Forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods BackgroundForecasting models have played a pivotal role in health policy decision making during the coronavirus disease-2019 (COVID-19) pandemic. A combined forecast from multiple models will be typically more accurate than an individual forecast, but there are few examples of studies of combined forecasts of COVID-19 data, focusing mainly on simple mean and median  ensembles and involving short forecast evaluation periods. We aimed to investigate the accuracy of different ways of combining probabilistic forecasts of weekly COVID-19 mortality data, including two weighted methods that we developed previously, on an extended dataset and new dataset, and evaluate over a period of 52 weeks.

MethodsWe considered 95% interval and point forecasts of weekly incident and cumulative COVID-19 mortalities between 16 May 2020 and 8 May 2021 in multiple locations in the United States. We compared the accuracy of simple and more complex combining methods, as well as individual models.

ResultsThe average of the forecasts from the individual models was consistently more accurate than the average performance of these models (the mean combination), which provides a fundamental motivation for combining. Weighted combining performed well for both incident and cumulative mortalities, and for both interval and point forecasting. Our inverse score with tuning method was the most accurate overall. The median combination was a leading method in the last quarter for both mortalities, and it was consistently more accurate than the mean combination for point forecasting. For interval forecasts of cumulative mortality, the mean performed better than the median. The best performance of the leading individual model was in point forecasting.

ConclusionsCombining forecasts can improve the contribution of probabilistic forecasting to health policy decision making during epidemics, and, when there are sufficient historical data on forecast accuracy, weighted combining provides the most accurate method.
SARS-CoV-2 infection dynamics revealed by wastewater sequencing analysis and deconvolution The use of RNA sequencing from wastewater samples is a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach is independent from testing individuals and can therefore become the key tool to monitor this and potentially other viruses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given sequencing data from wastewater. Here, we provide an analysis of lineage dynamics in Berlin and New York City using wastewater sequencing and present PiGx SARS-CoV-2, a highly reproducible computational analysis pipeline with comprehensive reports. This end-to-end pipeline includes all steps from raw data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analyses. Using simulated datasets (in silico generated and spiked-in samples) we could demonstrate the accuracy of our pipeline calculating proportions of Variants of Concern (VOC) from environmental as well as pre-mixed samples (spiked-in). By applying our pipeline on a dataset of wastewater samples from Berlin between February 2021 and January 2022, we could reconstruct the emergence of B.1.1.7(alpha) in February/March 2021 and the replacement dynamics from B.1.617.2 (delta) to BA.1 and BA.2 (omicron) during the winter of 2021/2022. Using data from very-short-reads generated in an industrial scale setting, we could see even higher accuracy in our deconvolution. Lastly, using a targeted sequencing dataset from New York City (receptor-binding-domain (RBD) only), we could reproduce the results recovering the proportions of the so-called cryptic lineages shown in the original study. Overall our study provides an in-depth analysis reconstructing virus lineage dynamics from wastewater, and that our tool can be used to identify new mutations and to detect any emerging new lineages with different amplification and sequencing methods. Our approach can support efforts to establish continuous monitoring and early-warning projects for detecting SARS-CoV-2 or any other pathogen.
The incidence of delirium in an acute geriatric community hospital: an observational cohort feasibility study. ObjectivesDelirium in hospitalised older adults is associated with negative health outcomes. Admission to an alternative care setting may lower the incidence of delirium. The Acute Geriatric Community Hospital (AGCH) was recently opened in the Netherlands and uses a multi-component non-pharmacological intervention strategy to prevent delirium. The objective of this study was to describe the incidence of delirium at the AGCH and compare this incidence to existing rates from literature. If a possible effect on delirium is seen in this comparison this would support conducting a larger prospectively controlled study on delirium in this new care setting.

DesignProspective cohort feasibility study; exploratory meta-analysis of proportions.

Setting and ParticipantsThe AGCH is an acute geriatric unit in a skilled nursing facility for patients aged >65 years with acute medical conditions.

MethodsDelirium assessment using the Confusion Assessment Method (CAM) upon admission and on day one, two and three or until delirium had resolved. Patients charts were reviewed if CAM was missing. In an linear mixed-effects model, the delirium incidence rate in AGCH was compared to pooled delirium incidence rates from six studies found in a high-quality review.

Results214 patients from the AGCH (mean age 81.9 years, 47% male, 12% with a history of dementia) were included in the analysis. Delirium developed in 8% (18/214) (95% confidence interval [CI] 5-13%) of patients during AGCH admission compared to 16% (95% CI 12-21%) in hospitals. Admission to the AGCH was associated with a decreased delirium incidence rate compared to the hospital control group (OR[odds ratio]= 0.49, 95% CI 0.24-0.98, p-value=0.044).

Conclusions and implicationsThe delirium incidence in the AGCH was low compared to those incidences found in general hospitals in literature. Based on these findings a controlled observational or randomized study measuring delirium in this care setting is recommended. Impact of tozinameran (BNT162b2) mRNA vaccine on kidney transplant and chronic dialysis patients: 3-5 months followup BackgroundDetermining the humoral immunogenicity of tozinameran (BNT162b2) vaccine in patients requiring chronic renal replacement therapy, and its impact on COVID-19 morbidity several months after vaccination, will guide risk assessment and subsequent changes in vaccination policy.

MethodsIn a prospective post-vaccination cohort study with up to 5 months follow-up we studied outpatient dialysis and kidney transplant patients and respective healthcare teams. Outcomes were anti S1/S2 antibody response to vaccine or infection and infection rate during followup.

Results175 dialysis patients (40% women, 65{+/-}15 years), 252 kidney transplant patients (33% women, 54{+/-}14 years) and 71 controls (65% women, 44{+/-}14 years) were followed. Three months or longer after vaccination we detected anti S1/S2 IgG antibodies in 80% of dialysis patients, 44% of transplant recipients and 100% of controls, whereas respective rates after infection were 94%, 75% and 100%. Predictors of non-response were older age, diabetes, history of cancer, lower lymphocyte count and lower vitamin-D levels. Factors associated with lower titers in dialysis patients were modality (hemodialysis vs peritoneal) and high serum ferritin levels. In transplant patients, hypertension and higher calcineurin or mTOR inhibitor drug levels were linked with diminished antibody response. Vaccination associated with fewer subsequent infections (HR=0.23, p<0.05). Moreover, higher antibody titers associated with fewer events, HR 0.41 for each unit increased in log10titer (p<0.05).

ConclusionsDialysis patients, and more so kidney transplant recipients, mounted reduced antibody response to COVID-19 mRNA vaccination, and lesser humoral response associated with more infections. Measures to identify and protect non-responsive patients are urgently required.

SignificanceReports on the humoral immunogenicity of SARS-CoV-2 mRNA vaccines in patients with end stage renal disease are scarce, and association with subsequent COVID-19 morbidity is unknown. In this cohort study that included 175 patients treated with dialysis, 252 kidney transplant recipients and 71 control volunteers, the proportion achieving an antibody response was time- and group-dependent, reaching 80%, 44% and 100% at 3 months post prime inoculation. Personal history of vaccination, positive antibody responses and antibody titers associated with significantly lower risk of COVID-19 infection. Thus, in patients with end stage renal disease, SARS-CoV-2 antibody testing may be warranted after vaccination, to identify non-responders at higher risk for disease. Estimating Vaccination Effects and Variant Strains on COVID-19 outbreak course in Japan, as of August, 2021 BackgroundAs of the end of 2021 year, the rate of completion for second-dose administration was almost 80% in Japan.

ObjectWe evaluated waning of vaccine effectiveness for COVID-19 in Japan, controlling for mutated strains, the Olympic Games, and countermeasures.

MethodThe effective reproduction number R(t) was regressed on current vaccine coverage and data of a certain number of days prior, as well as shares of mutated strains, and an Olympic Games dummy variable along with data of temperature, humidity, mobility, and countermeasures. The study period was February, 2020 through December 7, as of December 28, 2021.

ResultsEstimation results indicate that the past vaccine coverage of older than 60 days prior raises R(t) significantly and cancelled vaccine effectiveness completely.

Discussion and ConclusionResults indicate significant waning of vaccine effectiveness from 60 days after the second dose. Children develop strong and sustained cross-reactive immune responses against Spike protein following SARS-CoV-2 infection, with enhanced recognition of variants of concern SARS-CoV-2 infection is generally mild or asymptomatic in children but the biological basis for this is unclear. We studied the profile of antibody and cellular immunity in children aged 3-11 years in comparison with adults. Antibody responses against spike and receptor binding domain (RBD) were high in children and seroconversion boosted antibody responses against seasonal Beta-coronaviruses through cross-recognition of the S2 domain. Seroneutralisation assays against alpha, beta and delta SARS-CoV-2 variants demonstrated comparable neutralising activity between children and adults. T cell responses against spike were >2-fold higher in children compared to adults and displayed a TH1 cytokine profile. SARS-CoV-2 spike-specific T cells were also detected in many seronegative children, revealing pre-existing responses that were cross-reactive with seasonal Alpha and Beta-coronaviruses. Importantly, all children retained high antibody titres and cellular responses at 6 months after infection whilst relative antibody waning was seen in adults. Spike-specific responses in children also remained broadly stable beyond 12 months. Children thus distinctly generate robust, cross-reactive and sustained immune responses after SARS-CoV-2 infection with focussed specificity against spike protein. These observations demonstrate novel features of SARS-CoV-2-specific immune responses in children and may provide insight into their relative clinical protection. Furthermore, this information will help to guide the introduction of vaccination regimens in the paediatric population. Oral, similar to intranasal, administration of oxytocin decreases top-down social attention The neuropeptide oxytocin (OXT) modulates social cognition by increasing attention towards social cues and may have therapeutic potential for impaired social attention in disorders such as autism. Intranasal administration of OXT is widely used to examine its functional effects in both adults and children and is assumed to enter the brain directly via this route. However, OXT can also influence brain function via increased blood concentrations and we have recently shown that orally (lingual) administered OXT also modulates neural responses to emotional faces and may be better tolerated for therapeutic use. Here, we examined if 24IU OXT administered orally can facilitate social attention. In a randomized, placebo-controlled, pharmacological study we used a validated emotional anti-saccade eye-tracking paradigm to explore effects of oral OXT on bottom-up and top-down attention processing in 80 healthy male subjects. Our findings showed in terms of top-down attention, oral OXT increased errors for both social (angry, fearful, happy, sad and neutral emotion faces) and non-social stimuli (oval shapes) in the anti-saccade condition but only increased response latencies in the social condition. It also significantly reduced post-task state anxiety but this was not correlated with task performance. Comparison with our previous intranasal OXT study using the same task revealed both routes have a similar effect on increasing anti-saccade errors and response latencies and reducing state anxiety. Overall, findings suggest that oral administration of OXT produces similar effects on top-down social attention control and anxiety as intranasal administration and may therefore have therapeutic utility. Xenobiotic tracers uncover the gastrointestinal passage, intestinal epithelial cellular uptake and Ago2 loading of milk miRNAs in neonates BackgroundExclusive breastfeeding is the best source of nutrition for most infants, but it is not always possible. Enteral nutrition influences intestinal gene regulation and the susceptibility for inflammatory bowel disorders, such as necrotizing enterocolitis (NEC). In modern neonatology it is observed that lactase activity increases during intestinal maturation, but formula-fed infants exhibit lower activity levels than milk-fed infants.

ObjectiveWe interrogate the transmissibility of milk miRNAs, since human breast milk has a high miRNA content in comparison to other body fluids. Our data contribute to the controversial discussion whether milk miRNAs could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals.

DesignFollowing their cross-species profiling via miRNA deep-sequencing we utilized dietary xenobiotic taxon-specific milk miRNA as tracers in human and porcine neonates, followed by functional studies in primary human fetal intestinal epithelial cells (HIEC-6) using Ad5-mediated miRNA-gene transfer.

ResultsWe show that mammals have in common many milk miRNAs yet exhibit taxon-specific miRNA fingerprints. We traced intact bovine-specific miRNAs from formula-nutrition in human preterm stool and 9 days after the onset of enteral feeding in intestinal cells of preterm piglets. Few hours after introducing enteral feeding in preterm piglets with supplemented reporter miRNAs (cel-miR-39-5p/-3p), we observed enrichment of the xenobiotic cel-miR in blood serum and in Ago2-immunocomplexes from intestinal biopsies. In contrast, we did not observe xenobiotic miRNAs in neonatal porcine cerebrospinal fluid.

ConclusionsTaken together, our data point to a transmissibility of milk miRNA signals, which could be relevant at least for intestinal maturation. Ad5-based miRNA-gene transfer into HIEC-6 revealed putative milk miRNA targets on the protein and transcriptome levels. Results suggest that milk miRNAs could influence gene expression in intestinal epithelia of neonates under special conditions.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/21262525v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@8e0435org.highwire.dtl.DTLVardef@1b6747corg.highwire.dtl.DTLVardef@1998821org.highwire.dtl.DTLVardef@b84a04_HPS_FORMAT_FIGEXP  M_FIG C_FIG It is already known that exclusive breastfeeding is the best source of nutrition for neonates.Human breast milk has a high miRNA content in comparison to other body fluids. It is controversially discussed whether they could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals. Here, we contribute important new findings: Mammals have in common a significant number of milk miRNAs yet exhibit taxon-specific fingerprints. These differences allowed us to exploit xenobiotic miRNAs as tracers in human preterm neonates, who routinely received formula-supplemented nutrition in addition to breast milk. Tracer miRNAs survived the gastrointestinal (GI) transit in human preterm neonates. In a preterm piglet model the reporter miRNA did not only survive GI transit, but accumulated in the bloodstream few hours post-feeding. Moreover, we show that, cel-mir-39-5p and cel-miR-39-3p became loaded to Ago2 in intestinal tissue samples, which is prerequisite for milk microRNAs biological relevance. Adenovirus type 5-based miRNA-gene transfer into HIEC-6 allowed us to examine predicted bovine milk miRNA targets on the protein and transcriptome levels. Global reports of takotsubo (stress) cardiomyopathy following COVID-19 vaccination: a systematic review and meta-analysis Background and aimsConcerns have been raised recently about takotsubo cardiomyopathy after receiving COVID-19 vaccines, particularly the messenger RNA (mRNA) vaccines. The goal of this study was to compile case reports in order to provide a comprehensive overview of takotsubo cardiomyopathy associated with COVID-19 vaccines.

MethodsFrom inception until March 10, 2022, a systematic literature search was conducted in PubMed and Google Scholar. The study included individuals who developed cardiac takotsubo cardiomyopathy as a result of receiving COVID-19 vaccinations, regardless of the type of vaccine or dose.

ResultsEight studies, including 8 cases, participated in the current systematic review. The median age was 61.6 years; 87.5% were female, while 12.5% were male. 75% of the patients received the mRNA COVID-19 vaccines, while 25% received other types. In addition, takotsubo cardiomyopathy occurred in 62.5% of patients after receiving the first dose and another 25% after the second dose of COVID-19 vaccines. Moreover, the mean number of days to the onset of symptoms was 2.62 days. All cases had an elevated troponin test and abnormal ECG findings. The left ventricular ejection fraction (LVEF) was above 50% among all cases. In terms of the average length of stay in the hospital, 62.5% stayed for 10.2 days, and all cases recovered from their symptoms.

ConclusionTakotsubo (stress) cardiomyopathy complications that are associated with COVID-19 vaccination are rare, they can be life-threatening. Chest pain should be considered an alarming symptom, especially in those who had received a second dose of the vaccine in the last 3 days. For diagnosis, CK-MB and troponin are better biomarkers to confirm myocarditis than CRP, ESR, and NT-proBNP. All of cases completely recovered. Sensitivity of SARS-CoV-2 antigen-detecting rapid tests for Omicron variant BackgroundThe emergence of each novel SARS-CoV-2 variants of concern (VOCs) requires investigation of its potential impact on the performance of diagnostic tests in use, including Antigen-detecting rapid diagnostic tests (Ag-RDT). Although anecdotal reports have been circulating that the newly emerged Omicron variant is in principle detectable by Ag-RDTs, few data on sensitivity are available.

MethodsWe have performed 1) analytical sensitivity testing with cultured virus in eight Ag-RDTs and 2) retrospective testing in duplicates with clinical samples from vaccinated individuals with Omicron (n=18) or Delta (n=17) breakthrough infection on seven Ag-RDTs.

FindingsOverall, we have found large heterogenicity between Ag-RDTs for detecting Omicron. When using cultured virus, we observed a trend towards lower sensitivity for Omicron detection compared to earlier circulating SARS-CoV-2 and the other VOCs. When comparing performance for Delta and Omicron in a comparable set of clinical samples in seven Ag-RDTs, 124/252 (49.2%) of all test performed showed a positive result for Omicron compared to 156/238 (65.6%) for Delta samples. Sensitivity for both Omicron and Delta between Ag-RDTs was highly variable. Four out of seven Ag-RDTs showed significantly lower sensitivity (p<0.001) to detect Omicron when compared to Delta while three had comparable sensitivity to Delta.

InterpretationSensitivity for detecting Omicron is highly variable between Ag-RDTs, necessitating a careful consideration when using these tests to guide infection prevention measures. While analytical and retrospective testing may be a proxy and timely solution to generate performance data, it is not a replacement for clinical evaluations which are urgently needed. Biological and technical reasons for detection failure by some Ag-RDTs need to be further investigated.

FundingThis work was supported by the Swiss National Science Foundation (grant numbers 196383, 196644 and 198412), the Fondation Ancrage Bienfaisance du Groupe Pictet, the Fondation Privee des Hopiteaux Universitaires de Geneve and FIND, the global alliance for diagnostics. Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

MethodsUsing data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

FindingsThe model predicts the progression to diabetic kidney disease with accuracy: 0.96{+/-}0.25 and 0.96{+/-}0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75{+/-}0.14 and 0.79{+/-}0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

InterpretationWith further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

FundingThis study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Research in context

Evidence before this studyMicrovascular diabetes complications (DCs), such as diabetic kidney disease (DKD) and diabetic retinopathy (DR), lead to increased mortality, blindness, kidney failure and overall decreased quality of life in individuals with diabetes.

Added value of this studyWe have developed four algorithms based on traditional risk factors alone and risk factors with metabolomic and lipidomic data. Two accurately predicted the future progression in individuals with type 1 diabetes. The top predictors chosen by the algorithm were hemoglobin A1c, albuminuria and retinopathy status at baseline for diabetic retinopathy. The most promising models predicted future diabetic kidney disease in which albuminuria, eGFR, retinopathy status at baseline were complemented with a number of ketones and sugar derivatives.

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments. Comparison of respiratory protection during exercising tasks between different wearing methods of replaceable particulate respirators and powered air-purifying respirators BackgroundThis study evaluated the differences in respiratory protection between replaceable particulate respirators (RPRs) and powered air-purifying respirators (PAPRs), with different wearing methods, during exercising tasks.

MethodsTen participants wore either RPR or PAPR according to the recommended method, with a knit cover placed between the facepiece cushion and the face, or with the headband on a helmet. We measured the number of particles inside and outside the respiratory protective equipment (RPE) during exercising tasks for each wearing variation. The exercise state was set to exercise with an ergometer set at 80W load. While exercising tasks, the participants performed five actions adopted from JIS T8150 in 2018 (1. Normal breathing, 2. Deep breathing, 3. Turning head side to side, 4. Moving head up and down, 5. Talking). Each action was performed for 1 min. For measurements of exercise state, after 10 minutes of exercise tasks, we measured while the exercise was continued. The fit factor was calculated by dividing the concentration within the RPE by the concentration outside of it. Data were analyzed after they were log-transformed with a linear mixed model, with fit factor as the dependent variable.

ResultsWe compared the results with experimental data of resting state reported in our previous studies. Fit factor of RPRs in the exercise state was significantly lower (p<0.001) than that in the resting state, indicating inadequate respiratory protection. In contrast, the fit factor of PAPRs during exercising tasks was significantly lower (p<0.001) than that at rest; however, respiratory protection was maintained. PAPR did not show a significant decrease (p=1.000) in fit factor owing to the wearing variations during exercising tasks.

ConclusionsPAPRs were found to be superior to RPRs in terms of respiratory protection. PAPRs are better than RPRs for workers who have to wear RPE inappropriately due to health problems. Decision curve analysis to identify optimal candidates of liver resection for intermediate-stage hepatocellular carcinoma with hepatitis B cirrhosis：A cohort study BackgroundThe selection criterion for liver resection (LR) in intermediate-stage (IM) hepatocellular carcinoma (HCC) is still controversial. This study aims to compare LR and transarterial chemoembolization in the range of predicted death risk

MethodsThe multivariable Cox regression model (MVR) was estimated to predict mortality at 5yr. The cut-off values were determined by a two-piece-wise linear regression model, decision curve analysis with MVR model, and hazard ratio curve for treatment plotted against the predicted mortality.

Results825 IM-HCC with hepatitis B cirrhosis were included for analysis (TACE, n=622; LR, n=203). The 5-yr overall survival rate of LR patients was higher than the TACE group (52.8% vs. 20.8%; P<0.0001). The line of LR and TACE were crossing with predicted death risk at 100% (P for interaction =0.008). The benefit of LR versus TACE decreased progressively as predicted death risk>0.55 (95%CI: 0.45,0.62). When predicted death risk over 0.7, decision curve analysis suggested that LR and TACE did not increase net benefit. Patients were then divided into four subgroups by the cut-off values (<0.45, 0.45[&ge;] /<0.62, 0.62[&ge;] /<0.7, [&ge;] 0.7). The stratified analysis of treatment in different subgroups, hazard ratios were 0.39 (95%CI: 0.27, 0.56), 0.36 (95%CI: 0.23, 0.56), 0.51 (95%CI: 0.27, 0.98), and 0.46 (95%CI: 0.27, 0.80), respectively.

ConclusionsLR reached the maximal relative utility in the interval of 0.45 to 0.62, and both LR and TACE did not increase net benefit at the 5-yr death risk over 0.7. The Outcome of Gynecologic Cancer Patients With Covid-19 Infection: A Systematic Review And Meta-Analysis ObjectiveCancer is a comorbidity that leads to progressive worsening of Covid-19 with increased mortality. This is a systematic review and meta-analysis to yield evidence of adverse outcomes of Covid-19 in gynecologic cancer.

MethodsSearches through PubMed, Google Scholar, ScienceDirect, and medRxiv to find articles on the outcome of gynecologic cancer with Covid-19 (24 July 2021-19 February 2022). Newcastle-Ottawa Scale tool is used to evaluate the quality of included studies. Pooled odds ratio (OR), 95% confidence interval (CI), random-effects model were presented. This study was registered to PROSPERO (CRD42021256557).

ResultsWe accepted 51 studies (1991 gynecologic cancer with Covid-19). Covid-19 infection was lower in gynecologic cancer vs hematologic cancer (OR 0.71, CI 0.56-0.90, p 0.005). Severe Covid and death were lower in gynecologic cancer vs lung and hematologic cancer (OR 0.36, CI 0.16-0.80, p 0.01), (OR 0.52, CI 0.44-0.62, p <0.0001), (OR 0.26, CI 0.10-0.67 p 0.005), (OR 0.63, CI 0.47-0.83, p 0.001) respectively. Increased Covid death is seen in gynecologic cancer vs breast, non-covid cancer, and non-cancer covid (OR 1.50, CI 1.20-1.88, p 0.0004), (OR 11.83, CI 8.20-17.07, p <0.0001), (OR 2.98, CI 2.23-3.98, p <0.0001) respectively.

ConclusionGynecologic cancer has higher Covid-19 adverse outcomes compared to non-cancer, breast cancer, non-metastatic, and Covid-19 negative population. Gynecologic cancer has fewer Covid-19 adverse outcomes compared to other cancer types, lung cancer, and hematologic cancer. These findings may aid health policies and services during the ongoing global pandemic. Meta-analytic findings on reading in children with cochlear implants This meta-analysis study aims to quantify the group differences in reading skills between children with cochlear implants and their hearing peers and between children with cochlear implants and children with hearing aids (aged between 3 to 18 years old). Of the 5,642 articles screened, 47 articles met predetermined inclusion criteria (published between 2002 and 2019). The robust variance estimation based meta-analysis models were used to synthesize all the effect sizes. Children with cochlear implants scored significantly lower than their hearing peers in phonological awareness (g = - 1.62, p < .001), vocabulary (g = -1.50, p < .001), decoding (g = -1.24, p < .001), and reading comprehension (g = -1.39, p < .001), but not for fluency (g = -.67, p = .054). Compared to children with hearing aids, children with cochlear implants scored significantly lower in phonological awareness (g = -.30, p = .028). The percentage of unilateral cochlear implant negatively impacts the group difference between children with cochlear implants and their hearing peers. Findings from this study confirm a positive shift in reading outcomes for profoundly deaf children due to cochlear implantation. Some children with cochlear implants may need additional supports in educational settings. COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness BackgroundMultiple COVID-19 vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh province, Pakistan (population: 48 million).

Methods and FindingsWe fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalization outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario.

We project that one-year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5 year duration of protection is likely to avert around 0.9 (95% Credible Interval: 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Varying these assumptions, we generally find that prioritizing the older (65+) population prevents more deaths, but broad distribution from the outset is economically comparable in many scenarios, and either scheme can be cost-effective for low per-dose costs. However, high vaccine prices ($10/dose) may not be cost-effective.

The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses.

These projections are limited by the mechanisms present in the model. Because the model is a single-population compartmental model, detailed impacts of non-pharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritizing groups like healthcare or other essential workers. Additionally, because the future impact and implementation cost of NPIs is uncertain, how these would interact with vaccination remains an open question.

ConclusionsCOVID-19 vaccination can have a considerable health impact, and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact, but the advantage of focusing initially on older, high-risk populations may be smaller in generally younger populations where many people have already been infected, typical of many low- and -middle income countries, as long as vaccination gives good protection against infection as well as disease.

Author SummaryO_ST_ABSWhy Was This Study Done?C_ST_ABS- The evidence base for health and economic impact of COVID-19 vaccination in low- and middle-income settings is limited.
- Searching PubMed, medRxiv, and econLit using the search term ("coronavirus" OR "covid" OR "ncov") AND ("vaccination" OR "immunisation") AND ("model" OR "cost" OR "economic") for full text articles published in any language between 1 January 2020 and 20 January 2021, returned 29 (PubMed), 1,167 (medRxiv) and 0 (econLit) studies: 20 overall were relevant, with only 4 exclusively focused on low- or middle-income countries (India, China, Mexico), while 3 multi-country analyses also included low- or middle-income settings,
- However only three of these studies are considered economic outcomes, all of them comparing the costs of vaccination to the costs of non-pharmaceutical interventions and concluding that both are necessary to reduce infections and maximise economic benefit.
- The majority of studies are set in high-income settings and conclude that targeting COVID-19 vaccination to older age groups is the preferred strategy to minimise mortality, particularly when vaccine supplies are constrained, while other age- or occupational risk groups should be priorities when vaccine availability increases or when other policy objectives are pursued.


What Did the Researchers Do and Find?- We combined epidemiological and economic analysis of COVID-19 vaccination based on real-world disease and programmatic information in the Sindh province of Pakistan.
- We found vaccination in this setting is likely to be highly cost-effective, and even cost saving, as long as the vaccine is reasonably priced and efficacy is high.
- Unlike studies in high-income settings, we also found that vaccination programmes targeting all adults may have almost as much benefit as those initially targeted at older populations, likely reflecting the higher previous infection rates and different demography in these settings.


What Do These Findings Mean?- Lower- and middle-income countries (LMICs) and international bodies providing guidance for LMICs need to consider evidence specific to these settings when making recommendations about COVID-19 vaccination.
- Further data and model-based analyses in such settings are urgently needed in order to ensure that vaccination decisions are appropriate to these contexts. Genetic control of fetal placental genomics contributes to development of health and disease As the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we performed distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At P < 2.5 x 10-6, we detected 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explained 4 early-life traits but no later-in-life traits. 89 GTAs showed significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells showed that knockdown of mediator gene EPS15 upregulated predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course. Classifying Radiology Abstracts with Deep Learning BackgroundThe Radiological Society of North America (RSNA) receives more than 8000 abstracts yearly for scientific presentations, scientific posters, and scientific papers. Each abstract is assigned manually one of 16 top-level categories (e.g. "Breast Imaging") for workflow purposes. Additionally, each abstract receives a grade from 1-10 based on a variety of subjective factors such as style and perceived writing quality. Using machine learning to automate, at least partially, the categorization of abstract submissions can result in saving many hours of manual labor.

MethodsA total of 45527 RSNA abstract submissions from 2014 through 2019 were ingested, tokenized, and pre-processed with a standard natural language programming protocol. A bag-of-words (BOW) model was used as a baseline to evaluate two more sophisticated models, convolutional neural networks and recurrent neural networks, and also evaluate an ensemble model featuring all three neural networks.

Resultsensemble model was able to achieve 73% testing accuracy for classifying the 16 top-level categories, outperforming all other models. The top model for classifying abstract grade was also an ensemble model, achieving a mean average error (MAE) of 1.01.

ConclusionWhile the baseline BOW model was the highest performing individual classifier, ensemble models that included state-of-the-art neural networks were able to outperform it. Our research shows that machine learning techniques can, to a reasonable degree of accuracy, predict both objective factors such as abstract category as well as subjective factors such as abstract grade. This work builds upon previous research involving using natural language processing on scientific abstracts to make useful inferences that address a meaningful problem. Correction of measurement error in a commercial multiple-breath washout device RationaleNitrogen multiple-breath washout (N2MBW) is an established technique to assess functional residual capacity (FRC) and ventilation inhomogeneity in the lung. Accurate measurement of gas concentrations is essential for the appropriate calculation of clinical outcomes.

ObjectivesWe investigated the accuracy of oxygen and carbon dioxide measurements used for the indirect calculation of nitrogen concentration in a commercial MBW device (Exhalyzer D, Eco Medics AG, Duernten, Switzerland) and its impact on FRC and lung clearance index (LCI).

MethodsHigh precision calibration gas mixtures and mass spectrometry were used to evaluate sensor output. We assessed the impact of corrected signal processing on FRC and LCI in a dataset of healthy children and children with cystic fibrosis using custom analysis software.

ResultsWe found inadequate correction for the cross sensitivity of the oxygen and carbon dioxide sensors in the Exhalyzer D device. This results in an overestimation of expired nitrogen concentration, and consequently FRC and LCI outcomes. Breath-by-breath correction of this error reduced mean (SD) FRC by 8.9 (2.2)% and LCI by 11.9 (4.0)%. It also resulted in almost complete disappearance of the tissue nitrogen signal at the end of measurements.

ConclusionsInadequate correction for cross sensitivity between the oxygen and carbon dioxide gas sensors of the Exhalyzer D device leads to an overestimation of FRC and LCI. Correction of this error is possible and could be applied by re-analysing the measurements breath-by-breath in an updated software version.

Grants, Gifts, Equipment, DrugsEco Medics AG (Duernten, Switzerland) provided a research version of their commercial software Spiroware 3.2.1 including insight on signal processing algorithms and helped with the acquisition of mass spectrometry measurements. This project was funded by the Swiss National Science Foundation, Grant Nr. 182719 (P. Latzin) and 168173 (K. Ramsey) CD19+IgD+CD27- naive B Cells as predictors of humoral response to COVID 19 mRNA vaccination in immunocompromised patients Immunocompromised patients are considered high-risk and prioritized for vaccination against COVID-19. We aimed to analyze B-cell subsets in these patients to identify potential predictors of humoral vaccination response. Patients (n=120) suffering from hematologic malignancies or other causes of immunodeficiency and healthy controls (n=79) received a full vaccination series with an mRNA vaccine. B-cell subsets were analyzed prior to vaccination. Two independent anti-SARS-CoV-2 immunoassays targeting the receptor-binding domain (RBD) or trimeric S protein (TSP) were performed three to four weeks after the second vaccination. Seroconversion occurred in 100% of healthy controls, in contrast to 67% (RBD) and 82% (TSP) of immunocompromised patients, while only 32% (RBD) and 22% (TSP) achieved antibody levels comparable to those of healthy controls. The number of circulating CD19+IgD+CD27- naive B cells was strongly associated with antibody levels ({rho}=0.761, P<0.001) and the only independent predictor for achieving antibody levels comparable to healthy controls (OR 1.07 per 10-{micro}l increase, 95%CI 1.02-1.12, P=0.009). Receiver operating characteristic analysis identified a cut-off at [&ge;]61 naive B cells per {micro}l to discriminate between patients with and without an optimal antibody response. Consequently, measuring naive B cells in immunocompromised hematologic patients could be useful in predicting their humoral vaccination response. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Quantifying phenotype and genotype distributions in single muscle fibres from patients carrying the pathogenic mtDNA variant m.3243A>G Cells are thought to tolerate the presence of heteroplasmic pathogenic mitochondrial (mt)DNA variants, up to a threshold proportion with little or no functional consequence, only developing a detectable oxidative phosphorylation (OXPHOS) defect once this threshold is exceeded. We hypothesised that, given the highly variable phenotypic presentation and severity of disease caused by the most common heteroplasmic pathogenic mtDNA variant m.3243A>G, this threshold may vary between patients. To estimate this threshold we examined the relationship between m.3243A>G level and deficiency of respiratory complexes I and IV in hundreds of single skeletal muscle fibres captured by laser microdissection from 17 patients carrying the m.3243A>G variant. We confirmed that tissue homogenate m.3243A>G level is a poor surrogate for the broad and complex distributions of m.3243A>G level in single cells from individual patients. We used unsupervised machine learning to characterise the biochemical status of muscle fibres, based on immunocytochemical measurements and estimate that the m.3243A>G threshold proportion above which myofibres develop a respiratory complex defect is 82.8% (IQR:2.7%). We do not find any significant difference in threshold between individuals, however we demonstrate that the pattern of respiratory complex defect and the distribution of m.3243A>G varies considerably between patients. This observation suggests that the pathogenesis of m.3243A>G is more diverse than previously thought.