Multiple myeloma is the second most common hematologic malignancy in the world. Despite improvement in outcome, the disease is still incurable for most patients. However, not all myeloma are the same. With the same treatment, some patients can have very long survival whereas others can have very short survival. This suggests that there is underlying heterogeneity in myeloma. Studies over the years have revealed multiple layers of heterogeneity. First, clinical parameters such as age and tumor burden could significantly affect outcome. At the genetic level, there are also significant heterogeneity ranging for chromosome numbers, genetic translocations, and genetic mutations. At the clonal level, there appears to be significant clonal heterogeneity with multiple clones coexisting in the same patient. At the cell differentiation level, there appears to be a hierarchy of clonally related cells that have different clonogenic potential and sensitivity to therapies. These levels of complexities present challenges in terms of treatment and prognostication as well as monitoring of treatment. However, if we can clearly delineate and dissect this heterogeneity, we may also be presented with unique opportunities for precision and personalized treatment of myeloma. Some proof of concepts of such approaches has been demonstrated.

As the coronavirus disease 2019 (COVID-19) pandemic, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading rapidly worldwide, it has emerged as a leading cause of mortality, resulting in >1 million deaths over the past 10 months. The pathophysiology of COVID-19 remains unclear, posing a great challenge to the medical management of patients. Recent studies have reported an unusually high prevalence of thromboembolic events in COVID-19 patients, although the mechanism remains elusive. Several studies have reported the presence of aPLs in COVID-19 patients. We have noticed similarities between COVID-19 and APS, which is an autoimmune prothrombotic disease that is often associated with an infective aetiology. Molecular mimicry and endothelial dysfunction could plausibly explain the mechanism of thrombogenesis in acquired APS. In this review, we discuss the clinicopathological similarities between COVID-19 and APS, and the potential role of therapeutic targets based on the anti-phospholipid model for COVID-19 disease.

Immune suppression is a recognized risk factor for necrotizing fasciitis. In patients with hematological malignancies, a profoundly immunocompromised group, the predominant causative organisms are Gram negative. Clinical presentation and outcomes in these patients are similar to the immunocompetent. The Laboratory Risk Indicator for Necrotizing Fasciitis score is not reliable for risk stratification of the disease.

Background: Arterial and venous thrombosis are reported to be common in critically ill COVID-19 patients. Method and results: This is a national multicenter retrospective observational study involving all consecutive adult COVID-19 patients who required intensive care units (ICU) admission between 23 January 2020 and 30 April 2020 in Singapore. One hundred eleven patients were included and the venous and arterial thrombotic rates in ICU were 1.8% (n = 2) and 9.9% (n = 11), respectively. Major bleeding rate was 14.8% (n = 16). Conclusions: Critically ill COVID-19 patients in Singapore have lower venous thromboembolism but higher arterial thrombosis rates and bleeding manifestations than other reported cohorts.

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images – more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.