Physiological oxygen tension rises dramatically in the placenta between 8 and 14 weeks of gestation. Abnormalities in this period can lead to gestational diseases, whose underlying mechanisms remain unclear. We explored the changes at mRNA level by comparing the transcriptomes of human placentas at 8–10 gestational weeks and 12–14 gestational weeks. A total of 20 samples were collected and divided equally into four groups based on sex and age. Cytotrophoblasts were isolated and sequenced using RNAseq. Key genes were identified using two different methods: DESeq2 and weighted gene co-expression network analysis (WGCNA). We also constructed a local database of known targets of hypoxia-inducible factor (HIF) subunits, alpha and beta, to investigate expression patterns likely linked with changes in oxygen. Patterns of gene enrichment in and among the four groups were analyzed based on annotations of gene ontology (GO) and KEGG pathways. We characterized the similarities and differences between the enrichment patterns revealed by the two methods and the two conditions (age and sex), as well as those associated with HIF targets. Our results provide a broad perspective of the processes that are active in cytotrophoblasts during the rise in physiological oxygen, which should benefit efforts to discover possible drug-targeted genes or pathways in the human placenta. Normal development of the placenta can be divided into three trimesters, of which the first lays the foundation for all subsequent processes. Indeed, at the very beginning of the first trimester, it is the yolk sac that first establishes the supply of oxygen and nutrients to the embryo, and this role is gradually taken over by the growing placenta. From day 13 post-coitum, the placental villus begins to form and branch, and is subsequently infiltrated by allantoic blood vessels ,3. The eeks (GW) . Defectseks (GW) ,6.2 tension in the intervillous space [The oxygen tension in the intervillous space rises dramatically from 2 to 3% around 8–10 GW to more than 6% after 12 weeks . Oxygen,us space ,10.2), as an ever-present challenge throughout the duration of pregnancy, functions as a two-edged sword for the development of the placenta. While suitable levels of hypoxia/low O2 tension induce the remodeling of maternal spiral arteries, extreme hypoxia disables the remodeling and can result in adverse conditions such as preeclampsia [Oxygen is consumed in the mitochondria, and recent research has uncovered sexually dimorphic aspects of this process, particularly in cases of placental mitochondrial dysfunction ,12. For clampsia ,6 and inclampsia . Taken t2 tension: hypoxia inducible factors (HIFs), unfolded protein response (UPR), and mammalian target of rapamycin (mTOR). Their activation regulates gene expression, metabolic homeostasis, and cell survival [There are three conventional oxygen-sensitive pathways that regulate gene expression in the placenta under low Osurvival . Of thessurvival . HIF-α asurvival ,19. Intesurvival , whereassurvival . HoweverHere, we applied next-generation sequencing technology to sequence human villous cytotrophoblasts freshly isolated from placentas at either 8–10 GW or 12–14 GW with the goal of assessing changes in gene expression and the influence of placental sex differences in this key physiological period.https://www.ncbi.nlm.nih.gov/geo/) under the accession number GSE163023 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163023). The quality report generated by FastQC indicated that the raw data were appropriate for further use: the majority of plots were well above phred score 30 (green region), the average quality was in single peak, a well-overlapped single hump was shown in the center, and the data remained consistent before and after normalization  versus Late Male (LM), 41 key genes for Early Female (EF) versus Early Male (EM), 157 key genes for EF versus LF, and 801 key genes for EM versus LM. The expression patterns were then used to construct heatmaps , the “blue” and “dark turquoise” modules were retained for their association with age  and compared the patterns of enrichment in GO biological processes and KEGG pathways. The Venn diagram in For GO biological processes, both methods revealed a relationship between sex and enrichment in “dosage compensation by inactivation of X chromosome” and “purine nucleotide catabolic process”. Instead, the WGCNA_Sex dataset highlighted enrichment in regulatory processes such as “histone lysine demethylation”, “demethylation”, and “histone demethylation”, and the DESeq2_Sex dataset was mainly characterized by metabolic processes such as “nucleotide catabolic process”, “nucleotide phosphate catabolic process”, and “ribonucleotide catabolic process” b. With rFor KEGG pathways, there was no overlap between the WGCNA and DESeq2 datasets for sex-related genes. The analysis of enrichment in the WGCNA_Sex dataset revealed the importance of metabolic processes such as “glycine, serine, and threonine metabolism” and “cysteine and methionine metabolism”, while the DESeq2_Sex dataset was characterized by biological processes such as “staphylococcus aureus infection” and the “estrogen signaling pathway” c. With r2 levels, we specifically investigated the involvement of HIF in the biological processes in these cells. HIF transcriptional activity depends on its alpha and beta subunits; we therefore assembled a database of all published or predicted targets of HIF-1α or HIF-1β from the literature and public databases  and log2 enrichment ratio higher than 2. Of all the GO terms and KEGG pathways that were linked with HIF targets, the only ones that met these criteria were two GO terms associated with HIF-1β: “regulation of signal transduction by p53 class mediator” and “TOR signaling” . We then2 tension within the intervillous space before 10 GW limits the oxidative stress of the chorionic villi, which at this point do not express enzymes that protect from reactive oxygen species (ROS). From 10 to 12 GW, the trophoblastic plugs disintegrate, allowing oxygenated maternal blood into the intervillous space and dramatically raising the oxygen tension. Proper blood flow is thus shaped by oxygen conditions in early placentation, especially in the period from 8–12 GW when oxygen levels increase dramatically [The human placenta functions as a biological barrier, between the mother and the fetus, that facilitates the exchange of gases, nutrients, and wastes. Throughout pregnancy, perfusion of the chorionic villi by blood from the uterine spiral arteries is essential for placental development and, therefore, for the exchanges between maternal and fetal blood. Physiological obturation of the uterine spiral arteries by extravillous trophoblasts plugs in the early first trimester is critical for the growth of chorionic villi and development of feto-placental vasculatures. Moreover, the low physiological Oatically . Oxygen atically ,22. Abnoatically ,6. In ouhttps://www.ncbi.nlm.nih.gov/gds/) with the key words “human AND placenta” returned a total of 320 accessions that contained microarray or RNAseq data from Homo sapiens. Of these, however, only a few had performed tissue-specific sequencing or shared even superficial similarities with our study [Although several sequencing datasets have been published for cytotrophoblasts in this period, they have all been focused on different hypotheses. Our data provide what is to our knowledge the first overview of the changes in gene expression that accompany the dramatic increase in oxygen levels from 8 to 14 GW. A search of publicly available GEO DataSets . That is, the difference between sexes was partly obscured in the age-mixed set of samples, which indicated that, in the first trimester of pregnancy, gestational age exerted a stronger influence on the development of the placenta than sexual dimorphism did. This was similar to a report that age appeared to be more dominant than sex in affecting early fetal lung developments from 54–127 days post-conception . When weIn the placenta, oxygen-sensitive pathways are regulated by the actions of HIF on downstream genes. We thus specifically examined the key genes highlighted by our analyses to identify potential HIF targets. Of the 248 key genes linked with sex-based differences identified by DESeq2 and WGCNA, there were only three HIF targets in the intersections: FA complementation group C (FANCC), asparaginyl-tRNA synthetase 2 (NARS2), and RAB38; the latter two genes are known to be active in mitochondria, which could explain their potential correlations with oxygen metabolism. Overall, though, the small number of sexually dimorphic HIF targets could suggest that there is little difference in hypoxia-related biological processes between early male and female placentation. We thus excluded the sex-related genes from our enrichment analyses and focused only on HIF targets that demonstrated age-related expression changes. For the targets of HIF-1α, enrichment analyses highlighted GO terms that were predominantly associated with metabolic processes, and to a lesser extent with biological regulation, while targets of HIF-1β demonstrated the opposite pattern. This could indicate the existence of complementary roles for HIF-1α and HIF-1β under hypoxic conditions . With reNevertheless, this study does present some shortcomings that should be addressed in the future. Firstly, we focused on patterns of sexual differentiation only in villous cytotrophoblasts from first-trimester placentas, while previous research has revealed such patterns in different cell types, such as trophoblast epithelium and villous vessel endothelium from term placenta . SecondlA total of 20 human placentas were collected from normal gravidas in the first trimester. To characterize the processes that accompany the increase in physiological oxygen tension from 8 to 14 GW, we investigated the early and late stages of this period, 8–10 GW and 12–14 GW, respectively. Equal numbers of female and male placentas were collected for each stage. We used the letter “E” to represent “Early”, “L” for “Late”, “F” for “Female”, and “M” for “Male”. The final sample pool contained 5 “EF” samples, 5 “EM” samples, 5 “LF” samples, and 5 “LM” samples. All placental tissues were obtained from patients who voluntarily and legally chose to terminate pregnancy during the first trimester at the Cochin Port-Royal . These biological samples were obtained following informed written consent from patients and approval from our local ethics committee .2+-, Mg2+-free Hanks’ balanced salt solution. The pieces were then digested in Hanks’ balanced salt solution with 4.2 mM MgSO4, 0.25% (wt/vol) trypsin powder , 5 IU of DNase I per mL, 25 mM HEPES, 100 IU/mL penicillin, and 100 μg/mL streptomycin . Digestion was monitored by invert microscopy; the initial digested solution, which mainly consisted of red blood cells, was discarded and the subsequent digested solution, which mainly consisted of villous cytotrophoblasts, was retained for stratification. The digested solution was slowly transferred to a discontinuous Percoll gradient (5–70% in steps of 5%) in order to stratify the mixed cells and debris. The layer containing the cytotrophoblasts was retained and washed using Dulbecco’s modified Eagle’s medium (F12/DMEM), which contained 100 IU/mL penicillin, 100 mg/mL streptomycin, and 2 mM glutamine. Cells were counted using a TC20™ Automated Cell Counter . For RNASeq experiments, 1.5 × 106 cells were transferred into a 1.5 mL Eppendorf tube. After centrifugation , the supernatants were discarded and the cell pellets were snap-frozen in liquid nitrogen and stored at −80 °C until total RNA extraction, PCR, and RNAseq analyses were conducted.The first step was to isolate villous cytotrophoblasts from each sample. To do this, we purified the villous tissues by mincing them into pieces with forceps, removing the membrane on the surface, and rinsing them with CaZFX  and ZFY . The primers were ChrX-Y_F 5′-ATTTGTTCTAAGTCGCCATATTCTCT-3′, ChrX_R 5′-GAACACACTACT-GAGCAAAATGTATA-3′, and ChrY_R 5′-CATCTTTACAAGCTTGTAGACACACT-3′. Reagents for PCR reactions included gDNA (100–300 ng) 10 µL 5×green GoTaq reaction buffer, 2 µL 10 mM dNTPs, 2.5 µL 10 µM ChrX-Y_F, 2.5 µL 10 µM ChrX_R, 2.5 µL 10 µM ChrY_R, 0.2 µL (5 u/µL) GoTaq DNA polymerase , and water to reach a total volume of 50 µL. Amplification was conducted in a Perkin Elmer Applied Biosystems GeneAmp PCR Thermal Cycler System 2700, with the following cycling parameters: initial denaturation at 94 °C for 10 min, 35 cycles of denaturation at 94 °C for 45 s, annealing at 50 °C for 45 s, and synthesis at 72 °C for 30 s, and an extension of 5 min at the end of the final cycle. Amplification products (10 µL) were directly analyzed on 2% agarose gel and evaluated under UV light. Primers ChrX-Y_F/ChrY_R were present only in male samples and primers ChrX-Y_F/ChrX_R were present in all tested samples. For validation, we also analyzed the expression of the sex-linked genes XIST and DDX3Y in the RNAseq dataset, following the procedures described in [Fetal-sex determination was performed via PCR on stored cytotrophoblast cells, as described previously . GenomicRNAseq analyses were performed as described in . The RNep-value less than 0.05. For WGCNA, normalized RNAseq reads from all samples were submitted directly to the WGCNA package (version: 1.68) [To detect outliers, sample clustering was performed based on Euclidean distance, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). To identify differentially abundant genes, DESeq2 and WGCNA were applied separately and the results were then merged for a combined analysis. For DESeq2, gene expression was compared between the different groups, and the criteria for defining key genes were a fold-change of 2 and a n: 1.68)  in R . For each module, we created scatterplots of the modules’ eigengenes in which the x-coordinate represented module membership (the correlation coefficient between a gene’s expression profile and the module eigengene) and the y-coordinate represented gene significance . Only correlation coefficients higher than 0.6, with a http://bioinformatics.psb.ugent.be/webtools/Venn/). Enrichment in gene ontology (GO) terms and pathways was analyzed using the R package clusterProfiler [p-value lower than 0.05 were identified as being significantly enriched. WebGestalt was used to visualize the terms in volcano format and perform the network topology analysis [tftargets (https://github.com/slowkow/tftargets). These were then assembled into a local database of HIF targets.Venn diagrams were created to depict the intersections between different datasets using the online tool Draw Venn diagram (Profiler  (versionanalysis . FinallyIn conclusion, our results provide a broad perspective of the biological processes that are active in trophoblasts during the surge in physiological oxygen availability, specifically with regard to differences over time and between the sexes, which should open new avenues for future research and contribute to the discovery of possible drug-targeted genes or pathways in the human placenta.


Reading comprehension entails a set of distinct, yet interdependent cognitive, linguistic, and nonlinguistic processes. Previous second language (L2) Chinese studies have identified significant and positive impacts of grapho-morphological knowledge at the character and subcharacter  levels on passage reading comprehension; however, little is known regarding how early L2 grapho-morphological knowledge at the character and radical levels jointly predict later L2 reading comprehension. This study aimed to fill this gap. One hundred and five beginning-level L2 Chinese collegiate learners were recruited, and completed two character-related and two radical-related tasks in Week 8, as well as one reading comprehension tasks in Week 18. The main findings, based on correlational and path analyses, suggested that L2 Chinese learners’ early character-level and radical-level grapho-morphological knowledge significantly predicted later reading comprehension, yet the interrelations among grapho-morphological knowledge at the character and radical levels were complex. Path analyses identified direct and indirect paths from early character-level grapho-morphological knowledge to later reading comprehension, as well as indirect paths from early radical-level grapho-morphological knowledge to later reading comprehension. Methodological and pedagogical implications for L2 Chinese reading research and practices are discussed. Following According to the componential view of reading, reading comprehension entails a set of distinct, yet interdependent cognitive, linguistic, and nonlinguistic skills from the lower levels to higher levels , among wearly in this study) predict literacy development among native Chinese-speaking children  speakers e.g., , L1 non-en e.g., . Compareen e.g., . Howeveruage cf. , p.32.This study aimed to uncover how early character- and radical-level grapho-morphological knowledge jointly predicts reading comprehension in L2 Chinese in beginning-level collegiate learners. It is expected that it will provide theoretical, methodological, and pedagogical implications for L2 reading research and practices.radical in this study) offers information on the semantic category and a phonetic component provides a clue to the pronunciation. Compound characters sharing an identical semantic radical represent a similar semantic category. For example, the characters 湖 , 河 , and 池  have the same radical 氵 (water): thus, the meanings of these characters all relate to the meaning of 水 . Chinese pronunciation was transcribed into IPA following Unlike the writing systems of languages with alphabetic scripts , Chinese has a unique multilevel writing system based on characters . SpecifiIt has been generally accepted that grapho-morphological knowledge plays an important role in reading comprehension for native Chinese speakers e.g., . For exaRegarding the contribution of character-level grapho-morphological knowledge to L2 Chinese reading comprehension, a few empirical studies have recently investigated the mediated relationships among grapho-morphological awareness, vocabulary knowledge, and reading comprehension in L2 Chinese e.g., . For exaAlthough substantial research has supported that grapho-morphological knowledge at the radical level facilitated single-character and multicharacter word reading e.g., , few L2 Although a few studies have discussed the relations between early grapho-morphological knowledge and later reading comprehension in an alphabetic language  as L1 or L2 e.g., , evidencViewed collectively, grapho-morphological knowledge plays an important role in reading Chinese, which adopts a morphosyllabary writing system. Although a few empirical cross-sectional studies have provided evidence supporting the positive effects of grapho-morphological knowledge in L2 Chinese reading comprehension, there is still a need for a comprehensive investigation that measures grapho-morphological knowledge at character and radical levels and examines how character- and radical level grapho-morphological knowledge contributes to later L2 Chinese reading comprehension from a longitudinal perspective.This study focused on the relationship among early grapho-morphological knowledge at the character level  and at the radical level , as well as later reading comprehension for beginning-level L2 Chinese collegiate learners.What are the direct and indirect contributions of early character-level grapho-morphological knowledge and early radical-level grapho-morphological knowledge to later reading comprehension in L2 Chinese?Grounded in existing literature of reading research e.g., , it was Chinese in 10 Days . Their ages ranged from 18 to 20 years old, and they came from 40 countries. All of the participants self-reported their L1 or official language to be a language with an alphabetic script, like English, Spanish, Russian, and French. All participants were enrolled in the Beginning-I Chinese program, in which the participants received intensive Chinese instructions (20 h per week) and used the textbook  10 Days . They weThe study’s measures were all based on paper-pencil tasks, including character recognition, character manipulation, radical identification, radical analysis, and reading comprehension. The task scores were used to represent the participants’ corresponding L2 Chinese reading abilities. It is predicted that a participant with a stronger ability should perform better and receive a higher score on the corresponding task.This task was adapted from This task measured the participants’ ability to identify semantic radicals within a compound character and analyze whether the semantic radical is related to the character’s meaning. Twenty commonly used radicals were selected from the participants’ textbooks based on their radical familiarity, including “阝, 火, 冫, 饣, 穴, 辶, 雨, 彳, 贝, 廴, 犭, 钅, 忄, 灬, 刂, 广, 目, 竹, 囗, 纟.” The mean of radical familiarity was 3.20 out of 4, which was based on statistics from This task measured the learners’ ability to recognize familiar characters from graphic forms. The task was adapted from The format of this task was adopted from In summary, radical identification exclusively needs learners’ orthographic ability, whereas, radical analysis requires both orthographic and graphomorphemic ability.你记得儿子带伞  The answer in this case was 提醒 . There were 10 items in this part. In Part 2, the participants were asked to reorganize three clauses in each item and to create a new sentence. For example, Option A was “茶不仅仅是一种饮料 (Tea is not only a drink)”; Option B was “它在中国有着几千年的历史 ”; and Option C was “而且还是一种文化 [but also (it) is a kind of culture].” The expected answer in this example was “A, C, and B.” There were also 10 items. In Part 3, the participants were asked to read several short passages ranging from 30 to 150 characters, and after each passage they were asked to select correct answers regarding the passage’s main idea and/or detailed information from four options. There were 20 questions in Part 3. Each correct selection for the items in Part 1 and 2 was calculated as 2 points, and each correct selection for the items in Part 3 as 3 points in terms of the rubrics of HSK (This task was adopted from the reading section in the Chinese Proficiency Test (HSK)-level 4 and mainly measured learners’ general reading ability, including knowledge of vocabulary and grammar, as well as passage understanding and inference. This task included three parts: sentence reading by inserting appropriate words, sentence organizing by ordering clauses, and short-passage reading comprehension. In Part 1, the participants were asked to select an appropriate word from a vocabulary pool to insert a sentence with a blank, for example, 明天可能下雨 s of HSK . The totIn this study, all of the participants completed two character-level and two radical-level grapho-morphological knowledge tasks in Week 8 and one reading comprehension task in Week 18 during the first semester of the year . The participants received a background questionnaire online, which was developed by the Office of International Students at the university when they registered for classes at the beginning of the semester. The participants completed all the paper-pencil tasks in their classrooms. Upon completion of the testing, all participants were given souvenirs for their time.https://osf.io/avner/files/). To answer the research question posed earlier, descriptive statistics, correlational and path analyses results are presented below. The descriptive data for all the tasks are presented in A total of 103 participants were included in the statistical analysis because two participants missed at least one task . In the conceptual model 2, the chi-square goodness-of-fit test did not support the convergence between the conceptual model 2 and the observed model. The result does not indicate a good model fit, χ2  = 3.69, p = 0.055 . While in the conceptual model 3, the chi-square goodness-of-fit test confirmed the consistency between our hypothesized model and the observed model. The result indicates a good model fit, χ2  = 4.19, p = 0.12 . Taken together, we used the conceptual model 3 as the hypothesized model in this study. Then, path analyses were run to investigate the direct and indirect effects of grapho-morphological knowledge at the character and radical levels on later reading comprehension , character recognition (p = 0.10) and character manipulation (p = 0.09), and radical analysis ability significantly and directly contributed to character recognition (p < 0.001) and character manipulation (p < 0.001). (b) Character recognition ability directly had significant impacts on character manipulation ability and reading comprehension in Week 18 ; character manipulation ability significantly predicted reading comprehension in Week 18 (p < 0.05).To answer the research question, early grapho-morphological knowledge at both levels significantly affected later reading comprehension in L2 Chinese; character-level grapho-morphological knowledge made both direct and indirect contributions to later reading comprehension in L2 Chinese while radical-level grapho-morphological knowledge made indirect contributions.This study examined the relations between early grapho-morphological knowledge and later reading comprehension in beginning-level collegiate L2 Chinese learners, and measured grapho-morphological knowledge at both character and radical levels. First, the findings indicated that grapho-morphological knowledge at the character and radical levels in Chinese, particularly for beginning-level L2 learners, are both significant predictors of reading comprehension across time. Previous L1 Chinese studies have shown that grapho-morphological knowledge (at the character level) were unique and significant predictors of reading comprehension in Chinese e.g., , and theSecond, early radical-level grapho-morphological knowledge indirectly predict later reading comprehension via their relatively higher-level grapho-morphological knowledge (at the character level). Admittedly, radical-level grapho-morphological knowledge is about learners’ orthographic knowledge of characters, radicals’ semantic representations, and their understanding of how to compose radicals and simple characters in a systematic writing rule; and a better understanding of character-internal structures and their semantic categories might not give L2 learners advantages when determining the meaning of a phrase, sentence or short passage. However, this better understanding helps L2 learners, particularly at the early stage of learning L2 characters, more easily read, analyze, and memorize characters and multicharacter words . TherefoConsistent with the previous studies e.g., , the finFinally, this study has found that early character-level grapho-morphological knowledge directly and indirectly predicts later reading comprehension. The general findings were consistent with previous studies for native Chinese speakers e.g., , though In summary, this study investigated the relations among grapho-morphological knowledge at the character and subcharacter/radical levels in Week 8 and later reading comprehension in Week 18 for beginning-level collegiate L2 Chinese learners. The main findings showed that grapho-morphological knowledge both at the character and radical levels were significant predictors of later reading comprehension. Path analyses results provided the specific, direct and indirect paths among character- and radical-level grapho-morphological knowledge to later reading comprehension. Specifically, early character recognition and manipulation directly and indirectly predicted later reading comprehension; in addition, early radical identification and analysis indirectly predicted later reading comprehension through character recognition and manipulation.While this study has provided new empirical evidence, there were some limitations. First, only character recognition and manipulation at the character level were involved in this study. Other key reading abilities at the character and higher levels such as phonological awareness, and vocabulary knowledge, as well as cognitive abilities such as non-verbal reasoning, should be considered in the future. Second, the interactions of L1 effects and L2 reading subskills have not been considered. A future study would be improved if the participants’ L1 backgrounds were controlled with a larger sample size for a longer period . Participants with the same L1 could minimize the possible effects brought by different L1 backgrounds and L1-L2 linguistic distance e.g., , 2015. APedagogically, the empirical findings in this study not only reemphasize the importance of early character knowledge in reading Chinese, but also provide new evidence of the predictive roles of subcharacter/radical-level knowledge. It has been widely acknowledged that native speakers should memorize as many new characters as possible at the early stage of Chinese learning; however, no consensus has been reached regarding how to more efficiently instruct L2 learners in character learning. Given the roles of radical-related reading subskills, it is suggested that instructions and exercises related to character-internal structures and radicals’ roles should receive more attention. Identifying character-internal structures can help L2 Chinese learners who are unfamiliar with the Chinese writing system gradually understand the basic rules of how radicals compose characters. Learners who have a deeper understanding of compositional rules of characters have less memory burden when they remember new characters. Similarly, learners who know more characters and compositional rules of words more easily memorize new words, particularly for those composed of familiar characters. Learners’ Chinese reading comprehension builds on both character- and subcharacter-level reading subskills. Therefore, a combination of character-based and radical-based character learning in an L2 Chinese class may be considered, particularly at the initial stage of learning an L2. Nevertheless, emphasizing the importance of grapho-morphological knowledge at the initial period of learning Chinese does not mean that such corresponding instruction is the only important aspect in teaching and learning L2 Chinese reading. Reading development in L2 may also be expanded by recognizing various factors in learning to read, such as prior knowledge, reading strategies, extensive reading experience, and personal interest.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Carnegie Mellon University. The patients/participants provided their written informed consent to participate in this study.TC: responsible for manuscript writing, data collection, and data analysis. SK: responsible for literature review and discussion. KK: responsilbe for the framework and discussion. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


As a result of the limited resources available in IoT local devices, the large scale cloud consumer’s data that are produced by IoT related machines are contracted out to the cloud. Cloud computing is unreliable, using it can compromise user privacy, and data may be leaked. Because cloud-data and grid infrastructure are both growing exponentially, there is an urgent need to explore computational sources and cloud large-data protection. Numerous cloud service categories are assimilated into numerous fields, such as defense systems and pharmaceutical databases, to compute information space and allocation of resources. Attribute Based Encryption (ABE) is a sophisticated approach which can permit employees to specify a higher level of security for data stored in cloud storage facilities. Numerous obsolete ABE techniques are practical when applied to small data sets to generate cryptograms with restricted computational properties; their properties are used to generate the key, encrypt it, and decrypt it. To address the current concerns, a dynamic non-linear polynomial chaotic quantum hash technique on top of secure block chain model can be used for enhancing cloud data security while maintaining user privacy. In the proposed method, customer attributes are guaranteed by using a dynamic non- polynomial chaotic map function for the key initialization, encryption, and decryption. In the proposed model, both organized and unorganized massive clinical data are considered to be inputs for reliable corroboration and encoding. Compared to existing models, the real-time simulation results demonstrate that the stated standard is more precise than 90% in terms of bit change and more precise than 95% in terms of dynamic key generation, encipherment, and decipherment time. The various types of IoT applications include smart cities, smart health care, and smart transportation applications ,2. The cThe data are not stored locally because the local device has limited resources, such as insufficient memory for data storage and insufficient computation capacity for data analysis and action. This will result in the incorporation of cloud computing into the Internet of Things, with cloud computing providing services to IoT devices such as data storage and processing, as exemplified in As depicted in To address this issue securely, cloud computing and blockchain technology are combined to store and share IoT data. Blockchain technology is a distributed ledger  with numData collected from IoT devices are converted to a ciphered text, then combined with an attribute encryption mechanism ,18, whicThe smart contract provides scalability by storing access control policies in tables; users requesting to share data will interact with smart contracts via transactions.We propose a fusion of blockchain and attribute-based cryptosystems ,16 to adOver the fast evolution and growth of the cloud centralized computing and WWW centric operational strategy, there are large volumes of user’s information handling and distribution of resources over the cloud environments ,15,16,19ABE is a public key cryptosystem which performs the decipherment of a cipher-text by any person and fulfils the designed access policy based on users’ personal attributes. AB Encipherment scheme is part of the Identity Based Encipherment (IBE) base approach ,4,21,22.It is worth noticing the analysis of QKD practice in the noise-free channel as a part of base experiment level ,23,24,25The distinctive QKD approach is shown in In this article, a Novel Block Chain Non-linear Polynomial Quantum Ciphered text Policy Attribute Base Encryption model is offered which can be implemented with the help of chaotic randomized non-linear polynomial curves for massive volumes of users confidential cloud data like patient medical records, bank transactions, etc. The planned system is well structured and it can handle large cloud data volumes and also produce an optimum resolution to obtain control over the framework through the different layers as shown in This one reassures large volumes of cloud consumer confidential data which may be structured and unstructured or both.This one successfully moderates the cryptographic process and key generation time over the large volumes of personal cloud data.This one successfully works on structured, semi structured, unstructured, and hybrid patient clinical records like doc, xls,.pdf, images, decom images, x-rays, etc. and diversified image representations.The projected prototypical framework necessitates a reduced amount of computational time-band and smaller amount of network overhead to perform efficient user’s confidential data encryption, decryption, and key production as compared to traditional models. Moreover, the outmoded representations are not successful in accessing structure rules/policies revocation and policy structures dynamic updating as per necessity. The projected design successfully implements the revocation process and dynamically updates access policy structures by way of less processing overhead parallel. This model comparatively needs lower processing time for block chain based cryptographic process, chaotic dynamic key production with the help of QKD approach, and the QCPABE set of rules. The considerable objects of the proposed model are mentioned here:Chen, R. et al.  examinedThe main use of QKD is to generate a key with help of cubits which is used for the transmission of private data among sources and destination by using quantum signals without aware of what is the private key value. The QKD process is as shown in Thwarts unauthorized admittance access after unintended operators or invaders.Whole patient related information is secured by means of the biometric validation scheme.Tseng F.K. et al.  developeYang Y. et al.  offered Song X. et al.  presente0 and the extent outcome is a chaotic random position w.r.t Eigen-value λj0 (any prime number). The outcome is absolutely arbitrary/random and the consequence dimension devastated the previous state of Ψ so this is considered the primary condition ψ  at the time of initiation. None of this progression sequence evokes the past form/state and at every level it arises by way of totally arbitrarily designated function of the noticeable ψj0.The quantum state as shown above signifies the part of computing the size of the key which breakdown into an arbitrarily/randomly designated function of this evident, ψjProposed block chain and bi-linear polynomial based QCP-ABE need communiqué passages like a quantum network communication link and a normal network communication link. The source user and destination user together need chaotic randomized producers after the bi-linear cyclical cluster and a pair of rudimentary and polarizing cubits ,47,48. WThe offered prototypical framework has three methodologies: consumer integrity metric computation, QKRD, and encipher, decipher process of cloud users’ private data. In the initial process the input accepts the cloud consumer attribute values to compute user integrity, and then each user’s value can forward to the secure block chain based quantum key production after implement encipher and decipher algorithms. The next step consists in chaotic integrity metric based quantum key production process in cloud consumer attributes, control structures/policies, and individual session key generation based on CP-ABE ,21,22,25Y → Z: ∀ y ∈ Y, the map By then x → B is a bi-linear map from X to Z, and ∀ x ∈ X, the map By: y → B is a bilinear map from Y → Z. X, Y, Z are three vector spaces upon the same field F. The bilinear productive cyclical set with ‘o’ has a group order Order(o) ≤ Order). Our novel projected pseudo code, a bi-linear chaotic arbitrary polynomial curve, is used for the enhancement of the privacy metrics/input for the session wise key making progress. The rudimentary iterative co-relation of bi-linear randomized polynomial value can be articulated by way of0 is the initialization term is computed by the above relationA bi-linear map is a function B:X ∗ Z. Using the above method can get the different set of bi-linear randomized polynomial graphs along with a wide range of co-factors through determining the recurrence equivalence.Finally, Inputs: Start to prepare input cloud user attribute based parameters, message block size BLK_M, Over-all computational serial iterations CS_I, block-bytes, Cyclical confusion, diffusion set CD_S, cloud consumer private data load CP_L, first i/p info FI_I, TM_X and TM_K are transformation matrices.Outputs: Authorized Integrated Biometric measurement AIB_MStep 1: Declared and then initialized i/p cloud user attribute based parameters along with bi-linear cyclical hash vector. BCH_V [block-bytes/32] ← 0. Initially make bi-linear cyclical hash vector value as NULL.Step 2: Choosing any randomized bi-linear polynomial graph value with private key P(K). It can enhance the overall privacy and security with chaotic arbitrary behavior which is based on logistic model of Bernoulli which leads to generation of strong chaotic randomized practical structure ) BLK_M[j] ← LeftForward if(s+i<CS_I){BLK_M[j] ← LeftReverse BLK_M[j] ← RightShift BLK_M[j] ← LeftShift }C = c0 + c1 …… n−rc}1, g2, and g3 are G-pairs [1 × g2 → g3; i.e., it must followBi-linear coupling produces the multiplicative of any two pairs belonging to a polynomial cyclical set G. Once G is a state of identical elements what we selected from the pair the same pair produces a cyclic polynomial bi-linear relative set. Therefore, the bi-linear coupling gives a wide-range of randomized multiplicative pairs. Let G be a commutative cyclical group with transposed set t, and imagine that g G-pairs . The com1, g11, g12 ∈ G parallel whole g2, g21, g22 ∈ G2 which is an optimal pair of G-bilinear map. G1⊗g G2 → G3 and G1⊗G G2 indicates the multiplicative of G1, G2. A bilinear curve is also treated as a G-bilinear family of cures iffy and only if Ø: G3 → HomoM (G2 G1); which exactly suits through the definition by representing as Ø (g3) (g2): = ê. A G-bilinear family of curves said to be finite and apt if and only if given randomized curve instance Ø is also an isomorph of all G-pairs. A G-bilinear combination of curves are said to be not a degenerative type if and only if ê = null to all g3 belongs to g2 as same as null; similarly, ê is described as not degenerative if the pair  is also null for all g2 belong to g3 also said to be null. So, if all above mentioned constraints are satisfactory further the polynomial set of bi-linear curves can be valuated. This practice is efficiently combined with Bernoulli logistic map of family curves of the same type which provide more security in terms of chaotic randomization and enactment [For all g ∈ G and whole gnactment ,23,24,49Block chain based QKD uses numerous internetwork communication links, which are a combination of secure quantum link and a general user info link ,37,38,39k which must fulfill the G-bilinear principle and compliment degenerative principle so that Ø1, Ø2 belongs to GCO. The public key and master key generated as shown below.Let G be the cyclic bi-linear pair of curves with co-prime order Co and originator Ok), BQKD private key (Prk), and public key factors (Pbk).In this way we can generate Master key  and institutes q = Rn which understand that the middle level vertices, Mv, are arranged like  = Q ). Assume Lv to be the set of leaf vertices at the control access structure/policy; from this ciphered text can be generated over the existing access structure tree of policies Ast as shown below:The enciphered procedure gets the cloud consumers unique private info Confirming overall homomorphism principles to mien original text message enciphering:r0), Ω(r1) as initial values.Homomorphism based encipher, decipher uses Ω(r0) = CPEncD (j1): = CPEncD(j1) = (j1 + γµ ∗ Þ) mod Me Ω(r1) = CPEncD(j1): = CPEncD(j2) = (j2 + µ ∗ Þ) mod Me whereas Me = α ∗ β; CPEncD(j1 + j2): = CPEnc(Ω(r0)) + CPEnc(Ω(r1));Ω(j.j2): = CPMEncD(Ω(r0)).CPMEncD(Ω(r1)): = (j1 + µ ∗ Þ) mod Me + (j2 + µ ∗ Þ)mod Me.CPMEncD(rk) by using cloud consumers’ set of personal parameters (Spp). The QK_Pdn process ingests cloud consumers parameter set Spp act as initial i/p for BQKD (Open key), and the formed o/p is the secret key. This process opts for a couple of arbitrary numbers, A1 and A2; for combination of each cloud consumer parameter set Spp. These random values are part of selected co-factor of BQKD (shared key) which belongs to Znp.The session wise key production process can generate Private key  and public-key (PbK) as i/p. The deciphering procedure is implemented iteratively. Verification of homomorphism property for user information decipherment is as follows: let be Prk.Spp(CPEnc(j1 + j2), MCPEnc(j1.j2). Spp(Ct(j)1, K1,i). Spp. Spp(Ct(k)3,K1,f) to get the created cloud consumer control structure.In this process a private key PThe experimentations can be situated and executed over simple storage service (AWS-S3) with help after cloud consumer device details: processor i7 with speed of 2.30 GHz, 16 GB primary memory, 64-bit OS. This outline requires the usage of standard inbuilt packages and interfaces like EC2, Java, Net beans, and Eclipse.AWS cloud services are utilized in the projected secure block chain based cloud environment to act out the projected model on users’ confidential clinical and medical data. We used Amazon Elastic Compute Cloud and S3 buckets for generation of investigational outcomes to achieve effective public cloud security me integrating our proposed algorithms to the model. Elastic Compute Cloud offers upfront and tranquil cloud centric large scale calculations for all types of consumers. Elastic Compute Cloud cases are setup on Virtual Private Cloud. Using this cloud, consumers can do their trails in all possible cases with low cost for reliable services. For experimentation and analysis of Elastic Compute Cloud cases AWS, compromises an Internet based support, i.e., Cloud_Watch ,15,16,19The projected method is compared with the past models; runtime calculations are illustrated in The present approach provides a novel and enhanced bilinear QCPABE chaotic randomized key generation over the secure block chain cloud environment based user’s sensitive data. The proposed approach uses a group of bilinear polynomial curves by means of extensively randomized complex chaotic utility. Conventional ABE approaches fail to handle the cloud consumer’s large volumes of sensitive information and most existing methods are independent on integrity parameter due to lack of computational resources with less computational overhead. Our approach addresses all the traditional approaches issues and problems. Our proposed approach was implemented and successfully functional over the cloud consumers’ large volume sets of sensitive data which are in the format of structured, semi structured, and non-structured. Our proposed approach can secure the cloud consumers’ personal attributes by applying bilinear polynomial chaotic randomized map function designed for key setup, encipher, and decipher mention. The experimental replication results proved that our approach has the finest accuracy and rightness with respect to time required for dynamic key generation, encipher and decipherment process, and needed far less memory and computational overhead over the traditional approaches. Compared to existing models , the real-time simulation results demonstrate that the stated standard is more precise than 90% in terms of bit change and more precise than 95% in terms of dynamic key generation, encipherment, and decipherment time. In the future this work may be protracted to advance the efficiency of the encryption and decryption process for the multi-document file formats using deep learning framework without loss of quality and resolution of the users various data representations over the cloud.


The magnetotransport experiments assisted with mobility spectrum analysis clearly show that such an interpretation is incorrect. InAsSb layers are strongly p-type dominant, with a clear contribution from valence band carriers observed at the whole analyzed temperature range. Furthermore, the presence of thermally activated band electrons is detected at temperatures higher than 220 K.Narrow band-gap semiconductors, namely ternary InAsSb alloys, find substantial technological importance for mid-infrared application as photodetectors in medical diagnostics or environmental monitoring. Thus, it is crucial to develop electrical contacts for these materials because they are the fundamental blocks of all semiconductor devices. This study demonstrates that electroplated gold contacts can be considered as a simple and reliable metallization technology for the electrical-response examination of a test structure. Unalloyed electroplated Au contacts to InAsSb exhibit specific contact resistivity even lower than vacuum-deposited standard Ti–Au. Moreover, temperature-dependent transport properties, such as Hall carrier concentration and mobility, show similar trends, with a minor shift in the transition temperature. It can be associated with a difference in metallization technology, mainly the presence of a Ti interlayer in vacuum-deposited contacts. Such a transition may give insight into not only the gentle balance changes between conductivity channels but also an impression of changing the dominance of carrier type from  III–BV NBG semiconductors are arsenides  and antimonides  as well as their ternary alloys , considered as crucial materials for mid-infrared (MIR) optoelectronic devices, operating with a radiation of wavelength between 2 and 14 µm , and a water solution as an electrolyte under 350–375 µA/cm2 current density. K[Au(CN)2] solution was utilized for the deposition of Au on p- and n-type GaAs nearly three decades ago [The Au contact deposition was conducted by two methods: (i) wet technology, namely electroplating a, and ib. In theades ago ,42,43. Tades ago , provingIII–As, there have been only a few reports, not necessarily on InAsSb but rather on GaAs [Regarding Au electrodeposition on A on GaAs ,42,43. A on GaAs ,44. It w−6 mbar using an Angstrom Engineering Nexdep thin film deposition system . The adhesive Ti layer with noble metal overlayer has been used as a bilayer for decades because Ti is known to be more chemically reactive than Au and thereby increases the adhesion as it chemically binds to the dielectric or semiconductor substrate [The second approach, vacuum evaporation, is a standard dry method for semiconductor device metallization. Here, a 5-nm-thick adhesive Ti (99.995%) interlayer prior to a 150-nm-thick Au (99.999%) contact layer were coated on InAsSb at approximately 10ubstrate . This apcρ is a useful parameter, a figure of merit for ohmic contacts, defining contact resistivity because it is independent of the contact area and is convenient while comparing contacts of various sizes. A multiple-contact two-terminal measurement technique with the lateral structure (TLM) was implemented to determine cρ. The I and dR characteristics acquired for each pair of contacts are depicted in dR(V) data confirm the ohmic behavior of both types of metallic contacts, being a straight line independent of the voltage.cρ and SHR derived from the TLM measurements were estimated for both metallization types, and the results are presented in cρ slightly decreases with rising temperatures from 8.4 × 10−5 Ω·cm2 at 10 K to 3.6 × 10−5 Ω·cm2 at 300 K, while for vacuum deposited Ti-Au on InAsSb, it is rather constant: 3.3 × 10−4 Ω·cm2 at 10 K and 3.8 × 10−4 Ω·cm2 at 300 K. In the case of SHR derived from TLM . A similar phenomena was already observed for p-type Be-doped binary InAs epilayers for certain doping level, >1017 cm−3, but to a lower extent [III–BV semiconductor materials but rather interacts to form a variety of intermetallic compounds [Furthermore, the temperature-dependent r extent . It coulompounds . A recenompounds . Moreove19 cm−3) with cρ at a level of 10−6 Ω·cm2 [cρ of 1.3 × 10−8 Ω·cm2 [cρ estimated solely at room temperature.The contact resistance values for metallization schemes in Sb-containing InAs-based semiconductors have been limitedly reported. For instance, Mohney and co-workers presented an extended study on distinct three- and four-layered ohmic contact metallization with Au cap layer to maintain a low metal sheet resistance to highly Be-doped InAs , averaged Hall mobility (Hµ) as well as SHR ; see p-type doped InAsSb. Moreover, there is an approximately 5 K shift in the transition temperature: 281 K for electroplated Au and 286 K for Ti–Au. It can be associated with a difference in metallization technology, mainly the presence of a Ti interlayer in vacuum-deposited contacts. Consequently, it slightly changes the Fermi level position, reflected in a transition temperature shift. The calculated band profiles for p-type InAs0.81Sb0.19 (band-gap energy of 0.276 eV) can be found elsewhere [B data and by applying MSA.The Hall effect and resistivity measurements are important techniques to directly obtain the total charge carrier concentration , for InAsSb structures with both types of metallization are depicted in S(µ) are normalized to zero-field conductivity and are based on magnetoconductivity data collected in a high magnetic field up to maxB = 10.5 T.Interpretation of the above results is not straightforward because not all carriers have the same mobility. In modern materials containing multiple carrier mobilities, an analysis of magnetic-field-dependent Hall measurements is needed. To obtain mobility spectrum, which is not an easy task, several numerical approaches exist in the literature ,52. In tp-type dominant with hole mobility hhμ = 45 cm2/V·s and concentration hhp = 1.79 × 1018 cm−3 at T = 283 K (for the sample with electroplated Au contacts). Clearly, the contribution from valence band light holes  is also observed at the whole analyzed temperature range. Furthermore, the presence of thermally activated band electrons, with mobility eμ = 8143 cm2/V·s and concentration en = 1.13 × 1014 cm−3, at 283 K, is detected at higher temperatures, >220 K. Very similar parameters, which are responsible for the negative value of Hall voltage at low magnetic fields, were obtained for InAsSb with standard Ti–Au electrical contacts; see As expected, InAsSb layers are strongly HR parameter. We believe that the lower mobility peak (approximately 1000 cm2/V·s), observed for all temperatures, is related to the warping of the InAsSb heavy-hole band. Another higher mobility peak (approximately 2000 cm2/V·s), which appears at ≥283 K, may indicate the presence of a thermally activated surface inversion layer or n-type interface conduction. This subject definitely requires further studies; however, the appearance of both additional electron-like carriers is not related to the processing of electrical contacts.Interestingly, spectra obtained by MSA reveal the presence of two additional, electron-like carrier species, which may also contribute to the negative sign of low-field cρ lower than Ti–Au, approximately one order of magnitude; (ii) the carrier transport properties of InAsSb show similar temperature-dependent trends, independently of metallization type; and (iii) InAsSb, either with electroplated Au or Ti–Au contacts, is characterized by multiple populations of distinct carrier species with strong p-type dominance. It is also worthy to mention that the carrier characteristics obtained from MSA are not susceptible to SHR as standard Hall effect measurements at low B. Ultimately, it can be concluded that electroplated Au might be considered as facile and a reliable metallization technology for InAsSb-based test structure examination.The presented study was intended to compare the simple Au-electroplated route and standard vacuum-deposited Ti–Au for metallization to the InAsSb epilayer. The following main conclusions can be drawn: (i) unalloyed electroplated Au ohmic contacts exhibit


We designed a meta-analysis to evaluate the clinical significance and efficacy of circulating noncoding RNAs (ncRNAs) in the early prediction of preeclampsia.PubMed, Embase and the Cochrane Library were used to search for literature. The combined prediction performance was evaluated by calculating the area under the summary receiver operator characteristic (SROC) curve. The potential sources of heterogeneity were analysed by meta-regression analysis and subgroup analysis. All statistical analyses and mapping were performed by RevMan 5.3 and Stata 12.0.A total of 41 studies from 14 articles, including 557 preeclampsia patients and 842 controls, were included in our meta-analysis. All studies collected blood before onset. NcRNAs in blood performed relatively well in predicting preeclampsia. The combined sensitivity was 0.71, the specificity was 0.84, and the area under the SROC curve (AUC) was 0.86. Peripheral blood mononuclear cell (PBMC) samples showed the best diagnostic accuracy. The combined AUC was 0.93. Combined detection was better than single detection, and miRNA was better than circRNA. The heterogeneity of the study was determined by sample size, lncRNA characteristics, lncRNA source and race.Circulating ncRNAs can be valuable biomarkers used as candidates for noninvasive early predictive biomarkers of preeclampsia and have great clinical application prospects. The clinical value of ncRNAs needs to be tested by further multicentre, comprehensive and prospective studies, and the test criteria should be established.The online version contains supplementary material available at 10.1186/s12958-021-00852-8. Preeclampsia remains a main cause of maternal and perinatal mortality and morbidity, with a global incidence rate of 2–8%. It is a pregnancy-specific disease characterized by new onset hypertension and proteinuria, sometimes progressing into multiple organ damage , 2. How We searched literature databases  to identify relevant studies published through June 1, 2021. We used the following search terms to retrieve relevant data:  AND (“microRNAs” OR “microRNA” OR “miRNAs” OR “miRNA” OR “miR”) AND (“ROC” OR “sensitivity” OR “specificity”);  AND (“circular RNA” OR “circRNA” OR “circRNAs“) AND (“ROC” OR “sensitivity” OR “specificity”);  AND  AND (“ROC” OR “sensitivity” OR “specificity”);Studies were considered eligible if they met the following criteria: 1) predictive capacity of miRNA、circRNA、lncRNA for PE was provided; 2) the acknowledged gold reference standard was used to make diagnosis of PE patients: blood pressure 140/90 mmHg and proteinuria 0.3 g/day after 20 gestational weeks; 3) all women had singleton pregnancies, and those with pregnancy complications were excluded; 4) pregnant women with no signs or symptoms of preeclampsia at the time of sampling; and 5) FP, TP, FN and TN were provided to construct the 2 × 2 contingency table. The exclusion criteria were as follows: 1) written in a language other than English; 2) the expression level of ncRNA was obtained from cell lines or animals; 3) reviews, letters, and meeting records; 4) studies focusing on gene polymorphisms; and 5) studies with insufficient data.Articles were independently screened by two researchers, and disagreements were resolved by consulting a third researcher. The extracted data from these articles included first author, year of publication, country, sample size, time of sampling, type of PE, sample type, internal reference gene, ncRNA profiling, diagnostic value  and expression level. The two aforementioned researchers used the QUADAS-2 score system  to asses2 statistic. If P < .1 or I2 > 50%, heterogeneity was defined as significant. We also conducted meta-regression, subgroup and sensitivity analyses to identify potential sources of heterogeneity. We carried out all analyses using Review Manager 5.3  and Stata 12.0 , and a value of P < .05 was considered statistically significant.We extracted the TP, FP, FN, and TN of each study to calculate the pooled sensitivity, specificity, PLR, NLR, DOR, and corresponding 95% CI. We also tested the pooled diagnostic value of ncRNAs by examining the SROC curve and the area under the SROC curve (AUC). In the present study, Deeks’ funnel plot was also conducted to test publication bias. We assessed heterogeneity among the studies using the chi-squared test and IWe searched 153 records in PubMed, Embase, and the Cochrane Library. Of these, 54 duplicate studies were excluded. We excluded 18 records after reading the titles and 33 records after reviewing the abstracts. Subsequently, we assessed the full texts of the remaining 48 articles and excluded 34 studies based on the exclusion criteria, including 7 not studies on circulating ncRNAs, 8 without clinical data to make a 2 × 2 contingency table and 8 studies that used ncRNAs for diagnosis. In total, 14 studies were ultimately included in this study . The selAdditional file P < 0.01) and specificity (I2 = 79.68%) . Finally, subgroup analysis based on these parameters is limited due to insufficient published data.Then, subgroup analyses and meta-regression analysis were carried out to explore the potential sources of the heterogeneity. Our results demonstrated that both pooled sensitivity and specificity were influenced by sample size, ncRNA species, lncRNA profiling (single or combined), specimen type and ethnicity, indicating that the factors discussed above may be the principal sources of heterogeneity for ncRNA assays in PE.We performed the best possible analyses; however, our report is not perfect, mainly due to significant statistical heterogeneity. The sources of heterogeneity include sample size, lncRNA characteristics, lncRNA source and race, which are inevitable, and thus, the results were affected. In addition, the sensitivity and specificity of this test make it difficult to say that it is useful as a predictive marker for preeclampsia. It should be combined with other markers such as maternal risk factors,uterine artery Doppler measurement results and arterial pressure, to show its superiority over more convenient tests. Furthermore,there are individual differences in the clinical manifestations and organ involvement of preeclampsia. The differences in the expression of noncoding RNA in different gestational cycles and the interference of various internal and external factors during pregnancy may affect the accuracy of the data. The effectiveness of circulating noncoding RNA in the early prediction of preeclampsia is promising. We need larger multicentre sample studies to verify this hypothesis. Additionally, it is wise to identify recognized endogenous reference genes, detection reagents and methods and establish standardized ncRNAs.Our meta-analysis results showed that circulating ncRNAs can be valuable biomarkers used as candidates for noninvasive early predictive biomarkers of preeclampsia and have great clinical application prospects. The clinical value of ncRNAs needs to be tested by further multicentre, comprehensive and prospective studies, and the test criteria should be established.Additional file 1. Additional file 2.


Clustering of tumor samples can help identify cancer types and discover new cancer subtypes, which is essential for effective cancer treatment. Although many traditional clustering methods have been proposed for tumor sample clustering, advanced algorithms with better performance are still needed. Low-rank subspace clustering is a popular algorithm in recent years. In this paper, we propose a novel one-step robust low-rank subspace segmentation method (ORLRS) for clustering the tumor sample. For a gene expression data set, we seek its lowest rank representation matrix and the noise matrix. By imposing the discrete constraint on the low-rank matrix, without performing spectral clustering, ORLRS learns the cluster indicators of subspaces directly, i.e., performing the clustering task in one step. To improve the robustness of the method, capped norm is adopted to remove the extreme data outliers in the noise matrix. Furthermore, we conduct an efficient solution to solve the problem of ORLRS. Experiments on several tumor gene expression data demonstrate the effectiveness of ORLRS. Tumor is a group of cells that have undergone unregulated growth and often form a mass or lump. It is critical to reveal the pathogenesis of cancer by analyzing tumor gene expression data. The advances of various sequencing technologies have made it possible to measure the expression levels of thousands of genes simultaneously . IncreasMany traditional clustering methods, such as hierarchical clustering (HC) , 13, selHowever, real data rarely can be well represented by a single subspace. A more reasonable model is to assume that the data are lying near multiple subspaces . Subspace clustering (or segmentation) has been proposed to improve clustering accuracy. It is assumed that the data points are drawn from the combination of multiple low-dimensional subspaces. The goal of subspace clustering is to obtain such multiple low-dimensional subspaces with each subspace corresponding to a cluster. Subspace clustering has obtained promising results in previous studies, and subspace clustering methods have been found widespread applications in many areas, such as pattern recognition , image pWhen the data are clean, i.e., the samples can be strictly drawn from multiple subspaces, several existing methods, such as sparse subspace clustering (SSC) , low-ranL2,1-norm based objective functions since the nonsquared residuals of L2,1-norm can reduce the effects of data outliers. In [L2,1-norm is adopted in robust PCA (RPCA) for detecting outliers. In [L2,1-norm for subspace clustering. Although the L2,1-norm is robust to outliers, it still suffers from the extreme data outliers. The L2,1-norm just reduces, not completely removes, the effects of the outliers. Capped norm is a more robust strategy than L2,1-norm due to the fact that it can remove the effects of the outliers. It has been recently studied in many applications [As pointed out in , one majiers. In , 35, theiers. In , Liu et ications , 37.X ∈ ℝm×n with m genes and n samples, a low-rank representation matrix A ∈ ℝm×n and a noise matrix E ∈ ℝm×n, i.e., X=A+E, are being sought. The low-rank representation of the i-th subspace Ai can be denoted as rank(Ai). Here, we impose the discrete constraint on a diagonal matrix Ii ∈ ℝn×n to obtain the low-rank representation rank(XIi), where Ii⊆{0,1} and ∑i=1cIi=I . The indicators of the i-th cluster are included in Ii. In contrast to traditional low-rank based models, we can directly learn the cluster indicators. To avoid trivial solutions and approximate the low-rank constraint, the rank of all subspace simultaneously can be minimized as ∑i=1c(‖AIi‖Spk)2, where ‖•‖Spk denotes the Schatten p-norm which has a better relaxation than the nuclear norm [E, capped norm is used to improve the robustness. We define θ as a thresholding parameter for choosing the extreme data outliers, and then the capped norm of E can be formulated as ‖E‖Capped=minE∑i=1nmin{‖Ei‖2, θ}. This function treats Ei equally if ‖Ei‖2 is smaller than θ. Hence, it is more robust to outliers than L2,1-norm. Meanwhile, we derive an efficient optimization algorithm to solve ORLRS with a rigorous theoretical analysis.In this paper, a one-step robust low-rank subspace segmentation (ORLRS) method via the discrete constraint and capped norm is proposed for clustering tumor sample. For a data set ear norm . For the  ① Compared with traditional low-rank representation-based methods, ORLRS can obtain the clustering result directly by learning a subspace indicator matrix from the low-rank representation matrix without spectral clustering. This avoids the graph construction process in spectral clustering and makes the clustering process simpler.  ② We introduced the capped norm into our model and formed a novel objective function for the gene expression data clustering task. Capped norm is used to constrain the noise matrix to improve the robustness of ORLRS.  ③ Optimizing the objective function of ORLRS is a nontrivial problem, thus we derive a new optimization algorithm to solve the problem. Furthermore, we have also given a rigorous convergence analysis of ORLRS.The main contributions of our paper are given as follows:The remainder of the paper is structured as follows. In We start with a brief introduction of several classical clustering methods. Then, the proposed ORLRS is presented, and the optimal solution and convergence analysis of ORLRS is provided.X ∈ ℝm×n as a data set with m features and n samples. LRR can be defined asA‖∗=∑iσi(A), i.e., the nuclear norm of A [D is a dictionary, and λ > 0 is a balance parameter.Denote orm of A , E2,1=∑jA∗ to equation (A∗|+|(A∗)T|)/2, where |A∗| is the absolute value function. Finally, the data are clustered by using spectral clustering [A brief explanation of LRR subspace clustering process is provided as follows. Firstly, the low-rank problem is solved by equation . Then, tequation  is used ustering .In this paper, we propose the one-step robust low-rank subspace clustering (ORLRS) method via discrete constraint and capped norm. Different from LRR, ORLRS was proposed for clustering the data by learning the indicators.X has c subspaces {X1, X2,…, Xc}, the low-rank representation of each subspace needs to be optimized. In the clustering task, we want each subspace to belong to its own cluster. To obtain a low-rank representation of each subspace, the following formula should be computed: rank(Xi), which has trivial solution. Therefore, we need to solve the problem in another way. We define a cluster indicator matrix as C ∈ ℝc×n: C=1 if the j-th sample belongs to the i-th subspace, and C=0 otherwise. And, the c diagonal matrices are defined as I1, I2,…, Ic ∈ I, where the diagonal elements of Ii (1 ≤ i ≤ c) are formed by the i-th row of C and I is the identity matrix. Then, XIi can be represented as the i-th subspace of X. That is, rank(Xi) can be rewritten as rank(XIi). We can get the clustering label in one step by directly optimizing Ii [Suppose the data matrix izing Ii .XIi‖Spp is the Schatten p-norm of XIi. The clustering indicators of each subspace can be obtained from the optimized diagonal matrix Ii|i=1c directly.Finally, the problem of the one-step low-rank subspace clustering method can be defined asX ∈ ℝm×n with m genes and n samples as the addition of low-rank representation matrix A ∈ ℝm×n and the noise matrix E ∈ ℝm×n, i.e., X=A+E, which is the same strategy as in RPCA. Our one-step low-rank subspace clustering problem can be written asλ > 0 is a balance parameter and ‖•‖L indicates certain regularization strategy. Note that Schatten p-norm is used to approximate the low-rank problem in equation (p-norm (0 < p < ∞) of a matrix G ∈ ℝm×n was defined as ‖G‖Sp=min(σip)p1/, where σi is the i-th singular value of G. In [p-norm with 0 < p ≤ 2 is proved. Here, we set 0 < 2k ≤ 2 to guarantee the convergence of first term in equation  algorithm is used to optimize equation  encodes the constraints of Ii|i=1c. We rewrite equation .Equation  can be sP, Q ∈ ℝn×n, q > 0, the following inequality holds when 0 ≤ h < 1:. Foh ≥ 1, the inequality is reversed.While for k ≤ 1, ‖G‖Spp=Tr((GTG)p/2) [i=1cTr(Ii(ATA)k)=∑i=1c(‖AIi‖Spk)2 since Ii|i=1c⊆{0,1}n×n. According to ∑i=1cIi=I, we convert the first term in equation (Following 0 < GTG)p/2)  and Lemmequation  to(9)∑i=Then, equation  can be rA and setting to zero, the above formula becomesH=k(ATA)k−1. So, we can achieve the optimal A:Taking derivative w.r.t F=X − A+(Y/μ). It can be easily verified that the derivative of equation mimi(13)minO is a diagonal matrix with Oii=oi. The problem of equation J3Ii|i=1c and setting to zero, the above formulation can be written asLi=k‖AIi‖Spk(AIi2AT)k − 2)/2minIIi can be updated according to the optimal solution to equation 32), we hThat is to say,A in t when 0 < k ≤ 1.Thus, the updating rule for matrix E while fixing others will monotonically decrease the objective value in equation 38) at boE while fixing others will monotonically decrease the objective value in equation 43), we cIi|i=1c while fixing others will monotonically decrease the objective value in equation d,  (d > 2) (Li in dk/2)(‖AIi‖Spk)d−1(AIi2AT)k − 2)/2, the convergence is also observed [Equation  indicateequation  during tequation  is changobserved .A, E, and Ii|i=1c according to Theorems As a result, the objective of equation  is noninLi=k‖AIi‖Spk(AIi2AT)k − 2)/2. (AIi2AT)k − 2)/2. So, computing Li takes O(m3) and computing Li|I=1c takes O(m3c), where c is the number of clusters. For Zi, we only need to compute the diagonal elements, which takes O(m3). And, computing Zi|I=1c takes O(m3c). In summary, the computational complexity of O(m3ct), where t is the iteration number.In We test ORLRS on six publicly available gene expression data sets, i.e., Leukemia , DLBCL , Colon cxi, suppose Ni as the target label and Ti as the truth label. ACC can be denoted as [φ=0 if x ≠ y and φ=1 if x=y, map(Ni) maps Ni to the equivalent label from the raw data and n is the number of tumor samples.Following , 45–47, M is the mutual information function between the true class label C and the clustering label S and H(·) is the entropy function. The larger the NMI value is, the better the clustering result is.We also evaluate the clustering performance by normalized mutual information (NMI) . NMI is   Leukemia data contain 25 cases of AML and 47 cases of ALL. It is packaged into a 7129 × 72 matrix .  DLBCL data consist of 5469 genes and 77 samples. These samples include 58 patients of diffuse large B-cell lymphoma (DLBCL) and 19 patients of follicular lymphomas (FL) .  The colon cancer data  consists  Brain_Tumor1 data set consists of 5920 genes in 90 patient samples. These samples contain 5 types of histological diagnoses, i.e., 60 cases of medulloblastoma, 10 cases of malignant glioma, 10 cases of atypical teratoid/rhabdoid tumors (AT/RTs), 4 cases of normal cerebellum, and 6 cases of primitive neuroectodermal tumors (PNETs).  The Brain_Tumor2 data set contains 10367 genes in 50 samples. It contains 4 types of malignant glioma, i.e., classic glioblastomas (CG), classic anaplastic oligodendrogliomas (CAO), nonclassic glioblastomas (NCG), and nonclassic anaplastic oligodendrogliomas (NCAO) .  9_Tumors data set integrates 9 tumor types to develop a genomics-based approach to the prediction of drug response. It contains 5726 genes in 60 samples. The number of samples of 9 tumor types is shown as follows: 9 samples of non-small-cell carcinoma (NSCLC), 7 samples of colon cancer, 8 samples of breast cancer, 6 samples of ovary cancer, 6 samples of leukemia, 8 samples of renal cancer, 8 samples of melanoma, 2 samples of prostate cancer, and 6 samples central nervous system cancer (CNS).A brief introduction of six gene expression data sets is presented, and the detailed information of these datasets is summarized in K-means is the most commonly used clustering method and is embedded into many methods including PLRR, robust LRR, and LatLRR to achieve better performance. Since our proposed method is a novel one-step robust low-rank subspace clustering model, we choose these methods as our comparison algorithms.We compare LRS , Ext-LRRIi|i=1c in the proposed ORLRS. Here, three parameters, i.e., threshold parameter θ, balance parameter λ, and low-rank constraint parameter k, need to be determined. In the experiment, we investigated one parameter by fixing the other two parameters. Since the initialization of Ii|i=1c will bring some uncertainty, the proposed ORLRS method run 100 times, and the average of the accuracies of 100 times is reported. The choices of parameters in the following are heuristic and might not be the best for tumor clustering.Since gene expression data have the characteristics of high-dimensional and small samples, we use PCA to perform dimensionality reduction. And, we use the K-means method to initialize θ for each data set.In the ORLRS model, data outliers are not heuristically determined based on the magnitude. They are selected during the optimization process. The data outliers may be distinct at different iterations (with the same thresholding parameter), while we iteratively optimize the objective function of ORLRS method. When the algorithm converges, likely correct extreme data outliers can be found. So, we just need to determine one value of θ. Since the gene expression levels in different data are very different, the values of extreme data outliers are also very different. So, the value of θ has a large range in six data sets. From θ={103, 105, 40,90,400, 106} in Leukemia data, DLBCL data, Colon cancer data, Brain_Tumor1 data, Brain_Tumor2 data, and 9_Tumors data, respectively. The results indicate that the value of θ should be determined appropriately. If the value of θ is too large, we will miss some extreme outliers. If the value of θ is too small, some important information may be removed, thereby affecting the clustering performance.λ. ORLRS can obtain the best results in the case of λ={0.6, 1,1,1,0.9, 1.1} in Leukemia data, DLBCL data, Colon cancer data, Brain_Tumor1 data, Brain_Tumor2 data, and 9_Tumors data, respectively. According to the experimental results in each data set, before reaching the best results, the clustering accuracies showed an overall upward trend when λ increases; after achieving the best results, the clustering accuracies showed an overall downward trend when λ increases. So, we suggest a rough range 0.1 ≤ λ ≤ 2 on the choice of λ.p-norm parameter 0 < k ≤ 1, we determine the value of k in this range. k. ORLRS can achieve the best performance in the case of k={1,1,1,1,0.7, 0.4} in Leukemia data, DLBCL data, Colon cancer data, Brain_Tumor1 data, Brain_Tumor2 data, and 9_Tumors data, respectively. So, a general guidance is given 0 < k ≤ 1 on the choice of k.Since the algorithm is converged for the Schatten K-means to initialize the indicator matrix Ii|i=1c. PLRR, robust LRR, and LatLRR use the normalized cuts method to segment data, which cluster data points by using the K-means method. For robust NMF method, we initial the coefficient matrix and basis matrix randomly. To avoid randomness, we run all methods 100 times, and the mean and standard error results of the clustering accuracies of 100 times are shown in In this section, experimental results of our proposed method and six comparison algorithms, i.e., LRS, Ext-LRR, RPCA, PLRR, robust LRR, LatLRR, robust NMF, and K-means, are reported. ORLRS, LRS, and Ext-LRR use p-norm to better approximate the low-rank representation. Compared with traditional clustering methods, RPCA, robust NMF, and K-means, ORLRS achieves outstanding results on all of the six data sets.Based on the results reported in The NMI results on five gene expression data sets are shown in We plotted the convergence curves of our ORLRS on different datasets. The convergence curves can be found in p-norm and discrete constraint, low-rank representation of each subspace can be well obtained. Different from traditional low-rank-based methods, such as LRR and LatLRR, ORLRS learns indicators directly and perform clustering process in one step by using the discrete constraint. Capped norm is used to improve the robustness of ORLRS since it can effectively remove the extreme data outliers in the noise matrix. Furthermore, we propose an efficient algorithm to solve the proposed subspace clustering model, and the convergence of the proposed algorithm is proved. We thus can discover the clusters of tumor data depending on the optimal cluster indicators. We tested the proposed ORLRS method on six tumor data. The results are proved that ORLRS is an excellent method for clustering tumor sample.In this paper, a novel one-step robust low-rank subspace clustering method (ORLRS) is proposed for tumor clustering, where the gene expression data set is represented by a low-rank matrix and a noise matrix. By using the Schatten There remain several interesting directions for future work. First, it might be better to learn a dictionary for ORLRS since some low-rank subspace segmentation methods achieve significant improvements by learning a dictionary. Second, ORLRS may be extended to solve other problems, such as matrix recovery and classification. Third, ORLRS may be employed in other applications, such as gene clustering and coclustering.


Bacillus thuringiensis as seed treatment and application with silicon on lettuce plants exposed to salinity levels (4 dS m−1 and 8 dS m−1). Results revealed that leaves number, head weight, total yield, relative water content (RWC), and chlorophyll a and b declined considerably due to two salinity levels. Oxidative stress markers, i.e., hydrogen peroxide (H2O2), superoxide (O2−), and lipid peroxidation (MDA) dramatically augmented in stressed plants. On the other hand, leaves number, total yield, RWC, and chlorophyll a, b in stressed lettuce plants were considerably enhanced because of the application of Si or B. thuringiensis. In contrast, EL%, MDA, and H2O2 were considerably reduced in treated lettuce plants with Si and B. thuringiensis. In addition, the treatment with Si and B. thuringiensis increased head weight (g) and total yield (ton hectare-1), and caused up-regulation of proline and catalase, superoxide dismutase, peroxidase, and polyphenol oxidase activity in lettuce leaves under salinity conditions.We investigated the impact of  Lactuca sativa L.) belong to the Asteraceae family. It is an important and popular vegetable crop grown as an annual plant, which is used as a salad crop. It is a rich source of vitamins and antioxidants such as vitamins C, carotenoids, and fiber content  × V−1W, where V = volume (cm3); W = weight (g) [Lipid peroxidation was assayed as malondialdehyde (MDA) at 532 and 600 nm using spectrophotometer. MDA (μmol gight (g) .w/v) NBT or 0.1 w/v % DAB. H2O2 and O2− were assayed as arbitrary units using the method of Huckelhoven et al. [Lettuce leaves were infiltrated with 10 mM potassium salicylate buffer containing 0.1%  of lettuce were placed into bottles in 25 cm3 deionized water. Bottles were shaken for 20 h, electrical conductivity was recorded for each, and then flasks were heated (80 °C) for 1 h, and the samples were shaken again (at 21 °C) for 20 h. Final conductivity was calculated for each flask. Electrolyte leakage % was calculated with the following formula: initial/final conductivity × 100 [Ten fresh leaf discs /(TW − DW) × 100 .−1 FW [Proline in fresh lettuce leaves was determined using a spectrophotometer at 520 nm and calculated as μg g−1 FW .−1 FW) according to the Association of Official Analysis Chemists (A.O.A.C) [Samples of leaves were taken at the harvesting date to determine ascorbic acid (AsA) (vitamin C mg 100 gA.O.A.C) .The extraction from fresh leaves was prepared using N-N Dimethyl formamide and the chlorophyll a and b was determined at 647 and 664 nm using a spectrophotometer .Number of leaves, head weight, and total yield were recorded.p ≤ 0.05).The results were statistically analyzed using ANOVA procedures  using thB. thuringiensis as a seed treatment and Si (potassium silicate at 2.7 mmol L−1) as a foliar application in the alleviation of the deleterious impacts of salinity in lettuce plants and to increase yield production. These treatments cause increases in the number of leaves, chlorophyll a and b, and RWC, as well as total yield under the salinity levels. On the other side, the stress signals such as ROS (O2− and H2O2), MDA, and EL% were reduced considerably in stressed lettuce plants as a positive effect of these treatments. Therefore, we recommend the application of Si as a foliar application and B. thuringiensis as a seed treatment to mitigate the adverse impact of salinity on lettuce plants by improving the antioxidant system and improving plant production in the agro-biological system.Our results offer insights into the possible efficiency of


Scientific Reports 10.1038/s41598-021-82959-x, published online 09 February 2021Correction to: The original version of this Article contained an error.Erysipelothrix piscisicarius should be considered the official species name, rather than E. takahashiae.After publication it was brought to the authors' attention that according to the International Code of Nomenclature of Prokaryotes, the first taxonomically characterized and validated name for a species should be retained. Therefore, for E. sp. Strain 2 isolate 715, In light of this, the text in the Abstract,“Therefore, we confirm E. sp. Strain 2 represents a unique species that may be isolated from a broad host range, and the name “Erysipelothrix takahashiae” is suggested”now reads:Erysipelothrix piscisicarius” (meaning a killer of fish), may be isolated from a broad host range”“Therefore, we confirm E. sp. Strain 2 represents a unique species, that despite its official name “In addition, the text in the Results and discussion,44 recommends that when choosing a species name (Recommendation 12c) an epithet could indicate the source of the species or the name of the first discoverer. E. sp. Strain 2 has been isolated from a broad diversity of hosts, firstly from a pig (type strain 715)23, and then from fish (isolate 15TAL0474)19 and birds (isolates EsS2-6-Brazil and EsS2-7-Brazil)27. Given that the new species represents a pathogen of multiple distinct hosts (similarly to what is observed for E. rhusiopathiae) and that the name E. piscisicarius (meaning a killer of fish) does not represent the bacterium's full host spectrum, a more generic, unbiased name would be suitable. We suggest “Erysipelothrix takahashiae” after Toshio Takahashi who first discovered isolates of this clade and suggested it could represent a novel species23.”“The International Code of Nomenclature of Prokaryotesnow reads:44 recommends that when choosing a species name (Recommendation 12c), isolates deemed conspecific should retain the species epithet provided on List of Prokaryotic names with Standing in Nomenclature. E. sp. Strain 2 has been isolated from a broad diversity of hosts, firstly from a pig (type strain 715)23, and then from fish (isolate 15TAL0474)19 and birds (isolates EsS2-6-Brazil and EsS2-7-Brazil)27. Nevertheless, though the new species represents a pathogen of multiple distinct hosts (similarly to what is observed for E. rhusiopathiae), and the name E. piscisicarius (meaning a killer of fish) does not represent the bacterium's full host spectrum, as the first taxonomically characterized and validated name for the species19, “Erysipelothrix piscisicarius” should be considered the official species name for E. sp. Strain 2.”“The International Code of Nomenclature of ProkaryotesAnd the text,Thus, based on phylogenomics, and supported by dDDH and ANI values, we confirmed that the genus comprises a novel species, E. sp. Strain 2, for which we suggest the name “Erysipelothrix takahashiae”.”now reads:Erysipelothrix piscisicarius”.”“Thus, based on phylogenomics, and supported by dDDH and ANI values, we confirmed that the genus comprises a novel species, formerly known as E. sp. Strain 2, and recently named “These changes have been implemented in the PDF and HTML versions of the Article, and do not affect the findings and conclusion.


To the editor,We thank the comments made by Dr. Atan regarding our manuscript “Impact of COVID-19 pandemic on a urology residency program” , 3. ThesThe Authors