bluuebunny/crossref_metadata_2025 huggingface dataset:
Options for an environmental risk assessment of intentional and unintentional chemical mixtures under REACH: the status and ways forward
Authors: Hassold Enken , Galert Wiebke , Schulze Jona
Published: November 2021

It is acknowledged that a variety of chemicals enter the environment and may cause joint effects. Chemicals regulated under the European Chemicals Regulation REACH are often part of formulated mixtures and during their processing and use in various products they can be jointly released via sewage treatment plants or diffuse sources, and may combine in the environment. One can differentiate between intentional mixtures, and unintentional mixtures. In contrast to other substance-oriented legislations, REACH contains no explicit requirements for an assessment of combined effects, exposures and risks of several components. Still, it requires ensuring the safe use of substances on their own, in mixtures, and in articles. The available options to address intentional as well as unintentional mixtures are presented and discussed with respect to their feasibility under REACH, considering the responsibilities, communication tasks and information availability of the different actors (registrants, downstream-user and authorities). Specific mixture assessments via component-based approaches require a comprehensive knowledge on substances properties, uses, fate and behaviour, and the composition of the mixture under consideration. This information is often not available to the responsible actor. In principle, intentional mixtures of known composition can be assessed by the downstream-user. But approaches have to be improved to ensure a transparent communication and sound mixture assessment. In contrast, unintentional mixtures appear to be better addressable via generic approaches such as a mixture allocation factor during the chemical safety assessment, although questions on the magnitude, implementation and legal mandates remain. Authorities can conduct specific mixture risk assessments in well-defined and prioritized cases, followed by subsequent regulatory measures. In order to address intentional and unintentional mixtures within the current REACH framework, legal mandates together with guidance for the different actors are needed. Furthermore, further data on mixture compositions, uses and co-exposures need to be made accessible via shared databases.
Swimming training and Plantago psyllium ameliorate cognitive impairment and glucose tolerance in streptozotocin–nicotinamide-induced type 2 diabetic rats
Authors: Parsa Hesam , Moradi-Khaligh Zahra , Rajabi Sara , Ranjbar Kamal , Komaki Alireza
Published: November 2021

Brain malfunction is common in diabetic patients. On the other hand, a growing body of research points to the beneficial effect of medicinal plants and exercise training on insulin sensitivity and brain function. Therefore, the aim of the present study was to investigate the effect of co-administration of swimming training and Plantago psyllium (mixed with standard pelleted food at a weight ratio of 5%) on learning and memory impairment and glucose tolerance in type 2 diabetic rats. For this purpose, 10 healthy and 40 rats with type 2 diabetes were randomly allocated to five groups: healthy sedentary control group (Con), sedentary diabetic group (D), diabetic group subjected to swimming training (D + Tr), diabetic group receiving P. psyllium (D + Ps), and diabetic group subjected to swimming training and receiving P. psyllium (D + Ps + Tr). Diabetes was induced by a single intraperitoneal injection of nicotinamide (120 mg/kg) and streptozotocin (65 mg/kg) separately with 15 min intervals. Experimental groups were treated with swimming training and P. psyllium independently and simultaneously for 12 weeks. Lipid profile and food intake were measured and also, glucose tolerance was evaluated by glucose area under the curve (AUCg) using an oral glucose tolerance test. Passive avoidance learning (PAL) and memory were evaluated by shuttle box test and cognitive memory was assessed by novel object recognition (NOR) and elevated plus-maze (EPM) tests. Diabetic rats exhibited a significant increase in food intake, lipid profile, and AUCg compared to healthy rats. Step-through latency in the PAL acquisition trial (STL-a) and retention test (STL-r) were significantly lower in diabetic rats than in the control group. In the diabetic group without treatment, time spent in the dark compartment increased compared to the control group in the shuttle box test. Discrimination index and distance traveled reduced in diabetic rats. On the other hand, swimming training and P. psyllium alleviated food intake, lipid profile, and glucose tolerance in diabetic rats. Also, the STL-a, STL-r, discrimination index, and distance travelled in the D + Ps + Tr group were significantly more than the diabetic group. Results showed that 12 weeks of swimming training and receiving P. psyllium improved memory deficit in streptozotocin–nicotinamide-induced type 2 diabetic rats possibly through hypolipidemic and hypoglycemic effects. These results suggest that the administration of swimming training and P. psyllium simultaneously might be an effective intervention for the treatment of diabetes-induced behavioral deficits.
A combined miR-34a and arsenic trioxide nanodrug delivery system for synergistic inhibition of HCC progression after microwave ablation
Authors: Hu Jian , Pei Wenceng , Jiang Zhenyou , Li Zihuang
Published: November 2021

Background

Microwave ablation (MWA) has become an alternative treatment for unresectable hepatocellular carcinoma (HCC), but it does not eliminate the risk of recurrence and metastasis after treatment. Recent studies have demonstrated that miR-34a presents decreased gene expression in residual tumours after ablation therapy and can increase the therapeutic effect of arsenic trioxide against HCC, which brings new opportunities for HCC treatment.

Methods

A pH-sensitive charge inversion material was used to construct a nanotargeted delivery system based on the synergistic effects of miR-34a and As2O3. We established in vitro and in vivo models of HCC microwave ablation and performed in-depth research on the dual-drug system to inhibit the rapid progression and induce pyroptosis in HCC cells after microwave ablation.

Results

The antitumour effects were enhanced with the dual-drug nanoparticles relative to the single-drug formulations, and the therapeutic efficacy of the nanoparticles was more significant in a weakly acidic environment. The dual-drug nanoparticles increased the N-terminal portion of GSDME and decreased the expression of Cyt-c and c-met.

Conclusions

Dual-drug nanoparticles may improve the therapeutic efficacy of HCC treatment after insufficient ablation through Cyt-c and GSDME-N and decrease the expression levels of c-met. These nanoparticles are expected to provide new treatment methods for residual HCC after MWA, prolong the survival of patients and improve their quality of life.
Dissecting genetic trends to understand breeding practices in livestock: a maternal pig line example
Authors: Abdollahi-Arpanahi Rostam , Lourenco Daniela , Legarra Andres , Misztal Ignacy
Published: November 2021

Background

Understanding whether genomic selection has been effective in livestock and when the results of genomic selection became visible are essential questions which we have addressed in this paper. Three criteria were used to identify practices of breeding programs over time: (1) the point of divergence of estimated genetic trends based on pedigree-based best linear unbiased prediction (BLUP) versus single-step genomic BLUP (ssGBLUP), (2) the point of divergence of realized Mendelian sampling (RMS) trends based on BLUP and ssGBLUP, and (3) the partition of genetic trends into that contributed by genotyped and non-genotyped individuals and by males and females.

Methods

We used data on 282,035 animals from a commercial maternal line of pigs, of which 32,856 were genotyped for 36,612 single nucleotide polymorphisms (SNPs) after quality control. Phenotypic data included 228,427, 101,225, and 11,444 records for birth weight, average daily gain in the nursery, and feed intake, respectively. Breeding values were predicted in a multiple-trait framework using BLUP and ssGBLUP.

Results

The points of divergence of the genetic and RMS trends estimated by BLUP and ssGBLUP indicated that genomic selection effectively started in 2019. Partitioning the overall genetic trends into that for genotyped and non-genotyped individuals revealed that the contribution of genotyped animals to the overall genetic trend increased rapidly from ~ 74% in 2016 to 90% in 2019. The contribution of the female pathway to the genetic trend also increased since genomic selection was implemented in this pig population, which reflects the changes in the genotyping strategy in recent years.

Conclusions

Our results show that an assessment of breeding program practices can be done based on the point of divergence of genetic and RMS trends between BLUP and ssGBLUP and based on the partitioning of the genetic trend into contributions from different selection pathways. However, it should be noted that genetic trends can diverge before the onset of genomic selection if superior animals are genotyped retroactively. For the pig population example, the results showed that genomic selection was effective in this population.
Efficient iterative Hi-C scaffolder based on N-best neighbors
Authors: Guan Dengfeng , McCarthy Shane A. , Ning Zemin , Wang Guohua , Wang Yadong , Durbin Richard
Published: November 2021

Background

Efficient and effective genome scaffolding tools are still in high demand for generating reference-quality assemblies. While long read data itself is unlikely to create a chromosome-scale assembly for most eukaryotic species, the inexpensive Hi-C sequencing technology, capable of capturing the chromosomal profile of a genome, is now widely used to complete the task. However, the existing Hi-C based scaffolding tools either require a priori chromosome number as input, or lack the ability to build highly continuous scaffolds.

Results

We design and develop a novel Hi-C based scaffolding tool, pin_hic, which takes advantage of contact information from Hi-C reads to construct a scaffolding graph iteratively based on N-best neighbors of contigs. Subsequent to scaffolding, it identifies potential misjoins and breaks them to keep the scaffolding accuracy. Through our tests on three long read based de novo assemblies from three different species, we demonstrate that pin_hic is more efficient than current standard state-of-art tools, and it can generate much more continuous scaffolds, while achieving a higher or comparable accuracy.

Conclusions

Pin_hic is an efficient Hi-C based scaffolding tool, which can be useful for building chromosome-scale assemblies. As many sequencing projects have been launched in the recent years, we believe pin_hic has potential to be applied in these projects and makes a meaningful contribution.
EvalDNA: a machine learning-based tool for the comprehensive evaluation of mammalian genome assembly quality
Authors: MacDonald Madolyn L. , Lee Kelvin H.
Published: November 2021

Background

To select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment.

Results

EvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence based on continuity, completeness, and accuracy, and was able to explain 86% of the variation in reference-based quality scores within the testing data. EvalDNA was applied to human chromosome 14 assemblies from the GAGE study to rank genome assemblers and to compare EvalDNA to two other quality evaluation tools. In addition, EvalDNA was used to evaluate several genome assemblies of the Chinese hamster genome to help establish a better reference genome for the biopharmaceutical manufacturing community. EvalDNA was also used to assess more recent human assemblies from the QUAST-LG study completed in 2018, and its ability to score bacterial genomes was examined through application on bacterial assemblies from the GAGE-B study.

Conclusions

EvalDNA enables scientists to easily identify the best available genome assembly for their organism of interest without requiring a reference assembly. EvalDNA sets itself apart from other quality assessment tools by producing a quality score that enables direct comparison among assemblies from different species.
A multitask transfer learning framework for the prediction of virus-human protein–protein interactions
Authors: Dong Thi Ngan , Brogden Graham , Gerold Gisa , Khosla Megha
Published: November 2021

Background

Viral infections are causing significant morbidity and mortality worldwide. Understanding the interaction patterns between a particular virus and human proteins plays a crucial role in unveiling the underlying mechanism of viral infection and pathogenesis. This could further help in prevention and treatment of virus-related diseases. However, the task of predicting protein–protein interactions between a new virus and human cells is extremely challenging due to scarce data on virus-human interactions and fast mutation rates of most viruses.

Results

We developed amultitask transfer learningapproach that exploits the information of around 24 million protein sequences and the interaction patterns from the human interactome to counter the problem of small training datasets. Instead of using hand-crafted protein features, we utilize statistically rich protein representations learned by a deep language modeling approach from a massive source of protein sequences. Additionally, we employ an additional objective which aims to maximize the probability of observing human protein–protein interactions. This additional task objective acts as a regularizer and also allows to incorporate domain knowledge to inform the virus-human protein–protein interaction prediction model.

Conclusions

Our approach achieved competitive results on 13 benchmark datasets and the case study for theSARS-CoV-2virus receptor. Experimental results show that our proposed model works effectively for both virus-human and bacteria-human protein–protein interaction prediction tasks. We share our code for reproducibility and future research athttps://git.l3s.uni-hannover.de/dong/multitask-transfer.
Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations
Authors: Zhou Feng , Yin Meng-Meng , Jiao Cui-Na , Cui Zhen , Zhao Jing-Xiu , Liu Jin-Xing
Published: November 2021

Background

With the rapid development of various advanced biotechnologies, researchers in related fields have realized that microRNAs (miRNAs) play critical roles in many serious human diseases. However, experimental identification of new miRNA–disease associations (MDAs) is expensive and time-consuming. Practitioners have shown growing interest in methods for predicting potential MDAs. In recent years, an increasing number of computational methods for predicting novel MDAs have been developed, making a huge contribution to the research of human diseases and saving considerable time. In this paper, we proposed an efficient computational method, named bipartite graph-based collaborative matrix factorization (BGCMF), which is highly advantageous for predicting novel MDAs.

Results

By combining two improved recommendation methods, a new model for predicting MDAs is generated. Based on the idea that some new miRNAs and diseases do not have any associations, we adopt the bipartite graph based on the collaborative matrix factorization method to complete the prediction. The BGCMF achieves a desirable result, with AUC of up to 0.9514 ± (0.0007) in the five-fold cross-validation experiments.

Conclusions

Five-fold cross-validation is used to evaluate the capabilities of our method. Simulation experiments are implemented to predict new MDAs. More importantly, the AUC value of our method is higher than those of some state-of-the-art methods. Finally, many associations between new miRNAs and new diseases are successfully predicted by performing simulation experiments, indicating that BGCMF is a useful method to predict more potential miRNAs with roles in various diseases.
The effects of habitat fragmentation on the genetic structure of wild boar (Sus scrofa) population in Lithuania
Authors: Griciuvienė Loreta , Janeliūnas Žygimantas , Jurgelevičius Vaclovas , Paulauskas Algimantas
Published: November 2021

Background

Wild boar (Sus scrofa) is a widely distributed ungulate whose success can be attributed to a variety of ecological features. The genetic variation and population structure of Lithuania’s wild boar population have not yet been thoroughly studied. The purposes of this study were to investigate the genetic diversity of S. scrofa and assess the effects of habitat fragmentation on the population structure of wild boar in Lithuania. A total of 96 S. scrofa individuals collected from different regions of Lithuania were genotyped using fifteen microsatellite loci.

Results

The microsatellite analysis of the wild boars indicated high levels of genetic diversity within the population. Microsatellite markers showed evidence of a single panmictic wild boar population in Lithuania according to STRUCTURE’s highest average likelihood, which was K = 1. This was supported by pairwise Fst values and AMOVA, which indicated no differentiation between the four sampling areas. The results of the Mantel test revealed a weak isolation by distance and geographic diversity gradients that persisted between locations. Motorway fencing and heavy traffic were not an effective barrier to wild boar movement.

Conclusions

There was limited evidence of population genetic structure among the wild boar, supporting the presence of a single population across the study area and indicating that there may be no barriers hindering wild boar dispersal across the landscape. The widespread wild boar population in Lithuania, the high level of genetic variation observed within subpopulations, and the low level of variation identified between subpopulations suggest migration and gene flow between locations. The results of this study should provide valuable information in future for understanding and comparing the detailed structure of wild boar population in Lithuania following the outbreak of African swine fever.
Baiting out a full length sequence from unmapped RNA-seq data
Authors: Li Dongwei , Huang Qitong , Huang Lei , Wen Jikai , Luo Jing , Li Qing , Peng Yanling , Zhang Yubo
Published: November 2021

Background

As a powerful tool, RNA-Seq has been widely used in various studies. Usually, unmapped RNA-seq reads have been considered as useless and been trashed or ignored.

Results

We develop a strategy to mining the full length sequence by unmapped reads combining with specific reverse transcription primers design and high throughput sequencing. In this study, we salvage 36 unmapped reads from standard RNA-Seq data and randomly select one 149 bp read as a model. Specific reverse transcription primers are designed to amplify its both ends, followed by next generation sequencing. Then we design a statistical model based on power law distribution to estimate its integrality and significance. Further, we validate it by Sanger sequencing. The result shows that the full length is 1556 bp, with insertion mutations in microsatellite structure.

Conclusion

We believe this method would be a useful strategy to extract the sequences information from the unmapped RNA-seq data. Further, it is an alternative way to get the full length sequence of unknown cDNA.
Characterisation of novel endogenous geminiviral elements in macadamia
Authors: Zakeel Mohamed C. M. , Geering Andrew D. W. , Thomas John E. , Akinsanmi Olufemi A.
Published: November 2021

Background

The presence of geminivirus sequences in a preliminary analysis of sRNA sequences from the leaves of macadamia trees with abnormal vertical growth (AVG) syndrome was investigated.

Results

A locus of endogenous geminiviral elements (EGE) in the macadamia genome was analysed, and the sequences revealed a high level of deletions and/or partial integrations, thus rendering the EGE transcriptionally inactive. The replication defective EGE in the macadamia genome indicates its inability to be the source of new viral infections and thus cause AVG or any other disease in macadamia. The EGE sequences were detected in two edible Macadamia species that constitute commercial cultivars and the wild germplasm of edible and inedible species of Macadamia. This strongly suggests that the integration preceded speciation of the genus Macadamia. A draft genome of a locus of EGE in Macadamia was developed. The findings of this study provide evidence to suggest the endogenization of the geminiviral sequences in the macadamia genome and the ancestral relationship of EGE with Macadamia in the Proteaceae family. Random mutations accumulating in the EGE inform that the sequence is evolving.

Conclusions

The EGE in Macadamia is inactive and thus not a direct cause of any diseases or syndromes including AVG in macadamia. The insertion of the EGE in the macadamia genome preceded speciation of the genus Macadamia.
Alteration of the gut microbiota in rhesus monkey with spontaneous osteoarthritis
Authors: Yan Yaping , Yi Xiaoyan , Duan Yanchao , Jiang Bin , Huang Tianzhuang , Inglis Briauna Marie , Zheng Bingrong , Si Wei
Published: November 2021

Background

The spontaneous osteoarthritis (OA) in rhesus macaque is similar to OA in human, which maintains an upright body posture and shows very similar biomechanical properties of bones to humans. At present, there is no good treatment for OA. This study aims to explore relationship between OA and intestinal microbiota, and provide a reference for the treatment of clinical OA.

Results

We collected colonic contents of the 20 rhesus macaque (6–15 years old, female) for intestinal microbiota analysis by metagenomics sequencing, of which 10 were spontaneous OA monkeys and 10 were normal monkeys. Our results showed the diversity of gut microbiota in monkeys with OA was decreased compared to the normal monkeys (p = 0.16). Mollicutes, Tenericutes, Coprobacillus and Faecalitalea may be biomarkers for the monkeys of OA. Lactobacillus found significantly increased in OA monkeys. Prevotella and Ruminococcus were higher in the normal group than OA group. Zinc/manganese transport system permease protein (p = 0.0011) and Cyclopropane-fatty-acyl-phospholipid synthase (p = 0.0012) are a microbiota metabolic pathway related to cartilage production.

Conclusions

Our results indicate that the diversity and composition of intestinal microbiota in monkeys with OA are different compared to the normal monkeys. we have found microbes that may be a biomarker for the diagnosis of osteoarthritis. Functional analysis of the microbiota also predicts cartilage damage in the monkeys with osteoarthritis. Non-human primates are closely related to humans, so this study can provide a reference for the development of drugs for the treatment of OA.
ABCA1 and ABCG1 DNA methylation in epicardial adipose tissue of patients with coronary artery disease
Authors: Miroshnikova Valentina V. , Panteleeva Alexandra A. , Pobozheva Irina A. , Razgildina Natalia D. , Polyakova Ekaterina A. , Markov Anton V. , Belyaeva Olga D. , Berkovich Olga A. , Baranova Elena I. , Nazarenko Maria S. , Puzyrev Valery P. , Pchelina Sofya N.
Published: November 2021

Background

Recent studies have focused on the potential role of epicardial adipose tissue (EAT) in the development of coronary artery disease (CAD). ABCA1 and ABCG1 transporters regulate cell cholesterol content and reverse cholesterol transport. We aimed to determine whether DNA methylation and mRNA levels of the ABCA1 and ABCG1 genes in EAT and subcutaneous adipose tissue (SAT) were associated with CAD.

Methods

Paired EAT and SAT samples were collected from 82 patients undergoing elective cardiac surgery either for coronary artery bypass grafting (CAD group, N = 66) or valve surgery (NCAD group, N = 16). ABCA1 and ABCG1 mRNA levels in EAT and SAT samples were analyzed using real time polymerase chain reaction, ABCA1 protein levels in EAT samples were assessed by western blotting. ABCA1 and ABCG1 DNA methylation analysis was performed in 24 samples from the CAD group and 9 samples from the NCAD group via pyrosequencing.

Results

DNA methylation levels in the ABCA1 promoter and ABCG1 cg27243685 and cg06500161 CpG sites were higher in EAT samples from patients with CAD compared with NCAD (21.92% vs 10.81%, p = 0.003; 71.51% vs 68.42%, p = 0.024; 46.11% vs 37.79%, p = 0.016, respectively). In patients with CAD, ABCA1 and ABCG1 DNA methylation levels were higher in EAT than in SAT samples (p < 0.05). ABCA1 mRNA levels in EAT samples were reduced in the subgroup of patients with CAD and concomitant carotid artery disease or peripheral artery disease compared with the NCAD group (p = 0.024). ABCA1 protein levels in EAT samples tended to be lower in CAD patients than in the NCAD group (p = 0.053). DNA methylation levels at the ABCG1 cg27243685 site positively correlated with plasma triglyceride concentration (r = 0.510, p = 0.008), body mass index (r = 0.556, p = 0.013) and waist-to-hip ratio (r = 0.504, p = 0.012) in SAT samples.

Conclusion

CAD is associated with ABCA1 and ABCG1 DNA hypermethylation in EAT. CAD with concomitant carotid artery disease or peripheral artery disease is accompanied by decreased ABCA1 gene expression in EAT. DNA methylation levels at the ABCG1 cg27243685 locus in SAT are associated with hypertriglyceridemia and obesity.
Time-varying associations between an exposure history and a subsequent health outcome: a landmark approach to identify critical windows
Authors: Wagner Maude , Grodstein Francine , Leffondre Karen , Samieri Cécilia , Proust-Lima Cécile
Published: November 2021

Background

Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impact on disease risk is challenging. To assess the trajectory of association of an exposure history with an outcome, the weighted cumulative exposure index (WCIE) has been proposed, with weights reflecting the relative importance of exposures at different times. However, WCIE is restricted to a complete observed error-free exposure whereas exposures are often measured with intermittent missingness and error. Moreover, it rarely explores exposure history that is very distant from the outcome as usually sought in life-course epidemiology.

Methods

We extend the WCIE methodology to (i) exposures that are intermittently measured with error, and (ii) contexts where the exposure time-window precedes the outcome time-window using a landmark approach. First, the individual exposure history up to the landmark time is estimated using a mixed model that handles missing data and error in exposure measurement, and the predicted complete error-free exposure history is derived. Then the WCIE methodology is applied to assess the trajectory of association between the predicted exposure history and the health outcome collected after the landmark time. In our context, the health outcome is a longitudinal marker analyzed using a mixed model.

Results

A simulation study first demonstrates the correct inference obtained with this approach. Then, applied to the Nurses’ Health Study (19,415 women) to investigate the association between body mass index history (collected from midlife) and subsequent cognitive decline (evaluated after age 70), the method identified two major critical windows of association: long before the first cognitive evaluation (roughly 24 to 12 years), higher levels of BMI were associated with poorer cognition. In contrast, adjusted for the whole history, higher levels of BMI became associated with better cognition in the last years prior to the first cognitive interview, thus reflecting reverse causation (changes in exposure due to underlying disease).

Conclusions

This approach, easy to implement, provides a flexible tool for studying complex dynamic relationships and identifying critical time windows while accounting for exposure measurement errors.
Does advance contact with research participants increase response to questionnaires: an updated systematic review and meta-analysis
Authors: Woolf Benjamin , Edwards Phil
Published: November 2021

Background

Questionnaires remain one of the most common forms of data collection in epidemiology, psychology and other human-sciences. However, results can be badly affected by non-response. One way to potentially reduce non-response is by sending potential study participants advance communication. The last systematic review to examine the effect of questionnaire pre-notification on response is 10 years old, and lacked a risk of bias assessment.

Objectives

Update the section of the Cochrane systematic review, Edwards et al. (2009), on pre-notification to include 1) recently published studies, 2) an assessment of risk of bias, 3) Explore if heterogeneity is reduced by: delay between pre-contact and questionnaire delivery, the method of pre-contact, if pre-contact and questionnaire delivery differ, if the pre-contact includes a foot-in-the-door manipulation, and study’s the risk of bias.

Methods

Inclusion criteria: population: any population, intervention: comparison of some type of pre-notification, comparison group: no pre-notification, outcome: response rates. Study design: randomised controlled trails. Exclusion criteria: NA. Data sources: Studies which cited or were included in Edwards et al. (2009); We additionally searched: CINAHL, Web of Science, PsycInfo, MEDLINE, EconLit, EMBASE, Cochrane Central, Cochrane CMR, ERIC, and Sociological Abstracts. The searches were implemented in June 2018 and May 2021. Study screening: a single reviewer screened studies, with a random 10% sample independently screened to ascertain accuracy. Data extraction: data was extracted by a single reviewer twice, with a week between each extraction. Risk of Bias: within studies bias was assessed using the Cochrane Risk of Bias tool (ROB1) by a single unblinded reviewer, across studies bias was assessed using funnel plots. Synthesis Method: study results were meta-analysed with a random effects model using the final response rate as the outcome. Evaluation of Uncertainty: Uncertainty was evaluated using the GRADE approach.

Results

One hundred seven trials were included with 211,802 participants. Over-all pre-notification increased response, OR = 1.33 (95% CI: 1.20–1.47). However, there was a large amount of heterogeneity (I2 = 97.1%), which was not explained by the subgroup analyses. In addition, when studies at high or unclear risk of bias were excluded the effect was to reduced OR = 1.09 (95% CI: 0.99–1.20). Because of the large amount of heterogeneity, even after restricting to low risk of bias studies, there is still moderate uncertainty in these results.

Conclusions

Using the GRADE evaluation, this review finds moderate evidence that pre-notification may not have an effect on response rates.

Funding

Economic and Social Research Council.

Preregistration

None.
Predicting COVID-19 mortality risk in Toronto, Canada: a comparison of tree-based and regression-based machine learning methods
Authors: Feng Cindy , Kephart George , Juarez-Colunga Elizabeth
Published: November 2021

Background

Coronavirus disease (COVID-19) presents an unprecedented threat to global health worldwide. Accurately predicting the mortality risk among the infected individuals is crucial for prioritizing medical care and mitigating the healthcare system’s burden. The present study aimed to assess the predictive accuracy of machine learning methods to predict the COVID-19 mortality risk.

Methods

We compared the performance of classification tree, random forest (RF), extreme gradient boosting (XGBoost), logistic regression, generalized additive model (GAM) and linear discriminant analysis (LDA) to predict the mortality risk among 49,216 COVID-19 positive cases in Toronto, Canada, reported from March 1 to December 10, 2020. We used repeated split-sample validation andk-steps-ahead forecasting validation. Predictive models were estimated using training samples, and predictive accuracy of the methods for the testing samples was assessed using the area under the receiver operating characteristic curve, Brier’s score, calibration intercept and calibration slope.

Results

We found XGBoost is highly discriminative, with an AUC of 0.9669 and has superior performance over conventional tree-based methods, i.e., classification tree or RF methods for predicting COVID-19 mortality risk. Regression-based methods (logistic, GAM and LASSO) had comparable performance to the XGBoost with slightly lower AUCs and higher Brier’s scores.

Conclusions

XGBoost offers superior performance over conventional tree-based methods and minor improvement over regression-based methods for predicting COVID-19 mortality risk in the study population.
Predicting the natural history of metabolic syndrome with a Markov-system dynamic model: a novel approach
Authors: Rezaianzadeh Abbas , Morasae Esmaeil Khedmati , Khalili Davood , Seif Mozhgan , Bahramali Ehsan , Azizi Fereidoun , Bagheri Pezhman
Published: November 2021

Background

Markov system dynamic (MSD) model has rarely been used in medical studies. The aim of this study was to evaluate the performance of MSD model in prediction of metabolic syndrome (MetS) natural history.

Methods

Data gathered by Tehran Lipid & Glucose Study (TLGS) over a 16-year period from a cohort of 12,882 people was used to conduct the analyses. First, transition probabilities (TPs) between 12 components of MetS by Markov as well as control and failure rates of relevant interventions were calculated. Then, the risk of developing each component by 2036 was predicted once by a Markov model and then by a MSD model. Finally, the two models were validated and compared to assess their performance and advantages by using mean differences, mean SE of matrices, fit of the graphs, and Kolmogorov-Smirnov two-sample test as well as R2index as model fitting index.

Results

Both Markov and MSD models were shown to be adequate for prediction of MetS trends. But the MSD model predictions were closer to the real trends when comparing the output graphs. The MSD model was also, comparatively speaking, more successful in the assessment of mean differences (less overestimation) and SE of the general matrix. Moreover, the Kolmogorov-Smirnov two-sample showed that the MSD model produced equal distributions of real and predicted samples (p = 0.808 for MSD model andp = 0.023 for Markov model). Finally, R2for the MSD model was higher than Markov model (73% for the Markov model and 85% for the MSD model).

Conclusion

The MSD model showed a more realistic natural history than the Markov model which highlights the importance of paying attention to this method in therapeutic and preventive procedures.
Until death do us part Adult children’s perspective of their parents’ transition from living at home to moving into a nursing home and the time after death
Authors: Bökberg Christina , Sandberg Jonas
Published: November 2021

Background

Adult children are often key carers of frail older parents providing care for a long period of time in different care contexts. However, research concerning adult children’s caregiving experiences, from providing home-based care to facing the death of a parent in a nursing home is sparse. Thus, the aim was to explore the transition from living at home to moving into and living in a nursing home and the time after death from the perspective of next of kin to an older person.

Methods

A qualitative design using individual interviews with 15 adult children of older persons. The text was analysed using inductive content analysis.

Results

One main category was identified, until death do us part. With three generic categories, living at home, living at a nursing home and time after death, and eight sub-categories. The results describe the transition when an older person lives at home and moves into and lives in a nursing home and the time after death from the perspective of next of kin.

Conclusion

This study highlights many examples of tasks that adult children provide over a long period of time and in different care contexts since they felt that professional care was unable to provide safe and secure care for their older parents. It also highlights the importance for staff to recognize the support that next of kin provide. Furthermore, the study reveal that staff do not offer the relief that they are obligated to provide, to enable next of kin coping with this strenuous transition in life. First after the parent died, there was time for relief since the worrying and the doing of practical things for the parent had stopped.

Trial registration

Current Controlled Trials NCT02708498; date of registration: 26 February 2016.
A wind speed threshold for increased outdoor transmission of coronavirus: an ecological study
Authors: Clouston Sean A. P. , Morozova Olga , Meliker Jaymie R.
Published: November 2021

Background

To examine whether outdoor transmission may contribute to the COVID-19 epidemic, we hypothesized that slower outdoor wind speed is associated with increased risk of transmission when individuals socialize outside.

Methods

Daily COVID-19 incidence reported in Suffolk County, NY, between March 16th and December 31st, 2020, was the outcome. Average wind speed and maximal daily temperature were collated by the National Oceanic and Atmospheric Administration. Negative binomial regression was used to model incidence rates while adjusting for susceptible population size.

Results

Cases were very high in the initial wave but diminished once lockdown procedures were enacted. Most days between May 1st, 2020, and October 24th, 2020, had temperatures 16–28 °C and wind speed diminished slowly over the year and began to increase again in December 2020. Unadjusted and multivariable-adjusted analyses revealed that days with temperatures ranging between 16 and 28 °C where wind speed was < 8.85 km per hour (KPH) had increased COVID-19 incidence (aIRR = 1.45, 95% C.I. = [1.28–1.64], P < 0.001) as compared to days with average wind speed ≥ 8.85 KPH.

Conclusion

Throughout the U.S. epidemic, the role of outdoor shared spaces such as parks and beaches has been a topic of considerable interest. This study suggests that outdoor transmission of COVID-19 may occur by noting that the risk of transmission of COVID-19 in the summer was higher on days with low wind speed. Outdoor use of increased physical distance between individuals, improved air circulation, and use of masks may be helpful in some outdoor environments where airflow is limited.
Soil-transmitted helminths, intestinal protozoa and Clonorchis sinensis infections in southeast China
Authors: Feng Yan , Yu Kegen , Chen Hualiang , Zhang Xuan , Lu Qiaoyi , Wang Xiaoxiao , Zhang Xueying , Yao Linong , Ruan Wei
Published: November 2021

Background

Extensive parasitic diseases epidemiology in Zhejiang province has not been carried out since the second national survey in 2004. Therefore, dynamics in prevalence and infection pattern of the major intestinal parasites should be explored.

Methods

The distribution of three parasites including soil-transmitted helminths (STH), intestinal protozoa and C. sinensis in Zhejiang from 2014 to 2015 were explored. Kato-Katz technique was used for STH and C. sinensis detection, whereas transparent adhesive paper anal swab was used for pinworm detection, and iodine smear was used for protozoa detection. A questionnaire survey on alimentary habits and sanitary behaviors was conducted in half of the studied counties.

Results

This study recruited 23,552 participants: 19,935 from rural and 3617 from urban area. Overall prevalence of intestinal helminth infections was 1.80%. In this study, seven helminth species were identified including A. duodenale, N. americanus, Trichuris trichiura, Ascaris lumbricoides, C. sinensis, Fasciolopsis buski and pinworm. The average prevalence of STH infection was 1.71%: 1.94% in rural and 0.44% in urban area. Hookworm was the most prevalent infection at 1.58%: 1.79% in rural and 0.44% in urban area. Prevalence varied considerably in the studied counties. Prevalence was highest in Yongkang county at 10.25%. Only 2.79% of children from rural area were infected with pinworm. A proportion of 0.40% of rural participants were infected with protozoa, whereas Endolimax nana was the most prevalent at 0.23%. C. sinensis showed infection only in one man. Awareness on C. sinensis was 24.47% in rural and 45.96% in urban area, respectively.

Conclusions

Prevalence of STH and protozoa infections declined considerably whereas C. sinensis infections remained few in Zhejiang province compared with the prevalence reported in previous large scale surveys (19.56% for national STH infection in 2004, 18.66% and 4.57% for provincial STH and protozoa infection, respectively in 1999). The findings of this study showed that hookworm, mainly N. americanus remained a parasitic threat to population health, mainly in the central and western Zhejiang. Therefore, more health education regarding fertilization and farming habits is necessary in rural areas. The awareness concerning hookworm infection should be reinforced.
Primary hyperoxaluria diagnosed after kidney transplantation: a case report and literature review
Authors: Cai Zhitao , Ding Mao , Chen Rengui , Zhu Jiefu , Li Lian , Wu Xiongfei
Published: November 2021

Background

Primary hyperoxaluria (PH) is a rare inherited autosomal recessive disease caused by disturbed glyoxylate metabolism. The disease is characterized by calcium oxalate crystal deposition in various organs, especially in the kidney. Due to the lack of current understanding of PH, nearly all patients are only initially diagnosed with PH when recurrent lithiasis and progressive end-stage renal disease occur. Many cases are not diagnosed in patients until renal allograft insufficiency occurs after renal transplantation. This case report and literature review aim to emphasize the need for careful pre-transplant PH screening of patients with bilateral nephrocalcinosis or nephrolithiasis.

Case presentation

Renal allograft insufficiency was diagnosed as PH after kidney transplantation. Here, we detail the complete clinical course, including computed tomography images of the original kidney and renal graft, histopathological images of a biopsy of the transplanted kidney, the results of laboratory and molecular genetic tests, and the treatment. In addition, we reviewed the literature from 2000 to 2021 and analyzed 19 reported cases of PH diagnosed after kidney transplantation, and provide a summary of the characteristics, complications, treatment, and prognosis of these cases.

Conclusions

By reviewing and analyzing these cases, we concluded that patients with a history of nephrocalcinosis or nephrolithiasis in both kidneys need preoperative screening for PH and appropriate treatment before kidney transplantation. Delayed graft function caused by PH is easily misdiagnosed as acute rejection, and needle biopsy should be performed at an early stage.
Association between the psoas muscle index and hospitalization for pneumonia in patients undergoing hemodialysis
Authors: Yamaguchi Kosei , Kitamura Mineaki , Takazono Takahiro , Sato Shuntaro , Yamamoto Kazuko , Notomi Satoko , Sawase Kenji , Harada Takashi , Funakoshi Satoshi , Mukae Hiroshi , Nishino Tomoya
Published: November 2021

Background

Although muscle mass loss and pneumonia are common and crucial issues in hemodialysis (HD) patients, few reports have focused on their association, which remains unclear. This study assessed the association between skeletal muscle mass and the incidence of pneumonia in HD patients using the psoas muscle index (PMI).

Methods

This retrospective study included 330 patients on HD who were treated at a single center between July 2011 and June 2012. The observation period was between July 2011 and June 2021. Demographic, clinical, and HD data were collected, and the associations between PMI and hospitalization due to bacterial pneumonia were evaluated using Cox proportional hazards models adjusted for patients’ background data. Additionally, the correlation between patient characteristics and PMI was evaluated using multivariable linear regression.

Results

Among 330 patients (mean age, 67.3 ± 13.3; 56.7% male; median dialysis vintage 58 months, (interquartile range [IQR] 23–124), 79 were hospitalized for pneumonia during the observation period (median observation period was 4.5 years [IQR 2.0–9.1]). The multivariable Cox proportional analysis, which was adjusted for age, sex, dialysis vintage, diabetes mellitus, and stroke history and considered death as a competing risk, indicated that decreased PMI/(standard deviation) was closely associated with the development of pneumonia (hazard ratio: 0.67, 95% confidence interval: 0.47–0.95, p = 0.03).

Conclusions

Skeletal muscle mass was associated with the development of pneumonia in patients on HD and could be a useful marker for the risk of pneumonia.
Autoimmune encephalitis with coexistent LGI1 and GABABR1 antibodies: case report
Authors: Xie Yi , Wen Jia , Zhao Zhihua , Liu Hongbo , Xie Nanchang
Published: November 2021

Background

Autoimmune encephalitis (AE) with multiple auto-antibodies is of great clinical significance because its complex clinical manifestations and atypical imaging increase the difficulty of diagnosis, differential diagnosis and treatment, which may aggravate the disease, increase the recurrence rate and mortality. The coexistence of anti-Leucinie-rich Glioma Inactivated 1 (LGI1) and anti-γ-aminobutyric acid-beta-receptor 1 (GABABR1) has not been published before.

Case presentation

We herein present the case of a 60-year-old man with slow response, behavioral changes, psychosis and sleep disorders. Laboratory test included serum hyponatremia, positive serum LGI1 and GABABR1 antibodies using transfected cell-based assays. Electroencephalogram exhibited moderate diffusion abnormality. The patient responded well to steroid impulse treatment and sodium supplement therapy, and did not recur during the follow-up.

Conclusions

Here we report the first AE characterized by positive LGI1 and GABABR1 antibodies, as well as summarizing AE with multiple auto-antibodies reported so far, hopefully to provide experience for clinical practice.