bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria
Authors: Leifer Ian , Sánchez-Pérez Mishael , Ishida Cecilia , Makse Hernán A.
Published: July 2021

Background

Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the question whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression can be predicted from symmetries in the gene regulatory networks described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their ’input trees’, the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models—with gene input functions differencing between genes—predict symmetry breaking and desynchronization.

Results

To study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes.

Conclusions

Thus, gene fibrations provide a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.
Single-cell classification using graph convolutional networks
Authors: Wang Tianyu , Bai Jun , Nabavi Sheida
Published: July 2021

Background

Analyzing single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the identification of cell types. With the availability of a huge amount of single cell sequencing data and discovering more and more cell types, classifying cells into known cell types has become a priority nowadays. Several methods have been introduced to classify cells utilizing gene expression data. However, incorporating biological gene interaction networks has been proved valuable in cell classification procedures.

Results

In this study, we propose a multimodal end-to-end deep learning model, named sigGCN, for cell classification that combines a graph convolutional network (GCN) and a neural network to exploit gene interaction networks. We used standard classification metrics to evaluate the performance of the proposed method on the within-dataset classification and the cross-dataset classification. We compared the performance of the proposed method with those of the existing cell classification tools and traditional machine learning classification methods.

Conclusions

Results indicate that the proposed method outperforms other commonly used methods in terms of classification accuracy and F1 scores. This study shows that the integration of prior knowledge about gene interactions with gene expressions using GCN methodologies can extract effective features improving the performance of cell classification.
SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions
Authors: Lee Justin Y. , Nguyen Britney , Orosco Carlos , Styczynski Mark P.
Published: July 2021

Background

The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms—two characteristics that make it difficult to model metabolic networks accurately. While many computational methods have been built to unravel transcriptional regulation, there have been few approaches developed for systems-scale analysis and study of metabolic regulation. Here, we present a stepwise machine learning framework that applies established algorithms to identify regulatory interactions in metabolic systems based on metabolic data: stepwise classification of unknown regulation, or SCOUR.

Results

We evaluated our framework on both noiseless and noisy data, using several models of varying sizes and topologies to show that our approach is generalizable. We found that, when testing on data under the most realistic conditions (low sampling frequency and high noise), SCOUR could identify reaction fluxes controlled only by the concentration of a single metabolite (its primary substrate) with high accuracy. The positive predictive value (PPV) for identifying reactions controlled by the concentration of two metabolites ranged from 32 to 88% for noiseless data, 9.2 to 49% for either low sampling frequency/low noise or high sampling frequency/high noise data, and 6.6–27% for low sampling frequency/high noise data, with results typically sufficiently high for lab validation to be a practical endeavor. While the PPVs for reactions controlled by three metabolites were lower, they were still in most cases significantly better than random classification.

Conclusions

SCOUR uses a novel approach to synthetically generate the training data needed to identify regulators of reaction fluxes in a given metabolic system, enabling metabolomics and fluxomics data to be leveraged for regulatory structure inference. By identifying and triaging the most likely candidate regulatory interactions, SCOUR can drastically reduce the amount of time needed to identify and experimentally validate metabolic regulatory interactions. As high-throughput experimental methods for testing these interactions are further developed, SCOUR will provide critical impact in the development of predictive metabolic models in new organisms and pathways.
Dysbiosis of intestinal microbiota in early life aggravates high-fat diet induced dysmetabolism in adult mice
Authors: Miao Z. H. , Zhou W. X. , Cheng R. Y. , Liang H. J. , Jiang F. L. , Shen X. , Lu J. H. , Li M. , He F.
Published: July 2021

Background

Accumulating evidence have shown that the intestinal microbiota plays an important role in prevention of host obesity and metabolism disorders. Recent studies also demonstrate that early life is the key time for the colonization of intestinal microbes in host. However, there are few studies focusing on possible association between intestinal microbiota in the early life and metabolism in adulthood. Therefore the present study was conducted to examine whether the short term antibiotic and/or probiotic exposure in early life could affect intestinal microbes and their possible long term effects on host metabolism.

Results

A high-fat diet resulted in glucose and lipid metabolism disorders with higher levels of visceral fat rate, insulin-resistance indices, and leptin. Exposure to ceftriaxone in early life aggravated the negative influences of a high-fat diet on mouse physiology. Orally fed TMC3115 protected mice, especially those who had received treatment throughout the whole study, from damage due to a high-fat diet, such as increases in levels of fasting blood glucose and serum levels of insulin, leptin, and IR indices. Exposure to ceftriaxone during the first 2 weeks of life was linked to dysbiosis of the fecal microbiota with a significant decrease in the species richness and diversity. However, the influence of orally fed ceftriaxone on the fecal microbiota was limited to 12 weeks after the termination of treatment. Of note, at week 12 there were still some differences in the composition of intestinal microbiota between mice provided with high fat diet and antibiotic exposure and those only fed a high fat diet.

Conclusions

These results indicated that exposure to antibiotics, such as ceftriaxone, in early life may aggravate the negative influences of a high-fat diet on the physiology of the host animal. These results also suggest that the crosstalk between the host and their intestinal microbiota in early life may be more important than that in adulthood, even though the same intestinal microbes are present in adulthood.
Population genetic structure and connectivity of a riparian selfing herb Caulokaempferia coenobialis at a fine-scale geographic level in subtropical monsoon forest
Authors: Fu Qiong , Deng Jie , Chen Min , Zhong Yan , Lu Guo-Hui , Wang Ying-Qiang
Published: July 2021

Background

Rivers and streams facilitate movement of individuals and their genes across the landscape and are generally recognized as dispersal corridors for riparian plants. Nevertheless, some authors have reported directly contrasting results, which may be attributed to a complex mixture of factors, such as the mating system and dispersal mechanisms of propagules (seed and pollen), that make it difficult to predict the genetic diversity and population structure of riparian species. Here, we investigated a riparian self-fertilizing herbCaulokaempferia coenobialis, which does not use anemochory or zoochory for seed dispersal; such studies could contribute to an improved understanding of the effect of rivers or streams on population genetic diversity and structure in riparian plants. Using polymorphic ISSR and cpDNA loci, we studied the effect at a microgeographic scale of different stream systems (a linear stream, a dendritic stream, and complex transverse hydrological system) in subtropical monsoon forest on the genetic structure and connectivity ofC. coenobialispopulations across Dinghu Mountain (DH) and Nankun Mountain (NK).

Results

The results indicate that the most recent haplotypes (DH: H7, H8; NK: h6, h7, h11, h12) are not shared among local populations ofC. coenobialiswithin each stream system. Furthermore, downstream local populations do not accumulate genetic diversity, whether in the linear streamside local populations across DH (H: 0.091 vs 0.136) or the dendritic streamside local populations across NK (H: 0.079 vs 0.112, 0.110). Our results show that the connectivity of localC. coenobialispopulations across DH and NK can be attributed to historical gene flows, resulting in a lack of spatial genetic structure, despite self-fertilization. SelfingC. coenobialiscan maintain high genetic diversity (H = 0.251;I = 0.382) through genetic differentiation (GST = 0.5915;FST = 0.663), which is intensified by local adaptation and neutral mutation and/or genetic drift in local populations at a microgeographic scale.

Conclusion

We suggest that streams are not acting as corridors for dispersal ofC. coenobialis, and conservation strategies for maintaining genetic diversity of selfing species should be focused on the protection of all habitat types, especially isolated fragments in ecosystem processes.
RITS: a toolbox for assessing complex interventions via interrupted time series models
Authors: Cruz Maricela , Pinto-Orellana Marco A. , Gillen Daniel L. , Ombao Hernando C.
Published: July 2021

Background

Various interacting and interdependent components comprise complex interventions. These components create difficulty in assessing the true impact of interventions designed to improve patient-centered outcomes. Interrupted time series (ITS) designs borrow from case-crossover designs and serve as quasi-experimental methodology able to retrospectively assess the impact of an intervention while accounting for temporal correlation. While ITS designs are aptly situated for studying the impacts of large-scale public health policies, existing ITS software implement rigid ITS methodology that often assume the pre- and post-intervention phases are fully differentiated (by a known change-point or set of time points) and do not allow for changes in both the mean functions and correlation structure.

Results

This article describes the Robust Interrupted Time Series (RITS) toolbox, a stand-alone user-friendly application researchers can use to implement flexible ITS models that estimate the lagged effect of an intervention on an outcome, level and trend changes, and post-intervention changes in the correlation structure, for single and multiple ITS. The RITS toolbox incorporates a formal test for the existence of a change in the outcome and estimates a change-point over a set of possible change-points defined by the researcher. In settings with multiple ITS, RITS provides a global over-all units change-point and allows for unit-specific changes in the mean functions and correlation structures.

Conclusions

The RITS toolbox is the first piece of software that allows researchers to use flexible ITS models that test for the existence of a change-point, estimate the change-point (if estimation is desired), and allow for changes in both the mean functions and correlation structures at the change point. RITS does not require any knowledge of a statistical (or otherwise) programming language, is freely available to the community, and may be downloaded and used on a local machine to ensure data protection.
Intra-day variation in daily outdoor walking speed among community-dwelling older adults
Authors: Kawai Hisashi , Obuchi Shuichi , Hirayama Ryo , Watanabe Yutaka , Hirano Hirohiko , Fujiwara Yoshinori , Ihara Kazushige , Kim Hunkyung , Kobayashi Yoshiyuki , Mochimaru Masaaki , Tsushima Eiki , Nakamura Kozo
Published: July 2021

Background

Walking speed is an important measure associated with health outcomes in older individuals, such as dependency and death. This study aimed to examine whether the walking speed of community-dwelling older adults varies between time periods within a day, as measured outdoors in daily life. We aimed to determine the types of walking speed variations and examine the factors associated with them.

Methods

Daily life outdoor walking speed was measured in 92 participants (average age 71.9 years±5.64) using a GPS smartphone app for 1 month. Average walking speeds for five time periods were analyzed with a linear mixed model. Intra-day walking speed variation patterns were classified by latent class analysis. Factors associated with the class were identified by logistic regression analysis.

Results

A statistically significant difference in average walking speed was found between early morning (1.33 m/s), and afternoon (1.27 m/s) and evening (1.26 m/s) (p < 0.01). The intra-day variation in walking speed was attributed to variation in cadence. Two classes were identified: (1) fast walking speed with large variation and (2) slow walking speed with little variation; hypertension and frailty level were associated with the class.

Conclusion

The results suggest that there is intra-day variation in walking speed in daily life, wherein the speed is the fastest early in the morning and slower in the afternoon and evening. A larger variation in the walking speed was related to the health status without hypertension or frailty. These results suggest that if a person shows less intra-day variation in walking speed, this could be a sign that they are susceptible to hypertension and an increased frailty level.
Nasopharyngeal carriage of Streptococcus pneumoniae among healthy children in Kassena-Nankana districts of Northern Ghana
Authors: Narwortey Deborah K. , Owusu-Ofori Alex , Slotved Hans-Christian , Donkor Eric S. , Ansah Patrick O. , Welaga Paul , Agongo Godfred , Oduro Abraham R.
Published: July 2021

Background

Pneumococcal vaccine immunizations may be responsible for alterations in serotype epidemiology within a region. This study investigated the pneumococcal carriage prevalence and the impact of the 13-valent pneumococcal conjugate vaccine (PCV-13) on circulating serotypes among healthy children in Northern Ghana.

Methods

This was a cross sectional study conducted in the Kassena-Nankana districts of Northern Ghana from November to December during the dry season of 2018. Nasopharyngeal swabs collected from 193 participants were cultured per standard microbiological protocols and pneumococcal isolates were serotyped using the latex agglutination technique and the capsular Quellung reaction test. We examined for any association between the demographic characteristics of study participants and pneumococcal carriage using chi-square test and logistic regression.

Results

Of the 193 participants that were enrolled the mean age was 8.6 years and 54.4% were females. The carriage rate among the participants was 32.6% (63/193), and twenty different serotypes were identified. These included both vaccine serotypes (VT), 35% (7/20) and non-vaccine serotypes (NVT), 65% (13/20). The predominant serotypes (34 and 11A), both of which were NVT, accounted for a prevalence of 12.8%. PCV-13 covered only 35% of serotypes identified whiles 40% of serotypes are covered by PPV 23.

Conclusion

Post-vaccination carriage of S. pneumoniae is high and is dominated by non-vaccine serotypes. There is therefore a need for the conduct of invasive pneumococcal disease surveillance (IPD) to find out if the high non-vaccine serotype carriage translates to disease. And in addition, a review of the currently used PCV-13 vaccine in the country would be considered relevant.
Pooled sputum to optimise the efficiency and utility of rapid, point-of-care molecular SARS-CoV-2 testing
Authors: Burdett Alison , Toumazou Christofer , Sahoo Rashmita , Mujan Adam , Hon Tsz-Kin , Bedzo-Nutakor Judith , Casali Nicola , Karvela Maria , Sohbati Mohammadreza , Cooke Graham S. , Davies Gary W. , Moore Luke S. P.
Published: July 2021

Background

As SARS-CoV-2 testing expands, particularly to widespread asymptomatic testing, high sensitivity point-of-care PCR platforms may optimise potential benefits from pooling multiple patients’ samples.

Method

We tested patients and asymptomatic citizens for SARS-CoV-2, exploring the efficiency and utility of CovidNudge (i) for detection in individuals’ sputum (compared to nasopharyngeal swabs), (ii) for detection in pooled sputum samples, and (iii) by modelling roll out scenarios for pooled sputum testing.

Results

Across 295 paired samples, we find no difference (p = 0.1236) in signal strength for sputum (mean amplified replicates (MAR) 25.2, standard deviation (SD) 14.2, range 0–60) compared to nasopharyngeal swabs (MAR 27.8, SD 12.4, range 6–56). At 10-sample pool size we find some drop in absolute strength of signal (individual sputum MAR 42.1, SD 11.8, range 13–60 vs. pooled sputum MAR 25.3, SD 14.6, range 1–54; p < 0.0001), but only marginal drop in sensitivity (51/53,96%). We determine a limit of detection of 250 copies/ml for an individual test, rising only four-fold to 1000copies/ml for a 10-sample pool. We find optimal pooled testing efficiency to be a 12–3-1-sample model, yet as prevalence increases, pool size should decrease; at 5% prevalence to maintain a 75% probability of negative first test, 5-sample pools are optimal.

Conclusion

We describe for the first time the use of sequentially dipped sputum samples for rapid pooled point of care SARS-CoV-2 PCR testing. The potential to screen asymptomatic cohorts rapidly, at the point-of-care, with PCR, offers the potential to quickly identify and isolate positive individuals within a population “bubble”.
Clinical features and predictors for patients with severe SARS-CoV-2 pneumonia at the start of the pandemic: a retrospective multicenter cohort study
Authors: Cao Chao , He Li , Ma Jingping , Chen Meiping , Li Yiting , Jiang Qingwen , Wu Shiyu , Yu Lili , Huang Weina , Qian Guoqing , Zhu Chuanbing , Chu Jinguo , Chen Xiaomin
Published: July 2021

Background

This study was performed to investigate clinical features of patients with severe SARS-CoV-2 pneumonia and identify risk factors for converting to severe cases in those who had mild to moderate diseases at the start of the pandemic in China.

Methods

In this retrospective, multicenter cohort study, patients with mild to moderate SARS-CoV-2 pneumonia were included. Demographic data, symptoms, laboratory values, and clinical outcomes were collected. Data were compared between non-severe and severe patients.

Results

58 patients were included in the final analysis. Compared with non-severe cases, severe patients with SARS-CoV-2 pneumonia had a longer: time to clinical recovery (12·9 ± 4·4 vs 8·3 ± 4·7; P = 0·0011), duration of viral shedding (15·7 ± 6·7 vs 11·8 ± 5·0; P = 0·0183), and hospital stay (20·7 ± 1·2 vs 14·4 ± 4·3; P = 0·0211). Multivariate logistic regression indicated that lymphocyte count was significantly associated with the rate of converting to severe cases (odds ratio 1·28, 95%CI 1·06–1·54, per 0·1 ×  109/L reduced; P = 0·007), while using of low-to-moderate doses of systematic corticosteroids was associated with reduced likelihood of converting to a severe case (odds ratio 0·14, 95%CI 0·02–0·80; P = 0·0275).

Conclusions

The low peripheral blood lymphocyte count was an independent risk factor for SARS-CoV-2 pneumonia patients converting to severe cases. However, this study was carried out right after the start of the pandemic with small sample size. Further prospective studies are warranted to confirm these findings.

Trial registration

Chinese Clinical Trial Registry, ChiCTR2000029839. Registered 15 February 2020 - Retrospectively registered.
Lesion probability mapping in MS patients using a regression network on MR fingerprinting
Authors: Hermann Ingo , Golla Alena K. , Martínez-Heras Eloy , Schmidt Ralf , Solana Elisabeth , Llufriu Sara , Gass Achim , Schad Lothar R. , Zöllner Frank G.
Published: July 2021

Background

To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to $$T_1$$

T
1

, $${T_2}^*$$

T
2

∗

, NAWM, and GM- probability maps.

Methods

We performed MRF-EPI measurements in 42 patients with multiple sclerosis and 6 healthy volunteers along two sites. A U-net was trained to reconstruct the denoised and distortion corrected $$T_1$$

T
1

and $${T_2}^*$$

T
2

∗

maps, and to additionally generate NAWM-, GM-, and WM lesion probability maps.

Results

WM lesions were predicted with a dice coefficient of $$0.61\pm 0.09$$

0.61
±
0.09

and a lesion detection rate of $$0.85\pm 0.25$$

0.85
±
0.25

for a threshold of 33%. The network jointly enabled accurate $$T_1$$

T
1

and $${T_2}^*$$

T
2

∗

times with relative deviations of 5.2% and 5.1% and average dice coefficients of $$0.92\pm 0.04$$

0.92
±
0.04

and $$0.91\pm 0.03$$

0.91
±
0.03

for NAWM and GM after binarizing with a threshold of 80%.

Conclusion

DL is a promising tool for the prediction of lesion probability maps in a fraction of time. These might be of clinical interest for the WM lesion analysis in MS patients.
Validation of questionnaire-reported chest wall abnormalities with a telephone interview in Swiss childhood cancer survivors
Authors: Kasteler Rahel , Lichtensteiger Christa , Schindera Christina , Ansari Marc , Kuehni Claudia E. ,   for the Swiss Pediatric Oncology Group (SPOG) Scientific Committee, Rössler J. , Ansari M. , Beck Popovic M. , Brazzola P. , Greiner J. , Niggli F. , Hengartner H. , Kuehni C. , Schilling F. , Scheinemann K. , von der Weid N. , Gerber N.
Published: July 2021

Background

Chest wall abnormalities are a poorly studied complication after treatment for childhood cancer. Chest wall abnormalities are not well-described in the literature, and little is known on the impact on daily life of survivors.

Methods

We investigated prevalence and risk factors of chest wall abnormalities in childhood cancer survivors in a nationwide, population-based cohort study (Swiss Childhood Cancer Survivor Study) with a questionnaire survey. We then interviewed a nested sample of survivors to validate types of chest wall abnormalities and understand their impact on the daily life of survivors.

Results

Forty-eight of 2382 (95%CI 2–3%) survivors reported a chest wall abnormality. Risk factors were older age at cancer diagnosis (16–20 years; OR 2.5, 95%CI 1.0–6.1), lymphoma (OR 3.8, 95%CI 1.2–11.4), and central nervous system tumors (OR 9.5, 95%CI 3.0–30.1) as underlying disease, and treatment with thoracic radiotherapy (OR 2.0, 95%CI 1.0–4.2), surgery to the chest (OR 4.5, 95%CI 1.8–11.5), or chemotherapy (OR 2.9, 95%CI 1.0–8.1). The nature of the chest wall abnormalities varied and included thoracic wall deformities (30%), deformations of the spine (5%) or both (55%), and scars (10%). Chest wall abnormalities affected daily life in two thirds (13/20) of those who reported these problems and necessitated medical attention for 15 (75%) survivors.

Conclusion

It is important that, during follow-up care, physicians pay attention to chest wall abnormalities, which are rare late effects of cancer treatment, but can considerably affect the well-being of cancer survivors.
The platelet to lymphocyte ratio is a potential inflammatory marker predicting the effects of adjuvant chemotherapy in patients with stage II colorectal cancer
Authors: Fu Yu , Chen Xiaowan , Song Yongxi , Huang Xuanzhang , Chen Quan , Lv Xinger , Gao Peng , Wang Zhenning
Published: July 2021

Background

The effects of adjuvant chemotherapy in patients with stage II colorectal cancer (CRC) has been in controversy for a long time. Our study aimed to find an effective inflammatory marker to predict the effects of chemotherapy.

Methods

Seven hundred eight stage II CRC patients in our institution were included. The subpopulation treatment effect pattern plot (STEPP) analysis was used to determine the optimal inflammatory marker and cut-off value. Propensity score matching (PSM) was performed to balance discrepancy between the chemotherapy and non-chemotherapy group. Survival analyses based on overall survival (OS) and cancer-specific survival (CSS) were performed with Kaplan-Meier methods with log-rank test and Cox proportional hazards regression. The restricted mean survival time (RMST) was used to measure treatment effect.

Results

The platelet to lymphocyte ratio (PLR) was chosen as the optimal marker with a cut-off value of 130 according to STEPP. In OS analysis, PLR was significantly associated with the effects of chemotherapy (interaction p = 0.027). In the low-PLR subgroup, the chemotherapy patients did not have a longer OS than the non-chemotherapy patients (HR: 0.983, 95% CI: 0.528–1.829). In the high-PLR subgroup, the chemotherapy patients had a significantly longer OS than the non-chemotherapy patients (HR: 0.371, 95% CI: 0.212–0.649). After PSM, PLR was still associated with the effects of chemotherapy. In CSS analysis, PLR was not significantly associated with the effects of chemotherapy (interaction p = 0.116). In the low-PLR subgroup, the chemotherapy patients did not have a longer CSS than the non-chemotherapy patients (HR: 1.016, 95% CI: 0.494–2.087). In the high-PLR subgroup, the chemotherapy patients had a longer CSS than the non-chemotherapy patients (HR: 0.371, 95% CI: 0.212–0.649). After PSM, PLR was not associated with the effects of chemotherapy.

Conclusions

PLR is an effective marker to predict the effects of chemotherapy in patients with stage II CRC.
Barriers and opportunities to restricting marketing of unhealthy foods and beverages to children in Nepal: a policy analysis
Authors: Fisher Laura , Dahal Minakshi , Hawkes Sarah , Puri Mahesh , Buse Kent
Published: July 2021

Background

Marketing of foods and non-alcoholic beverages high in saturated fats, trans-fatty acids, free sugars, or salt (“unhealthy foods”) to children is contributing to increasing child obesity. However, many countries have not implemented WHO recommendations to restrict marketing of unhealthy foods to children. We sought to understand the absence of marketing restrictions and identify potential strategic actions to develop and implement such restrictions in Nepal.

Methods

Eighteen semi-structured interviews were conducted. Thematic analysis was based on Baker et al.’s 18 factor-framework for understanding what drives political commitment to nutrition, organised by five categories: Actors; Institutions; Political and societal contexts; Knowledge, evidence and framing; Capacities and resources.

Results

All factors in Baker et al.’s framework were reported to be acting largely as barriers to Nepal developing and implementing marketing restrictions. Six factors were identified by the highest number of respondents: the threat of private sector interference in policy-making; lack of international actor support; absence of well-designed and enacted policies and legislation; lack of political commitment to regulate; insufficient mobilisation of existing evidence to spur action and lack of national evidence to guide regulatory design; and weak implementation capacity. Opportunities for progress were identified as Nepal’s ability to combat private sector interference - as previously demonstrated in tobacco control.

Conclusions

This is the first study conducted in Nepal examining the lack of restrictions on marketing unhealthy foods to children. Our findings reflect the manifestation of power in the policy process. The absence of civil society and a multi-stakeholder coalition demanding change on marketing of unhealthy food to children, the threat of private sector interference in introducing marketing restrictions, the promotion of norms and narratives around modernity, consumption and the primary role of the individual in regulating diet - all have helped create a policy vacuum on marketing restrictions. We propose that stakeholders focus on five strategic actions, including: developing a multi-stakeholder coalition to put and keep marketing restrictions on the health agenda; framing the need for marketing restrictions as critical to protect child rights and government regulation as the solution; and increasing support, particularly through developing more robust global policy guidance.
Changes over time in the relationship between weight, body fat, motivation, impulsivity and eating behaviour
Authors: Foscarini-Craggs Paula , Lowe Rob , Lee Michelle
Published: July 2021

Background

University students are at a greater risk of gaining weight compared to others. We explored associations between changes in weight and a set of dispositional constructs related to eating behaviour: motivation, impulsivity, social comparison, and eating styles. We predicted that increases in controlled motivation, impulsivity, uncontrolled eating, emotional eating, and physical appearance comparison would be related to increased weight and body fat.

Methods

First year students at a British university completed baseline (n = 196) and three-month (n = 163) measures of impulsivity, physical appearance comparison, motivation for following a healthy diet, eating styles, weight and body fat. Baseline-follow-up changes in these constructs were computed and subjected to cluster analysis.

Results

Four participant groups were identified according to similarities in the way these constructs evolved over time. The Losing and Gaining groups tended to show opposing changes in key variables (physical appearance comparison, uncontrolled eating, motivation, weight, and percentage of body fat). Interestingly, two groups showed no change in weight and body fat but evidenced unique changes in key variables, indicating that individuals can have different psychological profiles but still maintain their weight.

Conclusions

The study highlighted how stable weight maintenance arises from sets of interdependent constructs rather than variables in isolation, as well as emphasizing a need to take a person-centred approach to examining those at risk of weight gain and in developing interventions.
Associations between CD160 polymorphisms and autoimmune thyroid disease: a case-control study
Authors: He Weiwei , Zhao Jing , Liu Xuerong , Li Sheli , Mu Kaida , Zhang Jing , Zhang Jin-an
Published: July 2021

Background

Recent researches suggest that the CD160/HVEM/LIGHT/BTLA signaling pathway may contribute to the pathogeneses of autoimmune diseases, but the relationship between CD160 polymorphisms and autoimmune thyroid disease (AITD) has not been reported yet. This study aimed to evaluate the associations between CD160 polymorphisms and AITD.

Methods

A total of 1017 patients with AITD (634 Graves’ disease and 383 Hashimoto’s thyroiditis) and 856 unrelated healthy controls were recruited into our study. Odds ratios (ORs) with 95% confidence interval (95%CI) were calculated through logistic regression analyses. The CD160 SNPs were detected using Hi-SNP high-throughput genotyping.

Results

There was a statistically significant difference between Graves’ disease patients and the control group with respect to both the genotype distribution (P = 0.014) and allele frequency of rs744877 (P = 0.034). A significant association of CD160 rs744877 with AITD was observed before adjusted age and gender under a dominant model (OR = 0.79, 95%CI 0.66–0.95;P = 0.013) and an additive model (OR = 0.77, 95%CI 0.64–0.94,P = 0.008), and was also observed after adjusted age and gender under a dominant model (OR = 0.78, 95%CI 0.65–0.95;P = 0.011) and an additive model (OR = 0.76, 95%CI 0.63–0.93,P = 0.007). A significant association of rs744877 with Graves’ disease was observed under an allele model (OR = 0.84, 95%CI 0.71–0.98,P = 0.027), a dominant model (OR = 0.74, 95%CI 0.60–0.91;P = 0.005), and an additive model (OR = 0.72, 95%CI 0.58–0.90,P = 0.004). Multivariate logistic regression analyses suggested that the association remained significant after adjustment for age and gender. However, rs744877 was not related to Hashimoto’s thyroiditis. Furthermore, CD160 rs3766526 was not significantly related to either Graves’ disease or Hashimoto’s thyroiditis.

Conclusion

This is the first identification of the association of CD160 rs744877 with Graves’ disease. Our findings add new data to the genetic contribution to Graves’ disease susceptibility and support the crucial role of the CD160/HVEM/LIGHT/BTLA pathway in the pathogenesis of Graves’ disease.
REAPing the benefits: development and use of a structured evaluation framework to codify learning resources for Global Health professionals
Authors: Schleiff Meike , Hahn Elizabeth , Dolive Caroline , James Lillian , Mishra Anant , Hansoti Bhakti
Published: July 2021

Background

The learning opportunities for global health professionals have expanded rapidly in recent years. The diverse array of learners and wide range in course quality underscore the need for an improved course vetting process to better match learners with appropriate learning opportunities.

Methods

We developed a framework to assess overall course quality by determining performance across four defined domains Relevance, Engagement, Access, and Pedagogy (REAP). We applied this framework across a learning catalogue developed for participants enrolled in the Sustaining Technical and Analytic Resources (STAR) project, a global health leadership training program.

Results

The STAR learning activities database included a total of 382 courses, workshops, and web-based resources which fulfilled 531 competencies across three levels: core, content, and skill. Relevance: The majority of activities were at an understanding or practicing level across all competency domains (486/531, 91.5%). Engagement: Many activities lacked any peer engagement (202/531, 38.0%) and had limited to no faculty engagement (260/531, 49.0%). Access: The plurality of courses across competencies were offered on demand (227/531, 42.7%) and were highly flexible in pace (240/531, 45.2%). Pedagogy: Of the activities that included an assessment, most matched activity learning objectives (217/531, 40.9%).

Conclusions

Through applying REAP to the STAR project learning catalogue, we found many online activities lacked meaningful engagement with faculty and peers. Further development of structured online activities providing learners with flexibility in access, a range of levels of advancement for content, and opportunities to engage and apply learning are needed for the field of global health.
Explaining multivariate molecular diagnostic tests via Shapley values
Authors: Roder Joanna , Maguire Laura , Georgantas Robert , Roder Heinrich
Published: July 2021

Background

Machine learning (ML) can be an effective tool to extract information from attribute-rich molecular datasets for the generation of molecular diagnostic tests. However, the way in which the resulting scores or classifications are produced from the input data may not be transparent. Algorithmic explainability or interpretability has become a focus of ML research. Shapley values, first introduced in game theory, can provide explanations of the result generated from a specific set of input data by a complex ML algorithm.

Methods

For a multivariate molecular diagnostic test in clinical use (the VeriStrat® test), we calculate and discuss the interpretation of exact Shapley values. We also employ some standard approximation techniques for Shapley value computation (local interpretable model-agnostic explanation (LIME) and Shapley Additive Explanations (SHAP) based methods) and compare the results with exact Shapley values.

Results

Exact Shapley values calculated for data collected from a cohort of 256 patients showed that the relative importance of attributes for test classification varied by sample. While all eight features used in the VeriStrat® test contributed equally to classification for some samples, other samples showed more complex patterns of attribute importance for classification generation. Exact Shapley values and Shapley-based interaction metrics were able to provide interpretable classification explanations at the sample or patient level, while patient subgroups could be defined by comparing Shapley value profiles between patients. LIME and SHAP approximation approaches, even those seeking to include correlations between attributes, produced results that were quantitatively and, in some cases qualitatively, different from the exact Shapley values.

Conclusions

Shapley values can be used to determine the relative importance of input attributes to the result generated by a multivariate molecular diagnostic test for an individual sample or patient. Patient subgroups defined by Shapley value profiles may motivate translational research. However, correlations inherent in molecular data and the typically small ML training sets available for molecular diagnostic test development may cause some approximation methods to produce approximate Shapley values that differ both qualitatively and quantitatively from exact Shapley values. Hence, caution is advised when using approximate methods to evaluate Shapley explanations of the results of molecular diagnostic tests.
DMD/BMD prenatal diagnosis and treatment expectation in a single centre in China for 15 years
Authors: Zhong Xingjian , Cui Siying , Liu Lina , Yang Yuxia , Kong Xiangdong
Published: July 2021

Objective

DMD/BMD prenatal diagnosis for 931 foetuses.

Background

DMD is the most common fatal X-linked recessive muscular disease. There is no effective clinical treatment method at present. Accurate gene diagnosis and prenatal diagnosis technology are important ways for early detection, early prevention and early treatment.

Methods

A total of 931 prenatal diagnoses were performed for pregnant women with a definite family history of DMD or a history of DMD childbirth between 2005 and 2019. This report may be considered the largest DMD prenatal diagnosis report in a single centre worldwide. Multiple ligation-dependent probe amplification (MLPA) and next-generation sequencing were used in combination. Techniques and short tandem repeat (STR) linkage analysis were used to determine the location of the DMD gene mutation in the pregnant woman and then to detect the DMD gene in the foetuses.

Results

There were 872 families in our study. Among all 931 foetuses, 20.73% (193/931) were males expected to develop DMD and 16.33% (152/931) were female carriers. In addition, gonadal mosaicism was observed in 5 mothers, and gene recombination was identified in three foetuses. The results of the prenatal diagnosis were consistent with the results of the CPK analysis, and the results of the prenatal diagnosis were 100% accurate.

Conclusions

MLPA and Sanger sequencing, when combined with STR linkage analyses, can provide an accurate and rapid prenatal diagnosis. Due to the high de novo rate, prenatal diagnosis and genetic counselling should be given great attention.
Characterization of glycoside hydrolase family 11 xylanase from Streptomyces sp. strain J103; its synergetic effect with acetyl xylan esterase and enhancement of enzymatic hydrolysis of lignocellulosic biomass
Authors: Marasinghe Svini Dileepa , Jo Eunyoung , Hettiarachchi Sachithra Amarin , Lee Youngdeuk , Eom Tae-Yang , Gang Yehui , Kang Yoon-Hyeok , Oh Chulhong
Published: July 2021

Background

Xylanase-containing enzyme cocktails are used on an industrial scale to convert xylan into value-added products, as they hydrolyse the β-1,4-glycosidic linkages between xylopyranosyl residues. In the present study, we focused on xynS1, the glycoside hydrolase (GH) 11 xylanase gene derived from the Streptomyces sp. strain J103, which can mediate XynS1 protein synthesis and lignocellulosic material hydrolysis.

Results

xynS1 has an open reading frame with 693 base pairs that encodes a protein with 230 amino acids. The predicted molecular weight and isoelectric point of the protein were 24.47 kDa and 7.92, respectively. The gene was cloned into the pET-11a expression vector and expressed in Escherichia coli BL21(DE3). Recombinant XynS1 (rXynS1) was purified via His-tag affinity column chromatography. rXynS1 exhibited optimal activity at a pH of 5.0 and temperature of 55 °C. Thermal stability was in the temperature range of 50–55 °C. The estimated Km and Vmax values were 51.4 mg/mL and 898.2 U/mg, respectively. One millimolar of Mn2+ and Na+ ions stimulated the activity of rXynS1 by up to 209% and 122.4%, respectively, and 1 mM Co2+ and Ni2+ acted as inhibitors of the enzyme. The mixture of rXynS1, originates from Streptomyces sp. strain J103 and acetyl xylan esterase (AXE), originating from the marine bacterium Ochrovirga pacifica, enhanced the xylan degradation by 2.27-fold, compared to the activity of rXynS1 alone when Mn2+ was used in the reaction mixture; this reflected the ability of both enzymes to hydrolyse the xylan structure. The use of an enzyme cocktail of rXynS1, AXE, and commercial cellulase (Celluclast® 1.5 L) for the hydrolysis of lignocellulosic biomass was more effective than that of commercial cellulase alone, thereby increasing the relative activity 2.3 fold.

Conclusion

The supplementation of rXynS1 with AXE enhanced the xylan degradation process via the de-esterification of acetyl groups in the xylan structure. Synergetic action of rXynS1 with commercial cellulase improved the hydrolysis of pre-treated lignocellulosic biomass; thus, rXynS1 could potentially be used in several industrial applications.
RETRACTED ARTICLE: LINC00115 promotes stemness and inhibits apoptosis of ovarian cancer stem cells by upregulating SOX9 and inhibiting the Wnt/β-catenin pathway through competitively binding to microRNA-30a
Authors: Hou Rui , Jiang Luo
Published: July 2021

Objective

Long non-coding RNAs (lncRNAs) and microRNAs (miRs) are differentially expressed in ovarian cancer (OC) cells and influence OC progression. This study intended to explore the underlying roles of LINC00115 and miR-30a in OC.

Methods

Gene Expression Omnibus database was used to find OC microarray datasets and bioinformatics analysis predicted the potential molecular mechanism of OC. OC stem cells (OCSCs) surface marker was isolated from human OC cell line and identified. CD133+ OCSCs were transfected with LINC00115, miR-30a and SOX9 alone or together to detect sphere-forming ability and apoptosis of OCSCs. Caspase-3 activity and DNA damage in cell supernatant were detected. The levels of CD44, NANOG, POU5F1, LINC00115, CD133, miR-30a and SOX9 were measured. Then sh-LNC00115-treated OCSCs were added with Wnt/β-catenin activator SKL2001 to observe the changes of cell stemness and activity. Finally, animal models were established to evaluate the effect of LINC00115 on OCSC in vivo.

Results

LINC00115 and SOX9 were highly expressed in OC, while miR-30a was lowly expressed. After silencing LINC00115 or overexpressing miR-30a, the sphere-forming rate of CD133+ OCSC and levels of CD133, CD44, NANOG and POU5F1 decreased, while apoptotic rate, Caspase-3 activity and histone-related DNA damage increased. SOX9 reversed these trends. Additionally, LINC00115 could bind to miR-30a and miR-30a could target SOX9. SKL2001 partially reversed cell stemness and activity in sh-LNC00115-treated OCSCs. Finally, silencing LINC00115 could inhibit OCSCs growth in vivo.

Conclusion

LINC00115 promoted stemness and inhibited apoptosis of OCSCs by upregulating SOX9 and in activating the Wnt/β-catenin pathway through competitively binding to miR-30a.
Usability of a point-of-care diagnostic to identify glucose-6-phosphate dehydrogenase deficiency: a multi-country assessment of test label comprehension and results interpretation
Authors: Gerth-Guyette Emily , Adissu Wondimagegn , Brito Marcelo , Garbin Eduardo , Macedo Marcela , Sharma Abhijit , Das Santasabuj , Lacerda Marcus V. G. , Pereira Dhélio , Talukdar Arunansu , Yilma Daniel , Pal Sampa , Zobrist Stephanie , Domingo Gonzalo J.
Published: July 2021

Background

Point-of-care glucose-6-phosphate dehydrogenase (G6PD) testing has the potential to make the use of radical treatment for vivax malaria safer and more effective. Widespread use of G6PD tests as part of malaria case management has been limited, in part due to due concerns regarding product usability, user training, and supervision. This study seeks to assess how well end users can understand the Standard™ G6PD Test (SD Biosensor, Suwon, South Korea) workflow, result output, and label after training. This will ultimately help inform test registration and introduction.

Methods

Potential G6PD test users who provide malaria case management at three sites in Brazil, Ethiopia, and India were trained on the use of the SD Biosensor Standard G6PD Test and assessed based on their ability to understand the test workflow and interpret results. The assessment was done through a questionnaire, designed to assess product usability against key technical product specifications and fulfill regulatory evidence requirements. Any participant who obtained 85% or above correct responses to the questionnaire was considered to adequately comprehend how to use and interpret the test.

Results

Forty-five participants, including malaria microscopists, laboratory staff, nurses, and community health workers took part in the study. Seventy-eight percent of all participants in the study (35/45) obtained passing scores on the assessment with minimal training. Responses to the multiple-choice questions indicate that most participants understood well the test intended use, safety claims, and warnings. The greatest source of error regarding the test was around the correct operating temperature. Most test results were also read and interpreted correctly, with the haemoglobin measurement being a more problematic output to interpret than the G6PD measurement.

Conclusions

These data results show how a standardized tool can be used to assess a user’s ability to run a point-of-care diagnostic and interpret results. When applied to the SD Biosensor Standard G6PD Test, this tool demonstrates that a range of users across multiple contexts can use the test and suggests improvements to the test instructions and training that can improve product usability, increase user comprehension, and ultimately contribute to more widespread effective use of point-of-care G6PD tests.

Trial registration: NCT04033640