Normalization of single cell RNA-seq data remains a challenging task. The performance of different methods can vary greatly between datasets when unwanted factors and biology are associated. Most normalization methods also only remove the effects of unwanted variation for the cell embedding but not from gene-level data typically used for differential expression (DE) analysis to identify marker genes. We propose RUV-III-NB, a method that can be used to remove unwanted variation from both the cell embedding and gene-level counts. Using pseudo-replicates, RUV-III-NB explicitly takes into account potential association with biology when removing unwanted variation. The method can be used for both UMI or read counts and returns adjusted counts that can be used for downstream analyses such as clustering, DE and pseudotime analyses. Using published datasets with different technological platforms, kinds of biology and levels of association between biology and unwanted variation, we show that RUV-III-NB manages to remove library size and batch effects, strengthen biological signals, improve DE analyses, and lead to results exhibiting greater concordance with independent datasets of the same kind. The performance of RUV-III-NB is consistent and is not sensitive to the number of factors assumed to contribute to the unwanted variation.

Background Population surveys across the world have examined the impact of the COVID-19 pandemic on mental health. However, few have simultaneously examined independent cross-sectional data with longitudinal data, each of which have different strengths and weaknesses and facilitate the investigation of distinct research questions. This study aimed to investigate psychological distress and life satisfaction during the first and second lockdowns in the state of Victoria, Australia, and the social factors that may be affected by lockdowns and could affect mental health. Methods The VicHealth Victorian Coronavirus Wellbeing Impact Study included two 20-min opt-in online panel surveys conducted in May and September 2020 in Victoria, each with a sample of 2000 adults aged 18 + . A two-part study design was used: a repeated cross-sectional study of respondents who participated in Survey One and Survey Two, followed by a longitudinal nested cohort study. The primary exposures were social solidarity, social connectedness and staying connected with family and friends. Using logistic regression modelling, we explored the associations between our exposures and primary outcomes of psychological distress and life satisfaction with and without adjustment for covariates, both cross-sectionally and longitudinally. The results from the multivariable models were summarised using adjusted Odds Ratios (aOR), 95% Confidence Intervals (CI). Results Cross-sectional results indicated that the percentage of participants with low life satisfaction was significantly higher in the second survey sample (53%) compared to the first (47%). The percentage of participants with high psychological distress was higher but not significantly different between the two survey samples (14% first survey vs 16% second survey). Longitudinal study results indicated that lower social connectedness was significantly associated with higher psychological distress (aOR:3.3; 95% CI: 1.3–8.4) and lower life satisfaction (aOR:0.2; 95% CI: 0.1–0.4). Younger adults had higher psychological distress compared to older adults (aOR:6.8; 95% CI:1.5–31.1). Unemployment at the time of the first survey was significantly associated with lower life satisfaction at the second survey (aOR:0.5; 95% CI: 0.3–0.9). Conclusion This study supports the findings of other international studies. It also highlights the need to promote increased social connection and maintain it at times of isolation and separation, particularly amongst younger adults.

Background/Purpose Health state utilities (HSU) are a subjective measure of an individual's health-related quality of life (HRQoL), adjusted by societal or patient relative preference weights for living in different states of health-related quality of life (HRQoL), derived from patient-reported responses to multi-attribute utility instrument (MAUI), and can be used as inputs for cost-utility analyses and in clinical assessment. This research assessed associations of diet with subsequent HSU in a large international cohort of people living with multiple sclerosis (MS), a progressive autoimmune condition of the central nervous system. Methods HSUs were generated from responses to Short-Form Six-Dimension (SF-6D) MAUI, and quality-of-the-diet by Diet Habits Questionnaire (DHQ). Cross-sectional, and short- and long-term prospective associations of DHQ with HSU evaluated by linear regression at 2.5- and 5-years. Pooled prospective associations between DHQ and HSU evaluated using linear and quantile regression. Analyses adjusted for relevant demographic and clinical covariates. Results Among 839 participants, baseline DHQ scores showed short- and long-term associations with subsequent HSU, each 10-unit increase in total DHQ score associated with 0.008–0.012 higher HSU (out of 1.00). These associations were dose-dependent, those in the top two quartiles of baseline DHQ scores having 0.01–0.03 higher HSU at follow-up, 0.03 being the threshold for a minimally clinically important difference. Fat, fiber, and fruit/vegetable DHQ subscores were most strongly and consistently associated with better HSU outcomes. However, baseline meat and dairy consumption were associated with 0.01–0.02 lower HSU at subsequent follow-up. Conclusions A higher quality-of-the-diet showed robust prospective relationships with higher HSUs 2.5- and 5-years later, substantiating previous cross-sectional relationships in this cohort. Subject to replication, these results suggest interventions to improve the quality-of-the-diet may be effective to improve HRQoL in people living with MS.

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Background Several lifestyle factors have been associated with the onset and progression of multiple sclerosis (MS). Combining these lifestyle factors into scoring indices is an efficient way to assess their collective relationship with clinical outcomes. We examined the association of two lifestyle scores with clinically significant fatigue and change thereof over two years’ follow-up. Methods Data on sociodemographic, lifestyle and clinical characteristics surveyed from the international HOLISM cohort of people with MS at baseline and 2.5-year follow-up. Fatigue was defined by Fatigue Severity Scale (FSS), and healthy lifestyle by the Healthy Lifestyle Index Score (HLIS), and SNAP (Smoking, Nutrition, Alcohol, Physical Activity) score. Analyses by standard logistic and inverse probability treatment weighting (IPTW) models adjusted for age, sex, MS type, disability, comorbidity number, immunomodulatory medication use, prescription antifatigue medication use, and ongoing relapse symptoms; change in fatigue models also adjusted for baseline fatigue. Results 1,160 participants completed the FSS questionnaire at both timepoints, and roughly 62% had fatigue at each timepoint. By logistic regression, baseline HLIS and SNAP were each associated with lower risk of being fatigued at follow-up, persisting on adjustment. Using doubly-robust IPTW these associations were attenuated but high HLIS (OR = 0.89, 95% CI = 0.81-0.97) and SNAP (OR = 0.82, 95% CI = 0.73-0.90) were each associated with lower risk of fatigue at follow-up. Evaluating change in fatigue, however, there was no consistent association of either HLIS or SNAP score by either statistical method. Conclusions In this sample of people with MS, healthy lifestyle scores were associated with less fatigue 2.5 years later, though not with change in fatigue over this interval.

IntroductionPelvic inflammatory disease (PID) and ectopic pregnancy (EP) among women are important sequelae of sexually transmissible infections (STIs). We assessed recent trends in these STI-related morbidities in three Australian states (Victoria, New South Wales, Queensland). MethodsHospital admission and emergency presentation PID and EP rates among women 15–44 years were extracted and analysed by residential postcode for 2009–2014 using population and live birth denominators where relevant. Final data were available in 2017. Zero Inflated Poisson (ZIP) models were used to assess variation in rates by year, age, socio-economic disadvantage and area of residence. A sub-analysis of acute and/or STI-confirmed PID admissions was undertaken.ResultsAdmission and emergency presentation rates respectively per 1 00 000 women in 2014 were: i) 63.3 (95%CI: 60.8–65.9) and 97.0 (95%CI: 93.9–100.2) for PID; and ii) 107.8 (95%CI: 104.5–111.2) and 96.7 (95%CI: 93.6–99.9) for EP. Of all emergency cases, 68% of PID and 22% of EP were managed without admission. PID admission rates did not change by year, but acute/STI-confirmed PID admissions increased by 40% between 2009 and 2014 (Incidence rate ratio [IRR]: 1.4; 95% CI: 1.2–1.7). Emergency PID rates increased by 30% between 2009 and 2014 (IRR: 1.3; 95% CI: 1.2–1.5). PID admission and emergency rates were highest among women 15–24 years. Population based EP rates increased by 10% in emergency between 2009 and 2014 (IRR: 1.1; 95% CI: 1.1–1.2). EP rates per 1000 live births increased by 8% (IRR: 1.08; 95% CI: 1.06–1.11) for admissions and 27% (IRR: 1.27; 95% CI: 1.21–1.33) for emergency between 2009 and 2014. Increasing disadvantage and remoteness of area tended to be associated with higher PID and EP rates. ConclusionThese data show that, for the first time in two decades, STI-related sequelae diagnoses at Australian hospitals are increasing.