Pathogenetics of alveolar capillary dysplasia with misalignment of pulmonary veins.

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal lung developmental disorder caused by heterozygous point mutations or genomic deletion copy-number variants (CNVs) of FOXF1 or its upstream enhancer involving fetal lung-expressed long noncoding RNA genes LINC01081 and LINC01082. Using custom-designed array comparative genomic hybridization, Sanger sequencing, whole exome sequencing (WES), and bioinformatic analyses, we studied 22 new unrelated families (20 postnatal and two prenatal) with clinically diagnosed ACDMPV. We describe novel deletion CNVs at the FOXF1 locus in 13 unrelated ACDMPV patients. Together with the previously reported cases, all 31 genomic deletions in 16q24.1, pathogenic for ACDMPV, for which parental origin was determined, arose de novo with 30 of them occurring on the maternally inherited chromosome 16, strongly implicating genomic imprinting of the FOXF1 locus in human lungs. Surprisingly, we have also identified four ACDMPV families with the pathogenic variants in the FOXF1 locus that arose on paternal chromosome 16. Interestingly, a combination of the severe cardiac defects, including hypoplastic left heart, and single umbilical artery were observed only in children with deletion CNVs involving FOXF1 and its upstream enhancer. Our data demonstrate that genomic imprinting at 16q24.1 plays an important role in variable ACDMPV manifestation likely through long-range regulation of FOXF1 expression, and may be also responsible for key phenotypic features of maternal uniparental disomy 16. Moreover, in one family, WES revealed a de novo missense variant in ESRP1, potentially implicating FGF signaling in the etiology of ACDMPV

A geotechnical investigation of marine deposits in a nearshore seabed for land reclamation

The properties of marine deposits in a nearshore seabed at a land reclamation site in Hong Kong were investigated. A variety of laboratory and in situ tests were conducted to define the geotechnical and consolidation characteristics of the marine deposits. The reliability and applicability of various laboratory and in situ testing techniques in evaluating the coefficient of consolidation were examined. Coefficients of consolidation were calculated from conventional oedometer tests, large-diameter (250 mm) Rowe cell tests, field permeability tests, and piezocone dissipation tests. Three techniques were adopted to evaluate the horizontal coefficient of consolidation ch from the results of in situ piezocone dissipation tests. Results from in situ pore pressure dissipation tests are compared with those from large-diameter Rowe cell tests performed on undisturbed samples under both vertical and horizontal drainage conditions and in situ permeability tests to provide reference values of the vertical coefficient of consolidation cv and ch. The engineering implications, particularly those related to land reclamation work in the nearshore environment, of various laboratory and field tests are discussed. </jats:p

Early detection of HCC by routine blood based-AI

Background Early detection of hepatocellular carcinoma (HCC) remained challenging because of the limited sensitivity of alpha-fetoprotein (aFP) test and inconclusive ultrasonography in cirrhotic liver, limiting timely curative interventions. Building on our previous research on constructing an AI classifier based on routine blood tests for HCC detection (sensitivity: 0.80, specificity: 0.81 AUROC: 0.894 at cutoff 0.43, trained by 220k patients data), our goal is to investigate whether the AI blood signature can be detected up to 1 year before clinical diagnosis. Methods Collection Laboratory. HCC and CLD patients were identified with ICD codes, antiviral drug history, virology test and radiology reports. Decompensated cases were excluded. Blood records (CBC, LFT, RFT, Clotting profile) within one year prior to the diagnosis of HCC were retrieved at intervals (1-3 months, 3-6 months, 6-9 months, and 9-12 months before diagnosis). The AI classifier was applied, and risk score was calculated. The test performance and the lead time created by early AI diagnosis were calculated. The AI performance was compared with AFP (using cutoff at 20 ng/mL). Results The cohort included 13,703 patients (3,415 HCC and 10,288 CLD patients). The screening sensitivity at above stated intervals with cutoff score of 0.43 is 61.3%, 50.1%, 44.2%, and 41.3% respectively, while ensuring specificity over 75%. The mean lead-time for detection in HCC patients is 167 days ahead of diagnosis. Routine blood test was 5 times more commonly used than aFP during the surveillance phase. The described performance of routine blood AI is superior to that of aFP, which remained under 45% in all intervals. Conclusions The study findings reveal that the AI routine blood signature exists up to 1 year before the clinical diagnosis of HCC and creates a meaningful window for timely early intervention to improve cure. The AI routine blood signature might advance the diagnosis of HCC in 40% of patients by one year and potentially lead to cancer mortality reduction