bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in lipid metabolism in acquired versus preexisting glucose intolerance during gestation: role of free fatty acids and sphingosine-1-phosphate
Authors: Liebmann Moritz , Grupe Katharina , Asuaje Pfeifer Melissa , Rustenbeck Ingo , Scherneck Stephan 
Published: October 2022

Abstract
Background
The prevalence of gestational diabetes mellitus (GDM) is increasing worldwide. There is increasing evidence that GDM is a heterogeneous disease with different subtypes. An important question in this context is whether impaired glucose tolerance (IGT), which is a typical feature of the disease, may already be present before pregnancy and manifestation of the disease. The latter type resembles in its clinical manifestation prediabetes that has not yet manifested as type 2 diabetes (T2DM). Altered lipid metabolism plays a crucial role in the disorder's pathophysiology. The aim was to investigate the role of lipids which are relevant in diabetes-like phenotypes in these both models with different time of initial onset of IGT.

Methods
Two rodent models reflecting different characteristics of human GDM were used to characterize changes in lipid metabolism occurring during gestation. Since the New Zealand obese (NZO)-mice already exhibit IGT before and during gestation, they served as a subtype model for GDM with preexisting IGT (preIGT) and were compared with C57BL/6 N mice with transient IGT acquired during gestation (aqIGT). While the latter model does not develop manifest diabetes even under metabolic stress conditions, the NZO mouse is prone to severe disease progression later in life. Metabolically healthy Naval Medical Research Institute (NMRI) mice served as controls.

Results
In contrast to the aqIGT model, preIGT mice showed hyperlipidemia during gestation with elevated free fatty acids (FFA), triglycerides (TG), and increased atherogenic index. Interestingly, sphingomyelin (SM) concentrations in the liver decreased during gestation concomitantly with an increase in the sphingosine-1-phosphate (S1P) concentration in plasma. Further, preIGT mice showed impaired hepatic weight adjustment and alterations in hepatic FFA metabolism during gestation. This was accompanied by decreased expression of peroxisome proliferator-activated receptor alpha (PPARα) and lack of translocation of fatty acid translocase (FAT/CD36) to the hepatocellular plasma membrane.

Conclusion
The preIGT model showed impaired lipid metabolism both in plasma and liver, as well as features of insulin resistance consistent with increased S1P concentrations, and in these characteristics, the preIGT model differs from the common GDM subtype with aqIGT. Thus, concomitantly elevated plasma FFA and S1P concentrations, in addition to general shifts in sphingolipid fractions, could be an interesting signal that the metabolic disorder existed before gestation and that future pregnancies require more intensive monitoring to avoid complications.

Graphical Abstract
This graphical abstract was created with BioRender.com.
FGF15 promotes hepatic NPC1L1 degradation in lithogenic diet-fed mice
Authors: Mo Pingfan , Chen Hongtan , Jiang Xin , Hu Fengling , Zhang Fenming , Shan Guodong , Chen Wenguo , Li Sha , Li Yiqiao , Xu Guoqiang 
Published: October 2022

Abstract
Background
Cholesterol gallstone disease (CGD) is accompanied by biliary cholesterol supersaturation. Hepatic Niemann-Pick C1-like 1 (NPC1L1), which is present in humans but not in wild-type (WT) mice, promotes hepatocyte cholesterol uptake and decreases biliary cholesterol supersaturation. In contrast, intestinal NPC1L1 promotes intestinal cholesterol absorption, increasing biliary cholesterol supersaturation. Ezetimibe (EZE) can inhibit both hepatic and intestinal NPC1L1. However, whether hepatic NPC1L1 can affect CGD progress remains unknown.

Methods
Mice expressing hepatic NPC1L1 (NPC1L1hepatic-OE mice) were generated using Adeno-associated viruses (AAV) gene delivery. The protein level and function of hepatic NPC1L1 were examined under chow diet, high fat-cholesterol diet (HFCD), and lithogenic diet (LD) feeding. Gallstone formation rates were examined with or without EZE treatment. Fibroblast growth factor 15 (FGF15) treatment and inhibition of fibroblast growth factor receptor 4 (FGFR4) were applied to verify the mechanism of hepatic NPC1L1 degradation.

Results
The HFCD-fed NPC1L1hepatic-OE mice retained the biliary cholesterol desaturation function of hepatic NPC1L1, whereas EZE treatment decreased biliary cholesterol saturation and did not cause CGD. The ubiquitination and degradation of hepatic NPC1L1 were discovered in LD-fed NPC1L1hepatic-OE mice. Treatment of FGF15 during HFCD feeding and inhibition of FGFR4 during LD feeding could affect the protein level and function of hepatic NPC1L1.

Conclusions
LD induces the ubiquitination and degradation of hepatic NPC1L1 via the FGF15-FGFR4 pathway. EZE may act as an effective preventative agent for CGD.
Potential novel biomarkers in small intestine for obesity/obesity resistance revealed by multi-omics analysis
Authors: Pang Yueshan , Zheng Yali , Yang Ni , Zan Meng , Zhang Lu , Ding WeiJun 
Published: October 2022

Abstract
Background
Although obesity is caused by different factors, individual susceptibility to obesity differs among people under the same circumstances. The microbiota in the caecum or fresh faeces and metabolites in blood or urine contribute to obesity resistance; however, the microbiota or metabolites in the small intestine have not been extensively studied.

Methods
To investigate the relationship between the microbiota or metabolites in the small intestine and susceptibility to obesity, eighty-eight male C57BL/6 mice were fed a high-fat diet (HFD) for 8 weeks to establish two models of obesity and obesity resistance. For further study, six mice were chosen from among the obesity models, and twelve mice were randomly chosen from among the obesity resistance models. After fasting plasma glucose and behavioural testing, the mice were fed in single cages for another 4 weeks to observe their weight and food intake. All mice were sacrificed at 20 weeks of age. Serum ALT, AST, HDL, LDL, TG and TC levels were measured using an automatic biochemical analyser. The microbiota and metabolites in the small intestine contents were analysed using 16 S sequencing and an ultrahigh-performance liquid chromatographic system, respectively. Transcripts in the jejunum were evaluated using full-length transcriptome sequencing and verified by qPCR.

Results
The results showed that HFD induced depression and anxiety behaviours and higher fasting plasma glucose, ALT, AST, HDL, LDL, TG and TC levels in the obese mice; however, these levels were improved in obese resistance mice. The correlation analysis showed that the phosphatidylcholine, TG, and phosphatidylethanolamine levels were higher in obese mice and correlated positively with intestinal microflora (Desulfovibrio and Gemella) and the Cxcl10 gene. A higher abundance of Clostridium_sensu_stricto_1 in obesity-resistant mice correlated negatively with the metabolite contents (neuromedin N and enkephalin L) and Pck1 gene expression and correlated positively with certain metabolites (5-hydroxy-L-tryptophan, cinnamyl alcohol and 1 H-indole-3-acetamide) and genes expression (Gdf15, Igfbp6 and Spp1).

Conclusion
Clostridium_sensu_stricto_1, neuromedin N, enkephalin L, Pck1, 5-hydroxy-L-tryptophan, Cxcl10 and cinnamyl alcohol may be novel biomarkers in the small intestine for obesity/obesity resistance. These might be helpful for obesity prevention or for treating obese patients.
Biologically synthesized black ginger-selenium nanoparticle induces apoptosis and autophagy of AGS gastric cancer cells by suppressing the PI3K/Akt/mTOR signaling pathway
Authors: Wang Rongbo , Ha Keum-yun , Dhandapani Sanjeevram , Kim Yeon-Ju 
Published: October 2022

Abstract
Background
Despite being a promising strategy, current chemotherapy for gastric cancer (GC) is limited due to adverse side effects and poor survival rates. Therefore, new drug-delivery platforms with good biocompatibility are needed. Recent studies have shown that nanoparticle-based drug delivery can be safe, eco-friendly, and nontoxic making them attractive candidates. Here, we develop a novel selenium-nanoparticle based drug-delivery agent for cancer treatment from plant extracts and selenium salts.

Results
Selenium cations were reduced to selenium nanoparticles using Kaempferia parviflora (black ginger) root extract and named KP-SeNP. Transmission electron microscopy, selected area electron diffraction, X-ray diffraction, energy dispersive X-ray, dynamic light scattering, and Fourier-transform infrared spectrum were utilized to confirm the physicochemical features of the nanoparticles. The KP-SeNPs showed significant cytotoxicity in human gastric adenocarcinoma cell (AGS cells) but not in normal cells. We determined that the intracellular signaling pathway mechanisms associated with the anticancer effects of KP-SeNPs involve the upregulation of intrinsic apoptotic signaling markers, such as B-cell lymphoma 2, Bcl-associated X protein, and caspase 3 in AGS cells. KP-SeNPs also caused autophagy of AGS by increasing the autophagic flux-marker protein, LC3B-II, whilst inhibiting autophagic cargo protein, p62. Additionally, phosphorylation of PI3K/Akt/mTOR pathway markers and downstream targets was decreased in KP-SeNP-treated AGS cells. AGS-cell xenograft model results further validated our in vitro findings, showing that KP-SeNPs are biologically safe and exert anticancer effects via autophagy and apoptosis.

Conclusions
These results show that KP-SeNPs treatment of AGS cells induces apoptosis and autophagic cell death through the PI3K/Akt/mTOR pathway, suppressing GC progression. Thus, our research strongly suggests that KP-SeNPs could act as a novel potential therapeutic agent for GC.

Graphical Abstract
Intracellular mRNA phase separation induced by cationic polymers for tumor immunotherapy
Authors: Xing Zhen , Xue Jing , Ma Xindian , Han Congwei , Wang Zhenzhen , Luo Shunhuang , Wang Chunming , Dong Lei , Zhang Junfeng 
Published: October 2022

AbstractThe formation of biomolecular condensates via liquid‒liquid phase separation (LLPS) is an advantageous strategy for cells to organize their subcellular compartments for diverse functions. Recent findings suggest that RNA or RNA-related LLPS techniques have potential for the development of new cellular regulation strategies. However, manipulating RNA LLPS in living cells has great challenges. Herein, we report that cationic polymers (CPs) have strong RNA LLPS-inducing activity. By introducing CPs into living cells or RNA solutions, significant RNA LLPS was verified through confocal imaging, turbidity assays, and fluorescence recovery after photobleaching (FRAP) tests. Among them, turbidity kinetics determinations indicated that the hydrophilic positively charged amino groups on the CPs play essential roles in RNA phase separation. Moreover, the LLPS induced by the cationic polymers dramatically changed the gene expression patterns in the cells. Interestingly, we found that TGFβ1 mRNA was highly encapsulated in the RNA droplets, which lowered the immunosuppressive capability of the tumor cells and triggered marked antitumor reactions in a mouse breast cancer model. Thus, we present here the CP-based modulation of RNA LLPS as a novel transcriptional manipulation method with potential for cancer immunotherapy drug development.
Graphical Abstract
Nurses’ steps, distance traveled, and perceived physical demands in a three-shift schedule
Authors: Chang Hyoung Eun , Cho Sung-Hyun 
Published: October 2022

Abstract
Background
The physical job demands of hospital nurses are known to be very high. Although many studies have measured the physical activities of nurses subjectively using questionnaires, it remains necessary to quantify and measure nurses’ physical activity at work using objective indicators. This study was conducted to address this gap in the literature by analyzing nurses’ physical activity using both objective measurements and subjective perceptions. The number of steps, distance traveled, and actual work hours were measured during work, and the influence of related factors was analyzed.

Methods
Using a cross-sectional design, survey and activity tracking data were collected from nurses who worked in three shifts in two tertiary hospitals located in the capital region of South Korea. The participants comprised 117 nurses working in four different units (medical ward, surgical ward, intensive care unit, emergency room), and data from 351 shifts were used in the final analysis. Between-group differences in the main variables were analyzed using the t-test, the Mann–Whitney test, analysis of variance, or the Kruskal–Wallis test, as appropriate. The relationships were examined through multiple linear regression analysis.

Results
The average number of steps and distance traveled were greatest for nurses working in the emergency room, followed by the intensive care unit, surgical ward, and medical ward (in descending order). Younger nurses and those with shorter unit experience tended to have the greatest number of steps and distance traveled.

Conclusion
Using activity trackers, this study derived physical activity measures such as number of steps and distance traveled, enabling an objective examination of physical activity during shifts. Nurses’ level of physical activity differed depending on the type of nursing unit, nurses’ age, and unit experience. These results suggest the need for support programs that are specific to the job demands of specific nursing units.
A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers
Authors: Thompson Jason , McClure Roderick , Scott Nick , Hellard Margaret , Abeysuriya Romesh , Vidanaarachchi Rajith , Thwaites John , Lazarus Jeffrey V. , Lavis John , Michie Susan , Bullen Chris , Prokopenko Mikhail , Chang Sheryl L. , Cliff Oliver M. , Zachreson Cameron , Blakely Antony , Wilson Tim , Ouakrim Driss Ait , Sundararajan Vijay 
Published: October 2022

AbstractThe COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models—developed at rapid pace and often in the absence of complete information—ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.
Improving the availability of prescription drugs in Lebanon: a critical analysis of alternative policy options
Authors: El-Harakeh Amena , Haley Sean J. 
Published: October 2022

AbstractThe economic downfall in Lebanon and the destruction of the Beirut Port have had a crippling effect on all players in the health sector, including hospitals, healthcare providers, and the pharmaceutical and medical supply industry. The outbreak of COVID-19 has further aggravated the crisis. To address the challenges facing the pharmaceutical industry, Lebanon must create a stable and secure source of prescription drug production. Two alternative approaches are presented to address the crisis: (1) amending the subsidy system and supporting local pharmaceutical production, and (2) promoting the prescription and use of generic drugs. Investing in local production is promising and can lead to establishing trust in the quality of drugs produced locally. These efforts can be complemented by promoting the prescription and use of generic drugs at a later stage, after having had established a well-operating system for local drug production.
Decoding the colorectal cancer ecosystem emphasizes the cooperative role of cancer cells, TAMs and CAFsin tumor progression
Authors: Shen Rongfang , Li Ping , Zhang Botao , Feng Lin , Cheng Shujun 
Published: October 2022

Abstract
Background
Single-cell transcription data provided unprecedented molecular information, enabling us to directly encode the ecosystem of colorectal cancer (CRC). Characterization of the diversity of epithelial cells and how they cooperate with tumor microenvironment cells (TME) to endow CRC with aggressive characteristics at single-cell resolution is critical for the understanding of tumor progression mechanism.

Methods
In this study, we comprehensively analyzed the single-cell transcription data, bulk-RNA sequencing data and pathological tissue data. In detail, cellular heterogeneity of TME and epithelial cells were analyzed by unsupervised classification and consensus nonnegative matrix factorization analysis, respectively. Functional status of epithelial clusters was annotated by CancerSEA and its crosstalk with TME cells was investigated using CellPhoneDB and correlation analysis. Findings from single-cell transcription data were further validated in bulk-RNA sequencing data and pathological tissue data.

Results
A distinct cellular composition was observed between tumor and normal tissues, and tumors exhibited immunosuppressive phenotypes. Regarding epithelial cells, we identified one highly invasiveQuery cluster, C4, that correlated closely with tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs). Further analysis emphasized the TAMs subclass TAM1 and CAFs subclass S5 are closely related with C4.

Conclusions
In summary, our study elaborates on the cellular heterogeneity of CRC, revealing that TAMs and CAFs were critical for crosstalk network epithelial cells and TME cells. This in-depth understanding of cancer cell-TME network provided theoretical basis for the development of new drugs targeting this sophisticated network in CRC.
Pivotal interplays between fecal metabolome and gut microbiome reveal functional signatures in cerebral ischemic stroke
Authors: Zhao Lanlan , Wang Cheng , Peng Shanxin , Zhu Xiaosong , Zhang Ziyi , Zhao Yanyan , Zhang Jinling , Zhao Guoping , Zhang Tao , Heng Xueyuan , Zhang Lei 
Published: October 2022

Abstract
Background
Integrative analysis approaches of metagenomics and metabolomics have been widely developed to understand the association between disease and the gut microbiome. However, the different profiling patterns of different metabolic samples in the association analysis make it a matter of concern which type of sample is the most closely associated with gut microbes and disease. To address this lack of knowledge, we investigated the association between the gut microbiome and metabolomic profiles of stool, urine, and plasma samples from ischemic stroke patients and healthy subjects.

Methods
We performed metagenomic sequencing (feces) and untargeted metabolomics analysis (feces, plasma, and urine) from ischemic stroke patients and healthy volunteers. Differential analyses were conducted to find key differential microbiota and metabolites for ischemic stroke. Meanwhile, Spearman’s rank correlation and linear regression analyses were used to study the association between microbiota and metabolites of different metabolic mixtures.

Results
Untargeted metabolomics analysis shows that feces had the most abundant features and identified metabolites, followed by urine and plasma. Feces had the highest number of differential metabolites between ischemic stroke patients and the healthy group. Based on the association analysis between metagenomics and metabolomics of fecal, urine, and plasma, fecal metabolome showed the strongest association with the gut microbiome. There are 1073, 191, and 81 statistically significant pairs (P < 0.05) in the correlation analysis for fecal, urine, and plasma metabolome. Fecal metabolites explained the variance of alpha-diversity of the gut microbiome up to 31.1%, while urine and plasma metabolites only explained the variance of alpha-diversity up to 13.5% and 10.6%. Meanwhile, there were more significant differential metabolites in feces than urine and plasma associated with the stroke marker bacteria.

Conclusions
The systematic association analysis between gut microbiome and metabolomics reveals that fecal metabolites show the strongest association with the gut microbiome, followed by urine and plasma. The findings would promote the association study between the gut microbiome and fecal metabolome to explore key factors that are associated with diseases. We also provide a user-friendly web server and a R package to facilitate researchers to conduct the association analysis of gut microbiome and metabolomics.
Record linkage based patient intersection cardinality for rare disease studies using Mainzelliste and secure multi-party computation
Authors: Kussel Tobias , Brenner Torben , Tremper Galina , Schepers Josef , Lablans Martin , Hamacher Kay 
Published: October 2022

AbstractBackgroundThe low number of patients suffering from any given rare diseases poses a difficult problem for medical research: With the exception of some specialized biobanks and disease registries, potential study participants’ information are disjoint and distributed over many medical institutions. Whenever some of those facilities are in close proximity, a significant overlap of patients can reasonably be expected, further complicating statistical study feasibility assessments and data gathering. Due to the sensitive nature of medical records and identifying data, data transfer and joint computations are often forbidden by law or associated with prohibitive amounts of effort. To alleviate this problem and to support rare disease research, we developed the Mainzelliste Secure EpiLinker (MainSEL) record linkage framework, a secure Multi-Party Computation based application using trusted-third-party-less cryptographic protocols to perform privacy-preserving record linkage with high security guarantees. In this work, we extend MainSEL to allow the record linkage based calculation of the number of common patients between institutions. This allows privacy-preserving statistical feasibility estimations for further analyses and data consolidation. Additionally, we created easy to deploy software packages using microservice containerization and continuous deployment/continuous integration. We performed tests with medical researchers using MainSEL in real-world medical IT environments, using synthetic patient data.ResultsWe show that MainSEL achieves practical runtimes, performing 10 000 comparisons in approximately 5 minutes. Our approach proved to be feasible in a wide range of network settings and use cases. The “lessons learned” from the real-world testing show the need to explicitly support and document the usage and deployment for both analysis pipeline integration and researcher driven ad-hoc analysis use cases, thus clarifying the wide applicability of our software. MainSEL is freely available under:https://github.com/medicalinformatics/MainSELConclusionsMainSEL performs well in real-world settings and is a useful tool not only for rare disease research, but medical research in general. It achieves practical runtimes, improved security guarantees compared to existing solutions, and is simple to deploy in strict clinical IT environments. Based on the “lessons learned” from the real-word testing, we hope to enable a wide range of medical researchers to meet their needs and requirements using modern privacy-preserving technologies.