomiasis-endemic counties (districts) in 3 prefectures (cities) of Yunnan Province as snail collection sites. From December 2021 to January 2022, about 200 snails were collected from each collection site, among which thirty adult snails (6 to 7 spirals) were randomly selected from each site, and the 11 morphological indexes of snail shells were measured and subjected to cluster analysis and principal component analysis. Results Of O. hupensis snails from 12 localities of Yunnan Province, the longest shell (7.33 mm) was detected in snails from Yongle Village, Eryuan County, with the shortest (4.68 mm) in Dongyuan Village, Gucheng District, and the largest angle of apex (59.47°) was measured in snails from Caizhuang Village, Midu County, with the smallest (41.40°) in Qiandian Village, Eryuan County. The mean coefficient of variation was 9.075% among O. hupensis snails from 12 localities of Yunnan Province, with the largest coefficient of variation seen in the thickness of the labra brim (29.809%). Among O. hupensis snails from 12 localities of Yunnan Province, the mean Euclidean distance was 2.26, with the shortest Euclidean distance seen between O. hupensis snails from Qiandian Village of Eryuan County and Wuxing Village of Dali City (0.26), and the largest found between O. hupensis snails from Caizhuang Village of Midu County and Cangling Village of Chuxiong County (8.17). Cluster analysis and principal component analysis classified O. hupensis snails from 12 localities of Yunnan Province into three categories, including the O. hupensis snail samples from Caizhuang Village of Midu County, O. hupensis snail samples from Cangling Village of Chuxiong County, and O. hupensis snail samples from Qiandian Village of Eryuan County, Wuxing Village of Dali City, Yangwu Village of Yongsheng County, Xiaoqiao Village of Xiangyun County, Yongle Village of Eryuan County, Xiaocen Village of Dali City, Anding Village of Nanjian County, Dongyuan Village of Gucheng District, Lianyi Village of Heqing County, and Dianzhong Village of Weishan County. The variations in these three categories of snail samples were mainly measured in the principal component 2 related to the angle of apex and the thickness of the labra brim. Conclusions The variations in the Euclidean distance and morphological features of shells of O. hupensis from 12 localities of Yunnan Province gradually rise with the decrease in the latitude of the collection sites. The angle of apex is an indicator for the growth of O. hupensis whorl.

Morphological and molecular identification of trematode isloates from laying ducks in Nanchang City / 中国血吸虫病防治杂志

Objective To identify the species of trematodes isolated from laying ducks in Nanchang City using morphological and molecular approaches. Methods Trematodes were isolated from the hepatobiliary duct, gallbladder and large intestine of market-sold laying ducks in Nanchang City. Following morphological characterization, total DNA was extracted from all trematode specimens, and internal transcribed spacer region (ITS) and cytochrome C oxidase subunit 1 (Cox1) genes were amplified using PCR assay and sequenced. Sequence alignment was performed using the Blast software, and homology and phylogenetic analyses were done in the trematode isolates based on ITS and Cox1 gene sequences. Results The morphological characteristics of two trematode isolates from the large intestine of laying ducks were similar to those of Echinostoma revolutum and E. miyagawai, and the morphological characteristics of eight trematode samples isolated from the hepatobiliary duct and gallbladder of laying ducks were similar to those of Amphimerus anatis. The ITS and Cox1 gene sequences of the two trematode isolates from the large intestine of laying ducks had 99.3% and 98.9%-99.4% homology with E. miyagawai, and the phylogenetic analysis showed that two trematode isolates had the closest genetic relationship with E. miyagawai based on ITS and Cox1 gene sequences. The ITS gene sequences of eight trematode isolates from the hepatobiliary duct and gallbladder of laying ducks shared 95.1%-95.5% with Opisthorchis sudarikovi and Clonorchis sinensis, while the Cox1 gene sequences of eight trematode isolates from the hepatobiliary duct and gallbladder of laying ducks shared 86.3%-86.4% and 85.5%-85.7% with O. viverrini and O. sudarikovi. ITS gene sequence-based phylogenetic analysis showed that the duck-derived trematode isolates had the closest genetic relationship with C. sinensis, and Cox1 gene sequence-based phylogenetic analysis showed that the duck-derived trematode isolates had the closest genetic relationship with Metorchis orientalis and O. viverrini. Conclusions The trematode isolates from the large intestine of laying ducts in Nanchang City may be E. miyagawai, and the trematode isolates from the hepatobiliary duct and gallbladder may be an unidentified trematode species of the family Opisthorchiidae.

A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours.

BACKGROUND: We sought to evaluate the performance of a computed tomography (CT)-based radiomics nomogram we devised in distinguishing benign from malignant bone tumours. METHODS: Two hundred and six patients with bone tumours were spilt into two groups: a training set (n = 155) and a validation set (n = 51). A feature extraction process based on 3D Slicer software was used to extract the radiomics features from unenhanced CT images, and least absolute shrinkage and selection operator logistic regression was used to calculate the radiomic score to generate a radiomics signature. A clinical model comprised demographics and CT features. A radiomics nomogram combined with the clinical model and the radiomics signature was constructed. The performance of the three models was comprehensively evaluated from three aspects: identification ability, accuracy, and clinical value, allowing for generation of an optimal prediction model. RESULTS: The radiomics nomogram comprised clinical and radiomics signature features. The nomogram model displayed good performance in training and validation sets with areas under the curve of 0.917 and 0.823, respectively. The areas under the curve, decision curve analysis, and net reclassification improvement showed that the radiomics nomogram model could obtain better diagnostic performance than the clinical model and achieve greater clinical net benefits than the clinical and radiomics signature models alone. CONCLUSIONS: We constructed a combined nomogram comprising a clinical model and radiomics signature as a noninvasive preoperative prediction method to distinguish between benign and malignant bone tumours and assist treatment planning.

Vitreomacular Interface Abnormalities in Myopic Foveoschisis: Correlation With Morphological Features and Outcome of Vitrectomy.

Purpose: To compare the morphologic characteristics and response to surgery of myopic foveoschisis (MF) with different patterns of vitreomacular interface abnormalities (VMIAs). Methods: In this observational case series, 158 eyes of 121 MF patients with epiretinal membrane (ERM) or vitreomacular traction (VMT) based on optical coherence tomography (OCT) were enrolled. All the eyes were divided into two groups by the pattern of VMIAs: ERM and VMT group. Sixty-one eyes underwent pars plana vitrectomy (PPV) and were followed up for at least 6 months. The morphologic characteristics based on OCT and the surgical outcome were evaluated. Outcome: ERM and VMT were found in 47.47 and 52.53% of the cases, respectively. A higher rate of foveal detachment (61.4 vs. 26.7%; p < 0.001) and a higher rate of outer lamellar macular hole (45.8 vs. 21.3%; p = 0.001) were detected in the eyes with VMT compared with those with ERM. In contrast, a lower rate of inner lamellar macular hole (28.9 vs. 60.0%; p = 0.001) was detected in the eyes with VMT compared with those with ERM. The disruption of the external limiting membrane (ELM) was more common in the eyes with VMT than in those with ERM (45.8 vs. 21.3%; p = 0.001). PPV was performed in 61 eyes with a mean follow-up time of 23.55 ± 19.92 months. After surgery, anatomical resolution was achieved in 51 eyes (83.6%). At the final visit, the mean central foveal thickness (CFT) decreased significantly from 547.83 to 118.74 µm, and the mean LogMAR BCVA improved significantly from 0.92 to 0.57. The VMT group was associated with a higher proportion of eyes with visual acuity improvement postoperatively (p = 0.02) and had more a decrease of CFT (P = 0.007) compared with the ERM group. Conclusion: In the eyes with MF, outer retinal lesions occurred more frequently in the eyes with VMT, whereas inner retinal lesions occurred more frequently in the eyes with ERM. Tangential force generated by ERM may act as a causative factor for the inner retinal lesions in MF, and inward-directed force resulting from VMT may act as a causative factor for outer retinal lesions in MF.

Noise robust automatic heartbeat classification system using support vector machine and conditional spectral moment.

Heartbeat classification is central to the detection of the arrhythmia. For the effective heartbeat classification, the noise-robust features are very significant. In this work, we have proposed a noise-robust support vector machine (SVM) based heartbeat classifier. The proposed classifier utilizes a novel noise-robust morphological feature which is based on the conditional spectral moment (CSM) of the heartbeat. In addition to the proposed CSM feature, we have also employed the existing RR interval, the wavelets, and the higher-order statistics (HOS) based temporal and morphological feature sets. The noise-robustness test of the proposed CSM and all the studied feature sets is performed for the SVM based heartbeat classifier. Further, we have studied the significance of combining these temporal and morphological features on the final classification performance. For this purpose, the individual SVMs were trained for each of the feature set. The final classification is based on the ensemble of these individual SVMs. Various combining scheme such as sum, majority, and product rules are employed to ensemble the result of the individually trained SVMs. The experimental results show the noise-robustness of the proposed CSM feature. The proposed classifier gives improved overall performance compared to the existing heartbeat classification systems.

[Characterization of Echinostoma miyagawai in domestic ducks in Wuhu City].

OBJECTIVE: To investigate the morphological characteristics of Echinostoma miyagawai in domestic ducks in Wuhu area, and to explore the feasibility of the cytochrome oxidase subunit-1 (Cox1) gene as a molecular marker for the identification of E. miyagawai. METHODS: E. miyagawai was isolated from free-ranged domestic ducks in Wuhu area, and the parasites were stained and identified. In addition, the mitochondrial Cox1 gene of E. miyagawai was amplified using a PCR assay, and the amplification product was sequenced and aligned with the GenBank database to yield the homology for the identification of parasite species in combination with morphological findings. Intra-species comparison was done based on the Cox1 gene sequence. RESULTS: The prevalence of E. miyagawai infection was 16.67% in domestic ducks in Wuhu area, and the adult E. miyagawai was 6.6 to 13.2 mm in length. The size of the E. miyagawai Cox1 gene was approximately 660 bp, which had a 99.68% homology to the E. miyagawai accessed in GenBank. The morphological findings were in agreement with molecular identification. CONCLUSIONS: E. miyagawai infection is common in domestic ducks in Wuhu area, and the mitochondrial Cox1 gene is a feasible marker of intra- and inter-species molecular identification of Echinostoma.

Rapid identification of chrysanthemum teas by computer vision and deep learning.

Seven commercial Chinese chrysanthemum tea products were classified by computer vision combined with machine learning algorithms. Without the need of building any specific hardware, the image acquisition was achieved in two computer vision approaches. In the first approach, a series of multivariate classification models were built after morphological feature extraction of the image. The best prediction accuracies when classifying flowering stages and tea types were respectively 90% and 63%. In comparison, the deep neural network was applied directly on the raw image, yielded 96% and 89% correct identifications when classifying flowering stage and tea type, respectively. The model can be applied for rapid and automatic quality determination of teas and other related foods. The result indicated that computer vision, especially when combined with deep learning or other machine learning techniques can be a convenient and versatile method in the evaluation of food quality.