bluuebunny/crossref_metadata_2025_split huggingface dataset:
Weighted Cox regression for the prediction of heterogeneous patient subgroups
Authors: Madjar Katrin , Rahnenführer Jörg 
Published: December 2021

AbstractBackgroundAn important task in clinical medicine is the construction of risk prediction models for specific subgroups of patients based on high-dimensional molecular measurements such as gene expression data. Major objectives in modeling high-dimensional data are good prediction performance and feature selection to find a subset of predictors that are truly associated with a clinical outcome such as a time-to-event endpoint. In clinical practice, this task is challenging since patient cohorts are typically small and can be heterogeneous with regard to their relationship between predictors and outcome. When data of several subgroups of patients with the same or similar disease are available, it is tempting to combine them to increase sample size, such as in multicenter studies. However, heterogeneity between subgroups can lead to biased results and subgroup-specific effects may remain undetected.MethodsFor this situation, we propose a penalized Cox regression model with a weighted version of the Cox partial likelihood that includes patients of all subgroups but assigns them individual weights based on their subgroup affiliation. The weights are estimated from the data such that patients who are likely to belong to the subgroup of interest obtain higher weights in the subgroup-specific model.ResultsOur proposed approach is evaluated through simulations and application to real lung cancer cohorts, and compared to existing approaches. Simulation results demonstrate that our proposed model is superior to standard approaches in terms of prediction performance and variable selection accuracy when the sample size is small.ConclusionsThe results suggest that sharing information between subgroups by incorporating appropriate weights into the likelihood can increase power to identify the prognostic covariates and improve risk prediction.
Modelling and identification of characteristic kinematic features preceding freezing of gait with convolutional neural networks and layer-wise relevance propagation
Authors: Filtjens Benjamin , Ginis Pieter , Nieuwboer Alice , Afzal Muhammad Raheel , Spildooren Joke , Vanrumste Bart , Slaets Peter 
Published: December 2021

Abstract
Background
Although deep neural networks (DNNs) are showing state of the art performance in clinical gait analysis, they are considered to be black-box algorithms. In other words, there is a lack of direct understanding of a DNN’s ability to identify relevant features, hindering clinical acceptance. Interpretability methods have been developed to ameliorate this concern by providing a way to explain DNN predictions.

Methods
This paper proposes the use of an interpretability method to explain DNN decisions for classifying the movement that precedes freezing of gait (FOG), one of the most debilitating symptoms of Parkinson’s disease (PD). The proposed two-stage pipeline consists of (1) a convolutional neural network (CNN) to model the reduction of movement present before a FOG episode, and (2) layer-wise relevance propagation (LRP) to visualize the underlying features that the CNN perceives as important to model the pathology. The CNN was trained with the sagittal plane kinematics from a motion capture dataset of fourteen PD patients with FOG. The robustness of the model predictions and learned features was further assessed on fourteen PD patients without FOG and fourteen age-matched healthy controls.

Results
The CNN proved highly accurate in modelling the movement that precedes FOG, with 86.8% of the strides being correctly identified. However, the CNN model was unable to model the movement for one of the seven patients that froze during the protocol. The LRP interpretability case study shows that (1) the kinematic features perceived as most relevant by the CNN are the reduced peak knee flexion and the fixed ankle dorsiflexion during the swing phase, (2) very little relevance for FOG is observed in the PD patients without FOG and the healthy control subjects, and (3) the poor predictive performance of one subject is attributed to the patient’s unique and severely flexed gait signature.

Conclusions
The proposed pipeline can aid clinicians in explaining DNN decisions in clinical gait analysis and aid machine learning practitioners in assessing the generalization of their models by ensuring that the predictions are based on meaningful kinematic features.
Including undocumented migrants in universal health coverage: a maternal health case study from the Thailand-Myanmar border
Authors: Tschirhart Naomi , Jiraporncharoen Wichuda , Thongkhamcharoen Rojanasak , Yoonut Kulyapa , Ottersen Trygve , Angkurawaranon Chaisiri 
Published: December 2021

AbstractBackgroundMany countries aspiring to achieve universal health coverage struggle with how to ensure health coverage for undocumented migrants. Using a case study of maternal health care in a Thailand-Myanmar border region this article explores coverage for migrants, service provision challenges and the contribution of a voluntary health insurance program.MethodsIn 2018 we interviewed 18 key informants who provided, oversaw or contributed to maternal healthcare services for migrant women in the border region of Tak province, Thailand.ResultsIn this region, we found that public and non-profit providers helped increase healthcare coverage beyond undocumented migrants’ official entitlements. Interview participants explained that Free and low-cost antenatal care (ANC) is provided to undocumented migrants through migrant specific clinics, outreach programs and health posts. Hospitals offer emergency birth care, although uninsured migrant patients are subsequently billed for the services. Care providers identified sustainability, institutional debt from unpaid obstetric hospital bills, cross border logistical difficulties and the late arrival of patients requiring emergency lifesaving interventions as challenges when providing care to undocumented migrants. An insurance fund was developed to provide coverage for costly emergency interventions at Thai government hospitals. The insurance fund, along with existing free and low-cost services, helped increase population coverage, range of services and financial protection for undocumented migrants.ConclusionsThis case study offers considerations for extending health coverage to undocumented populations. Non-profit insurance funds can help to improve healthcare entitlements, provide financial protection and reduce service providers’ debt. However, there are limits to programs that offer voluntary coverage for undocumented migrants. High costs associated with emergency interventions along with gaps in insurance coverage challenge the sustainability for NGO, non-profit and government health providers and may be financially disastrous for patients. Finally, in international border regions with high mobility, it may be valuable to implement and strengthen cross border referrals and health insurance for migrants.
Airway IL-1β associates with IL-5 production following dust mite allergen inhalation in humans
Authors: Burbank Allison J. , Schworer Stephen A. , Sood Amika , Almond Martha , Chason Kelly , Bean Nathan , Zhou Haibo , Hernandez Michelle L. 
Published: December 2021

AbstractBackgroundPreclinical studies implicate interleukin (IL)-1β as a key mediator of asthma and have shown the efficacy of IL-1 antagonism for treatment of allergic airway inflammation; human studies in this area are lacking.ObjectivesOur aim was to study the relationship of airway IL-1β to features of acute allergen-induced asthma exacerbation in humans.MethodsDust mite-allergic adults with mild asthma underwent inhalation challenge withDermatophagoides farinae. Fractional exhaled nitric oxide (FeNO), induced sputum and peripheral blood samples were obtained pre- and 24 h post-challenge. Spirometry was performed before and throughout the challenge at 10-min intervals, and allergen responsiveness was defined by a 20% fall in Forced Expiratory Volume in 1 s (FEV1). Sputum samples were analyzed for inflammatory cells, cytokines and chemokines. Multiple linear regression was employed to test the association between sputum IL-1β concentration and biomarkers of T helper type 2 (T2)-dominant inflammation.ResultsFourteen volunteers underwent inhaled allergen challenge. Allergen responsive volunteers showed a greater positive change in IL-1β in sputum following allergen challenge compared to non-responders. Higher pre-challenge sputum IL-1β was associated with greater increase in sputum IL-5 (p = 0.004), sputum eosinophils (p = 0.001) and blood IL-5 (p = 0.003) following allergen challenge. Allergen-induced sputum IL-1β production was significantly associated with sputum and blood IL-5 (p < 0.001 and p = 0.007, respectively), sputum IL-4 (p = 0.001), IL-13 (p = 0.026), eosinophils (p = 0.008) and FeNO (p = 0.03).ConclusionsThe positive association between production of IL-1β and biomarkers of T2 inflammation, particularly IL-5, in humans is consistent with work in animal models that demonstrates a link between IL-1β and the pathophysiology of allergic asthma. The role of IL-1β in human asthma warrants further study.
Oleaginous yeasts- substrate preference and lipid productivity: a view on the performance of microbial lipid producers
Authors: Shaigani Pariya , Awad Dania , Redai Veronika , Fuchs Monika , Haack Martina , Mehlmer Norbert , Brueck Thomas 
Published: December 2021

Abstract
Background
Oleaginous yeasts are promising microbial platforms for sustainable, bio-based production of biofuels and oleochemical building blocks. Bio-based residues provide sustainable and cost-effective carbon sources for fermentative yeast oil production without land-use change. Considering the regional abundancy of different waste streams, we chose complex biomass residue streams of marine origin; macroalgae hydrolysate, and terrestrial origin; wheat straw hydrolysate in the presence, and absence of corn steep liquor as a complex nitrogen source. We investigated the biomass and lipid yields of an array of well-described oleaginous yeasts; R. glutinis, T. asahii, R. mucilaginosa, R. toruloides, C. oleaginosus growing on these hydrolysates. Furthermore, their sugar utilization, fatty acid profile, and inhibitory effect of the hydrolysates on yeast growth were compared. For correlative reference, we initially performed comparative growth experiments for the strains on individual monomeric sugars separately. Each of these monomeric sugars was a dominant carbon source in the complex biomass hydrolysates evaluated in this study. In addition, we evaluated N-acetylglucosamine, the monomeric building block of chitin, as a low-cost nitrogen and carbon source in yeast fermentation.

Results
C. oleaginosus provided the highest biomass and lipid yields. In the wheat straw and brown algae hydrolysates, this yeast strain gained 7.5 g/L and 3.8 g/L lipids, respectively. Cultivation in algae hydrolysate resulted in a higher level of unsaturated fatty acids in the lipids accumulated by all yeast strains. R. toruloides and C. oleaginosus were able to effectively co-utilize mannitol, glucose, and xylose. Growth rates on wheat straw hydrolysate were enhanced in presence of corn steep liquor.

Conclusions
Among the yeast strains investigated in this study, C. oleaginosus proved to be the most versatile strain in terms of substrate utilization, productivity, and tolerance in the complex media. Various fatty acid profiles obtained on each substrate encourage the manipulation of culture conditions to achieve the desired fatty acid composition for each application. This could be accomplished by combining the element of carbon source with other formerly studied factors such as temperature and oxygen. Moreover, corn steep liquor showed promise for enhancement of growth in the oleaginous strains provided that carbon substrate is available.
The history, state of the art and future prospects for oleaginous yeast research
Authors: Abeln Felix , Chuck Christopher J. 
Published: December 2021

AbstractLipid-based biofuels, such as biodiesel and hydroprocessed esters, are a central part of the global initiative to reduce the environmental impact of the transport sector. The vast majority of production is currently from first-generation feedstocks, such as rapeseed oil, and waste cooking oils. However, the increased exploitation of soybean oil and palm oil has led to vast deforestation, smog emissions and heavily impacted on biodiversity in tropical regions. One promising alternative, potentially capable of meeting future demand sustainably, are oleaginous yeasts. Despite being known about for 143 years, there has been an increasing effort in the last decade to develop a viable industrial system, with currently around 100 research papers published annually. In the academic literature, approximately 160 native yeasts have been reported to produce over 20% of their dry weight in a glyceride-rich oil. The most intensively studied oleaginous yeast have beenCutaneotrichosporon oleaginosus(20% of publications),Rhodotorula toruloides(19%) andYarrowia lipolytica(19%). Oleaginous yeasts have been primarily grown on single saccharides (60%), hydrolysates (26%) or glycerol (19%), and mainly on the mL scale (66%). Process development and genetic modification (7%) have been applied to alter yeast performance and the lipids, towards the production of biofuels (77%), food/supplements (24%), oleochemicals (19%) or animal feed (3%). Despite over a century of research and the recent application of advanced genetic engineering techniques, the industrial production of an economically viable commodity oil substitute remains elusive. This is mainly due to the estimated high production cost, however, over the course of the twenty-first century where climate change will drastically change global food supply networks and direct governmental action will likely be levied at more destructive crops, yeast lipids offer a flexible platform for localised, sustainable lipid production. Based on data from the large majority of oleaginous yeast academic publications, this review is a guide through the history of oleaginous yeast research, an assessment of the best growth and lipid production achieved to date, the various strategies employed towards industrial production and importantly, a critical discussion about what needs to be built on this huge body of work to make producing a yeast-derived, more sustainable, glyceride oil a commercial reality.
MiR-155-5p suppresses SOX1 to promote proliferation of cholangiocarcinoma via RAF/MEK/ERK pathway
Authors: Wang Da , Xiong Fei , Wu Guanhua , Liu Wenzheng , Wang Bing , Chen Yongjun 
Published: December 2021

Abstract
Background
Accumulating evidence has demonstrated the close relation of SOX1 with tumorigenesis and tumor progression. Upregulation of SOX1 was recently shown to suppress growth of human cancers. However, the expression and role of SOX1 in cholangiocarcinoma (CCA) is not well characterized.

Methods
Expression levels of SOX1 in CCA tissues and normal bile duct tissues were examined using public GEO database. Western blot and immunohistochemistry were used to confirm the expression levels. Cell proliferation assay (CCK-8) and colony formation assay were performed to assess proliferation of CCA cells. A mouse model of subcutaneous transplantable tumors was used to evaluated proliferation of CCA in vivo. The putative regulating factor of SOX1 were determined using Targetscan and dual-luciferase reporter assay.

Results
SOX1 was downregulated in CCA tissues. Overexpression of SOX1 significantly inhibited cell proliferation in vitro and suppressed tumor growth in vivo. miR-155-5p directly targeted the 3′-untranslated region (3′UTR) of SOX1 and inhibited expression of SOX1, resulting in the activation of RAF, MEK and ERK phosphorylation, and thus CCA proliferation. However, restoration of SOX1 expression in miR-155-5p overexpressing cell lines decreased the phosphorylation level of RAF, MEK and ERK, as well as the proliferation of CCA cells.

Conclusion
MiR-155-5p decreased the expression of SOX1 by binding to its 3′UTR, which activated the RAF/MEK/ERK signaling pathway and promoted CCA progression.
Femtomolar and locus-specific detection of N6-methyladenine in DNA by integrating double-hindered replication and nucleic acid-functionalized MB@Zr-MOF
Authors: Zheng Qingyuan , Wang Tong , Li Xinmin , Qian Husun , Bian Xintong , Li Xingrong , Bai Huijie , Ding Shijia , Yan Yurong 
Published: December 2021

AbstractIn this study, a novel electrochemical biosensor was constructed for ultrasensitive and locus-specific detection of N6-Methyladenine (m6A) in DNA using double-hindered replication and nucleic acid-coated methylene blue (MB)@Zr-MOF. Based on the combination of m6A-impeded replication and AgI-mediated mismatch replication, this mode could effectively stop the extension of the strand once DNA polymerase encountered m6A site, which specifically distinguish the m6A site from natural A site in DNA. Also, Zr-MOF with high porosity and negative surface potential features was carefully chose to load cationic MB, resulting a stable and robust MB@Zr-MOF electrochemical tag. As a result, the developed biosensor exhibited a wide linear range from 1 fM to 1 nM with detection limit down to 0.89 fM. Profiting from the high sensitivity and selectivity, the biosensing strategy revealed good applicability, which had been demonstrated by quantitating m6A DNA at specific site in biological matrix. Thus, the biosensor provides a promising platform for locus-specific m6A DNA analysis.
Graphical Abstract
Delineation of colorectal cancer ligand-receptor interactions and their roles in the tumor microenvironment and prognosis
Authors: Lin Hexin , Xia Lu , Lian Jiabian , Chen Yinan , Zhang Yiyi , Zhuang Zhicheng , Cai HuaJun , You Jun , Guan Guoxian 
Published: December 2021

Abstract
Background
Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear.

Methods
We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated.

Results
We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated.

Conclusion
Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.
Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients
Authors: Luan Hemi , Gu Wanjian , Li Hua , Wang Zi , Lu Lu , Ke Mengying , Lu Jiawei , Chen Wenjun , Lan Zhangzhang , Xiao Yanlin , Xu Jinyue , Zhang Yi , Cai Zongwei , Liu Shijia , Zhang Wenyong 
Published: December 2021

Abstract
Background
Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum.

Methods
We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals.

Results
Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity.

Conclusions
A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity.
Renal function in Japanese HIV-1-positive patients who switch to tenofovir alafenamide fumarate after long-term tenofovir disoproxil fumarate: a single-center observational study
Authors: Abe Kensuke , Obara Taku , Kamio Satomi , Kondo Asahi , Imamura Junji , Goto Tatsuya , Ito Toshihiro , Sato Hiroshi , Takahashi Nobuyuki 
Published: December 2021

Abstract
Background
Tenofovir disoproxil fumarate (TDF) has a strong antiviral effect, but TDF is known to cause renal dysfunction. Therefore, we are investigating preventing renal dysfunction by replacing TDF with tenofovir alafenamide fumarate (TAF), which is known to be relatively safe to the kidneys. However, the changes in renal function under long-term use of TAF are not known. In this study, we evaluated renal function in Japanese HIV-1-positive patients switching to TAF after long-term treatment with TDF.

Methods
A single-center observational study was conducted in Japanese HIV-1-positive patients. TDF was switched to TAF after at least 48 weeks of the treatment so we could evaluate the long-term use of TDF. The primary endpoint was the estimated glomerular filtration rate (eGFR) at 144 weeks of TAF administration. In addition, we predicted the factors that would lead to changes in eGFR after long-term use of TAF.

Results
Of the 125 HIV-1-positive patients who were prescribed TAF at our hospital during the study period, 70 fulfilled the study criteria. The eGFR at the time of switching from TDF to TAF was 81.4 ± 21.1 mL/min/1.73 m2. eGFR improved significantly after 12 weeks of taking TAF but significantly decreased at 96 and 144 weeks. The factors significantly correlated with the decrease in eGFR at 144 weeks on TAF were eGFR and weight at the start of TAF.

Conclusions
In this study, it was confirmed that switching to TAF was effective for Japanese HIV-1-positive patients who had been taking TDF for a long period of time and had a reduced eGFR. It was also found that the transition status depended on the eGFR and weight at the time of switch. Since HIV-1-positive patients in Japan are expected to continue taking TAF for a long time, renal function and body weight should be carefully monitored.