bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel bi-directional heterogeneous network selection method for disease and microbial association prediction
Authors: Guan Jian , Zhang Zhao Gong , Liu Yong , Wang Meng 
Published: November 2022

AbstractMicroorganisms in the human body have a great impact on human health. Therefore, mastering the potential relationship between microorganisms and diseases is helpful to understand the pathogenesis of diseases and is of great significance to the prevention, diagnosis, and treatment of diseases. In order to predict the potential microbial disease relationship, we propose a new computational model. Firstly, a bi-directional heterogeneous microbial disease network is constructed by integrating multiple similarities, including Gaussian kernel similarity, microbial function similarity, disease semantic similarity, and disease symptom similarity. Secondly, the neighbor information of the network is learned by random walk; Finally, the selection model is used for information aggregation, and the microbial disease node pair is analyzed. Our method is superior to the existing methods in leave-one-out cross-validation and five-fold cross-validation. Moreover, in case studies of different diseases, our method was proven to be effective.
Single sample pathway analysis in metabolomics: performance evaluation and application
Authors: Wieder Cecilia , Lai Rachel P. J. , Ebbels Timothy M. D. 
Published: November 2022

Abstract
Background
Single sample pathway analysis (ssPA) transforms molecular level omics data to the pathway level, enabling the discovery of patient-specific pathway signatures. Compared to conventional pathway analysis, ssPA overcomes the limitations by enabling multi-group comparisons, alongside facilitating numerous downstream analyses such as pathway-based machine learning. While in transcriptomics ssPA is a widely used technique, there is little literature evaluating its suitability for metabolomics. Here we provide a benchmark of established ssPA methods (ssGSEA, GSVA, SVD (PLAGE), and z-score) alongside the evaluation of two novel methods we propose: ssClustPA and kPCA, using semi-synthetic metabolomics data. We then demonstrate how ssPA can facilitate pathway-based interpretation of metabolomics data by performing a case-study on inflammatory bowel disease mass spectrometry data, using clustering to determine subtype-specific pathway signatures.

Results
While GSEA-based and z-score methods outperformed the others in terms of recall, clustering/dimensionality reduction-based methods provided higher precision at moderate-to-high effect sizes. A case study applying ssPA to inflammatory bowel disease data demonstrates how these methods yield a much richer depth of interpretation than conventional approaches, for example by clustering pathway scores to visualise a pathway-based patient subtype-specific correlation network. We also developed the sspa python package (freely available at https://pypi.org/project/sspa/), providing implementations of all the methods benchmarked in this study.

Conclusion
This work underscores the value ssPA methods can add to metabolomic studies and provides a useful reference for those wishing to apply ssPA methods to metabolomics data.
Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies
Authors: Cormier Michael J. , Pedersen Brent S. , Bayrak-Toydemir Pinar , Quinlan Aaron R. 
Published: November 2022

Abstract
Background
Despite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites.

Results
Several existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in “cryptic” splicing regions beyond canonical donor or acceptor splice sites.

Conclusion
Integrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.
Meta-analysis of 16S rRNA microbial data identified alterations of the gut microbiota in COVID-19 patients during the acute and recovery phases
Authors: Cheng Xiaomin , Zhang Yali , Li Yifan , Wu Qin , Wu Jiani , Park Soo-Kyung , Guo Cheng , Lu Jiahai 
Published: November 2022

Abstract
Background
Dozens of studies have demonstrated gut dysbiosis in COVID-19 patients during the acute and recovery phases. However, a consensus on the specific COVID-19 associated bacteria is missing. In this study, we performed a meta-analysis to explore whether robust and reproducible alterations in the gut microbiota of COVID-19 patients exist across different populations.

Methods
A systematic review was conducted for studies published prior to May 2022 in electronic databases. After review, we included 16 studies that comparing the gut microbiota in COVID-19 patients to those of controls. The 16S rRNA sequence data of these studies were then re-analyzed using a standardized workflow and synthesized by meta-analysis.

Results
We found that gut bacterial diversity of COVID-19 patients in both the acute and recovery phases was consistently lower than non-COVID-19 individuals. Microbial differential abundance analysis showed depletion of anti-inflammatory butyrate-producing bacteria and enrichment of taxa with pro-inflammatory properties in COVID-19 patients during the acute phase compared to non-COVID-19 individuals. Analysis of microbial communities showed that the gut microbiota of COVID-19 recovered patients were still in unhealthy ecostates.

Conclusions
Our results provided a comprehensive synthesis to better understand gut microbial perturbations associated with COVID-19 and identified underlying biomarkers for microbiome-based diagnostics and therapeutics.
Insights into adaptive evolution of plastomes in Stipa L. (Poaceae)
Authors: Krawczyk Katarzyna , Myszczyński Kamil , Nobis Marcin , Sawicki Jakub 
Published: November 2022

Abstract
Background
The study presents results of research on the evolution of plastid genomes in Stipa L. which is a large genus of the Poaceae family, comprising species diverse in terms of geographic distribution, growing under highly variated habitat conditions. Complete plastome sequences of 43 taxa from Stipeae and Ampelodesmae tribes were analyzed for the variability of the coding regions against the background of phylogenetic relationships within the genus Stipa. The research hypothesis put forward in our research was that some of coding regions are affected by a selection pressure differentiated between individual phylogenetic lines of Stipa, potentially reducing the phylogenetic informativeness of these CDS. The study aimed to answer the question, which genes evolve in Stipa most rapidly and what kind of changes in the properties of encoded amino acids this entails. Another goal of this research was to find out whether individual genes are affected by positive selection and finally, whether selective pressure is uniform within the genus or does it vary between particular evolutionary lines within the genus.

Results
Results of our study proved the presence of selective pressure in 11 genes: ccsA, matK, ndhC, ndhF, ndhK, rbcL, rpoA rpoC1, rpoC2, rps8 and rps11. For the first time the effect of positive selection on the rps8, rps11, and ndhK genes was documented in grasses. The varied pace of evolution, different intensity and effects of selective pressure have been demonstrated between particular phylogenetic lines of the genus tested.

Conclusions
Positive selection in plastid genome in Stipa mostly affects photosynthetic genes. The potential strongest adaptive pressure was observed in the rbcL gene, especially in the oldest evolutionary group comprising Central Asian high-mountain species: S. basiplumosa, S. klimesii, S. penicillata and S. purpurea, where adaptive pressure probably affected the amino acids directly related to the efficiency of CO2 assimilation.
Seizures in adults with suspected central nervous system infection
Authors: Olie Sabine E. , van Zeggeren Ingeborg E. , ter Horst Liora ,   I.-PACE Study Group, Citroen J. , van Geel B. M. , Heckenberg S. G. B. , Jellema K. , Kester M. I. , Killestein J. , Mook B. B. , Titulaer M. J. , van Veen K. E. B. , Verschuur C. V. M. , van de Beek Diederik , Brouwer Matthijs C. 
Published: November 2022

AbstractBackgroundSeizures can be part of the clinical presentation of central nervous system (CNS) infections. We describe patients suspected of a neurological infection who present with a seizure and study diagnostic accuracy of clinical and laboratory features predictive of CNS infection in this population.MethodsWe analyzed all consecutive patients presenting with a seizure from two prospective Dutch cohort studies, in which patients were included who underwent cerebrospinal fluid (CSF) examination because of the suspicion of a CNS infection.ResultsOf 900 episodes of suspected CNS infection, 124 (14%) presented with a seizure. The median age in these 124 episodes was 60 years (IQR 45–71) and 53% of patients was female. CSF examination showed a leukocyte count ≥ 5/mm3in 41% of episodes. A CNS infection was diagnosed in 27 of 124 episodes (22%), a CNS inflammatory disorder in 8 (6%) episodes, a systemic infection in 10 (8%), other neurological disease in 77 (62%) and in 2 (2%) episodes another systemic disease was diagnosed. Diagnostic accuracy of clinical and laboratory characteristics for the diagnosis of CNS infection in this population was low. CSF leukocyte count was the best predictor for CNS infection in patients with suspected CNS infection presenting with a seizure (area under the curve 0.94, [95% CI 0.88 – 1.00]).ConclusionsClinical and laboratory features fail to distinguish CNS infections from other causes of seizures in patients with a suspected CNS infection. CSF leukocyte count is the best predictor for the diagnosis of CNS infection in this population.
Cultural influence on the expression of labour-associated pain
Authors: Navarro-Prado S , Sánchez-Ojeda MA , Marmolejo-Martín J , Kapravelou G , Fernández-Gómez E , Martín-Salvador A 
Published: November 2022

Abstract
Background
Every woman expresses pain differently during birth since it depends on a multitude of predictive factors. The medical care received, companionship during birth, cultural background and language barriers of the women in labour can influence on the expression of pain. This study aims to evaluate the expression of pain during birth and its associated factors in women treated in a Spanish border town.

Methods
The study included 246 women in labour. The expression of pain during labour was evaluated using the validated ESVADOPA scale. A descriptive analysis and association study were performed between cultural identity and dimensions of the scale. Multiple linear regression models were performed to assess the association between cultural identity, origin, language barrier, and companionship during labour.

Results
The women included in the study comprised 68.7% Berbers, 71.5% Muslims and 82.1% were accompanied during labour. An association between cultural identity and greater body expression of pain (p = 0.020; Cramer’s V = 0.163) in addition to its verbal expression was found during the latent phase of labour, (p = 0.028; Cramer’s V = 0.159). During the active phase of labour, cultural identity was associated with pain expression through greater body response, verbal expression, expression of the facial muscles, anxiety, inability to relax and vegetative symptoms. The different factors studied that had a predictive value were companionship (p = 0.027) during the latent phase of labour and Berber origin (p = 0.000), language barrier (p = 0.014) and companionship (p = 0.005) during the active phase of labour. The models designed predict pain expression in the latent phase by companionship and type of companionship (β = 1.483; 95%CI = 0.459–2.506, β = 0.238; 95%CI = 0.029–0. 448, respectively), and in the active phase by background, language barrier and companionship (β = 0.728; 95%CI = 0.258–1.198, β = 0.738; 95%CI = 0.150–1.326, β = 1.888; 95%CI = 0.984–2.791, respectively).

Conclusion
Culture, origin, language barrier and companionship during labour influences the manner in which women in labour express their pain. An understanding of this may help midwives correctly interpret the signs of pain expression and be able to offer the appropriate assistance depending on a woman's particular characteristics. There is a clear need for new models of maternity care that will take the cultural and language characteristics of women in labour into consideration.
Venetoclax combined with low dose cytarabine compared to standard of care intensive chemotherapy for the treatment of favourable risk adult acute myeloid leukaemia (VICTOR): Study protocol for an international, open-label, multicentre, molecularly-guided randomised, phase II trial
Authors: Dillon Richard , Maycock Shanna , Jackson Aimee , Fox Sonia , Freeman Sylvie , Craddock Charles , Thomas Catherine , Homer Emma , Leahy Jane , Mamwell Anna , Potter Nicola , Russell Nigel , Wei Andrew , Ommen Hans Beier , Hemmaway Claire , Knapper Steve , Billingham Lucinda 
Published: November 2022

Abstract
Background
For patients with acute myeloid leukaemia (AML), the only potentially curative treatment is intensive chemotherapy (IC). This is highly toxic, particularly for patients > 60 years, potentially leading to prolonged hospitalisations requiring intensive supportive care, and sometimes treatment-related death. This also results in extensive healthcare costs and negatively impacts quality of life (QoL). Venetoclax with low-dose cytarabine (VEN + LDAC) is a novel, low-intensity treatment for AML patients who cannot receive IC. VEN + LDAC is given as an outpatient and toxicity appears significantly lower than with IC. Analysis of clinical trials performed to date are promising for patients with the genotype NPM1mutFLT3 ITDneg, where remission and survival rates appear comparable to those achieved with IC.

Methods
VICTOR is an international, two-arm, open-label, multi-centre, non-inferiority, randomised-controlled phase II trial to assess VEN + LDAC compared to standard of care (IC) as first-line treatment in older patients (initially aged ≥ 60 years) with newly diagnosed AML. The trial will recruit patients with a NPM1mutFLT3 ITDneg genotype; those with a favourable risk in relation to the experimental treatment. University of Birmingham is the UK co-ordinating centre, with national hubs in Aarhus University Hospital, Denmark, and Auckland District Health Board, New Zealand. The primary outcome is molecular event-free survival time where an event is defined as failure to achieve morphological complete response (CR) or CR with incomplete blood count recovery after two cycles of therapy; molecular persistence, progression or relapse requiring treatment change; morphological relapse, or; death. Secondary outcomes include cumulative resource use at 12- and 24-months, and QoL as assessed by EORTCQLQ-C30 and EQ-5D-3L at 3-, 6-, 12-, 18- and 24-months. The trial employs an innovative Bayesian design with target sample size of 156 patients aged > 60 years.

Discussion
The principle underpinning the VICTOR trial is that the chance of cure for patients in the experimental arm should not be compromised, therefore, an adaptive design with regular checks on accumulating data has been employed, which will allow for a staged expansion of the trial population to include younger patients if, and when, there is sufficient evidence of non-inferiority in older patients.

Trial registration
EudraCT: 2020–000,273-24; 21-Aug-2020.
ISRCTN: 15,567,173; 08-Dec-2020.
Silva cumulative score and its relationship with prognosis in Endocervical adenocarcinoma
Authors: Li Yuemin , Jia Meng , Cao Lanqing , Yu Jiaqi , Gao Hongwen , Sun Ping-Li 
Published: November 2022

Abstract
Background
The Silva system has been demonstrated to have a good predictive value of lymph node metastasis (LNM) in endocervical adenocarcinoma (EAC). Tumours were classified based on the highest identified pattern of invasion in this system, this may not exactly reflect the true situation when it presents with a “mixed pattern” in some cases. Recent study has shown that patients with lymphovascular invasion (LVI) have worse prognosis in EAC. Here we design a Silva cumulative score (SCS) system which also combined the LVI status to explore its prognostic role in EAC patients.

Methods
A total of 120 patients with EAC were included in this study. Clinicopathological characteristics were retrospectively retrieved from the medical records and follow-up data were obtained. The clinicopathological information included age at diagnosis, depth of invasion (DOI), LNM, LVI, Silva classification, and SCS. SCS is a classification system based on the sum score of different Silva pattern which is founded on morphological phenomena. The relationships between the pathological characteristics and prognoses were analyzed.

Results
According to the Silva system, 11 (9.2%), 22 (18.3%) and 87 (72.5%) patients had patterns A, B, and C, respectively. Patients with pattern C had the highest incidence of LVI and LNM (p < 0.05). Although the Kaplan-Meier curves demonstrated that survival decreased with increasing Silva classification for A-C cancers, there was no statistically significant difference [disease-free survival (DFS): p = 0.181; overall survival (OS): p = 0.205]. There were 45 cases presented as mixed-type of Silva patterns. According to the SCS, 23 cases (19.2%) were rated as grade I, 31 cases (25.8%) as grade II and 66 (55.0%) cases as grade III. Patients with SCS grade III had the highest incidence of LVI and LNM (p < 0.05). Kaplan–Meier analysis revealed that patients with higher SCS had significantly shorter DFS and OS than those with lower SCS (p < 0.05). High SCS was an independent predictor of poorer OS and DFS (p < 0.05) in patients with EAC.

Conclusions
The application of the Silva system could effectively predict the LNM of patients and may be helpful in selecting an appropriate surgical procedure. The SCS system we designed showed a good predictive value for DFS and OS in EAC.
Participatory disease surveillance for a mass gathering — a prospective cohort study on COVID-19, Germany 2021
Authors: Hohmuth Nils , Khanyaree Ifrah , Lang Anna-Lena , Duering Ohad , Konigorski Stefan , Višković Vukašin , Heising Tobias , Egender Friedemann , Remschmidt Cornelius , Leistner Rasmus 
Published: November 2022

Abstract
Background
Mass gatherings (MGs) such as music festivals and sports events have been associated with a high risk of SARS-CoV-2 transmission. On-site research can foster knowledge of risk factors for infections and improve risk assessments and precautionary measures at future MGs. We tested a web-based participatory disease surveillance tool to detect COVID-19 infections at and after an outdoor MG by collecting self-reported COVID-19 symptoms and tests.

Methods
We conducted a digital prospective observational cohort study among fully immunized attendees of a sports festival that took place from September 2 to 5, 2021 in Saxony-Anhalt, Germany. Participants used our study app to report demographic data, COVID-19 tests, symptoms, and their contact behavior. This self-reported data was used to define probable and confirmed COVID-19 cases for the full “study period” (08/12/2021 – 10/31/2021) and within the 14-day “surveillance period” during and after the MG, with the highest likelihood of an MG-related COVID-19 outbreak (09/04/2021 – 09/17/2021).

Results
A total of 2,808 of 9,242 (30.4%) event attendees participated in the study. Within the study period, 776 individual symptoms and 5,255 COVID-19 tests were reported. During the 14-day surveillance period around and after the MG, seven probable and seven PCR-confirmed COVID-19 cases were detected. The confirmed cases translated to an estimated seven-day incidence of 125 per 100,000 participants (95% CI [67.7/100,000, 223/100,000]), which was comparable to the average age-matched incidence in Germany during this time. Overall, weekly numbers of COVID-19 cases were fluctuating over the study period, with another increase at the end of the study period.

Conclusion
COVID-19 cases attributable to the mass gathering were comparable to the Germany-wide age-matched incidence, implicating that our active participatory disease surveillance tool was able to detect MG-related infections. Further studies are needed to evaluate and apply our participatory disease surveillance tool in other mass gathering settings.