A tidal lung simulation to quantify lung heterogeneity with the Inspired Sinewave Test

We have created a lung simulation to quantify lung heterogeneity from the results of the inspired sinewave test (IST). The IST is a lung function test that is non-invasive, non-ionising and does not require patients' cooperation. A tidal lung simulation is developed to assess this test and also a method is proposed to calculate lung heterogeneity from IST results. A sensitivity analysis based on the Morris method and linear regression were applied to verify and to validate the simulation. Additionally, simulated emphysema and pulmonary embolism conditions were created using the simulation to assess the ability of the IST to identify these conditions. Experimental data from five pigs (pre-injured vs injured) were used for validation. This paper contributes to the development of the IST. Firstly, our sensitivity analysis reveals that the IST is highly accurate with an underestimation of about 5% of the simulated values. Sensitivity analysis suggested that both instability in tidal volume and extreme expiratory flow coefficients during the test cause random errors in the IST results. Secondly, the ratios of IST results obtained at two tracer gas oscillation frequencies can identify lung heterogeneity (ELV60/ELV180 and Qp60/Qp180). There was dissimilarity between simulated emphysema and pulmonary embolism (p < 0:0001). In the animal model, the control group had ELV60/ELV180 = 0.58 compared with 0.39 in injured animals (p < 0.0001)

Will fish be part of future healthy and sustainable diets?

First paragraph: The adoption of healthy and sustainable diets and food systems is recognised as a means to address the global challenge of malnutrition and poor-quality diets, and unprecedented environmental damage from food production and consumption.1 Sustainable diets have also been recognised as a key strategy to achieve the Sustainable Development Goals. Reducing consumption of animal-source foods is frequently presented as key to improving the sustainability of food systems.2 Fish and seafood can have a lower environmental impact and in many cases are considered more efficient than terrestrial animal production (albeit with wide variation) depending on the type of production or capture method,3 yet remain largely absent, or insufficiently articulated in the sustainable diets literature, rendering their future role in healthy diets unclear.4 This absence of specific consideration of fish and seafood extends to food security literature, in which the role of fish remains under-recognised and undervalued.5 Legitimate concerns exist regarding the environmental sustainability of fisheries and aquaculture systems; however, we argue that an overemphasis on the so-called doomsday portrayal of fish—which often dominates literature and the broader media—masks the myriad of positive contributions of the fisheries sector to nutrition and sustainability and limits its scope in contributing to healthy and sustainable food systems

A systematic review of machine learning models for management, prediction and classification of ARDS

Aim: Acute respiratory distress syndrome or ARDS is an acute, severe form of respiratory failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements in signal processing and machine learning have led to promising solutions for classification, event detection and predictive models in the management of ARDS. Method: In this review, we provide systematic description of different studies in the application of Machine Learning (ML) and artificial intelligence for management, prediction, and classification of ARDS. We searched the following databases: Google Scholar, PubMed, and EBSCO from 2009 to 2023. A total of 243 studies was screened, in which, 52 studies were included for review and analysis. We integrated knowledge of previous work providing the state of art and overview of explainable decision models in machine learning and have identified areas for future research. Results: Gradient boosting is the most common and successful method utilised in 12 (23.1%) of the studies. Due to limitation of data size available, neural network and its variation is used by only 8 (15.4%) studies. Whilst all studies used cross validating technique or separated database for validation, only 1 study validated the model with clinician input. Explainability methods were presented in 15 (28.8%) of studies with the most common method is feature importance which used 14 times. Conclusion: For databases of 5000 or fewer samples, extreme gradient boosting has the highest probability of success. A large, multi-region, multi centre database is required to reduce bias and take advantage of neural network method. A framework for validating with and explaining ML model to clinicians involved in the management of ARDS would be very helpful for development and deployment of the ML model

Death from early colorectal cancer is predicted by the presence of transcripts of the REG gene family

An intrinsic component of colorectal carcinogenesis may be the capacity to activate regenerative responses simultaneously with inhibition of apoptosis. Since apoptosis is known to be inhibited in colorectal cancer, this study sought evidence for the activation of the REG family of genes which are considered to be activated during regeneration of intestinal mucosa. Transcripts for the REG gene were found in 53% of colorectal cancers and for the PAP gene in 60% of colorectal cancers, by RT-PCR. Using in situ hybridization, the REG transcripts were found to be present in the tumour cells themselves rather than inflammatory or stromal cells. There were no significant correlations between the expression of these two genes and tumour stage, age or sex of the patient population or tumour site. However, in patients with non-metastatic disease who underwent ostensibly curative surgery, the expression of REG alone and co-expression of REG with PAP had a highly significantly adverse effect on survival. These data provide support for the concept that, in some tumours, carcinogenesis involves a regenerative process which co-exists with apoptotic inhibition and may provide a valuable selective indicator of the need for adjuvant therapy in those patients with early-stage colorectal cancer whose disease is destined to recur after curative surgery. © 2000 Cancer Research Campaig

Modelling mixing within the dead space of the lung improves predictions of functional residual capacity

Routine estimation of functional residual capacity (FRC) in ventilated patients has been a long held goal, with many methods previously proposed, but none have been used in routine clinical practice. This paper proposes three models for determining FRC using the nitrous oxide concentration from the entire expired breath in order to improve the precision of the estimate. Of the three models proposed, a dead space with two mixing compartments provided the best results, reducing the mean limits of agreement with the FRC measured by whole body plethysmography by up to 41%. This moves away from traditional lung models, which do not account for mixing within the dead space. Compared to literature values for FRC, the results are similar to those obtained using helium dilution and better than the LUFU device (Dräger Medical, Lubeck, Germany), with significantly better limits of agreement compared to plethysmography

Genomic evolution shapes prostate cancer disease type

H.R.F. was supported by a Cancer Research UK Programme Grant to Simon Tavaré (C14303/A17197), as, partially, was A.G.L. A.G.L. acknowledges the support of the University of St Andrews. A.G.L. and J.H.R.F. also acknowledge the support of the Cambridge Cancer Research Fund.The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Aalternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.Peer reviewe

VIP Enhances Phagocytosis of Fibrillar Beta-Amyloid by Microglia and Attenuates Amyloid Deposition in the Brain of APP/PS1 Mice

Vasoactive intestinal peptide (VIP) is a multifunctional neuropeptide with demonstrated immunosuppressive and neuroprotective activities. It has been shown to inhibit Amyloid beta (Aβ)-induced neurodegeneration by indirectly suppressing the production and release of a variety of inflammatory and neurotoxic factors by activated microglia. We demonstrated that VIP markedly increased microglial phagocytosis of fibrillar Aβ42 and that this enhanced phagocytotic activity depended on activation of the Protein kinase C (PKC) signaling pathway. In addition, VIP suppressed the release of tumor necrosis factor alpha (TNF-α) and nitric oxide(NO) from microglia activated by combined treatment with fibrillar Aβ42 and low dose interferon-γ (IFN-γ). We utilized an adenovirus-mediated gene delivery method to overexpress VIP constitutively in the hippocampus of APPswPS1 transgenic mice. The Aβ load was significantly reduced in the hippocampus of this animal model of Alzheimer's disease, possibly due to the accumulation and activation of cd11b-immunoactive microglial cells. The modulation of microglial activation, phagocytosis, and secretion by VIP is a promising therapeutic option for the treatment of Alzheimer's disease(AD)

Alzheimer's Disease-Linked Mutations in Presenilin-1 Result in a Drastic Loss of Activity in Purified γ-Secretase Complexes

BACKGROUND: Mutations linked to early onset, familial forms of Alzheimer's disease (FAD) are found most frequently in PSEN1, the gene encoding presenilin-1 (PS1). Together with nicastrin (NCT), anterior pharynx-defective protein 1 (APH1), and presenilin enhancer 2 (PEN2), the catalytic subunit PS1 constitutes the core of the γ-secretase complex and contributes to the proteolysis of the amyloid precursor protein (APP) into amyloid-beta (Aβ) peptides. Although there is a growing consensus that FAD-linked PS1 mutations affect Aβ production by enhancing the Aβ1-42/Aβ1-40 ratio, it remains unclear whether and how they affect the generation of APP intracellular domain (AICD). Moreover, controversy exists as to how PS1 mutations exert their effects in different experimental systems, by either increasing Aβ1-42 production, decreasing Aβ1-40 production, or both. Because it could be explained by the heterogeneity in the composition of γ-secretase, we purified to homogeneity complexes made of human NCT, APH1aL, PEN2, and the pathogenic PS1 mutants L166P, ΔE9, or P436Q. METHODOLOGY/PRINCIPAL FINDINGS: We took advantage of a mouse embryonic fibroblast cell line lacking PS1 and PS2 to generate different stable cell lines overexpressing human γ-secretase complexes with different FAD-linked PS1 mutations. A multi-step affinity purification procedure was used to isolate semi-purified or highly purified γ-secretase complexes. The functional characterization of these complexes revealed that all PS1 FAD-linked mutations caused a loss of γ-secretase activity phenotype, in terms of Aβ1-40, Aβ1-42 and APP intracellular domain productions in vitro. CONCLUSION/SIGNIFICANCE: Our data support the view that PS1 mutations lead to a strong γ-secretase loss-of-function phenotype and an increased Aβ1-42/Aβ1-40 ratio, two mechanisms that are potentially involved in the pathogenesis of Alzheimer's disease