Knee disorders in primary care: design and patient selection of the HONEUR knee cohort.

BACKGROUND: Knee complaints are a frequent reason for consultation in general practice. These patients constitute a specific population compared to secondary care patients. However, information to base treatment decisions on is generally derived from specialistic settings. Our cohort study is aimed at collecting knowledge about prognosis and prognostic factors of knee complaints presented in a primary care setting. This paper describes the methods used for data collection, and discusses potential selectiveness of patient recruitment. METHODS: This is a descriptive prospective cohort study with one-year follow-up. 40 Dutch GPs recruited consecutive patients with incident knee complaints aged 12 years and above from October 2001 to October 2003. Patients were assessed with questionnaires and standardised physical examinations. Additional measurements of subgroups included MRI for recent knee traumas and device assessed function measurements for non-traumatic patients. After the inclusion period we retrospectively searched the computerized medical files of participating GPs to obtain a sample to determine possible selective recruitment. We assessed differences in proportions of gender, traumatic onset of injury and age groups between participants and non-participants using Odds Ratios (OR) and 95% confidence intervals. RESULTS: We recruited 1068 patients. In a sample of 310 patients visiting the GP, we detected some selective recruitment, indicating an underrepresentation of patients aged 12 to 35 years (OR 1.70; 1.15-2.77), especially among men (OR 2.16; 1.12-4.18). The underrepresentation of patients with traumatic onset of injury was not statistically significant. CONCLUSION: This cohort is unique in its size, setting, and its range of both age and type of knee complaints. We believe the detected selective recruitment is unlikely to introduce significant bias, as the cohort will be divided into subgroups according to age group or traumatic onset of injury for future analyses. However, the underrepresentation of men in the age group of 12 to 35 years of age warrants caution. Based on the available data, we believe our cohort is an acceptable representation of patients with new knee complaints consulting the GP, and we expect no problems with extrapolation of the results to the general Dutch population

Two-component spike nanoparticle vaccine protects macaques from SARS-CoV-2 infection

Brouwer et al. present preclinical evidence in support of a COVID-19 vaccine candidate, designed as a self-assembling two-component protein nanoparticle displaying multiple copies of the SARS-CoV-2 spike protein, which induces strong neutralizing antibody responses and protects from high-dose SARS-CoV-2 challenge.The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is continuing to disrupt personal lives, global healthcare systems, and economies. Hence, there is an urgent need for a vaccine that prevents viral infection, transmission, and disease. Here, we present a two-component protein-based nanoparticle vaccine that displays multiple copies of the SARS-CoV-2 spike protein. Immunization studies show that this vaccine induces potent neutralizing antibody responses in mice, rabbits, and cynomolgus macaques. The vaccine-induced immunity protects macaques against a high-dose challenge, resulting in strongly reduced viral infection and replication i

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Angiogenic profiling and comparison of immortalized endothelial cells for functional genomics

Genomics efforts of the past decade have resulted in the identification of numerous genes with putative roles in disease processes, including tumor angiogenesis. To functionally validate these genes, cultured endothelial cells are indispensable tools, though these may not completely mimic the phenotype of tissue endothelial cells as the proper microenvironment is lacking. To obtain experimental data representative of normal physiology, the use of primary endothelial cells is preferred. However, these cells are usually limited in passage number, can be difficult to obtain and show great interindividual variety. Furthermore, transfection efficiency is very limited in primary cells, hampering applications in functional genomics and gene function analysis. The use of properly characterized alternative endothelial cell sources is therefore warranted. Here, we compared immortalized endothelial cells - HMEC, RF24 and EVLC2 - with primary HUVEC. We show that RF24, and to a slightly lesser extent HMEC, resembles primary HUVEC most on all facets examined. RF24, in contrast to EVLC2, express the endothelial markers CD31, CD34, CD105, vWF and VE-cadherin, and are capable of migration and tube formation in vitro. Furthermore, the expression levels of angiogenic growth factors and their receptors are comparable to that of primary EC. In addition, whereas primary HUVEC are resistant to transfection using common lipophilic transfection reagents, HMEC and RF24 could be readily transfected. Hence, these cells pose a valuable tool for functional genomics in angiogenesis research

Genetic map construction and QTL analysis of nitrogen use efficiency in spinach (Spinacia oleracea L.)

Cultivation of spinach requires high amounts of nitrogen (N), which puts a strain on the environment. A sustainable solution to this problem is to breed for crops with higher N use efficiency (NUE). The aim of this study was to provide tools for molecular breeding and to elucidate the genetic variation of factors contributing to NUE in spinach. A cross was made between two F1 hybrid cultivars contrasting in NUE. Several F1 progeny were self-pollinated and based on evaluation of the F2 generation, a mapping F2 population (335 individuals) of a single F1 was selected. SNP markers for the genetic map were discovered by RNA sequencing of the two parent cultivars, and 283 SNP markers were used to produce a genetic map comprising of six linkage groups (P01–P06), ranging in size from 46 to 116 cM. NUE related traits were determined for a set of F2:3 families grown under low and high N conditions in a hydroponics system under an Ingestad N-addition model. Interval mapping analysis detected 39 trait-specific QTLs, with several QTLs accumulating on P01 and P02 of the linkage map. The QTLs and in particular the P01 and P02 regions provide potential targets for the improvement of NUE in spinach