bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between gut microbiota and lung function decline in patients with chronic obstructive pulmonary disease: a 1-year follow-up study
Authors: Chiu Yu-Chi , Lee Shih-Wei , Liu Chi-Wei , Lan Tzuo-Yun , Wu Lawrence Shih-Hsin 
Published: January 2022

Abstract
Objective
Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease characterized by a persistent limitation in airflow. Gut microbiota is closely correlated with lung inflammation. However, gut microbiota has not been studied in patients with declining lung function, due to chronic lung disease progression.

Subjects and methods
Stool samples were obtained from 55 patients with COPD that were in stable condition at enrolment (stage 1) and at a 1-year follow-up (stage 2). After extracting stool DNA, we performed next generation sequencing to analyse the distribution of gut microbiota.

Results
Patients were divided to control and declining lung function groups, based on whether the rate of forced expiratory volume in 1 s (FEV1) had declined over time. An alpha diversity analysis of initial and follow-up stool samples showed a significant difference in the community richness of microbiota in the declining function group, but not in the control group. At the phylum level, Bacteroidetes was more abundant in the control group and Firmicutes was more abundant in the declining function group. The Alloprevotella genus was more abundant in the control group than in the declining function group. At 1-year follow-up, the mean proportions of Acinetobacter and Stenotrophomonas significantly increased in the control and declining function groups, respectively.

Conclusion
Some community shifts in gut microbiota were associated with lung function decline in COPD patients under regular treatment. Future studies should investigate the mechanism underlying alterations in lung function, due to changes in gut bacterial communities, in COPD.
Escherichia coli coculture for de novo production of esters derived of methyl-branched alcohols and multi-methyl branched fatty acids
Authors: Bracalente Fernando , Sabatini Martín , Arabolaza Ana , Gramajo Hugo 
Published: January 2022

Abstract
Background
A broad diversity of natural and non-natural esters have now been made in bacteria, and in other microorganisms, as a result of original metabolic engineering approaches. However, the fact that the properties of these molecules, and therefore their applications, are largely defined by the structural features of the fatty acid and alcohol moieties, has driven a persistent interest in generating novel structures of these chemicals.

Results
In this research, we engineered Escherichia coli to synthesize de novo esters composed of multi-methyl-branched-chain fatty acids and short branched-chain alcohols (BCA), from glucose and propionate. A coculture engineering strategy was developed to avoid metabolic burden generated by the reconstitution of long heterologous biosynthetic pathways. The cocultures were composed of two independently optimized E. coli strains, one dedicated to efficiently achieve the biosynthesis and release of the BCA, and the other to synthesize the multi methyl-branched fatty acid and the corresponding multi-methyl-branched esters (MBE) as the final products. Response surface methodology, a cost-efficient multivariate statistical technique, was used to empirical model the BCA-derived MBE production landscape of the coculture and to optimize its productivity. Compared with the monoculture strategy, the utilization of the designed coculture improved the BCA-derived MBE production in 45%. Finally, the coculture was scaled up in a high-cell density fed-batch fermentation in a 2 L bioreactor by fine-tuning the inoculation ratio between the two engineered E. coli strains.

Conclusion
Previous work revealed that esters containing multiple methyl branches in their molecule present favorable physicochemical properties which are superior to those of linear esters. Here, we have successfully engineered an E. coli strain to broaden the diversity of these molecules by incorporating methyl branches also in the alcohol moiety. The limited production of these esters by a monoculture was considerable improved by a design of a coculture system and its optimization using response surface methodology. The possibility to scale-up this process was confirmed in high-cell density fed-batch fermentations.
Recombinant production of the lantibiotic nisin using Corynebacterium glutamicum in a two-step process
Authors: Weixler Dominik , Berghoff Max , Ovchinnikov Kirill V. , Reich Sebastian , Goldbeck Oliver , Seibold Gerd M. , Wittmann Christoph , Bar Nadav S. , Eikmanns Bernhard J. , Diep Dzung B. , Riedel Christian U. 
Published: January 2022

Abstract
Background
The bacteriocin nisin is naturally produced by Lactococcus lactis as an inactive prepeptide that is modified posttranslationally resulting in five (methyl-)lanthionine rings characteristic for class Ia bacteriocins. Export and proteolytic cleavage of the leader peptide results in release of active nisin. By targeting the universal peptidoglycan precursor lipid II, nisin has a broad target spectrum including important human pathogens such as Listeria monocytogenes and methicillin-resistant Staphylococcus aureus strains. Industrial nisin production is currently performed using natural producer strains resulting in rather low product purity and limiting its application to preservation of dairy food products.

Results
We established heterologous nisin production using the biotechnological workhorse organism Corynebacterium glutamicum in a two-step process. We demonstrate successful biosynthesis and export of fully modified prenisin and its activation to mature nisin by a purified, soluble variant of the nisin protease NisP (sNisP) produced in Escherichia coli. Active nisin was detected by a L. lactis sensor strain with strictly nisin-dependent expression of the fluorescent protein mCherry. Following activation by sNisP, supernatants of the recombinant C. glutamicum producer strain cultivated in standard batch fermentations contained at least 1.25 mg/l active nisin.

Conclusions
We demonstrate successful implementation of a two-step process for recombinant production of active nisin with C. glutamicum. This extends the spectrum of bioactive compounds that may be produced using C. glutamicum to a bacteriocin harboring complex posttranslational modifications. Our results provide a basis for further studies to optimize product yields, transfer production to sustainable substrates and purification of pharmaceutical grade nisin.
Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer
Authors: Han Tenghui , Zhu Jun , Chen Xiaoping , Chen Rujie , Jiang Yu , Wang Shuai , Xu Dong , Shen Gang , Zheng Jianyong , Xu Chunsheng 
Published: January 2022

AbstractBackgroundLiver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically.MethodsWe integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model.ResultsA total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956).ConclusionWe successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.
Development and validation of a novel 3-gene prognostic model for pancreatic adenocarcinoma based on ferroptosis-related genes
Authors: Yang Jihua , Wei XiaoHong , Hu Fang , Dong Wei , Sun Liao 
Published: January 2022

Abstract
Background
Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD.

Methods
RNA-sequence and clinical data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The differentially expressed genes (DEGs) between different subtypes were used by “limma_3.42.2” package. The R software package clusterProfiler was used for functional enrichment analysis. Then, a multivariate Cox proportional and LASSO regression were used to develop a ferroptosis-related gene signature for pancreatic adenocarcinoma. A nomogram and corrected curves were constructed. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, migration and invasion assays.

Results
The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. KM-curve analysis showed that there were significant differences between the high and low-risk groups, samples with a high-risk score had a worse prognosis. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. For comparison with other models, that our model, with a reasonable number of genes, yields a more effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly expressed, whether ALOX12 and CISD1 were expressed at low levels in tissue samples. Finally, function assays results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes.

Conclusions
We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.
Study on the expression of TOP2A in hepatocellular carcinoma and its relationship with patient prognosis
Authors: Meng Jiali , Wei Yuanchao , Deng Qing , Li Ling , Li Xiaolong 
Published: January 2022

Abstract
Background
Hepatocellular carcinoma (HCC) is a primary liver cancer with a high mortality rate. However, the molecular mechanism of HCC formation remains to be explored and studied.

Objective
To investigate the expression of TOP2A in hepatocellular carcinoma (HCC) and its prognosis.

Methods
The data set of hepatocellular carcinoma was downloaded from GEO database for differential gene analysis, and hub gene was identified by Cytoscape. GEPIA was used to verify the expression of HUB gene and evaluate its prognostic value. Then TOP2A was selected as the research object of this paper by combining literature and clinical sample results. Firstly, TIMER database was used to study TOP2A, and the differential expression of TOP2A gene between normal tissues and cancer tissues was analyzed, as well as the correlation between TOP2A gene expression and immune infiltration of HCC cells. Then, the expression of top2a-related antibodies was analyzed using the Human Protein Atlas database, and the differential expression of TOP2A was verified by immunohistochemistry. Then, SRTING database and Cytoscape were used to establish PPI network for TOP2A and protein–protein interaction analysis was performed. The Oncomine database and cBioPortal were used to express and identify TOP2A mutation-related analyses. The expression differences of TOP2A gene were identified by LinkedOmics, and the GO and KEGG pathways were analyzed in combination with related genes. Finally, Kaplan–Meier survival analysis was performed to analyze the clinical and prognosis of HCC patients.

Results
TOP2A may be a new biomarker and therapeutic target for hepatocellular carcinoma.
The functions and prognostic value of Krüppel‐like factors in breast cancer
Authors: Zhu Ke-Yun , Tian Yao , Li Ying-Xi , Meng Qing-Xiang , Ge Jie , Cao Xu-Chen , Zhang Ti , Yu Yue 
Published: January 2022

Abstract
Background
Krüppel‐like factors (KLFs) are zinc finger proteins which participate in transcriptional gene regulation. Although increasing evidence indicate that KLFs are involved in carcinogenesis and progression, its clinical significance and biological function in breast cancer are still limited.

Methods
We investigated all the expression of KLFs (KLF1-18) at transcriptional levels by using Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA). The mRNA and protein expression levels of KLFs were also determined by using RT-qPCR and immunohistochemistry, respectively. CBioPortal, GeneMANIA and STRING were used to comprehensive analysis of the molecular characteristics of KLFs. The clinical value of prognostic prediction based on the expression of KLFs was determined by using the KM plotter. The relevant molecular pathways of KLFs were further analyzed by using Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Finally, we investigated the effect of KLF2 and KLF15 on biological behavior of breast cancer cells in vitro.

Results
The expression of KLF2/4/6/8/9/11/15 was significantly down-regulated in breast cancer. The patients with high KLF2, KLF4 or KLF15 expression had a better outcome, while patients with high KLF8 or KLF11 had a poor prognosis. Furthermore, our results showed that KLF2 or KLF15 can be used as a prognostic factor independent on the other KLFs in patients with breast cancer. Overexpression of KLF2 or KLF15 inhibited cell proliferation and migration, and blocked cell cycle at G0/G1 phase, resulting in cell apoptosis.

Conclusions
KLF2 and KLF15 function as tumor suppressors in breast cancer and are potential biomarkers for prognostic prediction in patients with breast cancer.
Immune-related lncRNA classification of head and neck squamous cell carcinoma
Authors: Cao Ruoyan , Cui Lin , Zhang Jiayu , Ren Xianyue , Cheng Bin , Xia Juan 
Published: January 2022

Abstract
Background
Long noncoding RNAs (lncRNAs) play a critical role in innate and adaptive immune responses. Thus, we aimed to identify ideal subtypes for head and neck squamous cell carcinoma (HNSCC) based on immune-related lncRNAs.

Methods
TCGA HNSCC cohort was divided into two datasets (training and validation dataset), and 960 previously characterized immune-related lncRNAs were extracted for non-negative matrix factorization analysis. We characterized our HNSCC subtypes based on biological behaviors, immune landscape and response to immunotherapy in both training and validation cohort. A lncRNA-signature was generated to predict our HNSCC subtypes, and essential lncRNAs involved in tumor microenvironment (TME) were identified.

Results
We developed and validated two HNSCC subtypes (C1 and C2) based on the 70 lncRNAs in the training and validation cohort. C2 subtype displayed good prognosis, high immune cell infiltration, immune-related genes expression and sensitivity to PD-1 blockade. C1 subtype was associated with high activity of mTORC1 signaling and glycolysis as well as high fraction of inactive immune cells. Finally, we generated a 31-lncRNA signature that could predict our above subtypes with high accurate. Additionally, TRG-AS1 was identified as the essential lncRNA involving TME formation. Knockdown of TRG-AS1 inhibited the expression of HLA-A, HLA-B, HLA-C, CXCL9, CXCL10 and CXCL11. High expression of TRG-AS1 indicated a favorable prognosis in HNSCC and anti-PD-L1 cohort (IMvigor210).

Conclusions
Our study establishes a novel HNSCC classification on the basis of 31-lncRNA, helping to identify beneficiaries for anti-PD-1 treatment. In addition, a critical lncRNA TRG-AS1 is identified as a new potential prognosis biomarker as well as therapeutic target.
Horizontal inequity in the utilisation of Continuum of Maternal Health care Services (CMHS) in India: an investigation of ten years of National Rural Health Mission (NRHM)
Authors: Gandhi Sumirtha , Dash Umakant , Suresh Babu M. 
Published: January 2022

Abstract
Background
Continuum of Maternal Health Care Services (CMHS) has garnered attention in recent times and reducing socio-economic disparity and geographical variations in its utilisation becomes crucial from an egalitarian perspective. In this study, we estimate inequity in the utilisation of CMHS in India between 2005 and 06 and 2015-16.

Methods
We used two rounds of National Family Health Survey (NFHS) - 2005-06 and 2015-16 encompassing a sample size of 34,560 and 178,857 pregnant women respectively. The magnitude of horizontal inequities (HI) in the utilisation of CMHS was captured by adopting the Erreygers Corrected Concentration indices method. Need-based standardisation was conducted to disentangle the variations in the utilisation of CMHS across different wealth quintiles and state groups. Further, a decomposition analysis was undertaken to enumerate the contribution of legitimate and illegitimate factors towards health inequity.

Results
The study indicates that the pro-rich inequity in the utilisation of CMHS has increased by around 2 percentage points since the implementation of National Rural Health Mission (NRHM), where illegitimate factors are dominant. Decomposition analysis reveals that the contribution of access related barriers plummeted in the considered period of time. The results also indicate that mother’s education and access to media continue to remain major contributors of pro-rich inequity in India. Considering, regional variations, it is found that the percentage of pro-rich inequity in high focus group states increased by around 3% between 2005 and 06 and 2015-16. The performance of southern states of India is commendable.

Conclusions
Our study concludes that there exists a pro-rich inequity in the utilisation of CMHS with marked variations across state boundaries. The pro-rich inequity in India has increased between 2005 and 06 and high focus group states suffered predominantly. Decentralisation of healthcare policies and granting greater power to the states might lead to equitable distribution of CMHS.
Prenatal and early childhood exposure to tetrachloroethylene (PCE)-contaminated drinking water and sleep quality in adulthood: a retrospective cohort study
Authors: Doran Charlotte R. , Aschengrau Ann 
Published: January 2022

Abstract
Background
Communities in Cape Cod, Massachusetts were exposed to tetrachloroethylene (PCE) through contaminated drinking water from 1969 to 1983. PCE exposure during adulthood has well-established neurotoxic effects; however, long-term impacts stemming from early life exposure, especially adverse effects on sleep quality, are not well understood.

Methods
The present analysis was based on data from the Cape Cod Health Study, a retrospective cohort study of the long-term neurotoxic impacts of early-life exposure to PCE-contaminated drinking water. Exposure to PCE-contaminated water was estimated using a validated leaching and transport model. Measures of sleep quality were obtained from self-administered questionnaires. Generalized estimating equations were used to generate risk ratios and 95% confidence intervals to estimate the association between early-life PCE exposure and sleep quality among 604 participants.

Results
Compared to unexposed participants, any PCE exposure during early life was associated with 1.57 times the risk of reporting breathing pauses during sleep (95% CI 0.92–2.68). Low-level exposure to PCE was associated with 1.50 times the risk of reporting sleep apnea or other sleep disorders (95% CI 0.78–2.89), while high levels of exposure had comparable risk compared to no exposure (RR = 0.94, 95% CI 0.50–1.79). Weak or no associations were observed for other sleep quality outcomes. In stratified analyses participants with mental illness and/or substance use disorder had increased risk ratios for short sleep duration associated with PCE exposure.

Conclusion
These findings suggest that early-life exposure to PCE may be associated with a moderate increase in the risk of reporting breathing pauses during sleep in adulthood and that a history of mental illness and/or substance use disorder may exacerbate the risk of short sleep duration.
Neighborhood greenspace exposure as a protective factor in dementia risk among U.S. adults 75 years or older: a cohort study
Authors: Slawsky Erik D. , Hajat Anjum , Rhew Isaac C. , Russette Helen , Semmens Erin O. , Kaufman Joel D. , Leary Cindy S. , Fitzpatrick Annette L. 
Published: January 2022

Abstract
Background
Research suggests that greenspace may confer neurocognitive benefits. This study examines whether residential greenspace is associated with risk of dementia among older adults.

Methods
Greenspace exposure was computed for 3047 participants aged 75 years and older enrolled in the Gingko Evaluation of Memory Study (GEMS) across four U.S. sites that prospectively evaluated dementia and its subtypes, Alzheimer’s disease (AD), vascular dementia (VaD), and mixed pathologies, using neuropsychiatric evaluations between 2000 and 2008. After geocoding participant residences at baseline, three greenspace metrics—Normalized Difference Vegetative Index, percent park overlap within a 2-km radius, and linear distance to nearest park—were combined to create a composite residential greenspace measure categorized into tertiles. Cox proportional hazards models estimated the associations between baseline greenspace and risk of incident all-cause dementia, AD, and Mixed/VaD.

Results
Compared to low residential greenspace, high residential greenspace was associated with a reduced risk of dementia (HR = 0.76 95% CI: 0.59,0.98) in models adjusted for multiple covariates. After additional adjustment for behavioral characteristics, Apolipoprotein E ɛ4 status, and other covariates, the association was slightly attenuated (HR = 0.82; 95% CI:0.63,1.06). Those exposed to medium levels of greenspace also had 28% lower risk (HR = 0.72; CI: 0.55, 0.95) of dementia compared to those with low greenspace in adjusted models. Subtype associations between high residential greenspace and AD were not statistically significant. Greenspace was not found to be significantly associated with mixed/vascular pathologies.

Conclusions
This study showed evidence for an association between residential greenspace and all-cause dementia among older adults. Future research with larger sample size, precise characterization of different dementia subtypes, and assessment of residential greenspace earlier in life may help clarify the role between exposure to greenspace and dementia risk.