AIMS: We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients.
METHODS: This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula.
RESULTS: MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p
METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards were followed when conducting the systematic review. We searched Web of Science, Embase, PubMed, Cochrane Controlled Trials Register, Cochrane Library, Highwire, CBM, CNKI, VIP, and Wanfang database in May 2023 to identify studies involving Intraoperative fluoroscopy versus no fluoroscopy during posterior or posterolateral approach total hip arthroplasty. Finally, we identified 1133 patients (1145 hips) assessed in seven studies.
RESULTS: There were no significant differences in terms of acetabular cup inclination angle (ACIA, P = 0.43), ACIA within safe zone rate (P = 0.58), acetabular cup anteversion angle (ACAA, P = 0.46); ACAA within safe zone rate (P = 0.72), Combined safe zone rate (P = 0.28), dislocation rate (P = 0.64) and infection rate (P = 0.94) between two groups. Compared with the no fluoroscopy group, the intraoperative fluoroscopy group had more operation time (P
RESULTS: Here, we reported the first Oceanospirillum phage, vB_OliS_GJ44, which was assembled into a 33,786 bp linear dsDNA genome, which includes abundant tail-related and recombinant proteins. The recombinant module was highly adapted to the host, according to the tetranucleotides correlations. Genomic and morphological analyses identified vB_OliS_GJ44 as a siphovirus, however, due to the distant evolutionary relationship with any other known siphovirus, it is proposed that this virus could be classified as the type phage of a new Oceanospirivirus genus within the Siphoviridae family. vB_OliS_GJ44 showed synteny with six uncultured phages, which supports its representation in uncultured environmental viral contigs from metagenomics. Homologs of several vB_OliS_GJ44 genes have mostly been found in marine metagenomes, suggesting the prevalence of this phage genus in the oceans.
CONCLUSIONS: These results describe the first Oceanospirillum phage, vB_OliS_GJ44, that represents a novel viral cluster and exhibits interesting genetic features related to phage-host interactions and evolution. Thus, we propose a new viral genus Oceanospirivirus within the Siphoviridae family to reconcile this cluster, with vB_OliS_GJ44 as a representative member.
RESULTS: We analyzed the whole-genome deep sequencing data (~ 30×) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81 × 10- 8 - 1.33 × 10- 8, 1.0 × 10- 9 - 2.9 × 10- 9, and ~ 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples.
CONCLUSION: Our study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia.
METHODS: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P
METHODS: By using preoperative computed tomography, magnetic resonance imaging, and 3-dimensional image reconstruction, 5 critical components were assessed: the ratio of the sinus area occupied by the tumor in relation to the whole sinus area (R), the compression of the renal segmental vessels or collection system by the tumor (O), the anteroposterior relation of the tumor relative to the segmental vessels or collection system (A), the tumor diameter (D), and whether the tumor affects a solitary kidney (S) ("ROADS"). The ROADS score, indicating low, moderate, or high surgical complexity, was then used to guide surgical strategy planning, including cooling techniques, surgical approaches, and parenchyma incision techniques. A cohort of 134 patients with renal sinus tumors was treated based on their ROADS score and was retrospectively analyzed.
RESULTS: The authors successfully performed 113 nephron-sparing surgeries and 21 radical nephrectomies with a complication rate of 7.9%. During follow-up, 3 cases were classified according to surgical margin status because they lacked an intact tumor capsule. There was only 1 case of local recurrence, and there were no cases of metastasis. A high ROADS score was correlated with greater operative complexity, such as longer operation and ischemia times and higher estimated blood loss and complication rates. However, renal function and short-term oncologic outcomes were not related to the score.
CONCLUSIONS: The ROADS scoring system provides a standardized, quantitative, 3-dimensional anatomic classification to guide surgical strategy in renal sinus tumors.
METHODS: In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image.
RESULTS: The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072.
CONCLUSION: our MV-SIR model can accurately perform 3D segmentation of lung nodules with the same segmentation accuracy as the U-net model.