A new species of Nanhsiungchelys (Testudines: Cryptodira: Nanhsiungchelyidae) from the Upper Cretaceous of Nanxiong Basin, China

Nanhsiungchelyidae are a group of large turtles that lived in Asia and North America during the Cretaceous. Here we report a new species of nanhsiungchelyid, Nanhsiungchelys yangi sp. nov., from the Upper Cretaceous of Nanxiong Basin, China. The specimen consists of a well-preserved skull and lower jaw, as well as the anterior parts of the carapace and plastron. The diagnostic features of Nanhsiungchelys include a large entire carapace length (∼55.5 cm), a network of sculptures consisting of pits and ridges on the surface of the skull and shell, shallow cheek emargination and temporal emargination, deep nuchal emargination, and a pair of anterolateral processes on the carapace. However, Nanhsiungchelys yangi differs from the other species of Nanhsiungchelys mainly in having a triangular-shaped snout (in dorsal view) and wide anterolateral processes on the carapace. Additionally, some other characteristics (e.g., the premaxilla is higher than wide, the maxilla is unseen in dorsal views, a small portion of the maxilla extends posterior and ventral of the orbit, and the parietal is bigger than the frontal) are strong evidence to distinguish Nanhsiungchelys yangi from Nanhsiungchelys wuchingensis. A phylogenetic analysis of nanhsiungchelyids places Nanhsiungchelys yangi and Nanhsiungchelys wuchingensis as sister taxa. Nanhsiungchelys yangi and some other nanhsiungchelyids bear distinct anterolateral processes on the carapace, which have not been reported in any extant turtles and may have played a role in protecting the head. The Nanxiong Basin was extremely hot during the Late Cretaceous, and so we suggest that nanhsiungchelyids might have immersed themselves in mud or water to avoid the heat, similar to some extant tortoises. If they were capable of swimming, our computer simulations of fluid flow suggest the anterolateral processes could have reduced drag during locomotion

Genome-Wide Identification and Expression Analysis of Heat Shock Protein 70 (<i>HSP70</i>) Gene Family in Pumpkin (<i>Cucurbita moschata</i>) Rootstock under Drought Stress Suggested the Potential Role of these Chaperones in Stress Tolerance

Heat shock protein 70s (HSP70s) are highly conserved proteins that are involved in stress responses. These chaperones play pivotal roles in protein folding, removing the extra amounts of oxidized proteins, preventing protein denaturation, and improving the antioxidant system activities. This conserved family has been characterized in several crops under drought stress conditions. However, there is no study on HSP70s in pumpkin (Cucurbita moschata). Therefore, we performed a comprehensive analysis of this gene family, including phylogenetic relationship, motif and gene structure analysis, gene duplication, collinearity, and promoter analysis. In this research, we found 21 HSP70s that were classified into five groups (from A to E). These genes were mostly localized in the cytoplasm, chloroplast, mitochondria, nucleus, and endoplasmic reticulum (ER). We could observe more similarity in closely linked subfamilies in terms of motifs, the number of introns/exons, and the corresponding cellular compartments. According to the collinearity analysis, gene duplication had occurred as a result of purifying selection. The results showed that the occurrence of gene duplication for all nine gene pairs was due to segmental duplication (SD). Synteny analysis revealed a closer relationship between pumpkin and cucumber than pumpkin and Arabidopsis. Promoter analysis showed the presence of various cis-regulatory elements in the up-stream region of the HSP70 genes, such as hormones and stress-responsive elements, indicating a potential role of this gene family in stress tolerance. We furtherly performed the gene expression analysis of the HSP70s in pumpkin under progressive drought stress. Pumpkin is widely used as a rootstock to improve stress tolerance, as well as fruit quality of cucumber scion. Since stress-responsive mobile molecules translocate through vascular tissue from roots to the whole plant body, we used the xylem of grafted materials to study the expression patterns of the HSP70 (potentially mobile) gene family. The results indicated that all CmoHSP70s had very low expression levels at 4 days after stress (DAS). However, the genes showed different expression patterns by progressing he drought period. For example, the expression of CmoHSP70-4 (in subgroup E) and CmoHSP70-14 (in subgroup C) sharply increased at 6 and 11 DAS, respectively. However, the expression of all genes belonging to subgroup A did not change significantly in response to drought stress. These findings indicated the diverse roles of this gene family under drought stress and provided valuable information for further investigation on the function of this gene family, especially under stressful conditions

Fault Detection-Based Multiple Local Manifold Learning and Its Application to Blast Furnace Ironmaking Process

Process safety plays a vital role in the modern process industry. To prevent undesired accidents caused by malfunctions or other disturbances in complex industrial processes, considerable attention has been paid to data-driven fault detection techniques. To explore the underlying manifold structure, manifold learning methods including Laplacian eigenmaps, locally linear embedding, and Hessian eigenmaps have been utilized in data-driven fault detection. However, only the partial local structure information is extracted from the aforementioned methods. This paper proposes fused local manifold learning (FLML), which synthesizes the typical manifold learning methods to find the underlying manifold structure from different angles. A more comprehensive local structure is discovered under a unified framework by constructing an objection optimization function for process data dimension reduction. The proposed method takes advantage of different manifold learning methods. Based on the proposed dimension reduction method, a new data-driven fault detection method is developed. Hotelling’s T2 and Q statistics are established for the purpose of fault detection. Experiments on an industrial benchmark Tennessee Eastman process whose average MDR and average FAR of FLML T2 are 7.58% and 0.21% and a real blast furnace ironmaking process whose MDR and FAR of FLML T2 are 2.80% and 0.00% are carried out to demonstrate the superiority and effectiveness of the proposed method

Effects of miR-107 on the Chemo-drug sensitivity of breast cancer cells

A growing body of evidence indicates that aberrant expression of miR-107 plays a core role in cancers. This study aims to demonstrate the function of miR-107 and its roles in chemo-drug resistance in breast cancer cells

Estimating construction waste generation in the Greater Bay Area, China using machine learning

Reliable construction waste generation data is a prerequisite for any evidence-based waste management effort, but such data remains scarce in many developing economies owing to their rudimentary recording systems. By referring to several models proposed for estimating waste generation, this study aims to develop a reliable and accessible method for estimating construction waste generation based on limited publicly available data. The study has two objectives. Firstly, it aims to estimate construction waste generation by focusing on the Greater Bay Area (GBA) in China, one of the world's most thriving regions in terms of construction activities. Secondly, it aims to compare the strengths and weaknesses of various waste quantification models. 43 sets of annual socio-economic, construction-related and C&amp;D waste generation data ranging from 2005 to 2019 were collected from the local government authorities. By analyzing the data using four types of machine learning models, namely multiple linear regression, decision tree, grey models, and artificial neural network, it is found that all calibrated models, with their respective strengths and weaknesses, can produce acceptable results with the testing R2 ranging from 0.756 to 0.977. This study also reveals that the 11 cities in the GBA produced a total of about 364 million m3 of construction waste in 2018. The result can be used for monitoring the urban metabolism, quantifying carbon emission, developing a circular economy, valorizing recycled materials, and strategic planning of waste management facilities in the GBA. The research findings also contribute to the methodologies for estimating waste generation using limited data.</p

Estimating construction waste generation in the Greater Bay Area, China using machine learning

Reliable construction waste generation data is a prerequisite for any evidence-based waste management effort, but such data remains scarce in many developing economies owing to their rudimentary recording systems. By referring to several models proposed for estimating waste generation, this study aims to develop a reliable and accessible method for estimating construction waste generation based on limited publicly available data. The study has two objectives. Firstly, it aims to estimate construction waste generation by focusing on the Greater Bay Area (GBA) in China, one of the world's most thriving regions in terms of construction activities. Secondly, it aims to compare the strengths and weaknesses of various waste quantification models. 43 sets of annual socio-economic, construction-related and C&amp;D waste generation data ranging from 2005 to 2019 were collected from the local government authorities. By analyzing the data using four types of machine learning models, namely multiple linear regression, decision tree, grey models, and artificial neural network, it is found that all calibrated models, with their respective strengths and weaknesses, can produce acceptable results with the testing R2 ranging from 0.756 to 0.977. This study also reveals that the 11 cities in the GBA produced a total of about 364 million m3 of construction waste in 2018. The result can be used for monitoring the urban metabolism, quantifying carbon emission, developing a circular economy, valorizing recycled materials, and strategic planning of waste management facilities in the GBA. The research findings also contribute to the methodologies for estimating waste generation using limited data.</p

A SNP Mutation in Homeodomain-DDT (HD-DDT) Transcription Factor Results in Multiple Trichomes (mt) in Cucumber (Cucumis sativus L.)

Trichome is a natural physical barrier protecting plants against environmental stresses, natural infestations, ultraviolet rays and pathogenicity. Trichome also helps plants in maintaining appropriate water content by reducing transpiration rate. The molecular mechanism regulating unicellular trichome development in Arabidopsis has been extensively elucidated, but the molecular mechanism regulating multicellular trichome development remains unclear. In this study, we identified a multiple trichomes (mt) mutant from a cucumber EMS (Ethylmethylsulfone) mutagenesis population. Genetic analysis indicated that an incomplete dominant gene controls the mt trait. Using a combination of map-based cloning and BSA-seq (Bulked Segregant Analysis -Sequencing), we identified the candidate gene, CsaV3_6G050410, responsible for the mt mutation. Sequence alignment revealed one base substitution in gene CsaV3_6G050410, resulting in an amino acid substitution. The deduced amino acid sequence of CsaV3_6G050410 encodes a HD-DDT (homeodomain-DDT) transcriptional regulatory protein containing a conserved homeobox domain and a DDT domain. Gene expression analysis revealed that the expression level of CsaV3_6G050410 in the mt mutant was similar to that in the WT (wild type). Transcriptome analysis indicated that the mt gene may regulate the development of the epidermis by influencing plant hormone signaling pathways or participating in several transcription factor pathways. The results of this study are fundamental for a better understanding of the function of the HD-DDT transcription factor in the trichome development of cucumber

Integration of high-resolution physical and genetic map reveals differential recombination frequency between chromosomes and the genome assembling quality in cucumber.

Cucumber is an important model crop and the first species sequenced in Cucurbitaceae family. Compared to the fast increasing genetic and genomics resources, the molecular cytogenetic researches in cucumber are still very limited, which results in directly the shortage of relation between plenty of physical sequences or genetic data and chromosome structure. We mapped twenty-three fosmids anchored by SSR markers from LG-3, the longest linkage group, and LG-4, the shortest linkage group on pachytene chromosomes 3 and 4, using uorescence in situ hybridization (FISH). Integrated molecular cytogenetic maps of chromosomes 3 and 4 were constructed. Except for three SSR markers located on heterochromatin region, the cytological order of markers was concordant with those on the linkage maps. Distinct structural differences between chromosomes 3 and 4 were revealed by the high resolution pachytene chromosomes. The extreme difference of genetic length between LG-3 and LG-4 was mainly attributed to the difference of overall recombination frequency. The significant differentiation of heterochromatin contents in chromosomes 3 and 4 might have a direct correlation with recombination frequency. Meanwhile, the uneven distribution of recombination frequency along chromosome 4 was observed, and recombination frequency of the long arm was nearly 3.5 times higher than that of the short arm. The severe suppression of recombination was exhibited in centromeric and heterochromatin domains of chromosome 4. Whereas a close correlation between the gene density and recombination frequency was observed in chromosome 4, no significant correlation was observed between them along chromosome 3. The comparison between cytogenetic and sequence maps revealed a large gap on the pericentromeric heterochromatin region of sequence map of chromosome 4. These results showed that integrated molecular cytogenetic maps can provide important information for the study of genetic and genomics in cucumber

Genome-wide analysis of a putative lipid transfer protein LTP_2 gene family reveals CsLTP_2 genes involved in response of cucumber against root-knot nematode (Meloidogyne incognita)

Plant lipid transfer proteins (LTPs) are small basic proteins that play important roles in the regulation of various plant biological processes as well as the response to biotic and abiotic stresses. However, knowledge is limited on how this family of proteins is regulated in response to nematode infection in cucumber. In the present study, a total of 39 CsLTP_2 genes were identified by querying databases for cucumber-specific LTP_2 using a Hidden Markov Model approach and manual curation. The family has a five-cysteine motif (5CM) with the basic form CC-Xn-CXC-Xn-C, which differentiates it from typical nsLTPs. The members of CsLTP_2 were grouped into six families according to their structure and their phylogenetic relationships. Expression data of CsLTP_2 genes in 10 cucumber tissues indicated that they were tissue-specific genes. Two genes showed significant expression change in roots of resistant and susceptible lines during nematode infection, indicating their involvement in response to Meloidogyne incognita. This systematic analysis provides a foundation of knowledge for future studies of the biological roles of CsLTP_2 genes in cucumber in response to nematode infection and may help in the efforts to improve M. incognita-resistance breeding in cucumber.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author