Molecular evolution of Phytocyanin gene and analysis of expression at different coloring periods in apple (Malus domestica).

BACKGROUND: PC (phytocyanin) is a class of copper-containing electron transfer proteins closely related to plant photosynthesis, abiotic stress responses growth and development in plants, and regulation of the expression of some flavonoids and phenylpropanoids, etc., however, compared with other plants, the PC gene family has not been systematically characterized in apple. RESULTS: A total of 59 MdPC gene members unevenly distributed across 12 chromosomes were identified at the genome-wide level. The proteins of the MdPC family were classified into four subfamilies based on differences in copper binding sites and glycosylation sites: Apple Early nodulin-like proteins (MdENODLs), Apple Uclacyanin-like proteins (MdUCLs), Apple Stellacyanin-like proteins (MdSCLs), and Apple Plantacyanin-like proteins (MdPLCLs). Some MdPC members with similar gene structures and conserved motifs belong to the same group or subfamily. The internal collinearity analysis revealed 14 collinearity gene pairs among members of the apple MdPC gene. Interspecific collinearity analysis showed that apple had 31 and 35 homologous gene pairs with strawberry and grape, respectively. Selection pressure analysis indicated that the MdPC gene was under purifying selection. Prediction of protein interactions showed that MdPC family members interacted strongly with the Nad3 protein. GO annotation results indicated that the MdPC gene also regulated the biosynthesis of phenylpropanoids. Chip data analysis showed that (MdSCL3, MdSCL7 and MdENODL27) were highly expressed in mature fruits and peels. Many cis-regulatory elements related to light response, phytohormones, abiotic stresses and flavonoid biosynthetic genes regulation were identified 2000 bp upstream of the promoter of the MdPC gene, and qRT-PCR results showed that gene members in Group IV (MdSCL1/3, MdENODL27) were up-regulated at all five stages of apple coloring, but the highest expression was observed at the DAF13 (day after fruit bag removal) stage. The gene members in Group II (MdUCL9, MdPLCL3) showed down-regulated or lower expression in the first four stages of apple coloring but up-regulated and highest expression in the DAF 21 stage. CONCLUSION: Herein, one objective of these findings is to provide valuable information for understanding the structure, molecular evolution, and expression pattern of the MdPC gene, another major objective in this study was designed to lay the groundwork for further research on the molecular mechanism of PC gene regulation of apple fruit coloration.

The asymmetric expression of plasma membrane H+-ATPase family genes in response to pulvinus-driven leaf phototropism movement in Vitis vinifera.

Phototropism movement is crucial for plants to adapt to various environmental changes. Plant P-type H+-ATPase (HA) plays diverse roles in signal transduction during cell expansion, regulation of cellular osmotic potential and stomatal opening, and circadian movement. Despite numerous studies on the genome-wide analysis of Vitis vinifera, no research has been done on the P-type H+-ATPase family genes, especially concerning pulvinus-driven leaf movement. In this study, 55 VvHAs were identified and classified into nine distinct subgroups (1 to 9). Gene members within the same subgroups exhibit similar features in motif, intron/exon, and protein tertiary structures. Furthermore, four pairs of genes were derived by segmental duplication in grapes. Cis-acting element analysis identified numerous light/circadian-related elements in the promoters of VvHAs. qRT-PCR analysis showed that several genes of subgroup 7 were highly expressed in leaves and pulvinus during leaf movement, especially VvHA14, VvHA15, VvHA16, VvHA19, VvHA51, VvHA52, and VvHA54. Additionally, we also found that the VvHAs genes were asymmetrically expressed on both sides of the extensor and flexor cell of the motor organ, the pulvinus. The expression of VvHAs family genes in extensor cells was significantly higher than that in flexor cells. Overall, this study serves as a foundation for further investigations into the functions of VvHAs and contributes to the complex mechanisms underlying grapevine pulvinus growth and development.

Proteomic characteristics of the treatment trajectory of patients with COVID-19.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has prompted global concern due to its profound impact on public health and the economy. Effective treatment of COVID-19 patients in the acute phase or of those with long COVID is a major challenge. Using data-independent acquisition (DIA) technology, we performed proteomic profiling on plasma samples from 22 COVID-19 patients and six healthy controls at Dazhou Central Hospital. Random forest and least absolute shrinkage and selection operator algorithms were used for analysis at various COVID-19 treatment stages. We identified 79 proteins that were differentially expressed between COVID-19 patients and healthy controls, mainly involving pathways associated with cell processes and binding. Across different treatment stages of COVID-19, five proteins-PI16, GPLD1, IGFBP3, KRT19, and VCAM1-were identified as potential molecular markers for dynamic disease monitoring. Furthermore, the proteins BTD, APOM, IGKV2-28, VWF, C4BPA, and C7 were identified as candidate biomarkers for distinguishing between SARS-CoV-2 positivity and negativity. Analysis of protein change profiles between the follow-up and healthy control groups highlighted cardiovascular changes as a concern for patients recovering from COVID-19. Our study revealed the infection profiles of SARS-CoV-2 at the protein expression level comparing different phases of COVID-19. DIA mass spectrometry analysis of plasma samples from COVID-19 patients undergoing treatment identified key proteins involved in signaling pathways that might be used as markers of the recovery phase. These findings provide insight for the development of therapy options and suggest potential blood biomarkers for COVID-19.

Mechanism of the Pulvinus-Driven Leaf Movement: An Overview.

Leaf movement is a manifestation of plant response to the changing internal and external environment, aiming to optimize plant growth and development. Leaf movement is usually driven by a specialized motor organ, the pulvinus, and this movement is associated with different changes in volume and expansion on the two sides of the pulvinus. Blue light, auxin, GA, H+-ATPase, K+, Cl-, Ca2+, actin, and aquaporin collectively influence the changes in water flux in the tissue of the extensor and flexor of the pulvinus to establish a turgor pressure difference, thereby controlling leaf movement. However, how these factors regulate the multicellular motility of the pulvinus tissues in a species remains obscure. In addition, model plants such as Medicago truncatula, Mimosa pudica, and Samanea saman have been used to study pulvinus-driven leaf movement, showing a similarity in their pulvinus movement mechanisms. In this review, we summarize past research findings from the three model plants, and using Medicago truncatula as an example, suggest that genes regulating pulvinus movement are also involved in regulating plant growth and development. We also propose a model in which the variation of ion flux and water flux are critical steps to pulvinus movement and highlight questions for future research.

Physiological, biochemical and molecular responses associated with drought tolerance in grafted grapevine.

BACKGROUND: Grafting is one of the promising techniques for improving abiotic stress tolerance in horticultural crops, but the underlying regulatory mechanisms of drought on grafted grapevine are largely unexplored. RESULTS: Herein, we investigated the phenotypic, physiologic, biochemical, and drought related genes change of self-rooted 1103P (1103 Paulsen), SM (Shine Muscat) and grafted SM/1103P (SM shoot/1103P root) under drought stress condition. The results indicated that grafted grapevine effectively alleviated drought damage in grape leaves by higher RWC, water potential and free water content. Drought stress led to the alterations of chlorophyll, carotenoid, photosynthetic parameters and chlorophyll fluorescence in grapevine leaves after drought treatment indicated grafted plants improved the photosystem response to drought stress. Moreover, grafted plants under drought stress exhibited higher levels of abscisic acid (ABA), indoleacetic acid (IAA) and soluble protein, but less contents of hydrogen peroxide (H2O2) and malondialdehyde (MDA) both in leaves and roots. Drought stress also increased the activities of antioxidant enzymes (SOD, POD and CAT) and activated the transcript expression of VvCu/ZnSOD, VvPOD4 and VvCAT1) in both leaves and roots. Further expression analysis by real-time PCR indicated that the expression levels of ABA-dependent and ABA-independent related genes could be activated in grafted grape after drought treatment. CONCLUSIONS: Taken together, our findings demonstrated that grafting onto 1103P enhanced tolerance against drought stress in grape by improving water content, photosynthesis and antioxidant defense capacity, which provided a valuable information for understanding the mechanisms of drought tolerance regulated by grafting plants.

Comparison of Operative Time Between Robotic and Laparoscopic Low Anterior Resection for Rectal Cancer:A Systematic Review and Meta-Analysis.

Background. Previous studies have shown that the robotic approach has better perioperative outcomes but longer operative time than the laparoscopic approach for patients undergoing low anterior resection. However, the impact of the learning curve on operative time is controversial. This study aimed to evaluate operative time and associated outcomes by comparing robotic low anterior resection (R-LAR) with laparoscopic low anterior resection (L-LAR). Methods. Pubmed, Embase, Cochrane Library, Ovid, Web of Science, and CNKI databases were interrogated from the inception to April 2021. Two authors screened all records through full-text reading and extracted and synthesized the data using a structured table. A random-effect model was used to evaluate heterogeneity. Meta-analysis was implemented by R 4.1.1 meta-package. Results. Twelve studies (1684 patients) were included in the present review. R-LAR compare to L-LAR approach has significant differences in operative time (min) (MD = 23.14, 95% CI: 6.89-39.40, P < .01), blood loss (mL) (MD = -42.66, 95% CI: [-68.51, -16.81], P < .01), number of lymph nodes harvested (MD = 1.06, 95% CI: [.16; 1.97], P < .05). Sensitivity analysis of the number of lymph nodes harvested indicated that the overall effect might not be stable. Subgroup analysis showed that mean age and sample size of R-LAR were 2 important factors affecting the estimation. Conclusions. Our results presented a prolonged operative time with the robotic approach compared to laparoscopy, but this gap diminished as the sample size increased. It might be more timesaving once surgeons are familiar with surgical robots.

Impact of negative pressure wound treatment on incidence of surgical site infection in varied orthopedic surgeries: A systematic review and meta-analysis.

Negative pressure wound therapy (NPWT) is a popular treatment to heal infected wounds. This meta-analysis aimed to determine if NPWT was more effective than conventional wound dressings for surgical site infections (SSI) in varied orthopaedic surgeries. Literature was retrieved from seven electronic databases (Medline, Web of Science, PubMed, Embase, Google Scholar, Cochrane Library, and CNKI). Randomised control trials (RCT) and retrospective cohort studies (RS) involving arthroplasty, fracture, and spinal surgery were extracted. SSI was our primary outcome, while total complications and length of hospital stay were secondary outcomes. We carried out the risk of bias assessment and meta-analysis using the Cochrane Risk of Bias 2.0 tool and Stata 17.0. Among the 798 studies retrieved, 18 of them met our inclusion criteria. We identified 13 RCTs and 5 RSs. The results of meta-analysis showed that the incidence of SSI in the NPWT group was significantly lower relative to the control group (OR = 0.60, 95% CI 0.47 to 0.77, P < 0.001). Subgroup analyses revealed that the incidences of SSI involving arthroplasty, fracture, and spinal surgery in the NPWT group accounted for 46%, 69%, and 37% relative to the control group, respectively. The incidence of SSI in RS (OR = 0.27, 95% CI 0.13 to 0.56) was significantly lower than that in RCT (OR = 0.69, 95% CI 0.54 to 0.90) (P = 0.02). Moreover, patients in the NPWT group had a lower total complication rate (OR = 0.51, 95% CI 0.34 to 0.76) and shorter hospital stays (SMD = -0.42, 95% CI -0.83 to -0.02), although high heterogeneity existed. NPWT may be an efficient alternative to help prevent the incidence of SSI and total complications as well as achieved shorten hospital stay in varied orthopaedic surgeries. The rational use of NPWT should be based on the presence of patients' clinical conditions and relevant risk factors.

Identification of upper GI diseases during screening gastroscopy using a deep convolutional neural network algorithm.

BACKGROUND AND AIMS: The clinical application of GI endoscopy for the diagnosis of multiple diseases using artificial intelligence (AI) has been limited by its high false-positive rates. There is an unmet need to develop a GI endoscopy AI-assisted diagnosis system (GEADS) to improve diagnostic accuracy and clinical utility. METHODS: In this retrospective, multicenter study, a convolutional neural network was trained to assess upper GI diseases based on 26,228 endoscopic images from Dazhou Central Hospital that were randomly assigned (3:1:1) to a training dataset, validation dataset, and test dataset, respectively. To validate the model, 6 external independent datasets comprising 51,372 images of upper GI diseases were collected. In addition, 1 prospective dataset comprising 27,975 images was collected. The performance of GEADS was compared with endoscopists with 2 professional degrees of expertise: expert and novice. Eight endoscopists were in the expert group with >5 years of experience, whereas 3 endoscopists were in the novice group with 1 to 5 years of experience. RESULTS: The GEADS model achieved an accuracy of .918 (95% confidence interval [CI], .914-.922), with an F1 score of .884 (95% CI, .879-.889), recall of .873 (95% CI, .868-.878), and precision of .890 (95% CI, .885-.895) in the internal validation dataset. In the external validation datasets and 1 prospective validation dataset, the diagnostic accuracy of the GEADS ranged from .841 (95% CI, .834-.848) to .949 (95% CI, .935-.963). With the help of the GEADS, the diagnosing accuracies of novice and expert endoscopists were significantly improved (P < .001). CONCLUSIONS: The AI system can assist endoscopists in improving the accuracy of diagnosing upper GI diseases.

The deubiquitinase USP6 affects memory and synaptic plasticity through modulating NMDA receptor stability.

Ubiquitin-specific protease (USP) 6 is a hominoid deubiquitinating enzyme previously implicated in intellectual disability and autism spectrum disorder. Although these findings link USP6 to higher brain function, potential roles for USP6 in cognition have not been investigated. Here, we report that USP6 is highly expressed in induced human neurons and that neuron-specific expression of USP6 enhances learning and memory in a transgenic mouse model. Similarly, USP6 expression regulates N-methyl-D-aspartate-type glutamate receptor (NMDAR)-dependent long-term potentiation and long-term depression in USP6 transgenic mouse hippocampi. Proteomic characterization of transgenic USP6 mouse cortex reveals attenuated NMDAR ubiquitination, with concomitant elevation in NMDAR expression, stability, and cell surface distribution with USP6 overexpression. USP6 positively modulates GluN1 expression in transfected cells, and USP6 down-regulation impedes focal GluN1 distribution at postsynaptic densities and impairs synaptic function in neurons derived from human embryonic stem cells. Together, these results indicate that USP6 enhances NMDAR stability to promote synaptic function and cognition.

Development and validation of a machine learning-derived radiomics model for diagnosis of osteoporosis and osteopenia using quantitative computed tomography.

BACKGROUND: To develop and validate a quantitative computed tomography (QCT) based radiomics model for discriminating osteoporosis and osteopenia. METHODS: A total of 635 patients underwent QCT were retrospectively included from November 2016 to November 2019. The patients with osteopenia or osteoporosis (N = 590) were divided into a training cohort (N = 414) and a test cohort (N = 176). Radiomics features were extracted from the QCT images of the third lumbar vertebra. Minimum redundancy and maximum relevance and least absolute shrinkage and selection operator were used for data dimensional reduction, features selection and radiomics model building. Multivariable logistic regression was applied to construct the combined clinical-radiomic model that incorporated radiomics signatures and clinical characteristics. The performance of the combined clinical-radiomic model was evaluated by the area under the curve of receiver operator characteristic curve (ROC-AUC), accuracy, specificity, sensitivity, positive predictive value, and negative predictive value. RESULTS: The patients with osteopenia or osteoporosis were randomly divided into training and test cohort with a ratio of 7:3. Six more predictive radiomics signatures, age, alkaline phosphatase and homocysteine were selected to construct the combined clinical-radiomic model for diagnosis of osteoporosis and osteopenia. The AUC of the combined clinical-radiomic model was 0.96 (95% confidence interval (CI), 0.95 to 0.98) in the training cohort and 0.96 (95% CI 0.92 to 1.00) in the test cohort, which were superior to the clinical model alone (training-AUC = 0.81, test-AUC = 0.79). The calibration curve demonstrated that the radiomics nomogram had good agreement between prediction and observation and decision curve analysis confirmed clinically useful. CONCLUSIONS: The combined clinical-radiomic model that incorporates the radiomics score and clinical risk factors, can serve as a reliable and powerful tool for discriminating osteoporosis and osteopenia.