Olivia Rennie

Background and Objective: Hepatobiliary diseases are a longstanding and significant medical challenge which, despite advances in surgical techniques, still carry risks for postoperative complications such as anastomotic leaks (ALs), which can include both postoperative pancreatic fistula (POPF) and bile leaks (BL). These complications incur significant human and economic costs on all those involved, including the patient, healthcare providers, and hospital systems. The aim of this study was to construct a narrative review of literature surrounding definitions and grading systems for ALs in the context of hepato-pancreato-biliary (HPB) procedures, and consequences of POPF and BL. Methods: A literature review was conducted by examining databases including PubMed, Web of Science, OVID Embase, Google Scholar, and Cochrane library databases. Searches were performed with the following search criteria: (((((((anastomosis) OR (anastomotic leak*)) OR (postoperative pancreatic fistula)) OR (bile leak*)) OR (pancreaticoduodenectomy)) OR (whipple)) AND ((hepatobiliary) OR (hepato-pancreato-biliary)) AND ((definition) OR (grading system*) OR (consequences) OR (outcomes) OR (risk factor*) OR (morbidity) OR (mortality))). Publications that were retrieved underwent further assessment to ensure other relevant publications were identified and included. Key Content and Findings: A universally accepted definition and grading system for POPF and BL continues to be lacking, leading to variability in reported incidence in the literature. Various groups have worked to publish guidelines for defining and grading POPF and BL, with the International Study Group in Pancreatic Surgery (ISGPS) and International Study Group for Liver Surgery (ISGLS) definitions the current most recommended definitions for POPF and BL, respectively. The burden of AL on patients, healthcare providers, and hospitals is well documented in evidence from leak consequences, such as increased morbidity and mortality, higher reoperation rates, and increased readmission rates, among others. Conclusions: AL remains a significant challenge in HPB surgery, despite medical advancements. Understanding the progress made in defining and grading leaks, as well as the range of negative outcomes that arise from AL, is crucial in improving patient care, reduce surgical mortality, and drive further advancements in earlier detection and treatment of AL.

The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow movement towards improved understanding of pathophysiology and treatments compared with more common illnesses. The push towards evidence-based medicine (EBM), which prioritizes certain types of evidence over others, poses a particular issue when mapped onto rare diseases, which may not be feasibly investigated using the methodologies endorsed by EBM, due to a number of constraints. While other trial designs have been suggested to overcome these limitations (with varying success), perhaps the most recent and enthusiastically adopted is the application of artificial intelligence to rare disease data. This paper critically examines the pitfalls of EBM (and its trial design offshoots) as it pertains to rare diseases, exploring the current landscape of AI as a potential solution to these challenges. This discussion is also taken a step further, providing philosophical commentary on the weaknesses and dangers of AI algorithms applied to rare disease research. While not proposing a singular solution, this article does provide a thoughtful reminder that no ‘one-size-fits-all’ approach exists in the complex world of rare diseases. We must balance cautious optimism with critical evaluation of new research paradigms and technology, while at the same time not neglecting the ever-important aspect of patient values and preferences, which may be challenging to incorporate into computer-driven models.

Hemodynamic models provide a mathematical representation and computational framework that describe the changes in blood flow, blood volume, and oxygenation levels that occur in response to neural activity and systemic changes, while near-infrared spectroscopy (NIRS) measures deoxyhemoglobin, oxyhemoglobin, and other chromophores to analyze cerebral hemodynamics and metabolism. In this study, we apply a dynamic hemometabolic model to NIRS data acquired during cardiac arrest and cardiopulmonary resuscitation (CPR) in pigs. Our goals were to test the model’s ability to accurately describe the observed phenomena, to gain an understanding of the intricate behavior of cerebral microvasculature, and to compare the obtained parameters with known values. By employing the inverse of the hemometabolic model, we measured a range of significant physiological parameters, such as the rate of oxygen diffusion from blood to tissue, the arteriole and venule volume fractions, and the Fåhraeus factor. Statistical analysis uncovered significant differences in the baseline and post-cardiac arrest values of some of the parameters.

Autism Spectrum Disorder (ASD) is characterized by impaired social communication, restricted interests, and repetitive and stereotyped behaviors. The TRPC6 (transient receptor potential channel 6) represents an ASD candidate gene under an oligogenic/multifactorial model based on the initial description and cellular characterization of an individual with ASD bearing a de novo heterozygous mutation disrupting TRPC6, together with the enrichment of disruptive TRPC6 variants in ASD cases as compared to controls. Here, we perform a clinical re-evaluation of the initial non-verbal patient, and also present eight newly reported individuals ascertained for ASD and bearing predicted loss-of-function mutations in TRPC6. In order to understand the consequences of mutations in TRPC6 on nervous system function, we used the fruit fly, Drosophila melanogaster, to show that null mutations in transient receptor gamma (trpγ; the fly gene most similar to TRPC6), cause a number of behavioral defects that mirror features seen in ASD patients, including deficits in social interactions (based on courtship behavior), impaired sleep homeostasis (without affecting the circadian control of sleep), hyperactivity in both young and old flies, and defects in learning and memory. Some defects, most notably in sleep, differed in severity between males and females and became normal with age. Interestingly, hyperforin, a TRPC6 agonist and the primary active component of the St. John’s wort antidepressant, attenuated many of the deficits expressed by trpγ mutant flies. In summary, our results provide further evidence that the TRPC6 gene is a risk factor for ASD. In addition, they show that the behavioral defects caused by mutations in TRPC6 can be modeled in Drosophila, thereby establishing a paradigm to examine the impact of mutations in other candidate genes.

Autism Spectrum Disorder (ASD) is genetically complex with ~100 copy number variants and genes involved. To try to establish more definitive genotype and phenotype correlations in ASD, we searched genome sequence data, and the literature, for recurrent predicted damaging sequence-level variants affecting single genes. We identified 18 individuals from 16 unrelated families carrying a heterozygous guanine duplication (c.3679dup; p.Ala1227Glyfs*69) occurring within a string of 8 guanines (genomic location [hg38]g.50,721,512dup) affecting SHANK3, a prototypical ASD gene (0.08% of ASD-affected individuals carried the predicted p.Ala1227Glyfs*69 frameshift variant). Most probands carried de novo mutations, but five individuals in three families inherited it through somatic mosaicism. We scrutinized the phenotype of p.Ala1227Glyfs*69 carriers, and while everyone (17/17) formally tested for ASD carried a diagnosis, there was the variable expression of core ASD features both within and between families. Defining such recurrent mutational mechanisms underlying an ASD outcome is important for genetic counseling and early intervention.

Autism spectrum disorder (ASD) is often grouped with other brain-related phenotypes into a broader category of neurodevelopmental disorders (NDDs). In clinical practice, providers need to decide which genes to test in individuals with ASD phenotypes, which requires an understanding of the level of evidence for individual NDD genes that supports an association with ASD. Consensus is currently lacking about which NDD genes have sufficient evidence to support a relationship to ASD. Estimates of the number of genes relevant to ASD differ greatly among research groups and clinical sequencing panels, varying from a few to several hundred. This Roadmap discusses important considerations necessary to provide an evidence-based framework for the curation of NDD genes based on the level of information supporting a clinically relevant relationship between a given gene and ASD.