Mental health support through primary care during and after covid-19.

Editorial Materia

Evidence of neutral transcriptome evolution in plants

The transcriptome of an organism is its set of gene transcripts (mRNAs) at a defined spatial and temporal locus. Because gene expression is affected markedly by environmental and developmental perturbations, it is widely assumed that transcriptome divergence among taxa represents adaptive phenotypic selection. This assumption has been challenged by neutral theories which propose that stochastic processes drive transcriptome evolution. To test for evidence of neutral transcriptome evolution in plants, we quantified 18 494 gene transcripts in nonsenescent leaves of 14 taxa of Brassicaceae using robust cross-species transcriptomics which includes a two-step physical and in silicobased normalization procedure based on DNA similarity among taxa. Transcriptome divergence correlates positively with evolutionary distance between taxa and with variation in gene expression among samples. Results are similar for pseudogenes and chloroplast genes evolving at different rates. Remarkably, variation in transcript abundance among root-cell samples correlates positively with transcriptome divergence among root tissues and among taxa. Because neutral processes affect transcriptome evolution in plants, many differences in gene expression among or within taxa may be nonfunctional, reflecting ancestral plasticity and founder effects. Appropriate null models are required when comparing transcriptomes in space and time

Screened and Unscreened Phases in Sedimenting Suspensions

A coarse-grained stochastic hydrodynamical description of velocity and concentration fluctuations in steadily sedimenting suspensions is constructed, and analyzed using self-consistent and renormalization group methods. We find that there exists a dynamical, non-equilibrium phase transition from an "unscreened" phase in which we recover the Caflisch-Luke (R.E. Caflisch and J.H.C. Luke, Phys. Fluids 28, 759 (1985)) divergence of the velocity variance to a "screened" phase where the velocity fluctuations have a finite correlation length growing as $\phi^{-1/3}$ where $\phi$ is the particle volume fraction, in agreement with Segr\`e et. al. (Phys. Rev. Lett. 79, 2574 (1997)) and the velocity variance is independent of system size. Detailed predictions are made for the correlation function in both phases and at the transition.Comment: 4 pages, revtex 1 figur

Genotype‐phenotype analysis of LMNA‐related diseases predicts phenotype‐selective alterations in lamin phosphorylation

Laminopathies are rare diseases associated with mutations in LMNA, which encodes nuclear lamin A/C. LMNA variants lead to diverse tissue‐specific phenotypes including cardiomyopathy, lipodystrophy, myopathy, neuropathy, progeria, bone/skin disorders, and overlap syndromes. The mechanisms underlying these heterogeneous phenotypes remain poorly understood, although post‐translational modifications, including phosphorylation, are postulated as regulators of lamin function. We catalogued all known lamin A/C human mutations and their associated phenotypes, and systematically examined the putative role of phosphorylation in laminopathies. In silico prediction of specific LMNA mutant‐driven changes to lamin A phosphorylation and protein structure was performed using machine learning methods. Some of the predictions we generated were validated via assessment of ectopically expressed wild‐type and mutant LMNA. Our findings indicate phenotype‐ and mutant‐specific alterations in lamin phosphorylation, and that some changes in phosphorylation may occur independently of predicted changes in lamin protein structure. Therefore, therapeutic targeting of phosphorylation in the context of laminopathies will likely require mutant‐ and kinase‐specific approaches.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155891/1/fsb220571.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155891/2/fsb220571_am.pd

Potential association of LMNA-associated generalized lipodystrophy with juvenile dermatomyositis

Abstract Background Juvenile dermatomyositis (JDM) is an auto-immune muscle disease which presents with skin manifestations and muscle weakness. At least 10% of the patients with JDM present with acquired lipodystrophy. Laminopathies are caused by mutations in the lamin genes and cover a wide spectrum of diseases including muscular dystrophies and lipodystrophy. The p.T10I LMNA variant is associated with a phenotype of generalized lipodystrophy that has also been called atypical progeroid syndrome. Case presentation A previously healthy female presented with bilateral proximal lower extremity muscle weakness at age 4. She was diagnosed with JDM based on her clinical presentation, laboratory tests and magnetic resonance imaging (MRI). She had subcutaneous fat loss which started in her extremities and progressed to her whole body. At age 7, she had diabetes, hypertriglyceridemia, low leptin levels and low body fat on dual energy X-ray absorptiometry (DEXA) scan, and was diagnosed with acquired generalized lipodystrophy (AGL). Whole exome sequencing (WES) revealed a heterozygous c.29C > T; p.T10I missense pathogenic variant in LMNA, which encodes lamins A and C. Muscle biopsy confirmed JDM rather than muscular dystrophy, showing perifascicular atrophy and perivascular mononuclear cell infiltration. Immunofluroscence of skin fibroblasts confirmed nuclear atypia and fragmentation. Conclusions This is a unique case with p.T10I LMNA variant displaying concurrent JDM and AGL. This co-occurrence raises the intriguing possibility that LMNA, and possibly p.T10I, may have a pathogenic role in not only the occurrence of generalized lipodystrophy, but also juvenile dermatomyositis. Careful phenotypic characterization of additional patients with laminopathies as well as individuals with JDM is warranted.https://deepblue.lib.umich.edu/bitstream/2027.42/142870/1/40842_2018_Article_58.pd

The local burden of disease during the first wave of the COVID-19 epidemic in England: estimation using different data sources from changing surveillance practices.

BACKGROUND: The COVID-19 epidemic has differentially impacted communities across England, with regional variation in rates of confirmed cases, hospitalisations and deaths. Measurement of this burden changed substantially over the first months, as surveillance was expanded to accommodate the escalating epidemic. Laboratory confirmation was initially restricted to clinical need ("pillar 1") before expanding to community-wide symptomatics ("pillar 2"). This study aimed to ascertain whether inconsistent measurement of case data resulting from varying testing coverage could be reconciled by drawing inference from COVID-19-related deaths. METHODS: We fit a Bayesian spatio-temporal model to weekly COVID-19-related deaths per local authority (LTLA) throughout the first wave (1 January 2020-30 June 2020), adjusting for the local epidemic timing and the age, deprivation and ethnic composition of its population. We combined predictions from this model with case data under community-wide, symptomatic testing and infection prevalence estimates from the ONS infection survey, to infer the likely trajectory of infections implied by the deaths in each LTLA. RESULTS: A model including temporally- and spatially-correlated random effects was found to best accommodate the observed variation in COVID-19-related deaths, after accounting for local population characteristics. Predicted case counts under community-wide symptomatic testing suggest a total of 275,000-420,000 cases over the first wave - a median of over 100,000 additional to the total confirmed in practice under varying testing coverage. This translates to a peak incidence of around 200,000 total infections per week across England. The extent to which estimated total infections are reflected in confirmed case counts was found to vary substantially across LTLAs, ranging from 7% in Leicester to 96% in Gloucester with a median of 23%. CONCLUSIONS: Limitations in testing capacity biased the observed trajectory of COVID-19 infections throughout the first wave. Basing inference on COVID-19-related mortality and higher-coverage testing later in the time period, we could explore the extent of this bias more explicitly. Evidence points towards substantial under-representation of initial growth and peak magnitude of infections nationally, to which different parts of the country contribute unequally

Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations

Syncope: experience at a tertiary care hospital in Karachi, Pakistan

Introduction:Our aim was to determine the characteristics of Patients presenting with syncope at a tertiary care hospital in Karachi, Pakistan.Methods: A review of medical records was conducted retrospectively at the Department of Medicine, Aga Khan University Hospital, Karachi. Patients aged 16 and above, admitted from January 2000 to December 2005 with the diagnosis of syncope made by the attending physician were included.Results:A total of 269 Patients were included (75% males, mean age: 57.4 years). Neurogenic (vasovagal) syncope was the most common cause (47%), followed by cardiogenic syncope (18%) and orthostatic syncope (9%). A total of 24% were discharged undiagnosed. Twenty Patients (7.4%) did not have any prodrome. Common prodromal symptoms included dizziness (61%), sweating (25%), palpitations (19%), nausea/vomiting (19%) and visual symptoms (17%). The distribution of symptoms according to cause of syncope revealed only breathlessness to be significantly associated with cardiogenic syncope (p = 0.002). Most Patients with cardiogenic syncope were aged above 40 (98%, p \u3c 0.001), had coronary artery disease (72%, p \u3c 0.001) and abnormal electrocardiogram at presentation (92%, p \u3c 0.001).Conclusion:Despite differences in burden of diseases, our findings were similar to those of published syncope literature. Further studies are needed to develop a protocol to expedite the evaluation and limit the work-up and admission in low-risk Patients

Mutant Huntingtin induces activation of the Bcl-2/adenovirus E1B 19-kDa interacting protein (BNip3)

Huntington's disease (HD) is a neurodegenerative disorder characterized by progressive neuronal death in the basal ganglia and cortex. Although increasing evidence supports a pivotal role of mitochondrial dysfunction in the death of patients' neurons, the molecular bases for mitochondrial impairment have not been elucidated. We provide the first evidence of an abnormal activation of the Bcl-2/adenovirus E1B 19-kDa interacting protein 3 (BNip3) in cells expressing mutant Huntingtin. In this study, we show an abnormal accumulation and dimerization of BNip3 in the mitochondria extracted from human HD muscle cells, HD model cell cultures and brain tissues from HD model mice. Importantly, we have shown that blocking BNip3 expression and dimerization restores normal mitochondrial potential in human HD muscle cells. Our data shed light on the molecular mechanisms underlying mitochondrial dysfunction in HD and point to BNip3 as a new potential target for neuroprotective therapy in HD

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN