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Abstract Background Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes). Results Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%. Conclusion Long-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Systemic vulnerabilities in the Internet of Things (IoT) pose a challenge for establishing robust cybersecurity strategies. These challenges leave IoT devices susceptible to infection, often falling victim to far-reaching Botnets. To counter these risks, Intrusion Detection Systems (IDS) are designed to detect attacks within the network, mitigating the dangers presented by architecturally vulnerable IoT devices. However, IDS solutions are designed to operate at the center of the network, requiring network traffic to be forwarded inwards and consequently hampers reaction times while straining network resources. This paper introduces an IoT Botnet detection pipeline composed of a novel network traffic visualization methodology and a Convolutional Neural Network (CNN). The pipeline operates on an embedded system at the edge of the network, transforming network traffic into a visual format for subsequent cyberattack classification by the CNN. By leveraging the advantages of CNNs in efficiently classifying images, the pipeline achieves high accuracy in detecting Botnet attacks while maintaining an efficient design. During testing, we applied the pipeline to the N-BaIoT and IoT-23 datasets and observed high cyberattack detection rates of 100% and 99.78%, respectively. Furthermore, we observed a 2.4 times greater throughput (packets/second) and a 21.4% reduction in model size compared to a Deep Neural Network of similar accuracy.

Abstract In this commentary, we discuss a recent article in Trials that raised concerns about the number of poorly performed randomised trials in the medical literature and discuss the trials literature more widely. Although we all aim for higher methodological standards in trials, we argue that (i) the idea that ‘most randomised trials are bad’, which the recent article concludes is an overly simplistic representation of the situation, and (ii) the suggestion that an increased focus on methodological review during trial development (e.g. ethical boards performing some assessment of the methodologists on a trial), while well meaning, may have negative unintended consequences. We therefore propose that (a) trials should be assessed on their merits and weaknesses, including an assessment of risk of bias but placing that in a wider context; (b) we should recognise that although the methodological conduct of trials is of utmost importance, interventions that aim to improve this could have unintended consequences—such as bureaucracy—that have an overall negative effect; and (c) we should therefore generate an evidence base for policy interventions to improve conduct of trials rather than applying arbitrary rules.

Coronavirus disease-19 (COVID-19) causes immune perturbations which may persist long term, and patients frequently report ongoing symptoms for months after recovery. We assessed immune activation at 3–12 months post hospital admission in 187 samples from 63 patients with mild, moderate, or severe disease and investigated whether it associates with long COVID. At 3 months, patients with severe disease displayed persistent activation of CD4+ and CD8+ T-cells, based on expression of HLA-DR, CD38, Ki67, and granzyme B, and elevated plasma levels of interleukin-4 (IL-4), IL-7, IL-17, and tumor necrosis factor-alpha (TNF-α) compared to mild and/or moderate patients. Plasma from severe patients at 3 months caused T-cells from healthy donors to upregulate IL-15Rα, suggesting that plasma factors in severe patients may increase T-cell responsiveness to IL-15-driven bystander activation. Patients with severe disease reported a higher number of long COVID symptoms which did not however correlate with cellular immune activation/pro-inflammatory cytokines after adjusting for age, sex, and disease severity. Our data suggests that long COVID and persistent immune activation may correlate independently with severe disease.

Abstract Xerosis, commonly referred to as dry skin, is a common dermatological condition affecting almost a third of the population. Successful treatment of the condition traditionally involves the application of cosmetic products facilitating the moisturisation of the skin with a range of ingredients including glycerol and fatty acids. While the effectiveness of these treatments is not in question, limited information exists on the impact on the skin microbiome following use of these products and the improvement in skin hydration. Here, we describe improvements in skin barrier properties together with increased levels of cholesterol, ceramides and long-chain fatty acids following application of Body Lotion. Concomitant alterations in the skin microbiome are also seen via 16S rRNA metataxonomics, in combination with both traditional and novel informatics analysis. Following 5 weeks of lotion use, beneficial skin bacteria are increased, with improvements in microbiome functional potential, and increases in pathways associated with biosynthesis of multiple long chain fatty acids.

Ultrasonic communication is a desirable method for information transfer through solid channels such as metallic bars, plates, or pipes by overcoming the physical barriers that prevent conventional wired or radiofrequency transmission. In this paper, we investigate the architecture of a reconfigurable software-defined ultrasonic communication (SDUC) platform that can make use of the complete channel bandwidth for real-time video transmission through a highly reverberant solid channel. Reverberations in solid channels are complex and generated by surface wave, lamb wave, longitudinal wave, shear wave, reflection, refraction, dispersion, mode conversion, and scattering phenomena. To explore the multipath and fading effects on bitrate, experimental studies were performed using an aluminum rectangular bar (ARB) of 25, 40, and 50 cm channel length. We investigated the feasibility of utilizing orthogonal frequency-division multiplexing (OFDM) combined with quadrature amplitude modulations (QAM) for peak bitrate performance. Design strategies and guidelines have been established for the best solutions to combat intersymbol interference caused by the severe reverberation inherent to ultrasonic solid channels. A practical solution for video transmission, adhering to the Digital Video Broadcasting Terrestrial (DVB-T) standard, is also examined for video streaming transmission of 240p, 480p, and 720p resolutions at 20 frames per second across an ARB channel. For experimental studies and performance evaluation, we designed a high-performance reconfigurable system-on-chip (SoC) SDUC platform for video transmission and bit error rate (BER) assessment. Through experimental studies for ultrasonic channel analysis, we achieved a peak video transmission rate of 1074 kbps with 3.3 $\times \,\,10 ^{-4}$ BER despite reverberation, the multipath effect, and signal fading within the ARB channel.

BackgroundSepsis is characterised by dysregulated, life-threatening immune responses, which are thought to be driven by cytokines such as interleukin 6 (IL-6). Genetic variants in IL6R known to down-regulate IL-6 signalling are associated with improved Coronavirus Disease 2019 (COVID-19) outcomes, a finding later confirmed in randomised trials of IL-6 receptor antagonists (IL6RAs). We hypothesised that blockade of IL6R could also improve outcomes in sepsis.Methods and findingsWe performed a Mendelian randomisation (MR) analysis using single nucleotide polymorphisms (SNPs) in and near IL6R to evaluate the likely causal effects of IL6R blockade on sepsis (primary outcome), sepsis severity, other infections, and COVID-19 (secondary outcomes). We weighted SNPs by their effect on CRP and combined results across them in inverse variance weighted meta-analysis, proxying the effect of IL6RA. Our outcomes were measured in UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative (HGI), and the GenOSept and GainS consortium. We performed several sensitivity analyses to test assumptions of our methods, including utilising variants around CRP and gp130 in a similar analysis. In the UK Biobank cohort (N = 486,484, including 11,643 with sepsis), IL6R blockade was associated with a decreased risk of our primary outcome, sepsis (odds ratio (OR) = 0.80; 95% confidence interval (CI) 0.66 to 0.96, per unit of natural log-transformed CRP decrease). The size of this effect increased with severity, with larger effects on 28-day sepsis mortality (OR = 0.74; 95% CI 0.47 to 1.15); critical care admission with sepsis (OR = 0.48, 95% CI 0.30 to 0.78) and critical care death with sepsis (OR = 0.37, 95% CI 0.14 to 0.98). Similar associations were seen with severe respiratory infection: OR for pneumonia in critical care 0.69 (95% CI 0.49 to 0.97) and for sepsis survival in critical care (OR = 0.22; 95% CI 0.04 to 1.31) in the GainS and GenOSept consortium, although this result had a large degree of imprecision. We also confirm the previously reported protective effect of IL6R blockade on severe COVID-19 (OR = 0.69, 95% CI 0.57 to 0.84) in the COVID-19 HGI, which was of similar magnitude to that seen in sepsis. Sensitivity analyses did not alter our primary results. These results are subject to the limitations and assumptions of MR, which in this case reflects interpretation of these SNP effects as causally acting through blockade of IL6R, and reflect lifetime exposure to IL6R blockade, rather than the effect of therapeutic IL6R blockade.ConclusionsIL6R blockade is causally associated with reduced incidence of sepsis. Similar but imprecisely estimated results supported a causal effect also on sepsis related mortality and critical care admission with sepsis. These effects are comparable in size to the effect seen in severe COVID-19, where IL-6 receptor antagonists were shown to improve survival. These data suggest that a randomised trial of IL-6 receptor antagonists in sepsis should be considered.

Low-volume antibody assays can be used to track SARS-CoV-2 infection rates in settings where active testing for virus is limited and remote sampling is optimal. We developed 12 ELISAs detecting total or antibody isotypes to SARS-CoV-2 nucleocapsid, spike protein or its receptor binding domain (RBD), 3 anti-RBD isotype specific luciferase immunoprecipitation system (LIPS) assays and a novel Spike-RBD bridging LIPS total-antibody assay. We utilized pre-pandemic (n=984) and confirmed/suspected recent COVID-19 sera taken pre-vaccination rollout in 2020 (n=269). Assays measuring total antibody discriminated best between pre-pandemic and COVID-19 sera and were selected for diagnostic evaluation. In the blind evaluation, two of these assays (Spike Pan ELISA and Spike-RBD Bridging LIPS assay) demonstrated >97% specificity and >92% sensitivity for samples from COVID-19 patients taken >21 days post symptom onset or PCR test. These assays offered better sensitivity for the detection of COVID-19 cases than a commercial assay which requires 100-fold larger serum volumes. This study demonstrates that low-volume in-house antibody assays can provide good diagnostic performance, and highlights the importance of using well-characterized samples and controls for all stages of assay development and evaluation. These cost-effective assays may be particularly useful for seroprevalence studies in low and middle-income countries.

Human skin and its commensal microbiome form the first layer of protection to the outside world. A dynamic microbial ecosystem of bacteria, fungi and viruses, with the potential to respond to external insult, the skin microbiome has been shown to evolve over the life course with an alteration in taxonomic composition responding to altered microenvironmental conditions on human skin. This work sought to investigate the taxonomic, diversity and functional differences between infant and adult leg skin microbiomes. A 16S rRNA gene-based metataxonomic analysis revealed significant differences between the infant and adult skin groups, highlighting differential microbiome profiles at both the genus and species level. Diversity analysis reveals differences in the overall community structure and associated differential predicted functional profiles between the infant and adult skin microbiome suggest differing metabolic processes are present between the groups. These data add to the available information on the dynamic nature of skin microbiome during the life course and highlight the predicted differential microbial metabolic process that exists on infant and adult skin, which may have an impact on the future design and use of cosmetic products that are produced to work in consort with the skin microbiome.

Background: Marked reductions in serum iron concentrations are commonly induced during the acute phase of infection. This phenomenon, termed hypoferremia of inflammation, leads to inflammatory anemia, but could also have broader pathophysiological implications. In patients with coronavirus disease 2019 (COVID-19), hypoferremia is associated with disease severity and poorer outcomes, although there are few reported cohorts. Methods: In this study, we leverage a well characterised prospective cohort of hospitalised COVID-19 patients and perform a set of analyses focussing on iron and related biomarkers and both acute severity of COVID-19 and longer-term symptomatology. Results: We observed no associations between acute serum iron and long-term outcomes (including fatigue, breathlessness or quality of life); however, lower haemoglobin was associated with poorer quality of life. We also quantified iron homeostasis associated parameters, demonstrating that among 50 circulating mediators of inflammation IL-6 concentrations were strongly associated with serum iron, consistent with its central role in inflammatory control of iron homeostasis. Surprisingly, we observed no association between serum hepcidin and serum iron concentrations. We also observed elevated erythroferrone concentrations in COVID-19 patients with anaemia of inflammation. Conclusions: These results enhance our understanding of the regulation and pathophysiological consequences of disturbed iron homeostasis during SARS-CoV-2 infection.

Preservatives play an essentially role in ensuring that cosmetic formulations remain safe for use via control of microbial contamination. Commonly used preservatives include organic acids, alcohols and phenols and these play an essential role in controlling the growth of bacteria, fungi and moulds in substrates that can potentially act as a rich food source for microbial contaminants. Whilst the activity of these compounds is clear, both in vitro and in formulation, little information exists on the potential impact that common preservative systems, in full formulation, have on the skin's resident microbiome. Dysbiosis of the skin's microbiome has been associated with a number of cosmetic conditions but there currently are no in vivo studies investigating the potential for preservative ingredients, when included in personal care formulations under normal use conditions, to impact the cutaneous microbiome. Here we present an analysis of four in vivo studies that examine the impact of different preservation systems in full formulation, in different products formats, with varying durations of application. This work demonstrates that despite the antimicrobial efficacy of the preservatives in vitro, the skin microbiome is not impacted by preservative containing products in vivo.

Here, we describe the case of a COVID-19 patient who developed recurring ventilator-associated pneumonia caused by Pseudomonas aeruginosa that acquired increasing levels of antimicrobial resistance (AMR) in response to treatment. Metagenomic analysis revealed the AMR genotype, while immunological analysis revealed massive and escalating levels of T-cell activation. These were both SARS-CoV-2 and P. aeruginosa specific, and bystander activated, which may have contributed to this patient’s persistent symptoms and radiological changes.

A recurring question in defining publicly funded research programmes is “what research should be funded publicly and what should be funded through the private sector?”. The way this question is usually answered has placed emphasis on seeking to ensure that research that has a payback in purely economic terms is funded (at least in part) by those most likely to receive the economic benefit, but evaluating “who benefits?” and “how?” is not always easy to deduce from the research questions posed.

Nigeria, like most African countries, has engaged in agricultural liberalization since 1986 in the hope that reforms emphasizing price incentives will encourage producers to respond. Thus far, the reforms seem to have introduced greater uncertainty into the market given increasing rates of price volatility. This study amongst other things therefore seeks to determine and model the responsiveness of rice supply to price risk in Nigeria. Statistical information on domestic and imported quantities of rice was obtained for 41 years (1970 to 2011) from various sources, such as the Food and Agriculture Organization (FAO) database, Federal Ministry of Agriculture statistical bulletins, Central Bank of Nigeria statistical bulletins and National Bureau of Statistic (NBS). Data were analyzed using equilibrium output supply function, co-integration models, and vector autoregressive distributed lag model. Rice importation was statistically significant and changes in output were also responsive to changes in price. The results indicate that producers are more responsive not only to price and non-price factor but also to price risk and exchange rate. It is therefore imperative to reduce the effects of price risk as to increase the response of producer to supply by bridging the gap in production