The Complete Mitogenome of Apostasia fujianica Y.Li & S.Lan and Comparative Analysis of Mitogenomes across Orchidaceae.

Apostasia fujianica belongs to the genus Apostasia and is part of the basal lineage in the phylogenetic tree of the Orchidaceae. Currently, there are only ten reported complete mitochondrial genomes in orchids, which greatly hinders the understanding of mitochondrial evolution in Orchidaceae. Therefore, we assembled and annotated the mitochondrial genome of A. fujianica, which has a length of 573,612 bp and a GC content of 44.5%. We annotated a total of 44 genes, including 30 protein-coding genes, 12 tRNA genes, and two rRNA genes. We also performed relative synonymous codon usage (RSCU) analysis, repeat sequence analysis, intergenomic transfer (IGT) analysis, and Ka/Ks analysis for A. fujianica and conducted RNA editing site analysis on the mitochondrial genomes of eight orchid species. We found that most protein-coding genes are under purifying selection, but nad6 is under positive selection, with a Ka/Ks value of 1.35. During the IGT event in A. fujianica's mitogenome, the trnN-GUU, trnD-GUC, trnW-CCA, trnP-UGG, and psaJ genes were identified as having transferred from the plastid to the mitochondrion. Compared to other monocots, the family Orchidaceae appears to have lost the rpl10, rpl14, sdh3, and sdh4 genes. Additionally, to further elucidate the evolutionary relationships among monocots, we constructed a phylogenetic tree based on the complete mitogenomes of monocots. Our study results provide valuable data on the mitogenome of A. fujianica and lay the groundwork for future research on genetic variation, evolutionary relationships, and breeding of Orchidaceae.

Differential Adaptation of Biventricular Myocardial Kinetic Energy in Patients With Repaired Tetralogy of Fallot Assessed by MR Tissue Phase Mapping.

BACKGROUND: The myocardial kinetic energy (KE) and its association with pulmonary regurgitation (PR) have yet to be investigated in repaired tetralogy of Fallot (rTOF) patients. PURPOSE: To evaluate the adaptation of myocardial KE in rTOF patients by tissue phase mapping (TPM). STUDY TYPE: Prospective. POPULATION: A total of 49 rTOF patients (23 ± 5 years old; male = 32), 47 normal controls (22 ± 1 year old; male = 29). FIELD STRENGTH/SEQUENCE: 3-T/2D dark-blood three-directional velocity-encoded gradient-echo sequence. ASSESSMENT: Left and right ventricle (LV, RV) myocardial KE in radial (KEr ), circumferential (KEø ), longitudinal (KEz ) directions. The proportions of KE in each direction to the sum of all KE (KErøz ): %KEr , %KEø , %KEz . PR fraction. STATISTICAL TEST: Student's t test, multivariable regression. Statistical significance: P < 0.05. RESULTS: In rTOF group, LV KEz remained normal in systole (P = 0.565) and diastole (P = 0.210), whereas diastolic LV %KEz (62% ± 14% vs. 72% ± 7%) and systolic LV %KEø (9% ± 6% vs. 20% ± 7%) were significantly decreased. The KEr and %KEr of both ventricles significantly increased in the rTOF group (RV in diastole: 6 ± 3 vs. 3 ± 1 µJ and 54% ± 13% vs. 27% ± 7%). The rTOF group exhibited significantly higher RV/LV ratios of %KEr (systole: 1.3 ± 0.3 vs. 1.0 ± 0.3) and %KEø (systole: 1.6 ± 0.8 vs. 1.0 ± 0.3) and significantly lower ratios of %KEz in systole (0.7 ± 0.2 vs. 1.0 ± 0.1) and diastole (0.5 ± 0.2 vs. 0.9 ± 0.1). In multivariable regression analysis, the RV peak systolic KErøz , RV systolic KEz , and LV diastolic %KEø were independently associated with PR fraction in the rTOF group (adjusted R2  = 0.479). DATA CONCLUSION: In rTOF patients, the adaptation of the KE proportion occurred earlier than that of the KE amplitude, and the biventricular balance of %KE was disrupted. PR may cause differential KE adaptation in RV and LV. TPM-derived KE may be useful in investigation of myocardial adaptation in rTOF patients. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Apostasia Mitochondrial Genome Analysis and Monocot Mitochondria Phylogenomics.

Apostasia shenzhenica belongs to the subfamily Apostasioideae and is a primitive group located at the base of the Orchidaceae phylogenetic tree. However, the A. shenzhenica mitochondrial genome (mitogenome) is still unexplored, and the phylogenetic relationships between monocots mitogenomes remain unexplored. In this study, we discussed the genetic diversity of A. shenzhenica and the phylogenetic relationships within its monocotyledon mitogenome. We sequenced and assembled the complete mitogenome of A. shenzhenica, resulting in a circular mitochondrial draft of 672,872 bp, with an average read coverage of 122× and a GC content of 44.4%. A. shenzhenica mitogenome contained 36 protein-coding genes, 16 tRNAs, two rRNAs, and two copies of nad4L. Repeat sequence analysis revealed a large number of medium and small repeats, accounting for 1.28% of the mitogenome sequence. Selection pressure analysis indicated high mitogenome conservation in related species. RNA editing identified 416 sites in the protein-coding region. Furthermore, we found 44 chloroplast genomic DNA fragments that were transferred from the chloroplast to the mitogenome of A. shenzhenica, with five plastid-derived genes remaining intact in the mitogenome. Finally, the phylogenetic analysis of the mitogenomes from A. shenzhenica and 28 other monocots showed that the evolution and classification of most monocots were well determined. These findings enrich the genetic resources of orchids and provide valuable information on the taxonomic classification and molecular evolution of monocots.

OrchidBase 5.0: updates of the orchid genome knowledgebase.

Containing the largest number of species, the orchid family provides not only materials for studying plant evolution and environmental adaptation, but economically and culturally important ornamental plants for human society. Previously, we collected genome and transcriptome information of Dendrobium catenatum, Phalaenopsis equestris, and Apostasia shenzhenica which belong to two different subfamilies of Orchidaceae, and developed user-friendly tools to explore the orchid genetic sequences in the OrchidBase 4.0. The OrchidBase 4.0 offers the opportunity for plant science community to compare orchid genomes and transcriptomes and retrieve orchid sequences for further study.In the year 2022, two whole-genome sequences of Orchidoideae species, Platanthera zijinensis and Platanthera guangdongensis, were de novo sequenced, assembled and analyzed. In addition, systemic transcriptomes from these two species were also established. Therefore, we included these datasets to develop the new version of OrchidBase 5.0. In addition, three new functions including synteny, gene order, and miRNA information were also developed for orchid genome comparisons and miRNA characterization.OrchidBase 5.0 extended the genetic information to three orchid subfamilies (including five orchid species) and provided new tools for orchid researchers to analyze orchid genomes and transcriptomes. The online resources can be accessed at https://cosbi.ee.ncku.edu.tw/orchidbase5/.

Automated quantification of COVID-19 severity and progression using chest CT images.

OBJECTIVE: To develop and test computer software to detect, quantify, and monitor progression of pneumonia associated with COVID-19 using chest CT scans. METHODS: One hundred twenty chest CT scans from subjects with lung infiltrates were used for training deep learning algorithms to segment lung regions and vessels. Seventy-two serial scans from 24 COVID-19 subjects were used to develop and test algorithms to detect and quantify the presence and progression of infiltrates associated with COVID-19. The algorithm included (1) automated lung boundary and vessel segmentation, (2) registration of the lung boundary between serial scans, (3) computerized identification of the pneumonitis regions, and (4) assessment of disease progression. Agreement between radiologist manually delineated regions and computer-detected regions was assessed using the Dice coefficient. Serial scans were registered and used to generate a heatmap visualizing the change between scans. Two radiologists, using a five-point Likert scale, subjectively rated heatmap accuracy in representing progression. RESULTS: There was strong agreement between computer detection and the manual delineation of pneumonic regions with a Dice coefficient of 81% (CI 76-86%). In detecting large pneumonia regions (> 200 mm3), the algorithm had a sensitivity of 95% (CI 94-97%) and specificity of 84% (CI 81-86%). Radiologists rated 95% (CI 72 to 99) of heatmaps at least "acceptable" for representing disease progression. CONCLUSION: The preliminary results suggested the feasibility of using computer software to detect and quantify pneumonic regions associated with COVID-19 and to generate heatmaps that can be used to visualize and assess progression. KEY POINTS: • Both computer vision and deep learning technology were used to develop computer software to quantify the presence and progression of pneumonia associated with COVID-19 depicted on CT images. • The computer software was tested using both quantitative experiments and subjective assessment. • The computer software has the potential to assist in the detection of the pneumonic regions, monitor disease progression, and assess treatment efficacy related to COVID-19.

Any unique image biomarkers associated with COVID-19?

OBJECTIVE: To define the uniqueness of chest CT infiltrative features associated with COVID-19 image characteristics as potential diagnostic biomarkers. METHODS: We retrospectively collected chest CT exams including n = 498 on 151 unique patients RT-PCR positive for COVID-19 and n = 497 unique patients with community-acquired pneumonia (CAP). Both COVID-19 and CAP image sets were partitioned into three groups for training, validation, and testing respectively. In an attempt to discriminate COVID-19 from CAP, we developed several classifiers based on three-dimensional (3D) convolutional neural networks (CNNs). We also asked two experienced radiologists to visually interpret the testing set and discriminate COVID-19 from CAP. The classification performance of the computer algorithms and the radiologists was assessed using the receiver operating characteristic (ROC) analysis, and the nonparametric approaches with multiplicity adjustments when necessary. RESULTS: One of the considered models showed non-trivial, but moderate diagnostic ability overall (AUC of 0.70 with 99% CI 0.56-0.85). This model allowed for the identification of 8-50% of CAP patients with only 2% of COVID-19 patients. CONCLUSIONS: Professional or automated interpretation of CT exams has a moderately low ability to distinguish between COVID-19 and CAP cases. However, the automated image analysis is promising for targeted decision-making due to being able to accurately identify a sizable subsect of non-COVID-19 cases. KEY POINTS: • Both human experts and artificial intelligent models were used to classify the CT scans. • ROC analysis and the nonparametric approaches were used to analyze the performance of the radiologists and computer algorithms. • Unique image features or patterns may not exist for reliably distinguishing all COVID-19 from CAP; however, there may be imaging markers that can identify a sizable subset of non-COVID-19 cases.

Stability and efficacy of frozen and lyophilized fecal microbiota transplant (FMT) product in a mouse model of Clostridium difficile infection (CDI).

Freezing donor fecal microbiota has simplified fecal microbiota transplantation (FMT) in the treatment of recurrent C. difficile infection (CDI). However, the optimal storage time for the frozen FMT products remains unknown. Using an established murine model of CDI, stability and efficacy of frozen and lyophilized FMT product was studied at time points from 2 months to 15 months. DNA was extracted from fecal samples from the mice with identification of specific bacterial species by real-time quantitative PCR (qPCR). FMT product stability and efficacy were measured by occurrence of diarrhea in the challenged mice together with stability of the microbiota composition. The results were analyzed and compared by SAS statistical software. All mice treated with only C. difficile developed diarrhea within 72 h. Mice treated with frozen (n = 5/group), lyophilized (n = 5/group) products stored for ≤ 7-month or fresh FMT product (n = 22) were protected from post C. difficile challenge diarrhea. There was no difference between frozen and lyophilized products (n = 5/group) stored for ≤ 7 months 95% CI 1.00 (0.38-2.64) and 1.00 (0.38-2.64), respectively. Prevention if CDI by frozen and lyophilized product was not different for storage of 9-, 11- and 15-months. qPCR results demonstrated there were no significant quantitative change in Bacteroides and Clostridium species during any of the storage times (P > 0.05). In the present study, frozen and lyophilized FMT products were stored up to 7 months without losing microbiota composition and therapeutic efficacy. The animal model described may be useful to study stability of human microbiota designed for FMT.

FOXD1 promotes breast cancer proliferation and chemotherapeutic drug resistance by targeting p27.

Forkhead transcription factors are essential for diverse processes in early embryonic development and organogenesis. As a member of the forkhead family, FOXD1 is required during kidney development and its inactivation results in failure of nephron progenitor cells. However, the role of FOXD1 in carcinogenesis and progression is still limited. Here, we reported that FOXD1 is a potential oncogene in breast cancer. We found that FOXD1 is up-regulated in breast cancer tissues. Depletion of FOXD1 expression decreases the ability of cell proliferation and chemoresistance in MDA-MB-231 cells, whereas overexpression of FOXD1 increases the ability of cell proliferation and chemoresistance in MCF-7 cells. Furthermore, we observed that FOXD1 induces G1 to S phase transition by targeting p27 expression. Our results suggest that FOXD1 may be a potential therapy target for patients with breast cancer.

Interleukin-11 receptor α is overexpressed in human osteosarcoma, and near-infrared-labeled IL-11Rα imaging agent could detect osteosarcoma in mouse tumor xenografts.

IL-11Rα is an important cytokine receptor that links oxidative stress and compensatory proliferation. Mounting evidence has demonstrated that IL-11Rα regulates autoimmune demyelination and the invasion and proliferation of cancer cells, making it an important therapeutic target for molecular targeted therapy. Moreover, overexpression of IL-11Rα indicates a poor long-term prognosis in cancer patients. However, the expression status and its potential as a biomarker for diagnosis, tumor imaging, and prognosis in osteosarcoma remain to be determined. We report here that IL-11Rα is highly expressed in osteosarcoma and near-infrared (NIR)-labeled IL-11Rα imaging agent could detect osteosarcoma in mouse tumor xenografts. In a panel of human osteosarcoma specimens, IL-11Rα protein was positively stained in most cases by immunohistochemistry. Western blot analysis and flow cytometry showed that IL-11Rα was overexpressed in osteosarcoma SOSP-9607 cells. Cell-binding assay demonstrated specific binding of the IL-11Rα targeted imaging agent to osteosarcoma SOSP-9607 cells in vitro. In addition, administration of an IL-11Rα targeted imaging agent in a nude mice orthotopic model resulted in selective accumulation of NIR fluorescent signals in the bone tumor as well as several metabolic organs. These results indicate that IL-11Rα is a potential target for the development of molecular targeted therapy and noninvasive tumor imaging in human osteosarcoma. Furthermore, NIR-labeled IL-11Rα imaging agent is a promising lead for the development of a tumor in vivo imaging method at the molecular level in the management of human osteosarcoma.

Interleukin 6 augments lung cancer chemotherapeutic resistance via ataxia-telangiectasia mutated/NF-kappaB pathway activation.

Although it is known that ataxia-telangiectasia mutated (ATM) and interleukin 6 (IL-6) contribute to multiple drug resistance (MDR) in tumor chemotherapy, the exact role of ATM activation in MDR resulting from increased IL-6 expression is still unclear. In the present study, we demonstrate that the activation of the ATM-NF-kappaB pathway, resulting from increased IL-6 expression, plays a central role in augmented chemoresistance in lung cancer cell lines. This result was supported by the increased expressions of Bcl-2, Mcl-1, Bcl-xl, and the upregulation of MDR-associated protein ABCG2. The higher level of IL-6 reveals not only higher ATM/NF-kappaB activity but also increased expressions of ABCG2, Bcl-2, Mcl-1 and Bcl-xl. Most importantly, lung cancer cells themselves upregulated IL-6 secretion by activating the p38/NF-kappaB pathway through treatment with cisplatin and camptothecin. Taken together, these findings demonstrate that chemotherapeutic agents increase IL-6 expression, hence activating the ATM/NF-kappaB pathway, augmenting anti-apoptotic protein expression and contributing to MDR. This indicates that both IL-6 and ATM are potential targets for the treatment of chemotherapeutic resistance in lung cancer.

Deep learning assisted fluid volume calculation for assessing anti-vascular endothelial growth factor effect in diabetic macular edema.

Objective: To develop an algorithm using deep learning methods to calculate the volume of intraretinal and subretinal fluid in optical coherence tomography (OCT) images for assessing diabetic macular edema (DME) patients' condition changes. Design: Cross-sectional study. Participants: Treatment-naive patients diagnosed with DME recruited from April 2020 to November 2021. Methods: The deep learning network, which was built for autonomous segmentation utilizing an encoder-decoder network based on the U-Net architecture, was used to calculate the volume of intraretinal fluid (IRF) and subretinal fluid (SRF). The alterations of retinal vessel density and thickness, and the correlation between best-corrected visual acuity (BCVA) and OCT parameters were analyzed. Results: 2,955 OCT images of fourteen eyes from DME patients with IRF and SRF who received anti-vascular endothelial growth factor (VEGF) agents were obtained. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the algorithm was 0.993 for IRF and 0.998 for SRF. The volumes of IRF and SRF were significantly decreased from 1.93 ± 0.58 /1.14 ± 0.25 mm3 (baseline) to 0.26 ± 0.13 /0.26 ± 0.18 mm3 (post-injection), respectively (p = 0.0170 for IRF, and p = 0.0004 for SRF). The Spearman correlation demonstrated that the reduction of IRF volume was negatively correlated with age (coefficient = -0.698, p = 0.006). Conclusion: We developed a deep learning assisted fluid volume calculation algorithm with high sensitivity and specificity for assessing the volume of IRF and SRF in DME patients. Key words: deep learning; diabetic macular edema; optical coherence tomography.

Rapid quantification of phenobarbital and barbital in human whole blood by liquid-liquid extraction combined with DART-orbitrap-HRMS.

PURPOSE: This study aims to develop and validate a rapid, simple, and efficient bioanalytical method for the simultaneous quantification of phenobarbital and barbital in human whole blood using liquid-liquid extraction combined with direct analysis in real time (DART) and high-resolution mass spectrometry (HRMS). METHOD: Phenobarbital-d5 and aprobarbital were selected as internal standards (ISs) of phenobarbital and barbital, respectively. A mixed solvent of o-xylene and ethyl acetate at a ratio of 1:6 was used to extract analytes of interest and ISs from 100 µL of human whole blood samples. Phenobarbital and barbital were detected by DART-HRMS. The proposed method has been validated in accordance with United States Food and Drug Administration Guidelines for Bioanalytical Method Validation in terms of selectivity, linearity, accuracy, precision, matrix effect, recovery, stability, and dilution integrity. RESULTS: The lower limits of quantification (LLOQs) of phenobarbital and barbital were both 10 ng/mL. The linearities were in the range of 10-1000 ng/mL (R2 ≥ 0.99). The mean recovery values of phenobarbital and barbital were 99.7% and 88.1%, respectively. The interday and intraday precision values were less than 10.4%, and the interday and intraday accuracy values ranged from 87.6 to 106.7%. Furthermore, the validated method was applied to four cases of phenobarbital poisoning at the Shanghai Institute of Forensic Science. CONCLUSION: The developed and fully validated method enabled the simultaneous quantification of phenobarbital and barbital in human whole blood and was successfully applied to authentic cases.

Vegetable Intake, but Not Fruit Intake Is Inversely Associated With Fasting Plasma Glucose in Kidney Transplant Recipients.

BACKGROUND: The association between dietary intake and glycemic control has been extensively investigated in type 2 diabetes. However, little is known about this association in kidney transplant recipients (KTRs). METHODS: We performed an observational study involving 263 adult KTRs with a functioning allograft for at least 1 year at the outpatient clinic of the Hospital from November 2020 to March 2021. Dietary intake was assessed by food frequency questionnaire. Linear regression analyses were performed to evaluate the association between fruit and vegetable intake and fasting plasma glucose. RESULTS: The vegetable and fruit intake were 238.24 g/d (102.38-416.67) and 511.94 g/d (321.19-849.05), respectively. The fasting plasma glucose was 5.15 ± 0.95 mmol/L. The linear regressions revealed that vegetable intake, but not fruit intake was inversely associated with fasting plasma glucose in KTRs (adjusted R2 = 0.203, P < .001). The clear dose-response relation was observed. Moreover, each 100 g increase in vegetable intake was associated with 11.6% reduction of fasting plasma glucose. CONCLUSIONS: Vegetable intake, but not fruit intake, is inversely associated with fasting plasma glucose in KTRs.

The value of serum TRAP1 in diagnosing small cell lung cancer and tumor immunity.

This study set out to investigate the clinical significance of serum tumor necrosis factor receptor-associated protein 1 (TRAP1) in diagnosing small cell lung cancer (SCLC) with different clinical stages, and to compare the diagnostic efficiency with neuron-specific enolase (NSE), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9). Besides, to analyze the role of serum TRAP1 in tumor immunity. A total of 91 patients with SCLC, 99 patients with non-small cell lung cancer (NSCLC), 102 patients with pulmonary nodules (PN), and 75 healthy people were included. The concentrations of serum TRAP1 was detected by enzyme-linked immunosorbent assay (ELISA). NSE, CEA, and CA19-9 were detected by chemiluminescence. The results showed that level of TRAP1 in Group SCLC was lower than other three groups (P < 0.01), whereas NSE in SCLC was significantly higher than the others (P < 0.01), and the levels of CEA and CA19-9 were higher than healthy people and PN patients (P < 0.01). There was a significant difference in TRAP1 levels between patients with limited-stage disease SCLC (LD-SCLC) and extensive-stage disease SCLC (ED-SCLC) (P < 0.0001). The sensitivity and specificity of TRAP1 in diagnosing LD-SCLC were 0.964 and 0.560, respectively, and the area under the curve (AUC) was 0.819. The sensitivity and specificity in diagnosing ED-SCLC were 0.810 and 0.868, respectively, and the AUC was 0.933, which showed high diagnostic value. The AUC of these two groups can be increased to 0.946 and 0.947 in combination of four biomarkers, effectively improving the diagnosis rate of SCLC. Our findings have revealed that serum TRAP1 has high diagnostic value for SCLC and high diagnostic sensitivity for LD-SCLC. It is a potential biomarker for SCLC. Combined detection can effectively improve the diagnosis rate of SCLC. TRAP1 may be secreted into the circulation by mature immune cells and participates in tumor immunity as a carrier of tumor antigens.

Bibliometric and visualized analysis of applying tumor markers in lung cancer diagnosis from 2000 to 2022.

Background: Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Tumor marker (TM) detection can indicate the existence and growth of a tumor and has therefore been used extensively for diagnosing LC. Here, we conducted a bibliometric analysis to examine TM-related publications for LC diagnosis to illustrate the current state and future trends of this field, as well as to identify additional promising TMs with high sensitivity. Methods: Publications regarding TMs in LC diagnosis were downloaded from the Web of Science Core Collection. CiteSpace was applied to perform a bibliometric analysis of journals, cocitation authors, keywords, and references related to this field. VOSviewer was used to generate concise diagrams about countries, institutions, authors, and keywords. Changes in the TM research frontier were analyzed through citation burst detection. Results: A total of 990 studies were analyzed in this work. The collaboration network analysis revealed that the People's Republic of China, Yonsei University, and Molina R were the most productive country, institution, and scholar, respectively. Additionally, Molina R was the author with the most citations. The National Natural Science Foundation of China was the largest funding source. "Carcinoembryonic antigen (CEA) as tumor marker in lung cancer" was the top reference with the most citations, Lung Cancer was the core journal, and "serum tumor marker" experienced a citation burst over the past 5 years. Conclusion: This bibliometric analysis of TMs in LC diagnosis presents the current trends and frontiers in this field. We summarized the research status of this field and the methods to improve the diagnostic efficacy of traditional serum TMs, as well as provided new directions and ideas for improving the LC clinical detection rate. Priority should be given to the transformation of computer-assisted diagnostic technology for clinical applications. In addition, circulating tumor cells, exosomes, and microRNAs were the current most cutting-edge TMs.

Developing fluorescent hyaluronan analogs for hyaluronan studies.

Two kinds of fluorescent hyaluronan (HA) analogs, one serving as normal imaging agent and the other used as a biosensitive contrast agent, were developed for the investigation of HA uptake and degradation. Our approach of developing HA imaging agents depends on labeling HA with varying molar percentages of a near-infrared (NIR) dye. At low labeling ratios, the hyaluronan uptake can be directly imaged while at high labeling ratios, the fluorescent signal is quenched and signal generation occurs only after degradation. It is found that the conjugate containing 1%-2% NIR dye can be used as a normal optical imaging agent, while bioactivable imaging agents are formed at 6% to 17% dye loading. It was determined that the conjugation of dye to HA with different loading percentages does not impact HA biodegradation by hyaluronidase (Hyal). The feasibility of using these two NIR fluorescent hyaluronan analogs for HA investigation was evaluated in vivo with optical imaging. The data demonstrates that the 1% dye loaded fluorescent HA can be used to monitor the behavior of HA and its fragments, whereas bioactivatable HA imaging agent (17% dye in HA) is more suitable for detecting HA fragments.

Advances and prospects of orchid research and industrialization.

Orchidaceae is one of the largest, most diverse families in angiosperms with significant ecological and economical values. Orchids have long fascinated scientists by their complex life histories, exquisite floral morphology and pollination syndromes that exhibit exclusive specializations, more than any other plants on Earth. These intrinsic factors together with human influences also make it a keystone group in biodiversity conservation. The advent of sequencing technologies and transgenic techniques represents a quantum leap in orchid research, enabling molecular approaches to be employed to resolve the historically interesting puzzles in orchid basic and applied biology. To date, 16 different orchid genomes covering four subfamilies (Apostasioideae, Vanilloideae, Epidendroideae, and Orchidoideae) have been released. These genome projects have given rise to massive data that greatly empowers the studies pertaining to key innovations and evolutionary mechanisms for the breadth of orchid species. The extensive exploration of transcriptomics, comparative genomics, and recent advances in gene engineering have linked important traits of orchids with a multiplicity of gene families and their regulating networks, providing great potential for genetic enhancement and improvement. In this review, we summarize the progress and achievement in fundamental research and industrialized application of orchids with a particular focus on molecular tools, and make future prospects of orchid molecular breeding and post-genomic research, providing a comprehensive assemblage of state of the art knowledge in orchid research and industrialization.

Corresponding Changes of Autophagy-Related Genes and Proteins in Different Stages of Knee Osteoarthritis: An Animal Model Study.

OBJECTIVE: To investigate the effect of autophagy expression levels of different weight-bearing states and different stages of osteoarthritis in animal models, as well as the corresponding mechanisms. METHODS: We used the male Sprague-Dawley (SD) rats (12-week-old, SPF) to establish the OA animal models by modified Hulth method, and grouped animal models according to the length of time after surgery and different weight-bearing areas. RT-qPCR was carried out for detection of autophagy-related genes such as Atg7, Atg12, P62, etc. Western blot analysis was used to detect the expression levels of corresponding autophagy-related proteins such as LC3B, P62, etc. T test was performed for statistical analysis to compare different groups, while the differences were deemed statistically significant with P < 0.05. Transmission electron microscopy was used to observe the autophagosome to demonstrate the level of autophagy expression and the status of the chondrocytes. RESULTS: The results of the RT-qPCR testing showed that when the weight-bearing cartilage of the 4-week group (relatively mild) was compared with that of the 10-week group (relatively severe), there were statistically significant differences in all the genes tested, in detail: Atg3 (P < 0.01), Atg7 (P < 0.01), Atg12 (P < 0.01), P62 (P < 0.0001). The expression of autophagy-related mRNA in the 4-week group is increased compared with that of the 10-week group. As for the expression of proteins, Western blotting showed that in the comparison between the 4- and the 10-week groups, statistically significant results include Atg12 (P < 0.01) in the non-weight-bearing area, with decreased autophagy in the 10-week group compared with that of the 4-week group, while expression of LC3B (P < 0.05) protein was significantly higher in the 4-week group than in the control in the non-weight-bearing area. The expression of LC3B (P < 0.0001) and P62 (P < 0.05) in the 10-week group were higher than that of the control. Transmission electron microscope showed that autophagy in the weight-bearing area is stronger than that in the non-weight-bearing area, and autophagy in the 4-week group is stronger than in the 10-week group for the weight-bearing area. CONCLUSIONS: The expression of autophagy varies during different stages of osteoarthritis, in which the autophagy is stronger in the early stage of osteoarthritis, and gradually decreases with the progression of the disease. Autophagy in different weight-bearing areas may also be different.

Identification of CDPKs involved in TaNOX7 mediated ROS production in wheat.

As the critical sensors and decoders of calcium signal, calcium-dependent protein kinase (CDPK) has become the focus of current research, especially in plants. However, few resources are available on the properties and functions of CDPK gene family in Triticum aestivum (TaCDPK). Here, a total of 79 CDPK genes were identified in the wheat genome. These TaCDPKs could be classified into four subgroups on phylogenesis, while they may be classified into two subgroups based on their tissue and organ-spatiotemporal expression profiles or three subgroups according to their induced expression patterns. The analysis on the signal network relationships and interactions of TaCDPKs and NADPH (reduced nicotinamide adenine dinucleotide phosphate oxidases, NOXs), the key producers for reactive oxygen species (ROS), showed that there are complicated cross-talks between these two family proteins. Further experiments demonstrate that, two members of TaCDPKs, TaCDPK2/4, can interact with TaNOX7, an important member of wheat NOXs, and enhanced the TaNOX7-mediated ROS production. All the results suggest that TaCDPKs are highly expressed in wheat with distinct tissue or organ-specificity and stress-inducible diversity, and play vital roles in plant development and response to biotic and abiotic stresses by directly interacting with TaNOXs for ROS production.

Torsional Fatigue Life Prediction of 30CrMnSiNi2A Based on Meso-Inhomogeneous Deformation.

In this paper, torsional fatigue failure of 30CrMnSiNi2A steel which exhibited non-Masing behavior was studied under different constant shear strain amplitudes, using thin-walled tubular specimens. The relationship between shear fatigue and the evolution of meso-deformation inhomogeneity and the prediction method of the torsional fatigue life curve were investigated. Shear fatigue of the material under constant amplitude was researched by numerical simulation with reference to tests, by using crystal plasticity of polycrystalline representative volume element (RVE) as the material model. Considering the non-Masing behavior of material, when determining the parameter values of the crystal plasticity model the correlation between these parameters and strain amplitude was taken into account. The meso-deformation inhomogeneity with increments in the number of cycles was characterized by using the statistical shear strain standard deviation of RVE as the basic parameter. Considering the effect of strain amplitude on fatigue damage, ratio cycle peak stress/yield stress was taken as the weight to measure the torsional fatigue damage and an improved fatigue indicator parameter (FIP) to measure the inhomogeneous deformation of the material was proposed. The torsional fatigue life curve of 30CrMnSiNi2A steel was predicted by the critical value of the FIP and then the result was confirmed.