bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sex hormones and physical function among the Chinese oldest-old and centenarian women
Authors: Zhu Qiao , Ping Ping , Zhang Pei , Ning Chaoxue , Zhao Yali , Yao Yao , Li Xiubing , Fu Shihui 
Published: July 2022

Abstract
Background
Physical independence is crucial for overall health in the elderly individuals. The life expectancy of women has been shown to be higher than that of men, which is also known as the “male–female health-survival paradox”. Sex hormones may be one of the explanations. However, the relationships between sex hormones and physical function remain unclear in the elderly females. This study was designed to explore these relationships among the Chinese oldest-old and centenarian women.

Methods
Data from 1226 women were obtained from the China Hainan Centenarian Cohort Study. Home interviews, physical examinations and blood analyses were conducted using standardized procedures. Variables including age, Han ethnicity, illiteracy, smoker, drinker, estradiol (E2), testosterone (T), follicle-stimulating hormone, and luteinizing hormone were used in the multivariate logistic and linear regression analyses.

Results
In all the participants, age [beta (95% confidence interval): − 0.84 (− 0.98, − 0.71)] and E2 levels [beta (95% confidence interval): − 0.22 (− 0.28, − 0.17)] were negatively associated with activities of daily living (ADLs) in the multivariate linear regression analyses (P < 0.05 for all). We also observed significantly negative associations of age [odds ratio (95% confidence interval): 0.90 (0.88, 0.91)] and E2 levels [odds ratio (95% confidence interval): 0.98 (0.98, 0.99)] with physical normality in the multivariate logistic regression analyses (P < 0.05 for all). Age and E2 levels gradually decreased with increases in the ADL quartiles across all the participants (P < 0.05 for all).

Conclusions
This study demonstrated that E2 levels were negatively associated with physical function among the Chinese oldest-old and centenarian women.
The BRD4 inhibitor JQ1 suppresses tumor growth by reducing c-Myc expression in endometrial cancer
Authors: Pang Yingxin , Bai Gaigai , Zhao Jing , Wei Xuan , Li Rui , Li Jie , Hu Shunxue , Peng Lu , Liu Peishu , Mao Hongluan 
Published: July 2022

Abstract
Background
Endometrial cancer (EC) is the most common gynecological malignancy in developed countries. Efficacy of the bromodomain 4 (BRD4) inhibitor JQ1 has been reported for the treatment of various human cancers, but its potential impact on EC remains unclear. We therefore aimed to elucidate the function of BRD4 and the effects of JQ1 in EC in vivo and in vitro.

Methods
The mRNA expression of BRD4 was evaluated using datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). BRD4 protein expression in EC tissues was measured using immunohistochemistry (IHC) assays. The effects of JQ1 on EC were determined by using MTT and colony formation assays, flow cytometry and xenograft mouse models. The underlying mechanism was also examined by western blot and small interfering RNA (siRNA) transfection.

Results
BRD4 was overexpressed in EC tissues, and the level of BRD4 expression was strongly related to poor prognosis. The BRD4-specific inhibitor JQ1 suppressed cell proliferation and colony formation and triggered cell apoptosis, cell cycle arrest, and changes in the expression of proteins in related signaling pathways. Moreover, JQ1 decreased the protein expression of BRD4 and c-Myc, and knockdown of BRD4 or c-Myc reduced the viability of EC cells. Intraperitoneal administration of JQ1 (50 mg/kg) significantly suppressed the tumorigenicity of EC cells in a xenograft mouse model.

Conclusion
Our results demonstrate that BRD4 is a potential marker of EC and that the BRD4 inhibitor JQ1 is a promising chemotherapeutic agent for the treatment of EC.
Prognostic and predictive value of radiomic signature in stage I lung adenocarcinomas following complete lobectomy
Authors: Nie Wei , Tao Guangyu , Lu Zhenghai , Qian Jie , Ge Yaqiong , Wang Shuyuan , Zhang Xueyan , Zhong Hua , Yu Hong 
Published: July 2022

Abstract
Background
The overall survival (OS) of stage I operable lung cancer is relatively low, and not all patients can benefit from adjuvant chemotherapy. This study aimed to develop and validate a radiomic signature (RS) for prediction of OS and adjuvant chemotherapy candidates in stage I lung adenocarcinoma.

Methods
A total of 474 patients from 2 centers were divided into 1 training (n = 287), 1 internal validation (n = 122), and 1 external validation (n = 65) cohorts. We extracted 1218 radiomic features from preoperative CT images and constructed RS. We further investigated the prognostic value of the RS in survival analysis. Interaction between treatment and RS was assessed to evaluate its predictive value. Propensity score matching (PSM) was conducted.

Results
Overall, 474 eligible patients with stage I lung adenocarcinoma (214 men [45.1%]; median age, 60 years) were identified. The RS was significantly associated with OS in the training and two validation cohorts (hazard ratios [HRs]  >  = 3.22). In multivariable analysis, the RS remained an independent prognostic factor adjusting for clinicopathologic variables (adjusted HRs >  = 2.63). The prognostic value of RS was also confirmed in PSM analysis. In stage I patients, the interaction between RS status and adjuvant chemotherapy was significant (interaction P = 0.020). Within the stratified analysis, good chemotherapy efficacy was only observed for patients with stage IB disease (interaction P < 0.001).

Conclusions
Our results suggested that the radiomic signature was associated with overall survival in patients with stage I lung adenocarcinoma and might predict adjuvant chemotherapy benefit, especially in stage IB patients. The potential of radiomic signature as a noninvasive predictor needed to be confirmed in future studies.
Inulin reduces visceral adipose tissue mass and improves glucose tolerance through altering gut metabolites
Authors: Nakajima Hanako , Nakanishi Naoko , Miyoshi Tomoki , Okamura Takuro , Hashimoto Yoshitaka , Senmaru Takafumi , Majima Saori , Ushigome Emi , Asano Mai , Yamaguchi Mihoko , Mori Jun , Sakui Norihiro , Sasano Ryoichi , Yamazaki Masahiro , Hamaguchi Masahide , Fukui Michiaki 
Published: July 2022

Abstract
Aim
Inulin, a soluble dietary fiber, is a source of energy for the host while the metabolites, such as short-chain fatty acids (SCFAs), produced in the gut through bacterial fermentation exerts the anti-obesity effect. In this study, we aimed to apply a metabolomics approach and clarify the role of this soluble dietary fiber on glucose and lipid metabolism under the calorie-matched condition.

Materials and methods
Eight-week-old male C57BL/6J mice were fed a high-fat/high-sucrose based diet containing maltodextrin or inulin for 12 weeks through calorie-matched pair feeding. We evaluated glucose tolerance, and energy expenditure using indirect calorimetry, comprehensive metabolites in the content of jejunum, feces, and portal vein serum using gas chromatography-mass spectrometry, and histological changes in the adipose tissue.

Results
The inulin group exhibited reduced visceral adipose tissue and smaller size of visceral adipocyte. It also exhibited improved glucose tolerance and an increase in energy expenditure. Reflecting the results of fermentation, the metabolomics analysis revealed an increase in the succinic acid and SCFA contents in both feces and portal vein serum in the inulin group.

Conclusions
Inulin altered the gut metabolites and reduced visceral adipose tissue, thereby resulting in improved glucose tolerance.
Organs-at-risk dose constraints in head and neck intensity-modulated radiation therapy using a dataset from a multi-institutional clinical trial (JCOG1015A1)
Authors: Inada Masahiro , Nishimura Yasumasa , Ishikura Satoshi , Ishikawa Kazuki , Murakami Naoya , Kodaira Takeshi , Ito Yoshinori , Tsuchiya Kazuhiko , Murakami Yuji , Saito Junichi , Akimoto Tetsuo , Nakata Kensei , Yoshimura Michio , Teshima Teruki , Toshiyasu Takashi , Ota Yosuke , Minemura Toshiyuki , Shimizu Hidetoshi , Hiraoka Masahiro 
Published: July 2022

Abstract
Background
JCOG1015A1 is an ancillary research study to determine the organ-specific dose constraints in head and neck carcinoma treated with intensity-modulated radiation therapy (IMRT) using data from JCOG1015.

Methods
Individual patient data and dose-volume histograms of organs at risk (OAR) were collected from 74 patients with nasopharyngeal carcinoma treated with IMRT who enrolled in JCOG1015. The incidence of late toxicities was evaluated using the cumulative incidence method or prevalence proportion. ROC analysis was used to estimate the optimal DVH cut-off value that predicted toxicities.

Results
The 5-year cumulative incidences of Grade (G) 1 myelitis, ≥ G1 central nervous system (CNS) necrosis, G2 optic nerve disorder, ≥ G2 dysphagia, ≥ G2 laryngeal edema, ≥ G2 hearing impaired, ≥ G2 middle ear inflammation, and ≥ G1 hypothyroidism were 10%, 5%, 2%, 11%, 5%, 26%, 34%, and 34%, respectively. Significant associations between DVH parameters and incidences of toxicities were observed in the brainstem for myelitis (D1cc ≥ 55.8 Gy), in the brain for CNS necrosis (D1cc ≥ 72.1 Gy), in the eyeball for optic nerve disorder (Dmax ≥ 36.6 Gy), and in the ipsilateral inner ear for hearing impaired (Dmean ≥ 44 Gy). The optic nerve, pharyngeal constrictor muscle (PCM), and thyroid showed tendencies between DVH parameters and toxicity incidence. The prevalence proportion of G2 xerostomia at 2 years was 17 versus 6% (contralateral parotid gland Dmean ≥ 25.8 Gy vs less).

Conclusions
The dose constraint criteria were appropriate for most OAR in this study, although more strict dose constraints might be necessary for the inner ear, PCM, and brainstem.
KLF9 and EPYC acting as feature genes for osteoarthritis and their association with immune infiltration
Authors: Zhang Jiayin , Zhang Shengjie , Zhou Yu , Qu Yuan , Hou Tingting , Ge Wanbao , Zhang Shanyong 
Published: July 2022

Abstract
Background
Osteoarthritis, a common degenerative disease of articular cartilage, is characterized by degeneration of articular cartilage, changes in subchondral bone structure, and formation of osteophytes, with main clinical manifestations including increasingly serious swelling, pain, stiffness, deformity, and mobility deficits of the knee joints. With the advent of the big data era, the processing of mass data has evolved into a hot topic and gained a solid foundation from the steadily developed and improved machine learning algorithms. Aiming to provide a reference for the diagnosis and treatment of osteoarthritis, this paper using machine learning identifies the key feature genes of osteoarthritis and explores its relationship with immune infiltration, thereby revealing its pathogenesis at the molecular level.

Methods
From the GEO database, GSE55235 and GSE55457 data were derived as training sets and GSE98918 data as a validation set. Differential gene expressions of the training sets were analyzed, and the LASSO regression model and support vector machine model were established by applying machine learning algorithms. Moreover, their intersection genes were regarded as feature genes, the receiver operator characteristic (ROC) curve was drawn, and the results were verified using the validation set. In addition, the expression spectrum of osteoarthritis was analyzed by immunocyte infiltration and the co-expression correlation between feature genes and immunocytes was construed.

Conclusion
EPYC and KLF9 can be viewed as feature genes for osteoarthritis. The silencing of EPYC and the overexpression of KLF9 are associated with the occurrence of osteoarthritis and immunocyte infiltration.
Association of low-dose glucocorticoid use and infection occurrence in systemic lupus erythematosus patients: a prospective cohort study
Authors: Abe Kazuya , Ishikawa Yuichi , Kita Yasuhiko , Yajima Nobuyuki , Inoue Eisuke , Sada Ken-ei , Miyawaki Yoshia , Yoshimi Ryusuke , Shimojima Yasuhiro , Ohno Shigeru , Kajiyama Hiroshi , Ichinose Kunihiro , Sato Shuzo , Fujiwara Michio 
Published: July 2022

Abstract
Background
Infection is a major cause of mortality in patients with systemic lupus erythematosus (SLE). Therefore, minimizing the risk of infection is an important clinical goal to improve the long-term prognosis of SLE patients. Treatment with ≥7.5 mg prednisolone (PSL) or equivalent has been reported to increase the risk of infections. However, it remains unclear whether <7.5 mg PSL or equivalent dose affects the risk of infection in SLE patients. This study evaluated the association between the occurrence of infection in patients with SLE and low-dose glucocorticoid (GC) usage, especially <7.5 mg PSL or equivalent, to explore the GC dose that could reduce infection occurrence.

Methods
This prospective cohort study included patients from the Japanese multicenter registry of patients with SLE (defined as ≥4 American College of Rheumatology 1997 revised criteria) over 20 years of age. The PSL dose was categorized as PSL 0–2.5, 2.6–5.0, 5.1–7.5, and 7.6–15.0 mg. The primary outcome was infection requiring hospitalization. We conducted a multivariable analysis using time-dependent Cox regression analysis to assess the hazard ratio of infection occurrence compared with a dose of 0–2.5 mg PSL or equivalent in the other three PSL dose groups. Based on previous reports and clinical importance, the covariates selected were age, sex, and concurrent use of immunosuppressants with GC. In addition, two sensitivity analyses were conducted.

Results
The mean age of the 509 SLE patients was 46.7 years; 89.0% were female, and 77.2% used multiple immunosuppressants concomitantly. During the observation period, 52 infections requiring hospitalization occurred. The incidence of infection with a PSL dose of 5.0–7.5 mg was significantly higher than that in the PSL 0–2.5 mg group (adjusted hazard ratio: 6.80, 95% confidence interval: 2.17–21.27). The results of the two sensitivity analyses were similar.

Conclusions
Our results suggested that the use of 5.0–7.5 mg PSL or equivalent could pose an infection risk in SLE patients. This finding indicates that PSL dose should be reduced to as low as possible in SLE patients to avoid infection.
Dataset for classifying and estimating the position, orientation, and dimensions of a list of primitive objects
Authors: Makki Alireza , Hadi Alireza , Tarvirdizadeh Bahram , Teimouri Mehdi 
Published: July 2022

AbstractObjectivesRobotic systems are moving toward more interaction with the environment, which requires improving environmental perception methods. The concept of primitive objects simplified the perception of the environment and is frequently used in various fields of robotics, significantly in the grasping challenge. After reviewing the related resources and datasets, we could not find a suitable dataset for our purpose, so we decided to create a dataset to train deep neural networks to classify a primitive object and estimate its position, orientation, and dimensions described in this report.Data descriptionThis dataset contains 8000 virtual data for four primitive objects, including sphere, cylinder, cube, and rectangular sheet with dimensions between 10 to 150 mm, and 200 real data of these four types of objects. Real data are provided by Intel Realsense SR300 3D camera, and virtual data are generated using the Gazebo simulator. Raw data are generated in.pcd format in both virtual and real types. Data labels include values of the object type and its position, orientation, and dimensions.
Spatial differences in Casuarina equisetifolia L. endophyte community structure
Authors: Lin Qi , Xu Zhixia , Li Miaomiao , Wang Ying , Li Lei 
Published: July 2022

Abstract
Purpose
Casuarina equisetifolia, a fast-growing, abundant tree species on the southeastern coast of China, plays an important role in protecting the coastal environment, but the ecological processes that govern microbiome assembly and within-plant microorganism transmission are poorly known.

Methods
In this paper, we used ITS and 16S amplification techniques to study the diversity of fungal and bacterial endophytes in critical plant parts of this species: seeds, branchlets, and roots. Additionally, we examined the litter of this species to understand the process of branchlets from birth to litter.

Result
We uncovered a non-random distribution of endophyte diversity in which branchlets had the greatest and seeds had the lowest endophytic fungal diversity. In contrast, litter endophytic bacteria had the highest diversity, and branchlets had the lowest diversity. As for fungi, a large part of the seed microbiome was transmitted to the phyllosphere, while a large part of the bacterial microbiome in the seed was transmitted to the root.

Conclusion
Our study provides comprehensive evidence on diversity, potential sources, and transmission pathways for non-crop microbiome assembly and has implications for the management and manipulation of the non-crop microbiome in the future.
A comparison of Covid-19 early detection between convolutional neural networks and radiologists
Authors: Albiol Alberto , Albiol Francisco , Paredes Roberto , Plasencia-Martínez Juana María , Blanco Barrio Ana , Santos José M. García , Tortajada Salvador , González Montaño Victoria M. , Rodríguez Godoy Clara E. , Fernández Gómez Saray , Oliver-Garcia Elena , de la Iglesia Vayá María , Márquez Pérez Francisca L. , Rayo Madrid Juan I. 
Published: July 2022

Abstract
Background
The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience.

Methods
The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx.

Results
Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx.

Conclusion
The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19.
Niemann-Pick type A disease with new mutation: a case report
Authors: Aghamahdi Fatemeh , Nirouei Matineh , Savad Shahram 
Published: July 2022

Abstract
Background
Niemann-Pick type A (NP-A) is a congenital, hereditary disease caused by a deficiency in acid sphingomyelinase, a lysosomal enzyme. This deficiency results in an accumulation of sphingomyelin in lysosomes, leading to cellular apoptosis and ultimately to hepatosplenomegaly, neurodegenerative disorder and failure to thrive. Cherry-red spots in the macula and foamy cells in the bone marrow are other manifestations of the disease that help with diagnosis. Type A is a rare, untreatable disease with early manifestations and a poor prognosis, with newborns rarely surviving for 2–3 years.

Case presentation
A 1-year-old Persian boy was referred to our clinic due to abdominal distention and poor weight gain. He was the first male offspring of consanguineous parents. Other findings were neurodevelopmental delay, hepatosplenomegaly, severe hypotonia, difficulty in breathing, and a slightly coarse face with an open mouth and protruding tongue. The initial diagnosis was clinical mucopolysaccharidosis (MPS) based on the coarse facial features, but further workup ruled out this inherited disorder. Enzyme histochemistry revealed that the level of acid sphingomyelinase was lower than normal. In the genetic study, next-generation sequencing of all coding exons and flanking intronic regions of the patient’s DNA demonstrated a homozygous c.682T>G variant in the SMPD1 gene. This variant was classified as a variant of unknown significance. Further evaluation of DNA extract from his parents and examined using Sanger sequencing showed a heterozygous c.682T>G variant in the SMPD1 gene of both parents.

Conclusions
We describe a 1-year-old boy with neurodevelopmental delay, hepatosplenomegaly, and severe hypotonia. Further investigation demonstrated a new mutation for Niemann-Pick disease.
TAS2R supports odontoblastic differentiation of human dental pulp stem cells in the inflammatory microenvironment
Authors: Kang Wen , Wang Yiwen , Li Jiaying , Xie Weige , Zhao Dan , Wu Li , Wang Hongwei , Xie Sijing 
Published: July 2022

AbstractBackgroundInflammatory microenvironment promotes odontoblastic differentiation in human dental pulp stem cells (hDPSCs), but the regulatory mechanisms remain unclear. In this study, we aimed to explore the role of TAS2R in odontoblastic differentiation of hDPSCs in the inflammatory microenvironment.MethodsMicroarray analysis was performed to explore the differential mRNA profiles in inflammatory and healthy pulp tissues from the patients. hDPSCs isolated from the healthy pulp tissues were stimulated by LPS, TNFα and IL-6, respectively, to verify the effect of TAS2R. The expression markers related to odontoblastic differentiation of hDPSCs were observed by qPCR and chemical staining methods. TAS2R10 was overexpressed or silenced to observe the effect on odontoblastic differentiation of hDPSCs under LPS stimulation. The G protein and intracellular Ca2+were detected, respectively, by qPCR and Fluo-4AM Ca2+fluorescent probe.ResultsThe expression of TAS2R was significantly upregulated in the inflammatory pulp tissues. In vitro, 5 subtypes of TAS2R mRNA expressions including TAS2R10, TAS2R14, TAS2R19, TAS2R30 and TAS2R31 in hDPSCs increased under the stimulation of LPS, TNFα or IL-6. In odontoblastic differentiation medium, we found LPS, TNFα or IL-6 stimulation promoted odontoblastic differentiation of hDPSCs. TAS2R10 overexpression in hDPSCs significantly increased the expression markers related to odontoblastic differentiation, whereas TAS2R10 silencing revealed the opposite effect. Furthermore, G protein was activated, and at the same time, intracellular Ca2+enhanced when TAS2R10 was overexpressed, but decreased when TAS2R10 was silenced.ConclusionsThis study demonstrated that TAS2R was found to be expressed in hDPSCs, and TAS2R promoted odontoblastic differentiation of hDPSCs by mediating the increase in intracellular Ca2+via the G protein-coupled receptors (GPCR) conventional signaling pathway in inflammatory microenvironment, which may be a potential target for the development of effective conservative treatments for dental pulp repair.