A New Variant Among Newcastle Disease Viruses Isolated in the Democratic Republic of the Congo in 2018 and 2019.

Newcastle disease (ND) is a highly transmissible and devastating disease that affects poultry and wild birds worldwide. Comprehensive knowledge regarding the characteristics and epidemiological factors of the ND virus (NDV) is critical for the control and prevention of ND. Effective vaccinations can prevent and control the spread of the NDV in poultry populations. For decades, the Democratic Republic of the Congo (DRC) has reported the impacts of ND on commercial and traditional poultry farming systems. The reports were preliminary clinical observations, and few cases were confirmed in the laboratory. However, data on the phylogenetic, genetic, and virological characteristics of NDVs circulating in the DRC are not available. In this study, the whole-genome sequences of three NDV isolates obtained using the next-generation sequencing method revealed two isolates that were a new variant of NDV, and one isolate that was clustered in the subgenotype VII.2. All DRC isolates were velogenic and were antigenically closely related to the vaccine strains. Our findings reveal that despite the circulation of the new variant, ND can be controlled in the DRC using the current vaccine. However, epidemiological studies should be conducted to elucidate the endemicity of the disease so that better control strategies can be implemented.

Re-Invasion of H5N8 High Pathogenicity Avian Influenza Virus Clade 2.3.4.4b in Hokkaido, Japan, 2020.

Global dispersion of high pathogenicity avian influenza (HPAI), especially that caused by H5 clade 2.3.4.4, has threatened poultry industries and, potentially, human health. An HPAI virus, A/northern pintail/Hokkaido/M13/2020 (H5N8) (NP/Hok/20) belonging to clade 2.3.4.4b, was isolated from a fecal sample collected at a lake in Hokkaido, Japan where migratory birds rested, October 2020. In the phylogenetic trees of all eight gene segments, NP/Hok/20 fell into in the cluster of European isolates in 2020, but was distinct from the isolates in eastern Asia and Europe during the winter season of 2017-2018. The antigenic cartography indicates that the antigenicity of NP/Hok/20 was almost the same as that of previous isolates of H5 clade 2.3.4.4b, whereas the antigenic distances from NP/Hok/20 to the representative strains in clade 2.3.4.4e and to a strain in 2.3.4 were apparently distant. These data imply that HPAI virus clade 2.3.4.4b should have been delivered by bird migration despite the intercontinental distance, although it was not defined whether NP/Hok/20 was transported from Europe via Siberia where migratory birds nest in the summer season. Given the probability of perpetuation of transmission in the northern territory, periodic updates of intensive surveys on avian influenza at the global level are essential to prepare for future outbreaks of the HPAI virus.

Molecular characterization of rabies viruses from two western provinces of the Democratic Republic of the Congo (2008-2017).

Although rabies is enzootic in the Democratic Republic of the Congo, there is very little molecular epidemiological information about the viruses circulating in animals. In this study, a fragment of the rabies virus (RABV) nucleoprotein gene was amplified and sequenced from 21 animal brain samples collected in two western provinces of the country between 2008 and 2017. The samples tested were from cat (n = 1), dog (n = 17), goat (n = 2), and sheep (n = 1). Phylogenetic analysis revealed that the sequences generated were highly similar to each other and belonged to lineage Africa 1b clustering with a single sample identified in a canine in the Republic of Congo in 2014. This is the first molecular epidemiological study of RABV in the DRC and the data generated will assist authorities in the development of effective control strategies for rabies in the country.

Molecular, antigenic, and pathogenic characterization of H5N8 highly pathogenic avian influenza viruses isolated in the Democratic Republic of Congo in 2017.

In May 2017, high mortality of chickens and Muscovy ducks due to the H5N8 highly pathogenic avian influenza virus (HPAIV) was reported in the Democratic Republic of Congo (DR Congo). In this study, we assessed the molecular, antigenic, and pathogenic features in poultry of the H5N8 HPAIV from the 2017 Congolese outbreaks. Phylogenetic analysis of the eight viral gene segments revealed that all 12 DR Congo isolates clustered in clade 2.3.4.4B together with other H5N8 HPAIVs isolated in Africa and Eurasia, suggesting a possible common origin of these viruses. Antigenically, a slight difference was observed between the Congolese isolates and a representative virus from group C in the same clade. After intranasal inoculation with a representative DR Congo virus, high pathogenicity was observed in chickens and Muscovy ducks but not in Pekin ducks. Viral replication was higher in chickens than in Muscovy duck and Pekin duck organs; however, neurotropism was pronounced in Muscovy ducks. Our data confirmed the high pathogenicity of the DR Congo virus in chickens and Muscovy ducks, as observed in the field. National awareness and strengthening surveillance in the region are needed to better control HPAIVs.

Highly Pathogenic Avian Influenza A(H5N8) Virus, Democratic Republic of the Congo, 2017.

In 2017, highly pathogenic avian influenza A(H5N8) virus was detected in poultry in the Democratic Republic of the Congo. Whole-genome phylogeny showed the virus clustered with H5N8 clade 2.3.4.4B strains from birds in central and southern Asia. Emergence of this virus in central Africa represents a threat for animal health and food security.

Unravelling viral camouflage: approaches to the study and characterization of conformational epitopes.

Antibodies are broadly used in clinical and basic research. Many of monoclonal antibodies are successfully adopted for therapeutic and diagnostic targeting of viral pathogens. Efficacy of antiviral neutralizing or protective antibodies depends on their ability to recognize epitopes interfering with viral infection. However, viruses are able to incessantly change their antigenic determinants to escape surveillance of humoral immune system and therefore the successful antiviral therapies require continuous development. Characterization of interactions of antibodies with prevalently conformational viral epitopes is important for understanding antibody mode of action and can help to identify conserved regions that may be exploited in designing new vaccines and virus neutralizing antibodies. In this article, we are reviewing techniques in use for characterization of conformational epitopes of monoclonal antibodies with focus on viruses.

Higher strains in the inner region of the meniscus indicate a potential source for degeneration.

Complex structural properties of menisci can be characterized in part by their inhomogeneous strain response under compression. This pilot study explored the feasibility to quantify characteristic strain distributions on meniscus cross-sections subjected to static compression using electronic speckle pattern interferometry (ESPI). Cross-sectional specimens of 5-mm thickness were harvested from eight human menisci. After application of 20% pre-strain, strain maps in response to 10µm compression were captured with ESPI. The 10µm compression induced an aggregate strain of nominally 0.14% and resulted in highly non-uniform strain distributions. Local compressive strain captured by ESPI ranged from 0.03% to 0.7%. The highest strain was in the central region of meniscus cross-sections, and the lowest magnitude of strain was at the femoral surface of the meniscus. After stratifying for age, peak compressive strain in older menisci (71±6 years, n=4) was 0.33%±0.09, compared to 0.25%±0.06 in younger menisci (34±9 years, n=4). In conclusion, this study captured for the first time continuous strain distribution maps over entire meniscus cross-sections. The non-uniform strain distributions demonstrated inhomogeneous structural properties. Age-related differences in characteristic strain distributions likely represent degenerative changes. As such, ESPI provides a novel strategy of further characterize meniscal function and degeneration.

A systematic review and meta-analysis of the efficacy of lixisenatide in the treatment of patients with type 2 diabetes.

The aim of this study is to assess the efficacy and safety of lixisenatide for treating type 2 diabetes. A systematic search in electronic databases (up to October 2012) was conducted and the manufacturer was contacted regarding unpublished data. Randomized controlled trials (RCTs) were included if they provided information on at least one of the following outcomes: mortality, health-related quality of life, hypoglycaemic events, adverse events, change in HbA1c, body weight, blood pressure, gastric emptying, fasting plasma glucose or 2 h postprandial glucose (PPG). Twenty-six publications and 10 unpublished study reports, relating to 14 RCTs (6156 patients) were included. Eleven studies related to placebo comparisons; active comparators were in three studies. Compared to placebo, lixisenatide significantly reduced HbA1c (-0.52%; 95% CI: -0.64 to -0.39), bodyweight (-0.65 kg; 95% CI: -0.94 to -0.37) and 2-h PPG level (-4.58 mmol/l; 95% CI: -5.88 to -3.28). There were significantly more symptomatic hypoglycaemic events among lixisenatide compared to placebo-treated patients (log OR: 0.54; 95% CI: 0.32-0.75), but significantly fewer compared to other incretin mimetics. In comparison to exenatide and liraglutide, lixisenatide was more effective in reducing 2 h-PPG with a better adverse events profile, but it showed a lower reduction in HbA1c and body weight. Lixisenatide improves HbA1c levels and moderately reduces body weight compared to placebo and showed less frequent symptomatic hypoglycaemic and gastrointestinal events and an improvement in PPG control compared to other GLP-1 agonists. Firm conclusions regarding the performance of lixisenatide compared to other incretin mimetics, however, can not yet be drawn, due to limited data.

Efficacy, usability and sequence of operations of a workflow-integrated algorithm for basal-bolus insulin therapy in hospitalized type 2 diabetes patients.

AIMS: To evaluate glycaemic control and usability of a workflow-integrated algorithm for basal-bolus insulin therapy in a proof-of-concept study to develop a decision support system in hospitalized patients with type 2 diabetes. METHODS: In this ward-controlled study, 74 type 2 diabetes patients (24 female, age 68 ± 11 years, HbA1c 8.7 ± 2.4% and body mass index 30 ± 7) were assigned to either algorithm-based treatment with a basal-bolus insulin therapy or to standard glycaemic management. Algorithm performance was assessed by continuous glucose monitoring and staff's adherence to algorithm-calculated insulin dose. RESULTS: Average blood glucose levels (mmol/l) in the algorithm group were significantly reduced from 11.3 ± 3.6 (baseline) to 8.2 ± 1.8 (last 24 h) over a period of 7.5 ± 4.6 days (p < 0.001). The algorithm group had a significantly higher percentage of glucose levels in the ranges from 5.6 to 7.8 mmol/l (target range) and 3.9 to 10.0 mmol/l compared with the standard group (33 vs. 23% and 73 vs. 53%, both p < 0.001). Physicians' adherence to the algorithm-calculated total daily insulin dose was 95% and nurses' adherence to inject the algorithm-calculated basal and bolus insulin doses was high (98 and 93%, respectively). In the algorithm group, significantly more glucose values <3.9 mmol/l were detected in the afternoon relative to other times (p < 0.05), a finding mainly related to pronounced morning glucose excursions and requirements for corrective bolus insulin at lunch. CONCLUSIONS: The workflow-integrated algorithm for basal-bolus therapy was effective in establishing glycaemic control and was well accepted by medical staff. Our findings support the implementation of the algorithm in an electronic decision support system.

Minimally invasive repair for pectus excavatum -- aesthetic and/or functional?

INTRODUCTION: Pectus excavatum is the most frequent anterior thoracic wall congenital malformation. This malformation is increasing its effects with the aging process and has its peak during teenage, when the clinical symptoms become more acute and psychological effects are really important. Across the course of time many treatment techniques have been proposed, among which conservative or surgical correction techniques. The minimally invasive repair of pectus excavatum, "Nuss technique", developed after 1987, is the most frequently performed technique world wide. MATERIAL AND METHOD: This article analyzes 52 patients, admitted to the University Emergency Military Hospital "Carol Davila" - Thoracic Surgery Department, diagnosed, investigated and surgically treated according to Nuss procedure. Therapeutic and diagnostic protocols will be presented and analyzed: clinical and paraclinical evaluation, indications and contraindications of Nuss procedure, as well as possible intraoperative and postoperative complications. RESULTS AND CONCLUSIONS: Nuss procedure's benefits will be presented, as well as improvements of functional and aesthetic parameters. Nuss procedure has a series of advantages: minimally invasive surgical procedure reduced operative time, minimal blood loss and fast socio-professional reinstatement.

Correction for covariate measurement error in nonparametric longitudinal regression.

We introduce a correction for covariate measurement error in nonparametric regression applied to longitudinal binary data arising from a study on human sleep. The data have been surveyed to investigate the association of some hormonal levels and the probability of being asleep. The hormonal effect is modeled flexibly while we account for the error-prone measurement of its concentration in the blood and the longitudinal character of the data. We present a fully Bayesian treatment utilizing Markov chain Monte Carlo inference techniques, and also introduce block updating to improve sampling and computational performance in the binary case. Our model is partly inspired by the relevance vector machine with radial basis functions, where usually very few basis functions are automatically selected for fitting the data. In the proposed approach, we implement such data-driven complexity regulation by adopting the idea of Bayesian model averaging. Besides the general theory and the detailed sampling scheme, we also provide a simulation study for the Gaussian and the binary cases by comparing our method to the naive analysis ignoring measurement error. The results demonstrate a clear gain when using the proposed correction method, particularly for the Gaussian case with medium and large measurement error variances, even if the covariate model is misspecified.

Evaluating microarray-based classifiers: an overview.

For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy.