Impact on emergency and elective hospital-based care in Scotland over the first 12 months of the pandemic: interrupted time-series analysis of national lockdowns

ObjectivesCOVID-19 has resulted in the greatest disruption to National Health Service (NHS) care in its over 70-year history. Building on our previous work, we assessed the ongoing impact of pandemic-related disruption on provision of emergency and elective hospital-based care across Scotland over the first year of the pandemic.DesignWe undertook interrupted time-series analyses to evaluate the impact of ongoing pandemic-related disruption on hospital NHS care provision at national level and across demographics and clinical specialties spanning the period 29 March 2020–28 March 2021.SettingScotland, UK.ParticipantsPatients receiving hospital care from NHS Scotland.Main outcome measuresWe used the percentage change of accident and emergency attendances, and emergency and planned hospital admissions during the pandemic compared to the average admission rate for equivalent weeks in 2018–2019.ResultsAs restrictions were gradually lifted in Scotland after the first lockdown, hospital-based admissions increased approaching pre-pandemic levels. Subsequent tightening of restrictions in September 2020 were associated with a change in slope of relative weekly admissions rate: –1.98% (–2.38, –1.58) in accident and emergency attendance, –1.36% (–1.68, –1.04) in emergency admissions and –2.31% (–2.95, –1.66) in planned admissions. A similar pattern was seen across sex, socioeconomic status and most age groups, except children (0–14 years) where accident and emergency attendance, and emergency admissions were persistently low over the study period.ConclusionsWe found substantial disruption to urgent and planned inpatient healthcare provision in hospitals across NHS Scotland. There is the need for urgent policy responses to address continuing unmet health needs and to ensure resilience in the context of future pandemics.     

Two Cases of Lassa Fever Successfully Treated with Ribavirin and Adjunct Dexamethasone for Concomitant Infections

Lassa fever is a viral hemorrhagic fever treated with supportive care and the broad-spectrum antiviral drug ribavirin. The pathophysiology, especially the role of hyperinflammation, of this disease is unknown. We report successful remission of complicated Lassa fever in 2 patients in Nigeria who received the antiinflammatory agent dexamethasone and standard ribavirin.     

The Role of Food Insecurity and Dietary Diversity on Recovery from Wasting among Hospitalized Children Aged 6–23 Months in Sub-Saharan Africa and South Asia

Background: Current guidelines for the management of childhood wasting primarily focus on the provision of therapeutic foods and the treatment of medical complications. However, many children with wasting live in food-secure households, and multiple studies have demonstrated that the etiology of wasting is complex, including social, nutritional, and biological causes. We evaluated the contribution of household food insecurity, dietary diversity, and the consumption of specific food groups to the time to recovery from wasting after hospital discharge. Methods: We conducted a secondary analysis of the Childhood Acute Illness Network (CHAIN) cohort, a multicenter prospective study conducted in six low- or lower-middle-income countries. We included children aged 6–23 months with wasting (mid-upper arm circumference [MUAC] ≤ 12.5 cm) or kwashiorkor (bipedal edema) at the time of hospital discharge. The primary outcome was time to nutritional recovery, defined as a MUAC > 12.5 cm without edema. Using Cox proportional hazards models adjusted for age, sex, study site, HIV status, duration of hospitalization, enrollment MUAC, referral to a nutritional program, caregiver education, caregiver depression, the season of enrollment, residence, and household wealth status, we evaluated the role of reported food insecurity, dietary diversity, and specific food groups prior to hospitalization on time to recovery from wasting during the 6 months of posthospital discharge. Findings: Of 1286 included children, most participants (806, 63%) came from food-insecure households, including 170 (13%) with severe food insecurity, and 664 (52%) participants had insufficient dietary diversity. The median time to recovery was 96 days (18/100 child-months (95% CI: 17.0, 19.0)). Moderate (aHR 1.17 [0.96, 1.43]) and severe food insecurity (aHR 1.14 [0.88, 1.48]), and insufficient dietary diversity (aHR 1.07 [0.91, 1.25]) were not significantly associated with time to recovery. Children who had consumed legumes and nuts prior to diagnosis had a quicker recovery than those who did not (adjusted hazard ratio (aHR): 1.21 [1.01,1.44]). Consumption of dairy products (aHR 1.13 [0.96, 1.34], p = 0.14) and meat (aHR 1.11 [0.93, 1.33]), p = 0.23) were not statistically significantly associated with time to recovery. Consumption of fruits and vegetables (aHR 0.78 [0.65,0.94]) and breastfeeding (aHR 0.84 [0.71, 0.99]) before diagnosis were associated with longer time to recovery. Conclusion: Among wasted children discharged from hospital and managed in compliance with wasting guidelines, food insecurity and dietary diversity were not major determinants of recovery.     

Evaluating a Model of Added Sugar Intake Based on Amino Acid Carbon Isotope Ratios in a Controlled Feeding Study of U.S. Adults

Previous studies suggest that amino acid carbon stable isotope ratios (CIR_AAs) may serve as biomarkers of added sugar (AS) intake, but this has not been tested in a demographically diverse population. We conducted a 15-day feeding study of U.S. adults, recruited across sex, age, and BMI groups. Participants consumed personalized diets that resembled habitual intake, assessed using two consecutive 7-day food records. We measured serum (n = 99) CIR_AAs collected at the end of the feeding period and determined correlations with diet. We used forward selection to model AS intake using participant characteristics and 15 CIR_AAs. This model was internally validated using bootstrap optimism correction. Median (25th, 75th percentile) AS intake was 65.2 g/day (44.7, 81.4) and 9.5% (7.2%, 12.4%) of energy. The CIR of alanine had the highest, although modest, correlation with AS intake (r = 0.32, p = 0.001). Serum CIR_AAs were more highly correlated with animal food intakes, especially the ratio of animal to total protein. The AS model included sex, body weight and 6 CIR_AAs. This model had modest explanatory power (multiple R² = 0.38), and the optimism-corrected R² was lower (R² = 0.15). Further investigations in populations with wider ranges of AS intake are warranted.     

The Impact of Job-Demand-Control-Support on Leptin and Ghrelin as Biomarkers of Stress in Emergency Healthcare Workers

Despite the available literature on the consequences of night shiftwork on stress and food intake, its impact on leptin and ghrelin has never been studied. We previously demonstrated that leptin and ghrelin were biomarkers related to stress, and acute stress-induced a decrease in leptin levels and an increase in ghrelin levels. We performed a prospective observational study to assess the influence of night work, nutrition, and stress on the levels of ghrelin and leptin among emergency healthcare workers (HCWs). We took salivary samples at the beginning of a day shift and/or at the end of a night shift. We also monitored stress using the job demand-control-support model of Karasek. We recorded 24-h food intake during the day shift and the consecutive night shift and during night work and the day before. We included 161 emergency HCWs. Emergency HCWs had a tendency for decreased levels of leptin following the night shift compared to before the dayshift (p = 0.067). Furthermore, the main factors explaining the decrease in leptin levels were an increase in job-demand (coefficient −54.1, 95 CI −99.0 to −0.92) and a decrease in job control (−24.9, −49.5 to −0.29). Despite no significant changes in ghrelin levels between shifts, social support was the main factor explaining the increase in ghrelin (6.12, 0.74 to 11.5). Food intake (kcal) also had a negative impact on leptin levels, in addition to age. Ghrelin levels also decreased with body mass index, while age had the opposite effect. In conclusion, we confirmed that ghrelin and leptin as biomarkers of stress were directly linked to the job demand-control-support model of Karasek, when the main cofounders were considered.     

Emerging nanomedical strategies for direct targeting of pediatric and adult diffuse gliomas

High-grade gliomas, in particularly diffuse midline glioma, H3K27-altered in children and glioblastoma in adults, are the most lethal brain tumour with a dismal prognosis. Developments in modern medicine are constantly being applied in the search for a cure, although finding the right strategy remains elusive. Circumventing the blood–brain barrier is one of the biggest challenges when it comes to treating brain tumours. The cat and mouse game of finding the Trojan horse to traverse this barrier and deliver therapeutics to the brain has been a long and hard-fought struggle. Research is ongoing to find new and feasible ways to reach specific targets in the brain, with a special focus on inoperable or recurring brain tumours. Many options and combinations of options have been tested to date and continue to be so in the search to find the most effective and least toxic treatment paradigm. Although improvements are often small and slow, some of these strategies have already shown promise, shining a light of hope that finding the cure is feasible. In this review, we discuss recent findings that elucidate promising but atypical strategies for targeting gliomas and the implications that this work has on developing new treatment regimens. Subject terms: CNS cancer, Targeted therapies     

Non-aspirin non-steroidal anti-inflammatory drugs in colorectal cancer: a review of clinical studies

Colorectal cancer (CRC) chemoprevention is an area of interest. Non-steroidal anti-inflammatory drugs (NSAIDs) are anti-inflammatory agents which have been identified as cancer chemoprevention agents given that inflammation is thought to contribute to tumorigenesis. Most studies have demonstrated that the NSAID, aspirin, plays a beneficial role in the prevention of CRC and colonic adenomas. Non-aspirin NSAIDs (NA-NSAIDs) have also been studied in CRC chemoprevention. There is increasing literature around their role in pre-cancerous polyp prevention and in decreasing CRC incidence and CRC-related outcomes in certain high-risk subgroups. However, the use of NA-NSAIDs may be accompanied by increased risks of toxicity. Further studies are required to establish the associations between concurrent aspirin and NA-NSAID use, and CRC-related outcomes.Subject terms: Colorectal cancer, Cancer prevention     

Mutant p53 gain of function mediates cancer immune escape that is counteracted by APR-246

Background p53 mutants contribute to the chronic inflammatory tumour microenvironment (TME). In this study, we address the mechanism of how p53 mutants lead to chronic inflammation in tumours and how to transform it to restore cancer immune surveillance.Methods Our analysis of RNA-seq data from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project revealed that mutant p53 (mtp53) cancers correlated with chronic inflammation. We used cell-based assays and a mouse model to discover a novel gain of function of mtp53 and the effect of the mtp53 reactivating compound APR-246 on the anti-tumour immune response.Results We found that tumour samples from patients with breast carcinoma carrying mtp53 showed elevated Interferon (IFN) signalling, Tumour Inflammation Signature (TIS) score and infiltration of CD8+ T cells compared to wild type p53 (wtp53) tumours. We showed that the expression of IFN and immune checkpoints were elevated in tumour cells in a mtp53-dependent manner, suggesting a novel gain of function. Restoration of wt function to mtp53 by APR-246 induced the expression of endogenous retroviruses, IFN signalling and repressed immune checkpoints. Moreover, APR-246 promoted CD4+ T cells infiltration and IFN signalling and prevented CD8+ T cells exhaustion within the TME in vivo.Conclusions Breast carcinomas with mtp53 displayed enhanced inflammation. APR-246 boosted the interferon response or represses immune checkpoints in p53 mutant tumour cells, and restores cancer immune surveillance in vivo. Subject terms: Immunosurveillance, Targeted therapies     

Epigenetic analysis of cell-free DNA by fragmentomic profiling

Cell-free DNA (cfDNA) fragmentation patterns contain important molecular information linked to tissues of origin. We explored the possibility of using fragmentation patterns to predict cytosine-phosphate-guanine (CpG) methylation of cfDNA, obviating the use of bisulfite treatment and associated risks of DNA degradation. This study investigated the cfDNA cleavage profile surrounding a CpG (i.e., within an 11-nucleotide [nt] window) to analyze cfDNA methylation. The cfDNA cleavage proportion across positions within the window appeared nonrandom and exhibited correlation with methylation status. The mean cleavage proportion was ∼twofold higher at the cytosine of methylated CpGs than unmethylated ones in healthy controls. In contrast, the mean cleavage proportion rapidly decreased at the 1-nt position immediately preceding methylated CpGs. Such differential cleavages resulted in a characteristic change in relative presentations of CGN and NCG motifs at 5′ ends, where N represented any nucleotide. CGN/NCG motif ratios were correlated with methylation levels at tissue-specific methylated CpGs (e.g., placenta or liver) (Pearson’s absolute r > 0.86). cfDNA cleavage profiles were thus informative for cfDNA methylation and tissue-of-origin analyses. Using CG-containing end motifs, we achieved an area under a receiver operating characteristic curve (AUC) of 0.98 in differentiating patients with and without hepatocellular carcinoma and enhanced the positive predictive value of nasopharyngeal carcinoma screening (from 19.6 to 26.8%). Furthermore, we elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93. FRAGmentomics-based Methylation Analysis (FRAGMA) presents many possibilities for noninvasive prenatal, cancer, and organ transplantation assessment.

Fragmentation patterns of cell-free DNA (cfDNA) molecules contain a wealth of molecular information related to their tissues of origin (1). For instance, compared with the background DNA molecules that are mainly derived from the hematopoietic system (2, 3), size shortening of fetal and tumoral DNA molecules occurs in the plasma DNA of pregnant women and cancer patients, respectively (4–6). In addition, a series of 10-bp periodicities were present in fetal and tumoral DNA molecules below 146 bp, with a relative reduction in the major peak at 166 bp (1). Such characteristic size profiles suggest that the fragmentation of cfDNA may be associated with nucleosome structures (5, 7). Many important characteristics pertaining to cfDNA fragmentation have been unveiled recently, such as nucleosome footprints (8, 9), fragment end motifs (10), preferred ends (7, 11), and jagged ends (12), which are examples of fragmentomic markers (1).cfDNA fragmentomics is an emergent and actively pursued area, with wide-ranging biological and clinical implications. It has been reported that the use of fragmentation patterns of cfDNA could inform the expression status of genes (13, 14). Using mouse models, DNA nucleases (e.g., DNASE1L3) were found to play important roles in the generation of plasma DNA molecules (15, 16). Fragmentomic features, such as cfDNA end motifs and jagged ends, were further demonstrated to be useful for monitoring DNA nuclease activities, providing biomarkers for autoimmune diseases (e.g., systemic lupus erythematosus) (17, 18). In addition, the deficiencies of nuclease activities in a mouse model resulted in altered DNA methylation profiles of plasma DNA molecules (19). However, how cfDNA fragmentation patterns interplay with DNA methylation in human individuals under different pathophysiological conditions, such as pregnancy and oncogenesis, and in healthy patients without nuclease deficiency, is unknown. It is also not known whether fragmentomic features can be used to deduce cfDNA methylation status.A widely employed way to assess DNA methylation is through bisulfite sequencing (20). A key limitation of this approach is the severe degradation of DNA molecules caused by the bisulfite treatment (21), which greatly increases the sampling variation when analyzing rare target molecules (e.g., tumoral cfDNA at early stages of cancer). Many efforts have been made toward overcoming this issue. For example, Vaisvila et al. developed enzymatic methyl sequencing for which DNA molecules were treated using tet methylcytosine dioxygenase 2 and T4 phage β-glucosyltransferase, followed by the apolipoprotein B mRNA editing enzyme catalytic subunit 3A (APOBEC3A) treatment. Cytosine conversion based on enzymatic processes was reported to be much less destructive (22). Recently, researchers developed approaches making use of third-generation sequencing technologies such as single-molecule real-time sequencing (Pacific Biosciences) (23) and nanopore sequencing (24) to analyze cytosine-phosphate-guanine (CpG) methylation patterns in native DNA molecules, theoretically overcoming the above-mentioned limitation. However, compared with second-generation sequencing (also called next-generation sequencing [NGS]) technologies, the throughput of third-generation sequencing technologies is generally lower and the sequencing cost per nucleotide (nt) is much higher, thus restricting its immediate application in clinical settings. Here, we explore the feasibility of enabling the assessment of DNA methylation using fragmentomic characteristics of cfDNA molecules deduced from NGS results without the use of bisulfite or enzymatic treatment. If successful, such an approach could leverage the high throughput of NGS while obviating the use of chemical/enzymatic conversion and could potentially be readily integrated into currently used NGS-based platforms for cfDNA analysis.In this study, we utilize the fragmentation patterns proximal to a CpG site for deducing its methylation status. The fragmentation pattern is depicted by the frequency of cfDNA fragment ends at each position within a certain nt range relative to a CpG of interest, termed a cleavage profile (Fig. 1). Such a cleavage profile varies according to the methylation status of the CpG site of interest, providing the basis for methylation analysis by using fragmentomic features. We further correlated two types of end motifs (CGN and NCG; N represents any nucleotide of A, C, G, or T) resulting from differential cutting in the measurement window related to DNA methylation, attempting to construct a simplified approach for methylation analysis. Modeling CpG methylation using cfDNA fragmentation may facilitate noninvasive prenatal testing, cancer detection, and tissue-of-origin analysis (Fig. 1). Furthermore, we explore the feasibility of using deep learning to deduce the methylation status at single CpG resolution through the cleavage profile (Fig. 1). We refer to this FRAGmentomics-based Methylation Analysis as FRAGMA in this study.Open in a separate windowFig. 1.Schematic for FRAGMA of cfDNA molecules. cfDNA molecules were sequenced by massively parallel sequencing and aligned to the human reference genome. The cleavage proportion within an 11-nt window (the cleavage measurement window) was used to measure the cutting preference of cfDNA molecules. The patterns of cleavage proportion within a window (the cleavage profile) depended on the methylation status of one or more CpG sites associated with that window. For example, a methylated CpG site might confer a higher probability of cfDNA cutting at the cytosine in the CpG context, but an unmethylated site might not. Such methylation-dependent differential fragmentation within a cleavage measurement window resulted in the change in CGN/NCG motif ratio. Thus, the CGN/NCG motif ratio provided a simplified version for reflecting CpG methylation, allowing cfDNA tissue-of-origin analysis of cfDNA and cancer detection. Furthermore, the great number of cleavage profiles derived from cfDNA molecules might provide an opportunity to train a deep learning model for methylation prediction at the single CpG resolution.