Tremendously enhanced catalytic performance of Fe(III)/peroxymonosulfate process by trace Cu(II): A high-valent metals domination in organics removal.

Dissolved copper and iron ions are regarded as friendly and economic catalysts for peroxymonosulfate (PMS) activation, however, neither Cu(II) nor Fe(III) shows efficient catalytic performance because of the slow rates of Cu(II)/Cu(I) and Fe(III)/Fe(II) cycles. Innovatively, we observed a significant enhancement on the degradation of organic contaminants when Cu(II) and Fe(III) were coupled to activate PMS in borate (BA) buffer. The degradation efficiency of Rhodamine B (RhB, 20 µmol/L) reached up to 96.3% within 10 min, which was higher than the sum of individual Cu(II)- and Fe(III)- activated PMS process. Sulfate radical, hydroxyl radical and high-valent metal ions (i.e., Cu(III) and Fe(IV)) were identified as the working reactive species for RhB removal in Cu(II)/Fe(III)/PMS/BA system, while the last played a predominated role. The presence of BA dramatically facilitated the reduction of Cu(II) to Cu(I) via chelating with Cu(II) followed by Fe(III) reduction by Cu(I), resulting in enhanced PMS activation by Cu(I) and Fe(II) as well as accelerated generation of reactive species. Additionally, the strong buffering capacity of BA to stabilize the solution pH was satisfying for the pollutants degradation since a slightly alkaline environment favored the PMS activation by coupling Cu(II) and Fe(III). In a word, this work provides a brand-new insight into the outstanding PMS activation by homogeneous bimetals and an expanded application of iron-based advanced oxidation processes in alkaline conditions.

Shapley Values-enabled Progressive Pseudo Bag Augmentation for Whole-Slide Image Classification.

In computational pathology, whole-slide image (WSI) classification presents a formidable challenge due to its gigapixel resolution and limited fine-grained annotations. Multiple-instance learning (MIL) offers a weakly supervised solution, yet refining instance-level information from bag-level labels remains challenging. While most of the conventional MIL methods use attention scores to estimate instance importance scores (IIS) which contribute to the prediction of the slide labels, these often lead to skewed attention distributions and inaccuracies in identifying crucial instances. To address these issues, we propose a new approach inspired by cooperative game theory: employing Shapley values to assess each instance's contribution, thereby improving IIS estimation. The computation of the Shapley value is then accelerated using attention, meanwhile retaining the enhanced instance identification and prioritization. We further introduce a framework for the progressive assignment of pseudo bags based on estimated IIS, encouraging more balanced attention distributions in MIL models. Our extensive experiments on CAMELYON-16, BRACS, TCGA-LUNG, and TCGA-BRCA datasets show our method's superiority over existing state-of-the-art approaches, offering enhanced interpretability and class-wise insights. We will release the code upon acceptance.

Enhancing lithium storage performance with silicon-based anodes: a theoretical study on transition metal-integrated SiOx/M@C (M = Fe, Co, Ni) heterostructures.

In lithium-ion batteries, infusible metals with lithium, such as Mg, Fe, Co, Ni, and Cu are often utilized. However, current research predominantly focuses on the experimental aspects of the (de)lithiation process, with limited exploration from a theoretical calculation perspective. The extensive use of experimental methods to study the many electrochemically inert metals is time-consuming and costly. In this study, we successfully constructed and optimized SiOx/M@C (M = Fe, Co, Ni) heterostructures, integrating transition metal nanoparticles to address the electrochemical inertness and slow diffusion kinetics of pristine SiOx. A comprehensive density functional theory (DFT) study was conducted to examine the effects of different metal heterostructures on the structural, migration potential energy, and adsorption properties during lithium-ion intercalation. The results demonstrate that the SiOx/Fe@C heterostructure exhibits the lowest migration energy barrier, significantly enhancing lithium-ion transport compared to SiOx/Co@C and SiOx/Ni@C. Consequently, the SiOx/Fe@C electrode shows superior high-rate discharge capability and excellent cycling performance through electrochemical measurements. Additionally, the study delves into the intrinsic mechanisms through charge density differences and Fermi level calculations, providing valuable insights into the importance of hybrid strategies for incorporating inert metals into anode materials for lithium-ion batteries.

Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learning.

BACKGROUND: Thyroid cancer is a common thyroid malignancy. The majority of thyroid lesion needs intraoperative frozen pathology diagnosis, which provides important information for precision operation. As digital whole slide images (WSIs) develop, deep learning methods for histopathological classification of the thyroid gland (paraffin sections) have achieved outstanding results. Our current study is to clarify whether deep learning assists pathology diagnosis for intraoperative frozen thyroid lesions or not. METHODS: We propose an artificial intelligence-assisted diagnostic system for frozen thyroid lesions that applies prior knowledge in tandem with a dichotomous judgment of whether the lesion is cancerous or not and a quadratic judgment of the type of cancerous lesion to categorize the frozen thyroid lesions into five categories: papillary thyroid carcinoma, medullary thyroid carcinoma, anaplastic thyroid carcinoma, follicular thyroid tumor, and non-cancerous lesion. We obtained 4409 frozen digital pathology sections (WSI) of thyroid from the First Affiliated Hospital of Sun Yat-sen University (SYSUFH) to train and test the model, and the performance was validated by a six-fold cross validation, 101 papillary microcarcinoma sections of thyroid were used to validate the system's sensitivity, and 1388 WSIs of thyroid were used for the evaluation of the external dataset. The deep learning models were compared in terms of several metrics such as accuracy, F1 score, recall, precision and AUC (Area Under Curve). RESULTS: We developed the first deep learning-based frozen thyroid diagnostic classifier for histopathological WSI classification of papillary carcinoma, medullary carcinoma, follicular tumor, anaplastic carcinoma, and non-carcinoma lesion. On test slides, the system had an accuracy of 0.9459, a precision of 0.9475, and an AUC of 0.9955. In the papillary carcinoma test slides, the system was able to accurately predict even lesions as small as 2 mm in diameter. Tested with the acceleration component, the cut processing can be performed in 346.12 s and the visual inference prediction results can be obtained in 98.61 s, thus meeting the time requirements for intraoperative diagnosis. Our study employs a deep learning approach for high-precision classification of intraoperative frozen thyroid lesion distribution in the clinical setting, which has potential clinical implications for assisting pathologists and precision surgery of thyroid lesions.

The value of FPR, FAR, CAR, CPR in the auxiliary diagnosis of colon cancer.

Chronic malnutrition, abnormal blood clotting, and systemic inflammation contribute to the occurrence and progression of colon cancer. This study aimed to assess the diagnostic utility of the 100fibrinogen-to-prealbumin ratio (FPR), 100fibrinogen-to-albumin ratio (FAR), 100C-reactive protein-to-albumin ratio (CAR), and 100C-reactive protein-to-prealbumin ratio (CPR) in aiding the diagnosis of colon cancer. A total of 129 patients with colon cancer were enrolled between April 2015 and August 2022. While 129 patients with colon adenoma were selected as the control group. The serum levels of FAR, FPR, CAR, CPR, CEA, and CA125 in the colon cancer group were significantly higher than those in the colon adenoma group (P < .05). In Logistic regression analysis, high FAR and high FPR were identified as independent risk factors for colon cancer. Receiver operating characteristic (ROC) curve analysis results showed that Among the combined measures, FAR, FPR, CAR, and CPR had the highest diagnostic efficacy in distinguishing colon cancer from colon adenomas (AUC = 0.886, Sen = 80.62%, Spe = 81.40%). Thus, FAR, FPR, CAR, and CPR may serve as valuable biomarkers for the diagnosis of colon cancer, and the combined detection of FAR, FPR, CAR, and CPR can enhance the diagnostic efficiency for both colon cancer and colon adenoma.

Synergistic enhancement of Ni2P anode for high lithium/sodium storage by N, P, S triply-doping and soft template-assisted strategy.

Transition metal phosphides have demonstrated excellent performance in the field of energy conversion and storage, where nickel phosphide is one of the most prominent type of phosphides. However, achieving long cycle life with higher specific capacity in the case of Ni2P is still a great challenge. In this study, the composition and structure of Ni2P composites are rationally and precisely adjusted by heteroatoms doping and micelle-assisted methods to attain high capacity for longer cycles at high rate. Among all studied combinations, nickel phosphide particles anchored to triple heteroatom (N, P, S) doped carbon network skeleton (Ni2P@NPS) exhibited specific capacities of 727.3, 586.6, and 321.5 mA h g-1 after 1000 cycles at 1, 2 and 6 A g-1 for lithium-ion batteries (LIBs) and 230.1 mA h g-1 at 1 A g-1 for sodium-ion batteries (SIBs) after 560 cycles. The introduction of heteroatoms optimized the electronic structure of the electrode materials and promoted mass and charge transfer, while triple-heteroatom doped carbon substrates and uniformly dispersed spherical structures formed an active three-dimensional conductive network structure that provided a stronger driving force and richer channels for Li+/Na+ transport. Theoretical calculations showed that the high content of pyrrole nitrogen as well as the additional sulfur ensured improved electrical conductivity and enhanced ion adsorption performance. This study encourages further research into the synergistic effect of N, P, S co-doping materials for improving Li+/Na+ storage and the exploration of other heteroatom co-doping systems.

Application prospects of the 2BS cell-adapted China fixed rabies virus vaccine strain 2aG4-B40.

BACKGROUND: Rabies is a fatal zoonotic disease whose pathogenesis has not been fully elucidated, and vaccination is the only effective method for protecting against rabies virus infection. Most inactivated vaccines are produced using Vero cells, which are African green monkey kidney cells, to achieve large-scale production. However, there is a potential carcinogenic risk due to nonhuman DNA contamination. Thus, replacing Vero cells with human diploid cells may be a safer strategy. In this study, we developed a novel 2BS cell-adapted rabies virus strain and analysed its sequence, virulence and immunogenicity to determine its application potential as a human diploid cell inactivated vaccine. METHODS AND RESULTS: The 2BS cell-adapted rabies virus strain 2aG4-B40 was established by passage for 40 generations and selection of plaques in 2BS cells. RNA sequence analysis revealed that mutations in 2BS cell-adapted strains were not located at key sites that regulate the production of neutralizing antibodies or virulence in the aG strain (GQ412744.1). The gradual increase in virulence (remaining above 7.0 logLD50/ml from the 40th to 55th generation) and antigen further indicated that these mutations may increase the affinity of the adapted strains for human diploid cells. Identification tests revealed that the 2BS cell-adapted virus strain was neutralized by anti-rabies serum, with a neutralization index of 19,952. PrEP and PEP vaccination and the NIH test further indicated that the vaccine prepared with the 2aG4-B40 strain had high neutralizing antibody levels (2.24 to 46.67 IU/ml), immunogenicity (protection index 270) and potency (average 11.6 IU/ml). CONCLUSIONS: In this study, a 2BS cell-adapted strain of the 2aG4 rabies virus was obtained by passage for 40 generations. The results of sequencing analysis and titre determination of the adapted strain showed that the mutations in the adaptive process are not located at key sequence regions of the virus, and these mutations may enhance the affinity of the adapted strain for human diploid cells. Moreover, vaccines made from the adapted strain 2aG4-B40 had high potency and immunogenicity and could be an ideal candidate rabies virus strain for inactivated vaccine preparation.

Automatic Annotation Diagnostic Framework for Nasopharyngeal Carcinoma via Pathology-Fidelity GAN and Prior-Driven Classification.

Non-keratinizing carcinoma is the most common subtype of nasopharyngeal carcinoma (NPC). Its poorly differentiated tumor cells and complex microenvironment present challenges to pathological diagnosis. AI-based pathological models have demonstrated potential in diagnosing NPC, but the reliance on costly manual annotation hinders development. To address the challenges, this paper proposes a deep learning-based framework for diagnosing NPC without manual annotation. The framework includes a novel unpaired generative network and a prior-driven image classification system. With pathology-fidelity constraints, the generative network achieves accurate digital staining from H&E to EBER images. The classification system leverages staining specificity and pathological prior knowledge to annotate training data automatically and to classify images for NPC diagnosis. This work used 232 cases for study. The experimental results show that the classification system reached a 99.59% accuracy in classifying EBER images, which closely matched the diagnostic results of pathologists. Utilizing PF-GAN as the backbone of the framework, the system attained a specificity of 0.8826 in generating EBER images, markedly outperforming that of other GANs (0.6137, 0.5815). Furthermore, the F1-Score of the framework for patch level diagnosis was 0.9143, exceeding those of fully supervised models (0.9103, 0.8777). To further validate its clinical efficacy, the framework was compared with experienced pathologists at the WSI level, showing comparable NPC diagnosis performance. This low-cost and precise diagnostic framework optimizes the early pathological diagnosis method for NPC and provides an innovative strategic direction for AI-based cancer diagnosis.

Effects of respiratory muscle training on post-stroke rehabilitation: A systematic review and meta-analysis.

BACKGROUND: Stroke often results in significant respiratory dysfunction in patients. Respiratory muscle training (RMT) has been proposed as a rehabilitative intervention to address these challenges, but its effectiveness compared to routine training remains debated. This systematic review and meta-analysis aim to evaluate the effects of RMT on exercise tolerance, muscle strength, and pulmonary function in post-stroke patients. AIM: To systematically assess the efficacy of RMT in improving exercise tolerance, respiratory muscle strength, and pulmonary function in patients recovering from a stroke, and to evaluate whether RMT offers a significant advantage over routine training modalities in enhancing these critical health outcomes in the post-stroke population. METHODS: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, a comprehensive search across PubMed, Embase, Web of Science, and the Cochrane Library was conducted on October 19, 2023, without temporal restrictions. Studies were selected based on the predefined inclusion and exclusion criteria focusing on various forms of RMT, control groups, and outcome measures [including forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), maximal voluntary ventilation (MVV), peak expiratory flow (PEF), maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), and 6-min walking test (6MWT)]. Only randomized controlled trials (RCTs) were included. Data extraction and quality assessment were conducted independently by two reviewers using the Cochrane Collaboration's risk of bias tool. Statistical analyses, including those using the fixed-effect and random-effects models, sensitivity analysis, and publication bias assessment, were performed using Review Manager software. RESULTS: A total of 15 RCTs were included. Results indicated significant improvements in MIP (12.51 cmH2O increase), MEP (6.24 cmH2O increase), and various pulmonary function parameters (including FEV1, FVC, MVV, and PEF). A substantial increase in 6MWT distance (22.26 meters) was also noted. However, the heterogeneity among studies was variable, and no significant publication bias was detected. CONCLUSION: RMT significantly enhances walking ability, respiratory muscle strength (MIP and MEP), and key pulmonary function parameters (FEV1, FVC, MVV, and PEF) in post-stroke patients. These findings support the incorporation of RMT into post-stroke rehabilitative protocols.

The roles of nitric oxide in improving postharvest fruits quality: Crosstalk with phytohormones.

Nowadays, improving the quality of postharvest fruits has become a hot research topic. Nitric oxide (NO) is often regarded as a signaling molecule that delays the postharvest senescence of fruits. Moreover, phytohormones affect the postharvest senescence of fruits. This review mainly describes how NO improves the postharvest quality of fruits by delaying postharvest fruit senescence, mitigating fruit cold damage and controlling postharvest diseases. Furthermore, the crosstalk of NO and multiple plant hormones effectively delays the postharvest senescence of fruits, and the major crosstalk mechanisms include (1) mediating phytohormone signaling. (2) inhibiting ETH production. (3) stimulating antioxidant enzyme activity. (4) decreasing membrane lipid peroxidation. (5) maintaining membrane integrity. (6) inhibiting respiration rate. (7) regulating gene expression related to fruit senescence. This review concluded the roles and mechanisms of NO in delaying postharvest fruit senescence. In addition, the crosstalk mechanisms between NO and various phytohormones on the regulation of postharvest fruit quality are also highlighted, which provides new ideas for the subsequent research.

Development and application of an RNA nanostructure to induce transient RNAi in difficult transgenic plants.

The development of RNA interference (RNAi) is crucial for studying plant gene function. Its use, is limited to a few plants with well-established transgenic techniques. Spray-induced gene silencing (SIGS) introduces exogenous double-stranded RNA (dsRNA) into plants by spraying, injection, or irrigation, triggering the RNAi pathway to instantly silence target genes. As is a transient RNAi technology that does not rely on transgenic methods, SIGS has significant potential for studying gene function in plants lacking advanced transgenic technology. In this study, to enhance their stability and delivery efficiency, siRNAs were used as structural motifs to construct RNA nanoparticles (NPs) of four shapes: triangle, square, pentagon, and hexagon. These NPs, when synthesized by Escherichia coli, showed that triangular and square shapes accumulated more efficiently than pentagon and hexagon shapes. Bioassays revealed that RNA squares had the highest RNAi efficiency, followed by RNA triangles, with GFP-dsRNA showing the lowest efficiency at 4 and 7 days post-spray. We further explored the use of RNA squares in inducing transient RNAi in plants that are difficult to transform genetically. The results indicated that Panax notoginseng-derived MYB2 (PnMYB2) and Camellia oleifera-derived GUT (CoGUT) were significantly suppressed in P. notoginseng and C. oleifera, respectively, following the application of PnMYB2- and CoGUT-specific RNA squares. These findings suggest that RNA squares are highly effective in SIGS and can be utilized for gene function research in plants.

Is online shopping addiction still a depressive illness? -- the induced consumption and traffic trap in live E-commerce.

While immersive shopping has injected new vitality into China's e-commerce, it has also resulted in consumers' over-reliance on online shopping. Psychological studies have linked online shopping addiction with depression, but business practices challenge this conclusion. This study, grounded in addiction theory, developed a theoretical model, and conducted an online survey with 214 live-streaming shoppers using structural equation modeling for validation. The primary focus was on determining whether consumers truly become addicted to online shopping in the four stages of the addiction model. The study unveils the process of consumers becoming addicted to online shopping. It explores the moderating role of perceived risk in the relationship between utilitarian and hedonic purchases and online shopping addiction. The findings suggest that through tactics such as traffic promotion, traffic trapping, anchor feature utilization, and incorporation of consumer aesthetics, merchants may induce utilitarian and hedonic purchases, leading to addiction to live-streaming shopping among consumers. Furthermore, perceived risk significantly and negatively moderates the relationship between utilitarian purchases and online shopping addiction. Our research indicates that merchants intentionally create external stimuli, enticing consumers to indulge in online shopping, suggesting that online shopping addiction is not merely a simple psychological state but may be influenced by external factors. This study provides novel insights into the phenomenon of online shopping addiction while offering valuable recommendations for consumers seeking to avoid succumbing to its allure.

A transformer-based pyramid network for coronary calcified plaque segmentation in intravascular optical coherence tomography images.

Characterizing coronary calcified plaque (CCP) provides essential insight into diagnosis and treatment of atherosclerosis. Intravascular optical coherence tomography (OCT) offers significant advantages for detecting CCP and even automated segmentation with recent advances in deep learning techniques. Most of current methods have achieved promising results by adopting existing convolution neural networks (CNNs) in computer vision domain. However, their performance can be detrimentally affected by unseen plaque patterns and artifacts due to inherent limitation of CNNs in contextual reasoning. To overcome this obstacle, we proposed a Transformer-based pyramid network called AFS-TPNet for robust, end-to-end segmentation of CCP from OCT images. Its encoder is built upon CSWin Transformer architecture, allowing for better perceptual understanding of calcified arteries at a higher semantic level. Specifically, an augmented feature split (AFS) module and residual convolutional position encoding (RCPE) mechanism are designed to effectively enhance the capability of Transformer in capturing both fine-grained features and global contexts. Extensive experiments showed that AFS-TPNet trained using Lovasz Loss achieved superior performance in segmentation CCP under various contexts, surpassing prior state-of-the-art CNN and Transformer architectures by more than 6.58% intersection over union (IoU) score. The application of this promising method to extract CCP features is expected to enhance clinical intervention and translational research using OCT.

Ginseng-Sanqi-Chuanxiong (GSC) extracts attenuate d-galactose-induced vascular aging in mice via inhibition of endothelial progenitor cells senescence.

Vascular aging is an independent risk factor for age-related diseases and a specific type of organic aging. Endothelial progenitor cells (EPCs), a type of bone marrow stem cell, has been linked to vascular aging. The purpose of this study is to investigate if Ginseng-Sanqi-Chuanxiong (GSC) extract, a traditional Chinese medicine, can delay aortic aging in mice by enhancing the performance and aging of EPCs in vivo and to analyze the potential mechanisms through a d-Galactose (D-gal)-induced vascular aging model in mice. Our study revealed that GSC extracts not only enhanced the aortic structure, endothelial function, oxidative stress levels, and aging in mice, but also enhanced the proliferation, migration, adhesion, and secretion of EPCs in vivo, while reducing the expression of p53, p21, and p16. To conclude, GSC can delay vascular senescence by enhancing the function and aging of EPCs, which could be linked to a decrease in p16 and p53/p21 signaling. Consequently, utilizing GSC extracts to enhance the function and senescence of autologous EPCs may present a novel avenue for enhancing autologous stem cells in alleviating senescence.

Structure, evolution, and roles of SWEET proteins in growth and stress responses in plants.

Carbohydrates are exported by the SWEET family of transporters, which is a novel class of carriers that can transport sugars across cell membranes and facilitate sugar's long-distance transport from source to sink organs in plants. SWEETs play crucial roles in a wide range of physiologically important processes by regulating apoplastic and symplastic sugar concentrations. These processes include host-pathogen interactions, abiotic stress responses, and plant growth and development. In the present review, we (i) describe the structure and organization of SWEETs in the cell membrane, (ii) discuss the roles of SWEETs in sugar loading and unloading processes, (iii) identify the distinct functions of SWEETs in regulating plant growth and development including flower, fruit, and seed development, (iv) shed light on the importance of SWEETs in modulating abiotic stress resistance, and (v) describe the role of SWEET genes during plant-pathogen interaction. Finally, several perspectives regarding future investigations for improving the understanding of sugar-mediated plant defenses are proposed.

Genome-wide characterization and function analysis of ginger (Zingiber officinale Roscoe) ZoGRFs in responding to adverse stresses.

Growth-regulating factors (GRFs) play crucial roles in plant growth, development, hormone signaling, and stress response. Despite their significance, the roles of GRFs in ginger remain largely unknown. Herein, 31 ginger ZoGRFs were identified and designated as ZoGRF1-ZoGRF31 according to their phylogenetic relationships. All ZoGRFs were characterized as unstable, hydrophilic proteins, with 29 predicted to be located in the nucleus. Functional cis-elements related to growth and development were enriched in ZoGRF's promoter regions. RNA-seq and RT-qPCR analysis revealed that ZoGRF12, ZoGRF24, and ZoGRF28 were highly induced in various growth and development stages, displaying differential regulation under waterlogging, chilling, drought, and salt stresses, indicating diverse expression patterns of ZoGRFs. Transient expression analysis in Nicotiana benthamiana indicated that overexpressing ZoGRF28 regulated the transcription levels of salicylic acid, jasmonic acid, and pattern-triggered immunity-related genes, increased chlorophyll content and contributed to reduced disease lesions and an increased net photosynthetic rate. This research lays the foundation for further understanding the biological roles of ZoGRFs.

RIRS with FV-UAS vs. MPCNL for 2-3-cm upper urinary tract stones: a prospective study.

To observe the efficacy and safety of retrograde intrarenal surgery (RIRS) combined with flexible vacuum-assisted ureteral access sheath (FV-UAS) and minimally invasive percutaneous nephrolithotomy (MPCNL) in patients with 2-3 cm upper urinary tract stones. A total of 160 patients with 2-3 cm upper urinary tract stones were prospectively randomized into 2 groups-80 in the FV-UAS group and 80 cases as control in the MPCNL group. The stone-free rates (SFRs) at different times (postoperative 1st day and 4th week) were considered as the primary outcome of the study. The secondary end points were operative time, hemoglobin decrease, postoperative hospital stay, and operation-related complications. There was no obvious difference between the two groups in patient's demographics and preoperative clinical characteristics (all P > 0.05). Postoperative data showed that mean decrease in hemoglobin level was less in FV-UAS group than that in MPCNL group (5.3 vs. 10.8 g/L, P < 0.001). Postoperative hospital stay in FV-UAS group was more shorten than that in MPCNL group (2.7 vs. 4.9 days, P < 0.001). There was no statistical significance between the two groups in SFRs during postoperative 1st day and 4th week (both P > 0.05). However, in terms of the rates of bleeding and pain, MPCNL group were both significantly higher than FV-UAS group (6.2 vs. 0.0%, P = 0.023; 16.2 vs. 2.5%, P = 0.003; respectively). Our study showed that RIRS with FV-UAS, a new partnership to treat 2-3 cm upper urinary tract stones, was satisfying as it achieved a high SFR rate and a low rate of complications. This method was safe and reproducible in clinical practice.

Genome-wide analysis and expression pattern of the ZoPP2C gene family in Zingiber officinale Roscoe.

BACKGROUND: Protein phosphatases type 2C (PP2C) are heavily involved in plant growth and development, hormone-related signaling pathways and the response of various biotic and abiotic stresses. However, a comprehensive report identifying the genome-scale of PP2C gene family in ginger is yet to be published. RESULTS: In this study, 97 ZoPP2C genes were identified based on the ginger genome. These genes were classified into 15 branches (A-O) according to the phylogenetic analysis and distributed unevenly on 11 ginger chromosomes. The proteins mainly functioned in the nucleus. Similar motif patterns and exon/intron arrangement structures were identified in the same subfamily of ZoPP2Cs. Collinearity analysis indicated that ZoPP2Cs had 33 pairs of fragment duplicated events uniformly distributed on the corresponding chromosomes. Furthermore, ZoPP2Cs showed greater evolutionary proximity to banana's PP2Cs. The forecast of cis-regulatory elements and transcription factor binding sites demonstrated that ZoPP2Cs participate in ginger growth, development, and responses to hormones and stresses. ZoERFs have plenty of binding sites of ZoPP2Cs, suggesting a potential synergistic contribution between ZoERFs and ZoPP2Cs towards regulating growth/development and adverse conditions. The protein-protein interaction network displayed that five ZoPP2Cs (9/23/26/49/92) proteins have robust interaction relationship and potential function as hub proteins. Furthermore, the RNA-Seq and qRT-PCR analyses have shown that ZoPP2Cs exhibit various expression patterns during ginger maturation and responses to environmental stresses such as chilling, drought, flooding, salt, and Fusarium solani. Notably, exogenous application of melatonin led to notable up-regulation of ZoPP2Cs (17/59/11/72/43) under chilling stress. CONCLUSIONS: Taken together, our investigation provides significant insights of the ginger PP2C gene family and establishes the groundwork for its functional validation and genetic engineering applications.

Genome-Wide Identification of DUF668 Gene Family and Expression Analysis under F. solani, Chilling, and Waterlogging Stresses in Zingiber officinale.

The domains of unknown function (DUF) superfamilies contain proteins with conserved amino acid sequences without known functions. Among them, DUF668 was indicated widely involving the stress response of plants. However, understanding ZoDUF668 is still lacking. Here, 12 ZoDUF668 genes were identified in ginger by the bioinformatics method and unevenly distributed on six chromosomes. Conserved domain analysis showed that members of the same subfamily had similar conserved motifs and gene structures. The promoter region of ZoDUF668s contained the light, plant hormone and stress-responsive elements. The prediction of miRNA targeting relationship showed that nine ginger miRNAs targeted four ZoDUF668 genes through cleavage. The expression patterns of 12 ZoDUF668 genes under biotic and abiotic stress were analyzed using RT-qPCR. The results showed that the expression of seven ZoDUF668 genes was significantly downregulated under Fusarium solani infection, six ZoDUF668 genes were upregulated under cold stress, and five ZoDUF668 genes were upregulated under waterlogging stress. These results indicate that the ZoDUF668 gene has different expression patterns under different stress conditions. This study provides excellent candidate genes and provides a reference for stress-resistance research in ginger.

Establishment of a forward primers-superposed amplification analysis for accurate aspirin pharmacogenomic measurement.

Genotyping of gDNA rs12041331 (PEAR1), rs6065 (GP1BA), and rs730012 (LTC4S) can provide systematic guidance on the use of aspirin. However, an accurate, reliable and economical approach to simultaneous detection of the above single nucleotide polymorphisms (SNPs) is not reported. Herein, we designed and substantiated an allele-specific (AS) forward primer-superposed amplification analysis for measurement of the SNPs in PEAR1, GP1BA and LTC4S genes, in which the values of ∆Cq (differences in threshold cycles between the wild-type forward primer-based assay and the mutated-type forward primer-based assay) were employed to decide genotype. Mismatch AS forward primers were screened with the singleplex amplification analysis. Moreover, Cq extension optimized by AS forward primer superposition was observed in the selected forward primer-based triplex analysis. Further, robustness assessment of the triplex analysis showed the amplification efficiency ranging from 0.9 to 1.1. Precision test demonstrated the coefficient of variation of less than 2%. And the detective results of 189 DNA samples was completely concordant with that of commercial Sanger sequencing. In summary, we developed a simple, accurate and economical approach to genotyping of rs12041331 (PEAR1), rs6065 (GP1BA) and rs730012 (LTC4S) to provide a valuable pharmacogenomics tool for guidance of aspirin delivery.