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The manual segmentation of retinal layers from OCT scan images is time-consuming and costly. The deep learning approach has potential for the automatic delineation of retinal layers to significantly reduce the burden of human graders. In this study, we compared deep learning model (DLM) segmentation with manual correction (DLM-MC) to conventional manual grading (MG) for the measurements of the photoreceptor ellipsoid zone (EZ) area and outer segment (OS) volume in retinitis pigmentosa (RP) to assess whether DLM-MC can be a new gold standard for retinal layer segmentation and for the measurement of retinal layer metrics. Ninety-six high-speed 9 mm 31-line volume scans obtained from 48 patients with RPGR-associated XLRP were selected based on the following criteria: the presence of an EZ band within the scan limit and a detectable EZ in at least three B-scans in a volume scan. All the B-scan images in each volume scan were manually segmented for the EZ and proximal retinal pigment epithelium (pRPE) by two experienced human graders to serve as the ground truth for comparison. The test volume scans were also segmented by a DLM and then manually corrected for EZ and pRPE by the same two graders to obtain DLM-MC segmentation. The EZ area and OS volume were determined by interpolating the discrete two-dimensional B-scan EZ-pRPE layer over the scan area. Dice similarity, Bland–Altman analysis, correlation, and linear regression analyses were conducted to assess the agreement between DLM-MC and MG for the EZ area and OS volume measurements. For the EZ area, the overall mean dice score (SD) between DLM-MC and MG was 0.8524 (0.0821), which was comparable to 0.8417 (0.1111) between two MGs. For the EZ area > 1 mm2, the average dice score increased to 0.8799 (0.0614). When comparing DLM-MC to MG, the Bland–Altman plots revealed a mean difference (SE) of 0.0132 (0.0953) mm2 and a coefficient of repeatability (CoR) of 1.8303 mm2 for the EZ area and a mean difference (SE) of 0.0080 (0.0020) mm3 and a CoR of 0.0381 mm3 for the OS volume. The correlation coefficients (95% CI) were 0.9928 (0.9892–0.9952) and 0.9938 (0.9906–0.9958) for the EZ area and OS volume, respectively. The linear regression slopes (95% CI) were 0.9598 (0.9399–0.9797) and 1.0104 (0.9909–1.0298), respectively. The results from this study suggest that the manual correction of deep learning model segmentation can generate EZ area and OS volume measurements in excellent agreement with those of conventional manual grading in RP. Because DLM-MC is more efficient for retinal layer segmentation from OCT scan images, it has the potential to reduce the burden of human graders in obtaining quantitative measurements of biomarkers for assessing disease progression and treatment outcomes in RP.

A microfluidics approach that links short sequence reads enables haplotype construction and complex variation identification from tiny amounts of input DNA. Haplotyping of human chromosomes is a prerequisite for cataloguing the full repertoire of genetic variation. We present a microfluidics-based, linked-read sequencing technology that can phase and haplotype germline and cancer genomes using nanograms of input DNA. This high-throughput platform prepares barcoded libraries for short-read sequencing and computationally reconstructs long-range haplotype and structural variant information. We generate haplotype blocks in a nuclear trio that are concordant with expected inheritance patterns and phase a set of structural variants. We also resolve the structure of the EML4 - ALK gene fusion in the NCI-H2228 cancer cell line using phased exome sequencing. Finally, we assign genetic aberrations to specific megabase-scale haplotypes generated from whole-genome sequencing of a primary colorectal adenocarcinoma. This approach resolves haplotype information using up to 100 times less genomic DNA than some methods and enables the accurate detection of structural variants.

A subset of patients undergoing total knee arthroplasty (TKA) for knee osteoarthritis develop debilitating knee stiffness (reduced range of motion) for poorly understood reasons. Dysregulated inflammatory and immune responses to surgery correlate with reduced surgical outcomes, but the dysregulated gene signatures in patients with stiffness after TKA are poorly defined. As a consequence, we are limited in our ability to identify patients at risk of developing poor surgical outcomes and develop preventative approaches. In this pilot study we aimed to identify perioperative blood gene signatures in patients undergoing TKA for knee osteoarthritis and its association with early surgical outcomes, specifically knee range of motion. To do this, we integrated clinical outcomes collected at 6 weeks after surgery with transcriptomics analyses in blood samples collected immediately before surgery and at 24 h after surgery. We found that patients with stiffness at 6 weeks after surgery have a more variable and attenuated circulating gene expression response immediately after surgery. Our results suggest that patients with stiffness following TKA may have distinct gene expression signatures detectable in peripheral blood in the immediate postoperative period.

Background. Existing severity assessment tools, such as the pneumonia severity index (PSI) and CURB-65 (tool based on confusion, urea level, respiratory rate, blood pressure, and age <65 years), predict 30-day mortality in community-acquired pneumonia (CAP) and have limited ability to predict which patients will require intensive respiratory or vasopressor support (IRVS). Methods. The Australian CAP Study (ACAPS) was a prospective study of 882 episodes in which each patient had a detailed assessment of severity features, etiology, and treatment outcomes. Multivariate logistic regression was performed to identify features at initial assessment that were associated with receipt of IRVS. These results were converted into a simple points-based severity tool that was validated in 5 external databases, totaling 7464 patients. Results. In ACAPS, 10.3% of patients received IRVS, and the 30-day mortality rate was 5.7%. The features statistically significantly associated with receipt of IRVS were low systolic blood pressure (2 points), multilobar chest radiography involvement (1 point), low albumin level (1 point), high respiratory rate (1 point), tachycardia (1 point), confusion (1 point), poor oxygenation (2 points), and low arterial pH (2 points): SMART-COP. A SMART-COP score of <3 points identified 92% of patients who received IRVS, including 84% of patients who did not need immediate admission to the intensive care unit. Accuracy was also high in the 5 validation databases. Sensitivities of PSI and CURB-65 for identifying the need for IRVS were 74% and 39%, respectively. Conclusions. SMART-COP is a simple, practical clinical tool for accurately predicting the need for IRVS that is likely to assist clinicians in determining CAP severity.

Background Lymphoma is a malignancy of lymphocytes and lymphoid tissues comprising a heterogeneous group of diseases, with up to 80 entities now described. Lymphoma is the 6 th most common cancer in Australia, affecting patients of all ages, with rising incidence rates. With the proliferation of efficacious novel agents, therapeutic strategies are increasingly diverse and survival is improving. There is a clear need for contemporary robust and detailed data on diagnostic, investigational and management strategies for this disease in Australia, New Zealand and worldwide, to inform and benchmark local and international standards of care. Clinical quality registries can provide these data, and support development of strategies to address variations in management, including serving as platforms for clinical trials and other research activities. The Lymphoma and Related Diseases Registry (LaRDR) was developed to capture details of patient demographics, disease characteristics, and management throughout their disease course and therapy and to develop outcome benchmarks nationally and internationally for lymphoma. This report describes the aims, development and implementation of the LaRDR, as well as challenges addressed in the process. Methods The LaRDR was established in 2016 as a multicentre, collaborative project at sites across Australia with a secure online database which collects prospective data on patients with a new diagnosis of lymphoma or chronic lymphocytic leukaemia (CLL). LaRDR development required multidisciplinary participation including specialist haematology, information technology, and biostatistical support, as well as secure funding. Here we describe the database development, data entry, ethics approval process, registry governance and support for participating sites and the coordinating centre. Results To date more than 5,300 patients have been enrolled from 28 sites in Australia and New Zealand. Multiple challenges arose during the development, which we describe, along with approaches used to overcome them. Several confirmed international collaborations are now in place, and the registry is providing valuable data for clinicians, researchers, industry and government, including through presentations of results at major national and international conferences. Conclusion Challenges in establishing the LaRDR have been successfully overcome and the registry is now a valuable resource for lymphoma clinicians, researchers, health economists and others in Australia, New Zealand and globally.

Background. Available data on the etiology of community-acquired pneumonia (CAP) in Australia are very limited. Local treatment guidelines promote the use of combination therapy with agents such as penicillin or amoxycillin combined with either doxycycline or a macrolide. Methods. The Australian CAP Study (ACAPS) was a prospective, multicenter study of 885 episodes of CAP in which all patients underwent detailed assessment for bacterial and viral pathogens (cultures, urinary antigen testing, serological methods, and polymerase chain reaction). Antibiotic agents and relevant clinical outcomes were recorded. Results. The etiology was identified in 404 (45.6%) of 885 episodes, with the most frequent causes being Streptococcus pneumoniae (14%), Mycoplasma pneumoniae (9%), and respiratory viruses (15%; influenza, picornavirus, respiratory syncytial virus, parainfluenza virus, and adenovirus). Antibiotic-resistant pathogens were rare: only 5.4% of patients had an infection for which therapy with penicillin plus doxycycline would potentially fail. Concordance with local antibiotic recommendations was high (82.4%), with the most commonly prescribed regimens being a penicillin plus either doxycycline or a macrolide (55.8%) or ceftriaxone plus either doxycycline or a macrolide (36.8%). The 30-day mortality rate was 5.6% (50 of 885 episodes), and mechanical ventilation or vasopressor support were required in 94 episodes (10.6%). Outcomes were not compromised by receipt of narrower-spectrum β-lactams, and they did not differ on the basis of whether a pathogen was identified. Conclusions. The vast majority of patients with CAP can be treated successfully with narrow-spectrum β-lactam treatment, such as penicillin combined with doxycycline or a macrolide. Greater use of such therapy could potentially reduce the emergence of antibiotic resistance among common bacterial pathogens.

Background: Innervation of blood vessels shows inter-species variability. There are few studies on the innervation of human vessels; thus, healthy mesenteric vessels were studied to identify the expression of immunomarkers and the morphology of sympathetic innervation as the basis for a study of mesenteric vessels in inflammatory bowel disease. Methods and Results: Electron microscopy studies examined the relationships of nerves to smooth muscle cells. In veins, nerves were distributed throughout the medial smooth muscle coat, often in close apposition (50 nm) to smooth muscle cells. In arteries, nerves were located at the adventitial-medial border, few closer than 2,000 nm to smooth muscle cells, often with interposing connective tissue and Schwann cell processes. There was a significantly greater nerve density in veins than in arteries (227 vs. 41 mm 2 ; p = 0.03). Immunohistochemical studies revealed the presence of sympathetic and sensory-motor nerves in arteries and veins. Conclusions: It is suggested that in humans with an upright stance, the mesenteric venous system plays a particularly important role in controlling mesenteric capacitance, which is reflected by their dense innervation. It is speculated that transmitters released from perivascular nerves supplying the human mesenteric arteries may play a long-term (trophic) role in addition to short-term signalling roles.