An analysis of the potential association between obstructive sleep apnea and osteoporosis from the perspective of transcriptomics and NHANES.

BACKGROUND: Obstructive sleep apnea (OSA) and osteoporosis (OP) are prevalent diseases in the elderly. This study aims to reveal the clinical association between OSA and OP and explore potential crosstalk gene targets. METHODS: Participants diagnosed with OSA in the National Health and Nutrition Examination Survey (NHANES) database (2015-2020) were included, and OP was diagnosed based on bone mineral density (BMD). We explored the association between OSA and OP, and utilized multivariate logistic regression analysis and machine learning algorithms to explore the risk factors for OP in OSA patients. Overlapping genes of comorbidity were explored using differential expression analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Random Forest (RF) methods. RESULTS: In the OSA population, the weighted prevalence of OP was 7.0%. The OP group had more females, lower body mass index (BMI), and more low/middle-income individuals compared to the non-OP group. Female gender and lower BMI were identified as independent risk factors for OP in OSA patients. Gene expression profiling revealed 8 overlapping differentially expressed genes in OP and OSA patients. KCNJ1, NPR3 and WT1-AS were identified as shared diagnostic biomarkers or OSA and OP, all of which are associated with immune cell infiltration. CONCLUSION: This study pinpointed female gender and lower BMI as OP risk factors in OSA patients, and uncovered three pivotal genes linked to OSA and OP comorbidity, offering fresh perspectives and research targets.

Host adaptation of codon usage in SARS-CoV-2 from mammals indicates potential natural selection and viral fitness.

SARS-CoV-2 infection, which is the cause of the COVID-19 pandemic, has expanded across various animal hosts, and the virus can be transmitted particularly efficiently in minks. It is still not clear how SARS-CoV-2 is selected and evolves in its hosts, or how mutations affect viral fitness. In this report, sequences of SARS-CoV-2 isolated from human and animal hosts were analyzed, and the binding energy and capacity of the spike protein to bind human ACE2 and the mink receptor were compared. Codon adaptation index (CAI) analysis indicated the optimization of viral codons in some animals such as bats and minks, and a neutrality plot demonstrated that natural selection had a greater influence on some SARS-CoV-2 sequences than mutational pressure. Molecular dynamics simulation results showed that the mutations Y453F and N501T in mink SARS-CoV-2 could enhance the binding of the viral spike to the mink receptor, indicating the involvement of these mutations in natural selection and viral fitness. Receptor binding analysis revealed that the mink SARS-CoV-2 spike interacted more strongly with the mink receptor than the human receptor. Tracking the variations and codon bias of SARS-CoV-2 is helpful for understanding the fitness of the virus in virus transmission, pathogenesis, and immune evasion.

Transcriptome analysis reveals antioxidant defense mechanisms in the red swamp crayfish Procambarus clarkia after exposure to chromium.

Chromium (Cr) as a chromate anion has a strong redox capacity that seriously threatens the ecological environment and human health. Cr can contaminate water and impart toxicity to aquatic species. Procambarus clarkii is an important food source that once represented a large proportion of the aquaculture industry due to its rapid reproduction and high economic value. However, there have been reports on the death of P. clarkii due to heavy metal pollution. The underlying mechanism regarding heavy metal toxicity was studied in this paper. The transcriptome data of hemocytes extracted from P. clarkii injected with Cr were analyzed by high-throughput sequencing and compared to the control group. In total, 48,128,748 clean reads were obtained in the treatment group and 56,480,556 clean reads were obtained in the control group. The reads were assembled using Trinity and the identified unigenes were then annotated. Then, 421 differentially-expressed genes (DEGs) were found, 170 of which were upregulated and 251 downregulated. Many of these genes were found to be related to glutathione metabolism and transportation. The glutathione metabolic pathway of P. clarkii was thus activated by Cr exposure to detoxify and maintain body function. Validation of DEGs with quantitative real-time PCR confirms the changes in gene expression. Thus, this study provides data supporting a glutathione-focused response of P. clarkii to exposure to heavy metals.

The interaction of cellular protein ANP32A with influenza A virus polymerase component PB2 promotes vRNA synthesis.

The subunits PA, PB1, and PB2 of influenza A virus RNA polymerase are essential for efficient viral RNA synthesis and virus replication because of their role in recruiting multiple nuclear proteins. ANP32A is an acidic leucine-rich nuclear phosphoprotein 32 (ANP32) family member and a crucial cellular protein that determines the species specificity of the influenza virus RNA polymerase activity. However, how ANP32A modulates polymerase activity remains largely unknown. In this study, we showed that viral RNA synthesis was increased in A549 cells overexpressing ANP32A and decreased after treatment with ANP32A RNAi. This decrease in RNA synthesis was reversed by rescued ANP32A expression. The results of docking modeling, co-immunoprecipitation, and yeast two-hybrid assays showed that PB2 was the only subunit of the three that interacted with ANP32A. The C-terminal portion of ANP32A and the middle domains (residues 307-534) of PB2 were required for PB2-ANP32A interaction. Glu189 and Glu196 in ANP32A and Gly450 and Gln447 in PB2 were essential for interaction between ANP32A and PB2. These residues were located in conserved regions of the ANP32A or PB2 protein sequences. These data suggest that ANP32A is recruited to the polymerase through direct interaction with PB2 via critical amino acid residue interactions and promotes viral RNA synthesis. Our findings might provide new insights into the molecular mechanisms underlying influenza virus RNA synthesis and replication in infected human cells.

GABA-Alleviated Oxidative Injury Induced by Salinity, Osmotic Stress and their Combination by Regulating Cellular and Molecular Signals in Rice.

This study was conducted in order to determine the effect of priming with γ-aminobutyric acid (GABA) at 0.5 mM on rice (Oryza sativa L.) seed germination under osmotic stress (OS) induced by polyethylene glycol (30 g/L PEG 6000); and salinity stress (S, 150 mM NaCl) and their combination (OS+S). Priming with GABA significantly alleviated the detrimental effects of OS, S and OS+S on seed germination and seedling growth. The photosynthetic system and water relation parameters were improved by GABA under stress. Priming treatment significantly increased the GABA content, sugars, protein, starch and glutathione reductase. GABA priming significantly reduced Na+ concentrations, proline, free radical and malonaldehyde and also significantly increased K+ concentration under the stress condition. Additionally, the activities of antioxidant enzymes, phenolic metabolism-related enzymes, detoxification-related enzymes and their transcription levels were improved by GABA priming under stress. In the GABA primed-plants, salinity stress alone resulted in an obvious increase in the expression level of Calcineurin B-like Protein-interacting protein Kinases (CIPKs) genes such as OsCIPK01, OsCIPK03, OsCIPK08 and OsCIPK15, and osmotic stress alone resulted in obvious increase in the expression of OsCIPK02, OsCIPK07 and OsCIPK09; and OS+S resulted in a significant up-regulation of OsCIPK12 and OsCIPK17. The results showed that salinity, osmotic stresses and their combination induced changes in cell ultra-morphology and cell cycle progression resulting in prolonged cell cycle development duration and inhibitory effects on rice seedlings growth. Hence, our findings suggested that the high tolerance to OS+S is closely associated with the capability of GABA priming to control the reactive oxygen species (ROS) level by inducing antioxidant enzymes, secondary metabolism and their transcription level. This knowledge provides new evidence for better understanding molecular mechanisms of GABA-regulating salinity and osmotic-combined stress tolerance during rice seed germination and development.

Molecular mechanism of Danxiong Tongmai Granules in treatment of coronary heart disease.

BACKGROUND: Danxiong Tongmai Granules (DXTMG) are widely utilized in treating coronary heart disease (CHD) in China. This study aims to explore the molecular mechanisms underlying the therapeutic effects of DXTMG on CHD by employing a network pharmacology approach, complemented with experimental validation. METHODS: Traditional Chinese Medicine (TCM) compounds and targets were identified via searches in the BATMAN-TCM database, and the GeneCards database was used to obtain the main target genes involved in CHD. We combined disease targets with the drug targets to identify common targets. The "TCM-compound-target" network was plotted using Cytoscape 3.7.2 software and a protein-protein interaction (PPI) network was constructed using the STRING database from which core targets were obtained. Gene ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for common drug-disease targets using R Version 4.0.4 (64 bit) software. Molecular docking of core protein-small molecule ligand interaction was modeled using AutoDock software. A molecular dynamics simulation was conducted on the optimal protein-small molecule complex identified through molecular docking, using Amber18 software. The rat model for myocardial ischemia was established through pre-gavage administration of DXTMG, followed by dorsal hypodermic injection of isoprenaline. Myocardial tissues from the rats were analyzed using hematoxylin and eosin (HE) staining and Masson's trichrome staining. Relevant targets were validated by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry. RESULTS: 162 potential targets of DXTMG involved in CHD were identified. These included INS, ALB, IL-6 and TNF according to PPI network studies. GO enrichment analysis identified a total of 3365 GO pathways, including 3049 biological process pathways (BP) concerned with the heart and circulatory system; 109 cellular component (CC) pathways, including cation channels and membrane rafts and 207 molecular function (MF) pathways related to receptor ligands and activators. KEGG analysis revealed a total of 137 pathways (P < 0.05), including those related to AGE-RAGE signaling associated with diabetic complications, fluid shear stress and atherosclerosis. The results of molecular docking and molecular dynamics simulations demonstrated the robust binding affinity between the compounds and target proteins. Animal experiment findings indicated that, compared with the model group, the DXTMG group effectively ameliorated inflammation and fibrosis in rat myocardial tissues, reduced LDH, cTn-I, and MDA levels (P < 0.05, P < 0.01), elevated SOD and GSH-PX levels (P < 0.05), and reduced the percentage of positive area for IL-6 and TNF-α (P < 0.05). CONCLUSION: This study preliminarily suggests that DXTMG can modulate oxidative stress, inflammation response, and cardiomyocyte regulation, thereby mitigating the onset and progression of CHD.

An evaluation of microplastic contamination in the marine waters and species in the coastal region of the South Yellow Sea, China.

Microplastics (MPs) contamination of marine environments poses a significant ecological risk, although impacts on species' realized niche spaces remain unclear. The current study investigates MPs distribution across pelagic habitats, benthic sediments, and key biota in the South Yellow Sea, China. Samples were collected via trawling across estuarine transects, and tissues were digested to extract MPs. Density gradient separations and vacuum-filtrations prepared particle extracts for ATR-FTIR and Micro-Raman spectroscopic characterization. Sampling along industrialized river transects reveals ubiquitous plastic particle presence, with concentrations ranging from 0 to 51.68 item/L seawater. Contamination levels reach their peak at station estuaries before dispersing offshore, indicating significant waste stream inputs. Importantly, MPs detected in demersal and pelagic fish species, as well as in bivalves, confirm exposure across trophic niches. Gastrointestinal tract and gill concentrations reached 0.6 items/g fresh tissue, reflecting significant biological uptake and in vivo retention. The greatest population of organisms occurred adjacent to polluted areas. Overall, distribution of MPs from polluted rivers to coastal food webs was evident, suggesting potential negative impacts on key ecological functions in this system. These findings underscore the need to develop upstream mitigation efforts so as to minimize MPs contamination in areas where nearshore and offshore niches intersect.

Distribution of mudsnail Bullacta caurina along smooth cordgrass Spartina alterniflora invasion stages on a coast of the Yellow Sea, China.

On a Chinese coast of the Yellow Sea, a 15-year Spartina alterniflora invasion sequence was classified into five stages: no invasion, initial invasion, immature invasion, mature invasion, and senescing invasion. The effects of invasion on Bullacta caurina distribution were studied. The stem density and vegetation coverage, and sediment organic matter content increased after S. alterniflora invaded, whereas chlorophyll a concentration and porewater salinity decreased. The stem density and vegetation coverage, and porewater salinity were the dominant factors explaining habitat variations. The invasion stages, seasons and their interaction had significant effects on B. caurina density, and the density decreased after initial invasion stage of S. alterniflora. Here, a clumped spatial distribution pattern was detected on B. caurina population. Organic matter content and chlorophyll a concentration were distinguished for predicting B. caurina density. The hydrologic condition, food resources, temperature, and predation risk comprehensively affected B. caurina distribution after S. alterniflora invasion.

Cross-Domain Federated Data Modeling on Non-IID Data.

Federated learning has received sustained attention in recent years for its distributed training model that fully satisfies the need for privacy concerns. However, under the nonindependent identical distribution, the data heterogeneity of different parties with different data patterns significantly degrades the prediction performance of the federated model. Additionally, the federated model adopts simple averaging in the model aggregation phase, which ignores the contributions of different parties and further limits the model performance. To conquer the above challenges, we propose a new cross-domain federated data modeling (CDFDM) scheme by combining the attention mechanism. Firstly, to mitigate the poor model performance caused by data heterogeneity, we propose a shared model that adjusts the number of shared data assigned to users according to their data size, which effectively alleviates data heterogeneity while avoiding shared data from overwriting the user's individual data features. Then, we introduce the attention mechanism in the model aggregation phase, which assigns weights to users according to their contributions, thus improving the model performance. Finally, we conducted a series of experiments on two real-world datasets (MNIST and CIFAR-10). The results show that our CDFDM outperforms existing schemes in both nonindependent identical distribution conditions. Furthermore, in terms of model prediction accuracy variation during the training phase, our approach is more stable.

A new digital single-axis fluxgate magnetometer according to the cobalt-based amorphous effects.

Fluxgate sensors are currently widely used for weak magnetic field measurement because of their relatively great performance, such as resolution, power consumption, and measurement of vector magnetic fields directly. Since the analog fluxgate sensor has some drawbacks, e.g., it would be influenced by the noise of the analog circuit. Hence, in recent years, the analog circuit is gradually inclined to be realized by digital processing in which the software parameter adjustment is employed to replace the analog components, which can greatly improve the flexibility of the design. This paper proposes a digital single-axis fluxgate sensor according to the cobalt-based amorphous effect. To be specific, the analog signal output by the fluxgate is sampled directly by an analog-to-digital converter to obtain the signal waveform in digital form after amplification. The demodulation, filtering, and integration of the signal are all solved by mathematical algorithms. Based on the working principle of the fluxgate sensor, the selection of the magnetic core material and coil winding method of the fluxgate sensor probe is introduced in detail. The design and function of the excitation circuit and preamplifier circuit, as well as the specific realization of digital signal processing, are described. Finally, the performance test of the digital fluxgate sensor was performed under laboratory conditions, and the magnetic anomaly detection comparison experiment was performed outdoors with commercial fluxgate sensors. To sum up, the linearity of the digital single-axis fluxgate sensor is better than 1 × 10-5, and the root mean square noise value is below 0.1 nT. At the same time, it has good magnetic field tracking performance and is extremely sensitive to the magnetic field of the measurement area.

A CNN model embedded with local feature knowledge and its application to time-varying signal classification.

A novel convolutional neural network is proposed for local prior feature embedding and imbalanced dataset modeling for multi-channel time-varying signal classification. This model consists of a single-channel signal feature parallel extraction unit, a multi-channel signal feature integration unit, a local feature embedding and feature similarity measurement unit, a full connection layer, and a Softmax classifier. An algorithm combining dynamic clustering and sliding window was used to select segments signals with typical local features in each pattern class, forming a typical local feature set. The one-dimensional CNNs were used to extract features from the single-channel signal in parallel, a comprehensive feature matrix of the multi-channel signal and the local feature matrix templates were produced. Using the method of external embedding, based on the sliding window and dynamic time warping (DTW) algorithm, the local feature similarities between the local feature template of each pattern class and the comprehensive feature sub-matrix of the input signal were measured, and the maximum values were selected to construct a local feature similarity vector in order. The information fusion was realized through a full connection layer. The proposed methodology can extract and represent both global and local signals features, strengthen the role of prior local feature in classification and improve the modeling properties of imbalanced datasets. A comprehensive learning algorithm is presented in this paper. The classification diagnosis of cardiovascular disease based on 12-lead ECG signals was used as a verification experiment. Results showed that the accuracy and generalization for the proposed technique were significantly improved.

A Fuzzy Radial Basis Adaptive Inference Network and Its Application to Time-Varying Signal Classification.

A fuzzy radial basis adaptive inference network (FRBAIN) is proposed for multichannel time-varying signal fusion analysis and feature knowledge embedding. The model which combines the prior signal feature embedding mechanism of the radial basis kernel function with the rule-based logic inference ability of fuzzy system is composed of a multichannel time-varying signal input layer, a radial basis fuzzification layer, a rule layer, a regularization layer, and a T-S fuzzy classifier layer. The dynamic fuzzy clustering algorithm was used to divide the sample set pattern class into several subclasses with similar features. The fuzzy radial basis neurons (FRBNs) were defined and used as parameterized membership functions, and typical feature samples of each pattern subclass were used as kernel centers of the FRBN to realize the embedding of the diverse prior feature knowledge and the fuzzification of the input signals. According to the signal categories of FRBN kernel centers, nodes in the rule layer were selectively connected with nodes in the FRBN layer. A fuzzy multiplication operation was used to achieve synthesis of pattern class membership information and establishment of fuzzy inference rules. The excitation intensity of each rule was used as the input of T-S fuzzy classifier to classify the input signals. The FRBAIN can adaptively establish fuzzy set membership functions, fuzzy inference, and classification rules based on the learning of sample set, realize structural and data constraints of the model, and improve the modeling properties of imbalanced datasets. In this paper, the properties of FRBAIN were analyzed and a comprehensive learning algorithm was established. Experimental validation was performed with classification diagnoses from four complex cardiovascular diseases based on 12-lead ECG signals. Results demonstrated that, in the case of small-scale imbalanced datasets, the proposed method significantly improved both classification accuracy and generalizability comparing with other methods in the experiment.

A Generative Adversarial Network Fused with Dual-Attention Mechanism and Its Application in Multitarget Image Fine Segmentation.

Aiming at the problem of insignificant target morphological features, inaccurate detection and unclear boundary of small-target regions, and multitarget boundary overlap in multitarget complex image segmentation, combining the image segmentation mechanism of generative adversarial network with the feature enhancement method of nonlocal attention, a generative adversarial network fused with attention mechanism (AM-GAN) is proposed. The generative network in the model is composed of residual network and nonlocal attention module, which use the feature extraction and multiscale fusion mechanism of residual network, as well as feature enhancement and global information fusion ability of nonlocal spatial-channel dual attention to enhance the target features in the detection area and improve the continuity and clarity of the segmentation boundary. The adversarial network is composed of fully convolutional networks, which penalizes the loss of information in small-target regions by judging the authenticity of prediction and label segmentation and improves the detection ability of the generative adversarial model for small targets and the accuracy of multitarget segmentation. AM-GAN can use the GAN's inherent mechanism that reconstruct and repair high-resolution image, as well as the ability of nonlocal attention global receptive field to strengthen detail features, automatically learn to focus on target structures of different shapes and sizes, highlight salient features useful for specific tasks, reduce the loss of image detail features, improve the accuracy of small-target detection, and optimize the segmentation boundary of multitargets. Taking medical MRI abdominal image segmentation as a verification experiment, multitargets such as liver, left/right kidney, and spleen are selected for segmentation and abnormal tissue detection. In the case of small and unbalanced sample datasets, the class pixels' accuracy reaches 87.37%, the intersection over union is 92.42%, and the average Dice coefficient is 93%. Compared with other methods in the experiment, the segmentation precision and accuracy are greatly improved. It shows that the proposed method has good applicability for solving typical multitarget image segmentation problems such as small-target feature detection, boundary overlap, and offset deformation.

An optimized free induction decay signal sensing coil and its matching circuit for miniaturized Overhauser geomagnetic sensor.

An Overhauser geomagnetic sensor is a precise instrument commonly employed for geomagnetic field observation, magnetic surveys, and so on. Currently, the miniaturization of the Overhauser geomagnetic sensor is limited due to the lower signal-to-noise ratio. Thus, how to effectively extract weaker free induction decay (FID) signal from a miniaturized sensor and how to improve the signal quality have become the bottleneck. To address these problems, we came up with an optimal design of the FID signal sensing coil for a miniaturized Overhauser geomagnetic sensor and propose a front-end matching circuit for the sensing coil to inhibit the attenuation of the signal amplitude caused by high impedance, further reducing the overall noise floor of the signal acquisition system. Finally, the field experimental results show that the miniaturized prototype sensor has a smaller volume and mass with an approximate performance compared with the commercial sensor.

SARS-CoV-2 Accessory Protein ORF7b Mediates Tumor Necrosis Factor-α-Induced Apoptosis in Cells.

The accessory proteins of coronaviruses are essential for virus-host interactions and the modulation of host immune responses. It has been reported that accessory protein ORF3a encoded by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can induce apoptosis, and accessory protein ORF6 and ORF8 could be inhibitors of the type-I interferon (IFN) signaling pathway. However, the function of accessory protein ORF7b is largely unknown. We investigated the apoptosis-inducing activity of ORF7b in cells. Cytokine levels and host innate immune responses, including expression of interferon regulatory transcription factor (IRF)-3, signal transducer and activator of transcription (STAT)-1, interferon (IFN)-ß, tumor necrosis factor (TNF)-α, and interleukin (IL)-6, were also investigated. We found that ORF7b promoted expression of IFN-ß, TNF-α, and IL-6, activated type-I IFN signaling through IRF3 phosphorylation, and activated TNFα-induced apoptosis in HEK293T cells and Vero E6 cells. These results could provide deeper understanding about the pathogenicity of SARS-CoV-2 as well as the interaction between the accessory protein ORF7b with host immune responses.

Hepatocyte Growth Factor Attenuates the Development of TGF-ß1- Induced EndMT through Down-regulating the Notch Signaling.

BACKGROUND AND OBJECTIVE: Endothelial-mesenchymal transition (EndMT) not only occurs during embryonic development, but also contributes to various diseases including cardiovascular diseases, fibrosis, and even cancer. However, the specific molecular biological mechanism and relationship of related pathways have not been fully elucidated. This study aims to explore the inhibitory effect of HGF on EndMT and the molecular mechanism of Notch signal in this process. METHODS: HUVECs were treated with TGF-ß1 and/or HGF for 72 hours. Expression levels of EndMT markers and the key transcriptional regulators of Notch signaling pathway were assessed by qRT-PCR and western blotting. C-Met expression was measured by qRT-PCR. RESULTS: CD31 was downregulated and α-SMA, FSP1 were upregulated during TGF-ß1-induced EndMT. HGF treatment significantly attenuates the development of TGF-ß1-induced EndMT by down-regulating the signal transduction of the Notch signal pathway. CONCLUSION: This study proves that HGF treatment significantly attenuates the development of TGF- ß1-induced EndMT by inhibiting the Notch signaling, which may provide new theoretical basis for the treatment of vascular diseases and numerous fibrotic diseases caused by EndMT.

Functional characterization of maize heat shock transcription factor gene ZmHsf01 in thermotolerance.

BACKGROUND: Heat waves can critically influence maize crop yields. Plant heat shock transcription factors (HSFs) play a key regulating role in the heat shock (HS) signal transduction pathway. METHOD: In this study, a homologous cloning method was used to clone HSF gene ZmHsf01 (accession number: MK888854) from young maize leaves. The transcript levels of ZmHsf01 were detected using qRT-PCR in different tissues and treated by HS, abscisic acid (ABA), hydrogen peroxide (H2O2), respectively, and the functions of gene ZmHsf01 were studied in transgenic yeast and Arabidopsis. RESULT: ZmHsf01 had a coding sequence (CDS) of 1176 bp and encoded a protein consisting of 391 amino acids. The homologous analysis results showed that ZmHsf01 and SbHsfA2d had the highest protein sequence identities. Subcellular localization experiments confirmed that ZmHsf01 was localized in the nucleus. ZmHsf01 was expressed in many maize tissues. It was up-regulated by HS, and up-regulated in roots and down-regulated in leaves under ABA and H2O2treatments. ZmHsf01-overexpressing yeast cells showed increased thermotolerance. In Arabidopsis seedlings, ZmHsf01 compensated for the thermotolerance defects of mutant athsfa2, and ZmHsf01-overexpressing lines showed enhanced basal and acquired thermotolerance. When compared to wild type (WT) seedlings, ZmHsf01-overexpressing lines showed higher chlorophyll content and survival rates after HS. Heat shock protein (HSP) gene expression levels were more up-regulated in ZmHsf01-overexpressing Arabidopsis seedlings than WT seedlings. These results suggest that ZmHsf01 plays a vital role in response to HS in plant.

Two new steroidal saponins from Tribulus terrestris.

Two new steroidal saponins and two known flavonoid glycosides were isolated from the fruits of Tribulus terrestris. Their structures were assigned by spectroscopic analysis and chemical reaction as 26-O-beta-D-glucopyranosyl-(25R)-5 alpha-furostan-12-one-3beta,22 alpha,26-triol-3-O-beta-D-glucopyranosyl (1 --> 2)-beta-D-glucopyranosyl(1 --> 4)-beta-D-galactopyranoside (1), 26-O-beta-D-glucopyranosyl-(25S)-5 alpha-furostan-22-methoxy-2 alpha,3beta,26-triol-3-O-beta-D-glucopyranosyl(1 --> 2)-beta-D-glucopyranosyl(1 --> 4)-beta-D-galactopyranoside (2), kaempferol-3-gentiobioside (3), and isorhamnetin-3-gentiobioside (4).

Cyclic AMP-CRP Modulates the Cell Morphology of Klebsiella pneumoniae in High-Glucose Environment.

Bacteria can modify their morphology in response to environmental stimuli for survival or host defense evasion. The rich glucose in vivo or in the Luria-Bertani (LB) medium shortened the cell length of Klebsiella pneumoniae. The environmental glucose decreased the levels of cyclic AMP (cAMP) and the transcription of crp, which declined the cAMP-cAMP receptor protein (cAMP-CRP) activity. The cell length of crp deletion mutant was significantly shorter than that of the wild type (0.981 ± 0.057 µm vs. 2.415 ± 0.075 µm, P < 0.001). These results indicated that the high environmental glucose alters the bacterial morphology to a round form through regulating the activity of cAMP-CRP complex. Comparative proteomics analysis showed increased expression of 10 proteins involved in cell division or cell wall biosynthesis in the crp deletion strain. Five of them (ompA, tolB, ybgC, ftsI, and rcsF) were selected to verify their expression in the high-glucose environment, and overexpression of tolB or rcsF shortened the bacterial length similar to that of the crp deletion strain. Electrophoretic mobility shift assay indicated that CRP directly negatively regulates the transcription of tolB and rcsF by binding to the promoter regions. This study first proved the role and partial regulation mechanism of CRP in altering cell morphology during infection and provided a theoretical basis for elucidating the mechanism in diabetes mellitus susceptible to K. pneumoniae.

The Effects of Cattle Manure and Garlic Rotation on Soil under Continuous Cropping of Watermelon (Citrullus lanatus L.).

Continuous cropping of watermelon (Citrullus lanatus L.) can lead to reduced yield and quality. We aimed to determine the effects of cattle manure addition and rotation with green garlic to improve yield and reduce disease incidence in watermelon and to examine the effects on the biological and chemical characteristics of the soil. Field experiments were performed during 2012-2014 on land previously under two years of continuous watermelon cropping in northwest China. We examined three treatment combinations: watermelon and garlic rotation, cattle manure application before watermelon planting, and combined cattle manure addition and crop rotation. Watermelon monoculture was retained as a control. Watermelon yield was significantly higher and disease incidence was lower in the treatments than the control. The populations of soil bacteria and actinomycetes and the bacteria/fungi ratio increased significantly and soil enzyme activities were generally enhanced under treatments. Available nutrients and soil organic matter contents were much higher under experimental treatments than the control. Results suggest both cattle manure application and garlic rotation can ameliorate the negative effects of continuous cropping. The combined treatment of cattle manure addition and green garlic rotation was optimal to increase yield, reduce disease incidence and enhance soil quality.