bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative and phylogenetic analyses of six Kenya Polystachya (Orchidaceae) species based on the complete chloroplast genome sequences
Authors: Jiang Hui , Tian Jing , Yang Jiaxin , Dong Xiang , Zhong Zhixiang , Mwachala Geoffrey , Zhang Caifei , Hu Guangwan , Wang Qingfeng 
Published: April 2022

Abstract
Background
Polystachya Hook. is a large pantropical orchid genus (c. 240 species) distributed in Africa, southern Asia and the Americas, with the center of diversity in Africa. Previous studies on species of this genus have not obtained the complete chloroplast genomes, structures and variations. Additionally, the phylogenetic position of the genus in the Orchidaceae is still controversial and uncertain. Therefore, in this study, we sequenced the complete plastomes of six Kenya Polystachya species based on genome skimming, subjected them to comparative genomic analysis, and reconstructed the phylogenetic relationships with other Orchidaceae species.

Results
The results exhibited that the chloroplast genomes had a typical quadripartite structure with conserved genome arrangement and moderate divergence. The plastomes of the six Polystachya species ranged from 145,484 bp to 149,274 bp in length and had an almost similar GC content of 36.9–37.0%. Gene annotation revealed 106–109 single-copy genes. In addition, 19 genes are duplicated in the inverted regions, and 16 genes each possessd one or more introns. Although no large structural variations were observed among the Polystachya plastomes, about 1 kb inversion was found in Polystachya modesta and all 11 ndh genes in the Polystachya plastomes were lost or pseudogenized. Comparative analysis of the overall sequence identity among six complete chloroplast genomes confirmed that for both coding and non-coding regions in Polystachya, SC regions exhibit higher sequence variation than IRs. Furthermore, there were various amplifications in the IR regions among the six Polystachya species. Most of the protein-coding genes of these species had a high degree of codon preference. We screened out SSRs and found seven relatively highly variable loci. Moreover, 13 genes were discovered with significant positive selection. Phylogenetic analysis showed that the six Polystachya species formed a monophyletic clade and were more closely related to the tribe Vandeae. Phylogenetic relationships of the family Orchidaceae inferred from the 85 chloroplast genome sequences were generally consistent with previous studies and robust.

Conclusions
Our study is the initial report of the complete chloroplast genomes of the six Polystachya species, elucidates the structural characteristics of the chloroplast genome of Polystachya, and filters out highly variable sequences that can contribute to the development of DNA markers for use in the study of genetic variability and evolutionary studies in Polystachya. In addition, the phylogenetic results strongly support that the genus of Polystachya is a part of the tribe Vandeae.
Identification and functional analysis of cation-efflux transporter 1 from Brassica juncea L.
Authors: Han Lu , Wu Xiaohua , Zhang Xinyu , Hou Kailin , Zhang Hongshan , Shen Chenjia 
Published: April 2022

Abstract
Background
Brassica juncea behaves as a moderate-level accumulator of various heavy metal ions and is frequently used for remediation. To investigate the roles of metal ion transporters in B. juncea, a cation-efflux family gene, BjCET1, was cloned and functionally characterized.

Results
BjCET1 contains 382 amino acid residues, including a signature motif of the cation diffusion facilitator protein family, six classic trans-membrane-spanning structures and a cation-efflux domain. A phylogenetic analysis showed that BjCET1 has a high similarity level with metal tolerance proteins from other Brassica plants, indicating that this protein family is highly conserved in Brassica. BjCET1 expression significantly increased at very early stages during both cadmium and zinc treatments. Green fluorescence detection in transgenic tobacco leaves revealed that BjCET1 is a plasma membrane-localized protein. The heterologous expression of BjCET1 in a yeast mutant increased the heavy-metal tolerance and decreased the cadmium or zinc accumulations in yeast cells, suggesting that BjCET1 is a metal ion transporter. The constitutive expression of BjCET1 rescued the heavy-metal tolerance capability of transgenic tobacco plants.

Conclusions
The data suggest that BjCET1 is a membrane-localized efflux transporter that plays essential roles in heavy metal ion homeostasis and hyper-accumulation.
Adaptive design for identifying maximum tolerated dose early to accelerate dose-finding trial
Authors: Kojima Masahiro 
Published: April 2022

Abstract
Purpose
The early identification of maximum tolerated dose (MTD) in phase I trial leads to faster progression to a phase II trial or an expansion cohort to confirm efficacy.

Methods
We propose a novel adaptive design for identifying MTD early to accelerate dose-finding trials. The early identification of MTD is determined adaptively by dose-retainment probability using a trial data via Bayesian analysis. We applied the early identification design to an actual trial. A simulation study evaluates the performance of the early identification design.

Results
In the actual study, we confirmed the MTD could be early identified and the study period was shortened. In the simulation study, the percentage of the correct MTD selection in the early identification Keyboard and early identification Bayesian optimal interval (BOIN) designs was almost same from the non-early identification version. The early identification Keyboard and BOIN designs reduced the study duration by about 50% from the model-assisted designs. In addition, the early identification Keyboard and BOIN designs reduced the study duration by about 20% from time-to-event model-assisted designs.

Conclusion
We proposed the early identification of MTD maintaining the accuracy to be able to short the study period.
Perioperative changes in cell-free DNA for patients undergoing surgery for colon cancer
Authors: Rosen Andreas W. , Gögenur Mikail , Paulsen Isabella W. , Olsen Jesper , Eiholm Susanne , Kirkeby Lene T. , Pedersen Ole B. , Pallisgaard Niels , Gögenur Ismail 
Published: April 2022

AbstractBackgroundVarious conditions with cellular decay are associated with elevated cell-free DNA (cfDNA). This study aimed to investigate if perioperatively measured cfDNA levels were associated with the surgical approach, complications, or recurrence.MethodsPlasma was obtained from patients who underwent surgery for colon cancer at admission and at the time of discharge. Quantitative measurement of cfDNA was performed by amplifying two amplicons of 102 base pairs (bp) and 132 bp ofBeta-2-Microglobulin(B2M) andPeptidyl-Prolyl cis–trans Isomerase A(PPIA), respectively.ResultscfDNA was measured in 48 patients who underwent surgery for colonic cancer. Sixteen patients had recurrence during the follow-up period, fifteen developed a postoperative complication, and seventeen patients developed neither, acting as the control group. Postoperative cfDNA levels were significantly elevated from baseline samples, across all groups, with a median preoperativelyB2Mlevel of 48.3 alleles per mL and postoperatively of 220 alleles per mL and a median preoperatively levelPPIAof 26.9 alleles per mL and postoperatively of 111.6 alleles per mL (p < 0.001 forB2Mandp < 0.001 forPPIA). Postoperative levels of PPIA, but not B2M, were significantly higher in patients experiencing complications than in the control group (p = 0.036). However, a tendency towards an association between the surgical approach and the changes in cfDNA levels was found for PPIA (p = 0.058), and B2M (p = 0.087).ConclusionsPlasma cfDNA was increased after surgery in all patients with colon cancer. Postoperative PPIA levels were significantly higher in patients experiencing surgical complications but not in B2M levels.
Infectious diseases prevention and control using an integrated health big data system in China
Authors: Zhou Xudong , Lee Edmund Wei Jian , Wang Xiaomin , Lin Leesa , Xuan Ziming , Wu Dan , Lin Hongbo , Shen Peng 
Published: April 2022

Abstract
Background
The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children.

Methods
IHBDP is composed of medical data from clinics, electronic health records, residents’ annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods.

Results
IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones.

Conclusions
Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods.
Influences of gestational diabetes mellitus on the oral microbiota in offspring from birth to 1 month old
Authors: Song Qiying , Xiao Bin , Huang Hongli , Ma Liya , Zhang Jian V. , Zhu Yuanfang 
Published: April 2022

Abstract
Background
Maternal gestational diabetes mellitus (GDM) had long-term influences on the health of their children. However, the influences of GDM on the oral microbiota, which was closely related to oral and systemic health in offspring, were less documented. The present study aimed to explore the oral microbiota of neonates born to mothers with GDM is differentially colonized compared with those born to mothers without GDM, and whether any such differences persist to 1 month of age.

Methods
Oral samples were collected from children of mothers with (n = 20) and without GDM (n = 34) at birth and again at an average age of 1 month. The oral microbiota was characterized by 16S rRNA sequencing (V3-V4). Differences in diversity and composition according to maternal GDM status were assessed, and different metabolic functional pathways and microbial ecological networks were also analyzed.

Results
Although no significant differences were observed in diversity metrics between GDM and non-GDM groups (P > 0.05), we found significant differences in the taxonomic composition of oral microbiota from phylum to genus level between the two groups, with the GDM group exhibiting less abundance of Veillonella in both “Day 1” (P < 0.001) and “Day 30” (P < 0.05) phases. Metabolic pathways analysis showed that 5-aminoimidazole ribonucleotide biosynthesis and inosine-5'-phosphate biosynthesis were enriched in GDM subjects in the “Day 30” phase. Moreover, ecological network analysis revealed apparent differences between GDM and control groups, with the non-GDM group containing more high-degree nodes and microbial interactions compared with the GDM group.

Conclusion
Maternal GDM was associated with an altered oral microbial composition in neonates, although the distinct difference between GDM and non-GDM groups diminished in infancy. The oral microbiota functions and ecological networks differed dramatically between the two groups, highlighting the importance of maternal GDM status on initial oral microbiota in offspring.
HOXA-AS2 enhances GBM cell malignancy by suppressing miR-2116-3p thereby upregulating SERPINA3
Authors: Sun Jianrui , Wang Lin 
Published: April 2022

Abstract
Background
Glioblastoma (GBM) is malignant, demanding more attention to the improvement of the diagnosis and therapy. LncRNAs have been implicated in the malignancy of GBM cells.

Methods
HOXA-AS2, miR-2116-3p and SERPINA3 expression levels in GBM tissues and cell lines were detected by qRT-PCR. Western blotting was performed to detect the protein levels of Bax and Bcl-2. Dual-luciferase reporter assay was for detection of relationship among these factors, together with RIP and RNA pull-down. CCK-8, EdU, wound healing and transwell assays were for detection of the role of HOXA-AS2, miR-2116-3p and SERPINA3 in cell viability, proliferation, migration and invasion in GBM, respectively.

Results
HOXA-AS2 and SERPINA3 showed higher level in GBM tissues and cell lines. Low level of HOXA-AS2 attenuated GBM cell growth in vitro. Moreover, the anti-tumor impact of silenced HOXA-AS2 was restored by miR-2116-3p inhibitor, but its tumor-promotional effect could be reversed by silenced SERPINA3.

Conclusion
HOXA-AS2 enhanced GBM cell malignancy through sponging miR-2116-3p and releasing SERPINA3, which might shed light on the diagnosis and therapy for GBM in the future.
Addressing the COVID-19 pandemic challenges for operational adaptations of a cluster randomized controlled trial on dengue vector control in Malaysia
Authors: Saadatian-Elahi Mitra , Alexander Neal , Möhlmann Tim , Ariffin Farah Diana , Schmitt Frederic , Richardson Jason H. , Rabilloud Muriel , Hamid Nurulhusna Ab 
Published: April 2022

Abstract
Introduction
The COVID-19 pandemic placed an unprecedented overload on healthcare system globally. With all medical resources being dedicated to contain the spread of the disease, the pandemic may have impacted the burden of other infectious diseases such as dengue, particularly in countries endemic for dengue fever. Indeed, the co‐occurrence of COVID‐19 made dengue diagnosis challenging because of some shared clinical manifestations between the two pathogens. Furthermore, the sudden emergence and novelty of this global public health crisis has forced the suspension or slow-down of several research trials due to the lack of sufficient knowledge on how to handle the continuity of research trials during the pandemic. We report on challenges we have faced during the COVID-19 pandemic and measures that were implemented to continue the iDEM project (intervention for Dengue Epidemiology in Malaysia).

Methods
This randomized controlled trial aims to assess the effectiveness of Integrated Vector Management (IVM) on the incidence of dengue in urban Malaysia by combining: targeted outdoor residual spraying (TORS), deployment of auto-dissemination devices (ADDs), and active community engagement (CE). Our operational activities started on February 10, 2020, a few weeks before the implementation of non-pharmaceutical interventions to contain the spread of COVID-19 in Malaysia.

Results
The three main issues affecting the continuity of the trial were: ensuring the safety of field workers during the interventions; ensuring the planned turnover of TORS application and ADD deployment and services; and maintaining the CE activities as far as possible.

Conclusions
Even though the pandemic has created monumental challenges, we ensured the safety of field workers by providing complete personal protective equipment and regular COVID-19 testing. Albeit with delay, we maintained the planned interval time between TORS application and ADDs services by overlapping the intervention cycles instead of having them in a sequential scheme. CE activities continued remotely through several channels (e.g., phone calls and text messages). Sustained efforts of the management team, significant involvement of the Malaysian Ministry of Health and a quick and smart adaptation of the trial organisation according to the pandemic situation were the main factors that allowed the successful continuation of our research.

Trial registration
Trial registration number: ISRCTN-81915073. Date of registration: 17/04/2020, 'Retrospectively registered'.
Prediction of metabolic and pre-metabolic syndromes using machine learning models with anthropometric, lifestyle, and biochemical factors from a middle-aged population in Korea
Authors: Kim Junho , Mun Sujeong , Lee Siwoo , Jeong Kyoungsik , Baek Younghwa 
Published: April 2022

Abstract
Background
Metabolic syndrome (MetS) is a complex condition that appears as a cluster of metabolic abnormalities, and is closely associated with the prevalence of various diseases. Early prediction of the risk of MetS in the middle-aged population provides greater benefits for cardiovascular disease-related health outcomes. This study aimed to apply the latest machine learning techniques to find the optimal MetS prediction model for the middle-aged Korean population.

Methods
We retrieved 20 data types from the Korean Medicine Daejeon Citizen Cohort, a cohort study on a community-based population of adults aged 30–55 years. The data included sex, age, anthropometric data, lifestyle-related data, and blood indicators of 1991 individuals. Participants satisfying two (pre-MetS) or ≥ 3 (MetS) of the five NECP-ATP III criteria were included in the MetS group. MetS prediction used nine machine learning models based on the following algorithms: Decision tree, Gaussian Naïve Bayes, K-nearest neighbor, eXtreme gradient boosting (XGBoost), random forest, logistic regression, support vector machine, multi-layer perceptron, and 1D convolutional neural network. All analyses were performed by sequentially inputting the features in three steps according to their characteristics. The models’ performances were compared after applying the synthetic minority oversampling technique (SMOTE) to resolve data imbalance.

Results
MetS was detected in 33.85% of the subjects. Among the MetS prediction models, the tree-based random forest and XGBoost models showed the best performance, which improved with the number of features used. As a measure of the models’ performance, the area under the receiver operating characteristic curve (AUC) increased by up to 0.091 when the SMOTE was applied, with XGBoost showing the highest AUC of 0.851. Body mass index and waist-to-hip ratio were identified as the most important features in the MetS prediction models for this population.

Conclusions
Tree-based machine learning models were useful in identifying MetS with high accuracy in middle-aged Koreans. Early diagnosis of MetS is important and requires a multidimensional approach that includes self-administered questionnaire, anthropometric, and biochemical measurements.
Malignant epithelioid neoplasm of the ileum with ACTB-GLI1 fusion mimicking an adnexal mass
Authors: Ambrosio Marco , Virgilio Agnese , Raffone Antonio , Arena Alessandro , Raimondo Diego , Alletto Andrea , Seracchioli Renato , Casadio Paolo 
Published: April 2022

Abstract
Background
Malignant epithelioid neoplasm with ACTB-GLI1 fusion are considered different from the more common pericytic lesions, such myopericytoma, because they have a spectrum of different genetic abnormalities. They appear to pursue a benign clinical course in young adults, although in sporadic cases lymph node metastasis were described.
The categorization of this new type of tumor may also lead to new therapeutic strategies, because they might be sensitive to SHH pathway inhibitors.

Case presentation
The case involves a 72-years-old multiparous woman who accessed our department after an incidental finding of a right adnexal mass of 43 mm with contrast-enhancement on a control computed tomography scan made for suspected diverticulitis. Our intervention was a detailed ultrasound description of the suspected neoplasm;
a diagnostic laparoscopy and the contextual laparotomic removal of abdominal mass; its histological and immunohistochemical analysis. Our main outcome measure is the definition and future recognition of new pathologic entity called malignant epithelioid neoplasm with ACTB-GLI1 fusion.

Conclusions
We described for the first time the ultrasound characteristic of this type of lesion using standardized terminology and we believe that it may be the first step to improve the acknowledgement of this novel pathologic entity defined as malignant epithelioid neoplasm with GLI-1 fusions.
Hinokiflavone induces apoptosis, cell cycle arrest and autophagy in chronic myeloid leukemia cells through MAPK/NF-κB signaling pathway
Authors: Qin Xiang , Chen Xi , Guo Ling , Liu Jing , Yang You , Zeng Yan , Li Cheng , Liu Wenjun , Ma Wenzhe 
Published: April 2022

Abstract
Background
Chronic myeloid leukemia (CML) is a myeloproliferative tumor originating from hematopoietic stem cells, and resistance to tyrosine kinase inhibitors (TKI) has become a major cause of treatment failure. Alternative drug therapy is one of the important ways to overcome TKI resistance. Hinokiflavone (HF) is a C-O-C type biflavonoid with low toxicity and antitumor activity. This study investigated the antitumor effect and possible mechanisms of HF in CML cells.

Methods
Cell viability was measured by CCK-8 assay. Cell apoptosis and cell cycle distribution were analyzed by flow cytometry. Western blotting was used to assess protein expression levels.

Results
Our results showed that HF significantly inhibited the viability of K562 cells in a concentration- and time-dependent manner and induced G2/M phase arrest by up-regulating p21 and down-regulating Cdc2 protein. Furthermore, HF induced caspase-dependent apoptosis by activating JNK/p38 MAPK signaling pathway and inhibiting NF-κB activity. In addition, HF induced autophagy by increasing LC3-II expression and p62 degradation. Pretreatment with CQ, a late autophagy inhibitor, significantly increased the levels of LC3-II and p62 proteins and promoted cell survival.

Conclusion
HF shows a good anti-leukemia effect and is expected to become a potential therapeutic drug for CML.
Developing a random forest algorithm to identify patent foramen ovale and atrial septal defects in Ontario administrative databases
Authors: Oliva Laura , Horlick Eric , Wang Bo , Huszti Ella , Hall Ruth , Abrahamyan Lusine 
Published: April 2022

Abstract
Purpose
Routinely collected administrative data is widely used for population-based research. However, although clinically very different, atrial septal defects (ASD) and patent foramen ovale (PFO) share a single diagnostic code (ICD-9: 745.5, ICD-10: Q21.1). Using machine-learning based approaches, we developed and validated an algorithm to differentiate between PFO and ASD patient populations within healthcare administrative data.

Methods
Using data housed at ICES, we identified patients who underwent transcatheter closure in Ontario between October 2002 and December 2017 using a Canadian Classification of Interventions code (1HN80GPFL, N = 4680). A novel random forest model was developed using demographic and clinical information to differentiate those who underwent transcatheter closure for PFO or ASD. Those patients who had undergone transcatheter closure and had records in the CorHealth Ontario cardiac procedure registry (N = 1482) were used as the reference standard. Several algorithms were tested and evaluated for accuracy, sensitivity, and specificity. Variable importance was examined via mean decrease in Gini index.

Results
We tested 7 models in total. The final model included 24 variables, including demographic, comorbidity, and procedural information. After hyperparameter tuning, the final model achieved 0.76 accuracy, 0.76 sensitivity, and 0.75 specificity. Patient age group had the greatest influence on node impurity, and thus ranked highest in variable importance.

Conclusions
Our random forest classification method achieved reasonable accuracy in identifying PFO and ASD closure in administrative data. The algorithm can now be applied to evaluate long term PFO and ASD closure outcomes in Ontario, pending future external validation studies to further test the algorithm.