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"Lim, David"
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Network data mining and analysis
\"Consider an online social networking site with millions of members in which members have the opportunity to befriend one another, send messages to each other, and post content on the site. Facebook, LinkedIn, and Twitter are examples of such sites. To make sense of data from these sites, we resort to social media mining to answer the following questions: 1. What are social communities in bipartite graphs and signed graphs? 2. How robust are the networks? How can we apply the robustness of networks? 3. How can we find identical social users across heterogeneous social networks? Social media shatters the boundaries between the real world and the virtual world. We can now integrate social theories with computational methods to study how individuals interact with each other and how social communities form in bipartite and signed networks. The uniqueness of social media data calls for novel data mining techniques that can effectively handle user generated content with rich social relations. The study and development of these new techniques are under the purview of social media mining, an emerging discipline under the umbrella of data mining. Social Media Mining is the process of representing, analyzing, and extracting actionable patterns from social media data\"-- Provided by publisher.
Book
Prediction models used in the progression of chronic kidney disease: A scoping review
To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD).
Scoping review.
Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022.
All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression.
Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications.
From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models.
Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.
Journal Article
Isolation and Evaluation of Oil-Producing Microalgae from Subtropical Coastal and Brackish Waters
Microalgae have been widely reported as a promising source of biofuels, mainly based on their high areal productivity of biomass and lipids as triacylglycerides and the possibility for cultivation on non-arable land. The isolation and selection of suitable strains that are robust and display high growth and lipid accumulation rates is an important prerequisite for their successful cultivation as a bioenergy source, a process that can be compared to the initial selection and domestication of agricultural crops. We developed standard protocols for the isolation and cultivation for a range of marine and brackish microalgae. By comparing growth rates and lipid productivity, we assessed the potential of subtropical coastal and brackish microalgae for the production of biodiesel and other oil-based bioproducts. This study identified Nannochloropsis sp., Dunaniella salina and new isolates of Chlorella sp. and Tetraselmis sp. as suitable candidates for a multiple-product algae crop. We conclude that subtropical coastal microalgae display a variety of fatty acid profiles that offer a wide scope for several oil-based bioproducts, including biodiesel and omega-3 fatty acids. A biorefinery approach for microalgae would make economical production more feasible but challenges remain for efficient harvesting and extraction processes for some species.
Journal Article
Microalgal biofactories: a promising approach towards sustainable omega-3 fatty acid production
Omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) provide significant health benefits and this has led to an increased consumption as dietary supplements. Omega-3 fatty acids EPA and DHA are found in animals, transgenic plants, fungi and many microorganisms but are typically extracted from fatty fish, putting additional pressures on global fish stocks. As primary producers, many marine microalgae are rich in EPA (C20:5) and DHA (C22:6) and present a promising source of omega-3 fatty acids. Several heterotrophic microalgae have been used as biofactories for omega-3 fatty acids commercially, but a strong interest in autotrophic microalgae has emerged in recent years as microalgae are being developed as biofuel crops. This paper provides an overview of microalgal biotechnology and production platforms for the development of omega-3 fatty acids EPA and DHA. It refers to implications in current biotechnological uses of microalgae as aquaculture feed and future biofuel crops and explores potential applications of metabolic engineering and selective breeding to accumulate large amounts of omega-3 fatty acids in autotrophic microalgae.
Journal Article
Approach to the Patient With Suspected Silver-Russell Syndrome
Abstract
Silver-Russell syndrome (SRS) is a clinical diagnosis requiring the fulfillment of ≥ 4/6 Netchine-Harbison Clinical Scoring System (NH-CSS) criteria. A score of ≥ 4/6 NH-CSS (or ≥ 3/6 with strong clinical suspicion) warrants (epi)genetic confirmation, identifiable in ∼60% patients. The approach to the investigation and diagnosis of SRS is detailed in the only international consensus guidance, published in 2016. In the intervening years, the clinical, biochemical, and (epi)genetic characteristics of SRS have rapidly expanded, largely attributable to advancing molecular genetic techniques and a greater awareness of related disorders. The most common etiologies of SRS remain loss of methylation of chromosome 11p15 (11p15LOM) and maternal uniparental disomy of chromosome 7 (upd(7)mat). Rarer causes of SRS include monogenic pathogenic variants in imprinted (CDKN1C and IGF2) and non-imprinted (PLAG1 and HMGA2) genes. Although the age-specific NH-CSS can identify more common molecular causes of SRS, its use in identifying monogenic causes is unclear. Preliminary data suggest that NH-CSS is poor at identifying many of these cases. Additionally, there has been increased recognition of conditions with phenotypes overlapping with SRS that may fulfill NH-CSS criteria but have distinct genetic etiologies and disease trajectories. This group of conditions is frequently overlooked and under-investigated, leading to no or delayed diagnosis. Like SRS, these conditions are multisystemic disorders requiring multidisciplinary care and tailored management strategies. Early identification is crucial to improve outcomes and reduce the major burden of the diagnostic odyssey for patients and families. This article aims to enable clinicians to identify key features of rarer causes of SRS and conditions with overlapping phenotypes, show a logical approach to the molecular investigation, and highlight the differences in clinical management strategies.
Journal Article
The risk of contralateral breast cancer: a SEER-based analysis
Background
We sought to estimate the annual risk and 25-year cumulative risk of contralateral breast cancer among women with stage 0–III unilateral breast cancer.
Methods
We identified 812,851 women with unilateral breast cancer diagnosed between 1990 and 2015 in the SEER database and followed them for contralateral breast cancer for up to 25 years. Women with a known bilateral mastectomy were excluded. We calculated the annual risk of contralateral breast cancer by age at diagnosis, by time since diagnosis and by current age. We compared risks by ductal carcinoma in situ (DCIS) versus invasive disease, by race and by oestrogen receptor (ER) status of the first cancer.
Results
There were 25,958 cases of contralateral invasive breast cancer diagnosed (3.2% of all patients). The annual risk of contralateral breast cancer over the 25-year follow-up period was 0.37% and the 25-year actuarial risk of contralateral invasive breast cancer was 9.9%. The annual risk varied to a small degree by age of diagnosis, by time elapsed since diagnosis and by current age. The 25-year actuarial risk was similar for DCIS and invasive breast cancer patients (10.1 versus 9.9%). The 25-year actuarial risk was higher for black women (12.7%) than for white women (9.7%) and was lower for women with ER-positive breast cancer (9.5%) than for women with ER-negative breast cancer (11.2%).
Conclusions
Women with unilateral breast cancer experience an annual risk of contralateral breast cancer ~0.4% per year, which persists over the 25-year follow-up period.
Journal Article
Advances in Diagnosis and Management of Childhood Osteoporosis
Childhood osteoporosis leads to increased propensity to fracture, and thus is an important cause of morbidity, pain and healthcare utilisation. Osteoporosis in children may be caused by a primary bone defect or secondary to an underlying medical condition and/or its treatment. Primary osteoporosis is rare, but there is an increasing number of children with risk factors for secondary osteoporosis. Therefore it is imperative that all paediatricians are aware of the diagnostic criteria and baseline investigations for childhood osteoporosis to enable timely referral to a specialist in paediatric bone health. This review will discuss the approach to diagnosis, investigation and management of childhood osteoporosis, with particular consideration to advances in molecular diagnosis of primary bone disorders, and current and emerging therapies for fracture reduction.
Journal Article
Silver-Russell syndrome secondary to rare (epi)genotypes exhibits phenotypic heterogeneity challenging clinical diagnosis
Context
Silver-Russell syndrome (SRS) is a complex multisystem condition requiring timely diagnosis for appropriate management. A clinical diagnosis is made in individuals scoring ≥ 4 Netchine-Harbison Clinical Scoring System (NH-CSS) criteria, with (epi)genetic investigations undertaken in those with NH-CSS ≥ 3 and strong clinical suspicion. Monogenic variants in imprinted (
CDKN1C
and
IGF2
) and non-imprinted (
HMGA2
and
PLAG1
) genes are recognised as rare causes of SRS. The frequency of associated phenotypes is unclear.
Objective
We evaluated the suitability of SRS as an umbrella term for these (epi)genotypes by identifying key clinical features and assessing the validity of NH-CSS.
Methods
An extensive literature search identified 22
IGF2,
18
HMGA2
, 11
CDKN1C
and 11
PLAG1
published reports.
Main outcome measure
Clinical phenotypes including the NH-CSS criteria were interrogated to assess (dis)similarity between the molecular subgroups of SRS.
Results
Strict adherence to the NH-CSS identified clinical SRS in 91%
IGF2,
82%
CDKN1C,
78%
HMGA2
and 45%
PLAG1
affected individuals. Relative macrocephaly was observed in 82%
IGF2
, 82%
CDKN1C
, 44%
HMGA2
, and 27%
PLAG1
affected individuals. Prominent forehead was reported in 100%
CDKN1C
, 91%
IGF2
, 72%
HMGA2
, and 64%
PLAG1
and body asymmetry in 23%
IGF2
and 11%
HMGA2
affected individuals. Clinical features not typically associated with SRS included: microcephaly, challenging behaviour, cardiac abnormalities, cleft palate, and asthma.
Conclusions
The NH-CSS missed 9–55% of monogenic SRS. The diverse phenotypes of
PLAG1, CDKN1C, HMGA2
and
IGF2
variants may hinder a clinical diagnosis of SRS. These rarer (epi)genotypes could be considered as distinct entities.
Journal Article