bluuebunny/crossref_metadata_2025_split huggingface dataset:
Red algae acclimate to low light by modifying phycobilisome composition to maintain efficient light harvesting
Authors: Voerman Sofie E. , Ruseckas Arvydas , Turnbull Graham A. , Samuel Ifor D. W. , Burdett Heidi L. 
Published: December 2022

Abstract

Background
Despite a global prevalence of photosynthetic organisms in the ocean’s mesophotic zone (30–200+ m depth), the mechanisms that enable photosynthesis to proceed in this low light environment are poorly defined. Red coralline algae are the deepest known marine benthic macroalgae — here we investigated the light harvesting mechanism and mesophotic acclimatory response of the red coralline alga Lithothamnion glaciale.

Results
Following initial absorption by phycourobilin and phycoerythrobilin in phycoerythrin, energy was transferred from the phycobilisome to photosystems I and II within 120 ps. This enabled delivery of 94% of excitations to reaction centres. Low light intensity, and to a lesser extent a mesophotic spectrum, caused significant acclimatory change in chromophores and biliproteins, including a 10% increase in phycoerythrin light harvesting capacity and a 20% reduction in chlorophyll-a concentration and photon requirements for photosystems I and II. The rate of energy transfer remained consistent across experimental treatments, indicating an acclimatory response that maintains energy transfer.

Conclusions
Our results demonstrate that responsive light harvesting by phycobilisomes and photosystem functional acclimation are key to red algal success in the mesophotic zone.
Multi-omics gut microbiome signatures in obese women: role of diet and uncontrolled eating behavior
Authors: Barone Monica , Garelli Silvia , Rampelli Simone , Agostini Alessandro , Matysik Silke , D’Amico Federica , Krautbauer Sabrina , Mazza Roberta , Salituro Nicola , Fanelli Flaminia , Iozzo Patricia , Sanz Yolanda , Candela Marco , Brigidi Patrizia , Pagotto Uberto , Turroni Silvia 
Published: December 2022

Abstract
Background
Obesity and related co-morbidities represent a major health challenge nowadays, with a rapidly increasing incidence worldwide. The gut microbiome has recently emerged as a key modifier of human health that can affect the development and progression of obesity, largely due to its involvement in the regulation of food intake and metabolism. However, there are still few studies that have in-depth explored the functionality of the human gut microbiome in obesity and even fewer that have examined its relationship to eating behaviors.

Methods
In an attempt to advance our knowledge of the gut-microbiome-brain axis in the obese phenotype, we thoroughly characterized the gut microbiome signatures of obesity in a well-phenotyped Italian female cohort from the NeuroFAST and MyNewGut EU FP7 projects. Fecal samples were collected from 63 overweight/obese and 37 normal-weight women and analyzed via a multi-omics approach combining 16S rRNA amplicon sequencing, metagenomics, metatranscriptomics, and lipidomics. Associations with anthropometric, clinical, biochemical, and nutritional data were then sought, with particular attention to cognitive and behavioral domains of eating.

Results
We identified four compositional clusters of the gut microbiome in our cohort that, although not distinctly associated with weight status, correlated differently with eating habits and behaviors. These clusters also differed in functional features, i.e., transcriptional activity and fecal metabolites. In particular, obese women with uncontrolled eating behavior were mostly characterized by low-diversity microbial steady states, with few and poorly interconnected species (e.g., Ruminococcus torques and Bifidobacterium spp.), which exhibited low transcriptional activity, especially of genes involved in secondary bile acid biosynthesis and neuroendocrine signaling (i.e., production of neurotransmitters, indoles and ligands for cannabinoid receptors). Consistently, high amounts of primary bile acids as well as sterols were found in their feces.

Conclusions
By finding peculiar gut microbiome profiles associated with eating patterns, we laid the foundation for elucidating gut-brain axis communication in the obese phenotype. Subject to confirmation of the hypotheses herein generated, our work could help guide the design of microbiome-based precision interventions, aimed at rewiring microbial networks to support a healthy diet-microbiome-gut-brain axis, thus counteracting obesity and related complications.
Distinct metabolic biomarkers to distinguish IgG4-related disease from Sjogren’s syndrome and pancreatic cancer and predict disease prognosis
Authors: Yan Songxin , Peng Yu , Wu Ziyan , Cheng Linlin , Li Haolong , Xu Honglin , Huang Yuan , Zhang Wen , Li Yongzhe 
Published: December 2022

Abstract
Background
The pathogenesis of immunoglobulin G4-related disease (IgG4-RD) remains unclear. IgG4-RD often mimics other diseases, including pancreatic cancer (PC) and Sjogren’s syndrome (SS), which may easily lead to misdiagnosis. This study was performed to explore the metabolite changes and potential biomarkers of IgG4-RD and other misdiagnosed diseases.

Methods
Untargeted liquid chromatography–tandem mass spectrometry metabolomics profiling of plasma samples from a cohort comprising healthy controls (HCs) and patients with IgG4-RD (n = 87), PC (n = 33), and SS (n = 31) was performed. A random forest machine learning model was used to verify the relevance of the identified metabolites in the diagnosis of different diseases and the prediction of disease prognosis.

Results
The ATP-binding cassette transporter pathway was found to be most closely related to IgG4-RD, which was significantly up-regulated in the IgG4-RD group than in all the matched groups. Five metabolites were proved to be valuable biomarkers for IgG4-RD. Caftaric acid, maltotetraose, d-glutamic acid, 1-stearoyl-2-arachidonoyl-sn-glycero-3-phosphoserine, and hydroxyproline were useful in distinguishing between IgG4-RD, PC, SS, and HC [area under the curve (AUC) = 1]. A combination of phenylalanine betaine, 1-(1z-hexadecenyl)-sn-glycero-3-phosphocholine, Pi 40:8, uracil, and N1-methyl-2-pyridone-5-carboxamide showed a moderate value in predicting relapse in patients with IgG4-RD (AUC = 0.8).

Conclusions
Our findings revealed the metabolite changes of IgG4-RD and provide new insights for deepening our understanding of IgG4-RD despite the lack of validation in external cohorts. Metabolomic biomarkers have significance in the clinical diagnosis and disease prognosis of IgG4-RD.
Ethical and regulatory issues of stem cell-derived 3-dimensional organoid and tissue therapy for personalised regenerative medicine
Authors: Harris Alexander R. , Walker Mary Jean , Gilbert Frederic 
Published: December 2022

Abstract
Background
Regenerative medicine has the potential to treat genetic disorders and replace damaged or missing tissue. The use of donor or animal tissue raises many well-known issues, including limited tissue availability, the possibility of rejection and patient infection. Stem cell therapy raised hope of overcoming these issues, but created new risks including tumour formation and limited benefit if the desired target tissue does not form. The recent development of 3-dimensional tissues, including organoids, allows the creation of more complex tissues for personalised regenerative medicine.

Methods
This article details the potential health risks of 3-dimensional organoid and tissue therapy versus dissociated stem cell therapy. The current ethical and regulatory issues surrounding 3-dimensional organoid and tissue therapy are presented with a focus on the highly influential FDA and International Society of Stem Cell Research (ISSCR) guidelines.

Conclusions
The potential use of 3-dimensional organoid and tissue therapy may deliver greater patient benefits than other regenerative medicine approaches, but raises new health and ethical risks. Preclinical testing of these therapies will not mitigate some of their risks; they may only be understood after first-in-human trials. The potential irreversibility and high risk of these therapies affects how clinical trials should be structured, including post-trial care for participants.
Protective effects of Gypenoside XVII against cerebral ischemia/reperfusion injury via SIRT1-FOXO3A- and Hif1a-BNIP3-mediated mitochondrial autophagy
Authors: Xie Weijie , Zhu Ting , Zhang Shuxia , Sun Xiaobo 
Published: December 2022

Abstract
Background
Mitochondrial autophagy maintains mitochondrial function and cellular homeostasis and plays a critical role in the pathological process of cerebral ischemia/reperfusion injury (CIRI). Whether Gypenoside XVII (GP17) has regulatory effects on mitochondrial autophagy against CIRI remains unclear. The purpose of this study was to investigate the pharmacodynamic effects and mechanisms of GP17 on mitochondrial autophagy after CIRI.

Methods
A rat middle cerebral artery occlusion/reperfusion (MCAO/R) model was used to assess the effects of GP17 against CIRI and to explore the underlying mechanisms. An oxygen-glucose deprivation/reoxygenation (OGD/R) cell model was used to verify the ameliorative effects on mitochondrial damage and to probe the autophagy pathways involved in combating neural injuries.

Results
The in vivo results showed that GP17 significantly improved mitochondrial metabolic functions and suppressed cerebral ischemic injury, possibly via the autophagy pathway. Further research revealed that GP17 maintains moderate activation of autophagy under ischemic and OGD conditions, producing neuroprotective effects against CIRI, and that the regulation of mitochondrial autophagy is associated with crosstalk between the SIRT1-FOXO3A and Hif1a-BNIP3 signalling pathway that is partially eliminated by the specific inhibitors AGK-7 and 2-ME.

Conclusion
Overall, this work offers new insights into the mechanisms by which GP17 protects against CIRI and highlights the potential of therapy with Notoginseng leaf triterpene compounds as a novel clinical strategy in humans.
Non-invasive intravoxel incoherent motion MRI in prediction of histopathological response to neoadjuvant chemotherapy and survival outcome in osteosarcoma at the time of diagnosis
Authors: Baidya Kayal Esha , Bakhshi Sameer , Kandasamy Devasenathipathy , Sharma Mehar Chand , Khan Shah Alam , Kumar Venkatesan Sampath , Khare Kedar , Sharma Raju , Mehndiratta Amit 
Published: December 2022

AbstractBackgroundEarly prediction of response to neoadjuvant chemotherapy (NACT) is important to aid personalized treatment in osteosarcoma. Diffusion-weighted Intravoxel Incoherent Motion (IVIM) MRI was used to evaluate the predictive value for response to NACT and survival outcome in osteosarcoma.MethodsTotal fifty-five patients with biopsy-proven osteosarcoma were recruited prospectively, among them 35 patients were further analysed. Patients underwent 3 cycles of NACT (Cisplatin + Doxorubicin) followed by surgery and response adapted adjuvant chemotherapy. Treatment outcomes were histopathological response to NACT (good-response ≥ 50% necrosis and poor-response < 50% necrosis) and survival outcome (event-free survival (EFS) and overall survival (OS)). IVIM MRI was acquired at 1.5T at baseline (t0), after 1-cycle (t1) and after 3-cycles (t2) of NACT. Quantitative IVIM parameters (D, D*, f&D*.f) were estimated using advanced state-of-the-art spatial penalty based IVIM analysis method bi-exponential model with total-variation penalty function (BETV) at 3 time-points and histogram analysis was performed.ResultsGood-responders: Poor-responders ratio was 13 (37%):22 (63%). EFS and OS were 31% and 69% with 16.27 and 25.9 months of median duration respectively. For predicting poor-response to NACT, IVIM parameters showed AUC = 0.87, Sensitivity = 86%, Specificity = 77% at t0, and AUC = 0.96, Sensitivity = 86%, Specificity = 100% at t1. Multivariate Cox regression analysis showed smaller tumour volume (HR = 1.002,p = 0.001) higherADC-25th-percentile (HR = 0.047,p = 0.005) &D-Mean (HR = 0.1,p = 0.023) and lowerD*-Mean (HR = 1.052,p = 0.039) were independent predictors of longer EFS (log-rankp-values: 0.054, 0.0034, 0.0017, 0.0019 respectively) and non-metastatic disease (HR = 4.33,p < 10–3), smaller tumour-volume (HR = 1.001,p = 0.042), lowerD*-Mean (HR = 1.045,p = 0.056) and higherD*.f-skewness (HR = 0.544,p = 0.048) were independent predictors of longer OS (log-rankp-values: < 10–3, 0.07, < 10–3, 0.019 respectively).ConclusionIVIM parameters obtained with a 1.5T scanner along with novel BETV method and their histogram analysis indicating tumour heterogeneity were informative in characterizing NACT response and survival outcome in osteosarcoma.
Describing the safety of abortion at the population level using network-based survey approaches
Authors: Rossier Clémentine , Owolabi Onikepe , Kouanda Seni , Bangha Martin , Kim Caron R. , Ganatra Bela , Feehan Dennis , Breen Casey , Zan Moussa , Compaoré Rachidatou , Baguiya Adama , Ouédraogo Ramatou , Oduor Clement , Bagnoa Vincent , Athero Sherine 
Published: December 2022

Abstract
Background
Despite the negative impact of unsafe abortions on women's health and rights, the degree of abortion safety remains strikingly undocumented for a large share of abortions globally. Data on how women induce abortions (method, setting, provider) are central to the measurement of abortion safety. However, health-facility statistics and direct questioning in population surveys do not yield representative data on abortion care seeking pathways in settings where access to abortion services is highly restricted. Recent developments in survey methodologies to study stigmatized / illegal behaviour and hidden populations rely on the fact that such information circulates within social networks; however, such efforts have yet to give convincing results for unsafe abortions.

Objective
This article presents the protocol of a study whose purpose is to apply and develop further two network-based methods to contribute to the generation of reliable population-level information on the safety of abortions in contexts where access to legal abortion services is highly restricted.

Methods
This study plans to obtain population-level data on abortion care seeking in two Health and Demographic Surveillance Systems in urban Kenya and rural Burkina Faso by applying two methods: Anonymous Third-Party Reporting (ATPR) (also known as confidantes’ method) and Respondent Driven Sampling (RDS). We will conduct a mixed methods formative study to determine whether these network-based approaches are pertinent in the study contexts. The ATPR will be refined notably by incorporating elements of the Network Scale-Up Method (NSUM) to correct or account for certain of its biases (transmission, barrier, social desirability, selection). The RDS will provide reliable alternative estimates of abortion safety if large samples and equilibrium can be reached; an RDS multiplex variant (also including social referents) will be tested.

Discussion
This study aims at documenting abortion safety in two local sites using ATPR and RDS. If successful, it will provide data on the safety profiles of abortion seekers across sociodemographic categories in two contrasted settings in sub-Saharan Africa. It will advance the formative research needed to determine whether ATPR and RDS are applicable or not in a given context. It will improve the questionnaire and correcting factors for the ATPR, improve the capacity of RDS to produce quasi-representative data on abortion safety, and advance the validation of both methods.
Ureteral tumor with morphological features analogous to phyllodes tumor: a unique case with concomitant urothelial carcinoma
Authors: Zhou Wei , Dang Linlin , Chong Chuangang , Cheng Xiankui , Qin Yejun , Su Wenjing 
Published: December 2022

Abstract
Background
Phyllodes tumors belong to a spectrum of biphasic fibroepithelial lesions and are most commonly found in the breast. They are extremely rare in the urinary tract and only one case of bladder phyllodes tumor has been reported.

Case presentation
We present a 69-year-old man with gross hematuria without an apparent cause. Computed tomography-urography and cystoscopic examination revealed a 5 × 4 cm lesion in the right ureteral orifice. He underwent a laparoscopic nephroureterectomy and partial cystectomy. Postoperative pathology confirmed a leaf-like structure consisting of myxoid stroma and peripheral urothelium. Stromal cells were spindle-shaped and stellate in appearance with no conspicuous cytological atypia or mitosis. The outlining urothelium had varying degrees of dysplasia, while in areas with moderate-to-severe dysplasia, active mitotic activity, abnormal giant cells, and focal early infiltration were observed. Overall, this case had the morphological features of benign phyllodes tumors and concomitant invasive urothelial carcinoma inside. The patient remained disease-free at 7 months after surgery.

Conclusion
We report the first ureteral tumor with the morphological characteristics of a phyllodes tumor and concomitant invasive urothelial carcinoma inside. Considering the potential for local recurrence of phyllodes tumors and invasive urothelial carcinoma, long-term clinical and radiological follow-up of such lesions are advisable.
Machine learning models predict overall survival and progression free survival of non-surgical esophageal cancer patients with chemoradiotherapy based on CT image radiomics signatures
Authors: Cui Yongbin , Li Zhengjiang , Xiang Mingyue , Han Dali , Yin Yong , Ma Changsheng 
Published: December 2022

Abstract
Purpose
To construct machine learning models for predicting progression free survival (PFS) and overall survival (OS) with esophageal squamous cell carcinoma (ESCC) patients.

Methods
204 ESCC patients were randomly divided into training cohort (n = 143) and test cohort (n = 61) according to the ratio of 7:3. Two radiomics models were constructed by radiomics features, which were selected by LASSO Cox model to predict PFS and OS, respectively. Clinical features were selected by univariate and multivariate Cox proportional hazards model (p < 0.05). Combined radiomics and clinical model was developed by selected clinical and radiomics features. The receiver operating characteristic curve, Kaplan Meier curve and nomogram were used to display the capability of constructed models.

Results
There were 944 radiomics features extracted based on volume of interest in CT images. There were six radiomics features and seven clinical features for PFS prediction and three radiomics features and three clinical features for OS prediction; The radiomics models showed general performance in training cohort and test cohort for prediction for prediction PFS (AUC, 0.664, 0.676. C-index, 0.65, 0.64) and OS (AUC, 0.634, 0.646.C-index, 0.64, 0.65). The combined models displayed high performance in training cohort and test cohort for prediction PFS (AUC, 0.856, 0.833. C-index, 0.81, 0.79) and OS (AUC, 0.742, 0.768. C-index, 0.72, 0.71).

Conclusion
We developed combined radiomics and clinical machine learning models with better performance than radiomics or clinical alone, which were used to accurate predict 3 years PFS and OS of non-surgical ESCC patients. The prediction results could provide a reference for clinical decision.
Traumatic blunt thoracic aortic injury: a 10-year single-center retrospective analysis
Authors: Sun Jingwei , Ren Kai , Zhang Liyun , Xue Chao , Duan Weixun , Liu Jincheng , Cong Ren 
Published: December 2022

Abstract
Background
Approximately 80% of patients with blunt thoracic aortic injury (BTAI) die before reaching the hospital. Most people who survive the initial injury eventually die without appropriate treatment. This study analyzed and reported the treatment strategy of a single center for BTAI in the last 10 years and the early and middle clinical results.

Methods
This retrospective study included patients diagnosed with BTAI at Xijing Hospital from 2013 to 2022. All inpatients with BTAI aged ≥ 18 years were included in this study. The clinical data, imaging findings, and follow-up results were retrospectively collected and analyzed. The Kaplan–Meier curve and multivariate logistic regression were used to compare survivors and nonsurvivors.

Results
A total of 72 patients (57% men) were diagnosed with BTAI, with a mean age of 54.2 ± 9.1 years. The injury severity score was 24.3 ± 18, with Grade I BTAI1 (1.4%), Grade II 17 (23.6%), Grade III 52 (72.2%), and Grade IV 2 (2.8%) aortic injuries. Traffic accidents were the main cause of BTAI in 32 patients (44.4%). Most patients had trauma, 37 had rib fractures (51.4%), Sixty patients (83.3%) underwent thoracic endovascular aortic repair (TEVAR) surgery, eight (11.1%) underwent conservative treatment, and only four (5.6%) underwent open surgery. The overall hospitalization mortality was 12.5%. In multivariate logistic regression, elevated creatinine levels (P = 0.041) and high Glasgow coma scale (GCS) score (P = 0.004) were the predictors of hospital mortality. The median follow-up period was 57 (28–87) months. During the follow-up period, all-cause mortality was 5.6% and no aortic-related deaths were reported. Three patients (4.2%) needed secondary surgery and two of them underwent endovascular repair.

Conclusion
Although TEVAR surgery may be associated with intra- or postoperative dissection rupture or serious complications in the treatment of Grade III BTAI, the incidence rate was only 8.9%. Nevertheless, TEVAR surgery remains a safe and feasible approach for the treatment of Grade II or III BTAI, and surgical treatment should be considered first,. A high GCS score and elevated creatinine levels in the emergency department were closely associated with hospital mortality. Younger patients need long-term follow-up after TEVAR.