Search

Abstract Glaucoma poses a significant threat to vision, capable of causing irreversible damage and, in severe instances, leading to permanent blindness. Accurate optic cup (OC) and optic disc (OD) segmentation are essential in glaucoma screening. In this study, a novel OC and OD segmentation approach is proposed. Based on U‐Net, it is optimized by introducing cardinality dimensions. Moreover, attention gates are implemented to reinforce salient features while suppressing irrelevant information. Additionally, a convolutional block attention module (CBAM) is integrated into the decoder segment. This fusion hones in on effective information in both channel and spatial dimensions. Meanwhile, an image processing procedure is proposed for image normalization and enhancement. All of these increase the accuracy of the model. This model is evaluated on the ORIGA and REFUGE datasets, demonstrating the model's superiority in OC and OD segmentation compared to the state‐of‐the‐art methods. Additionally, after the proposed image processing, cup‐to‐disc ratio (CDR) prediction on a batch of 155 in‐house fundus images yields an absolute CDR error of 0.099, which is reduced by 0.04 compared to the case where only conventional processing was performed.

Background: Education level significantly impacts individual health outcomes. This research investigates the correlation between education level and the prevalence of overactive bladder (OAB). Methods: This study employed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005 to 2020 to conduct a thorough investigation of the association between educational level and OAB using multivariable logistic regression, smooth curve fitting, and generalized additive model. Results: Out of 37,423 surveyed participants from the United States, 8,033 were identified with OAB. The comprehensive adjusted model revealed a notable inverse correlation between education level and OAB prevalence (odds ratio [OR] = 0.86, 95 % confidence interval [CI] = 0.83–0.89, P < 0.001). When education level was categorized, participants with the highest educational qualification (college graduates or higher) had a 44 % lower likelihood of having OAB compared to those with the lowest education (below 9th grade) (OR = 0.56, 95 % CI = 0.47–0.66, P < 0.001). Conclusion: The findings underscore a substantial inverse correlation between education level and OAB prevalence. Although continued research is required to confirm these findings, educational attainment may guide the development of preventative and therapeutic strategies for OAB.

Abstract Background Hematological metastasis has been recognized as a crucial factor contributing to the high rates of metastasis and mortality observed in colorectal cancer (CRC). Notably, exosomes derived from cancer cells participate in the formation of CRC pre-metastatic niches; however, the mechanisms underlying their effects are largely unknown. While our preliminary research revealed the role of exosome-derived disintegrin and metalloproteinase 17 (ADAM17) in the early stages of CRC metastasis, the role of exosomal ADAM17 in CRC hematogenous metastasis remains unclear. Methods In the present study, we isolated and purified exosomes using ultracentrifugation and identified exosomal proteins through quantitative mass spectrometry. In vitro, co-culture assays were conducted to evaluate the impact of exosomal ADAM17 on the permeability of the blood vessel endothelium. Vascular endothelial cell resistance, the cell index, membrane protein separation, flow cytometry, and immunofluorescence were employed to investigate the mechanisms underlying exosomal ADAM17-induced vascular permeability. Additionally, a mouse model was established to elucidate the role of exosomal ADAM17 in the modulation of blood vessel permeability and pre-metastatic niche formation in vivo. Results Our clinical data indicated that ADAM17 derived from the circulating exosomes of patients with CRC could serve as a blood-based biomarker for predicting metastasis. The CRC-derived exosomal ADAM17 targeted vascular endothelial cells, thus enhancing vascular permeability by influencing vascular endothelial cadherin cell membrane localization. Moreover, exosomal ADAM17 mediated the formation of a pre-metastatic niche in nude mice by inducing vascular leakage, thereby promoting CRC metastasis. Nonetheless, ADAM17 selective inhibitors effectively reduced CRC metastasis in vivo. Conclusions Our results suggest that exosomal ADAM17 plays a pivotal role in the hematogenous metastasis of CRC. Thus, this protein may serve as a valuable blood-based biomarker and potential drug target for CRC metastasis intervention.

Abstract The nasal cavity harbors diverse microbiota that contributes to human health and respiratory diseases. However, whether and to what extent the host genome shapes the nasal microbiome remains largely unknown. Here, by dissecting the human genome and nasal metagenome data from 1401 healthy individuals, we demonstrated that the top three host genetic principal components strongly correlated with the nasal microbiota diversity and composition. The genetic association analyses identified 63 genome-wide significant loci affecting the nasal microbial taxa and functions, of which 2 loci reached study-wide significance (p

Abstract Fine needle aspiration (FNA) biopsy of thyroid nodules is a safe, cost-effective, and accurate diagnostic method for detecting thyroid cancer. However, about 10% of initial FNA biopsy samples from patients are non-diagnostic and require repeated FNA, which delays the diagnosis and appropriate care. On-site evaluation of the FNA sample can be performed to filter out non-diagnostic FNA samples. Unfortunately, it involves a time-consuming staining process, and a cytopathologist has to be present at the time of FNA. To bypass the staining process and expert interpretation of FNA specimens at the clinics, we developed a deep learning-based ensemble model termed FNA-Net that allows in situ screening of adequacy of unstained thyroid FNA samples smeared on a glass slide which can decrease the non-diagnostic rate in thyroid FNA. FNA-Net combines two deep learning models, a patch-based whole slide image classifier and Faster R-CNN, to detect follicular clusters with high precision. Then, FNA-Net classifies sample slides to be non-diagnostic if the total number of detected follicular clusters is less than a predetermined threshold. With bootstrapped sampling, FNA-Net achieved a 0.81 F1 score and 0.84 AUC in the precision-recall curve for detecting the non-diagnostic slides whose follicular clusters are less than six. We expect that FNA-Net can dramatically reduce the diagnostic cost associated with FNA biopsy and improve the quality of patient care.

Objective: This paper discusses the feasibility of using mineral element fingerprinting technology of to identify tobacco producing areas, screens out the effective indicators, and constructs the discrimination model of tobacco producing areas. Methods: The contents of 20 mineral elements in tobacco leaves from 11 producing areas were simultaneously determined by ICP-MS, and the data were analyzed by variance analysis, cluster analysis, principal component analysis and discriminant analysis. Results: The contents of 16 elements were significantly different among producing areas, and principal component analysis resulted in 6 principal components, with the cumulative variance contribution of 89.253%. Using linear discriminant analysis, four elementsmineral, K, Mn, Se and Ba, were screened as the effective indicators to discriminate the geographical origin of tobacco leaves. The established discriminant model could accurately distinguish tobacco leaf samples from different tobacco producing areas. Conclusion: Significant differences were showed in the contents of mineral elements in tobacco leaves from 11 producing areas. Four elements, K, Mn, Se and Ba, are important indicators for distinguishing tobacco producing areas. Mineral element fingerprinting technology can be used for distinguishing tobacco producing areas.

Abstract The skin is the largest organ in the human body. Various skin environments on its surface constitutes a complex ecosystem. One of the characteristics of the skin micro‐ecosystem is low biomass, which greatly limits a comprehensive identification of the microbial species through sequencing. In this study, deep‐shotgun sequencing (average 21.5 Gigabyte (Gb)) from 450 facial samples and publicly available skin metagenomic datasets of 2069 samples to assemble a Unified Human Skin Genome (UHSG) catalog is integrated. The UHSG encompasses 813 prokaryotic species derived from 5779 metagenome‐assembled genomes, among which 470 are novel species covering 20 phyla with 1385 novel assembled genomes. Based on the UHSG, the core functions of the skin microbiome are described and the differences in amino acid metabolism, carbohydrate metabolism, and drug resistance functions among different phyla are identified. Furthermore, analysis of secondary metabolites of the near‐complete genomes further find 1220 putative novel secondary metabolites, several of which are found in previously unknown genomes. Single nucleotide variant (SNV) reveals a possible skin protection mechanism: the negative selection process of the skin environment to conditional pathogens. UHSG offers a convenient reference database that will facilitate a more in‐depth understanding of the role of skin microorganisms in the skin.

BackgroundAccurate preoperative assessment of surgical difficulty is crucial to the success of the surgery and patient safety. This study aimed to evaluate the difficulty for endoscopic resection (ER) of gastric gastrointestinal stromal tumors (gGISTs) using multiple machine learning (ML) algorithms.MethodsFrom December 2010 to December 2022, 555 patients with gGISTs in multi-centers were retrospectively studied and assigned to a training, validation, and test cohort. A difficult case was defined as meeting one of the following criteria: an operative time ≥ 90 min, severe intraoperative bleeding, or conversion to laparoscopic resection. Five types of algorithms were employed in building models, including traditional logistic regression (LR) and automated machine learning (AutoML) analysis (gradient boost machine (GBM), deep neural net (DL), generalized linear model (GLM), and default random forest (DRF)). We assessed the performance of the models using the areas under the receiver operating characteristic curves (AUC), the calibration curve, and the decision curve analysis (DCA) based on LR, as well as feature importance, SHapley Additive exPlanation (SHAP) Plots and Local Interpretable Model Agnostic Explanation (LIME) based on AutoML.ResultsThe GBM model outperformed other models with an AUC of 0.894 in the validation and 0.791 in the test cohorts. Furthermore, the GBM model achieved the highest accuracy among these AutoML models, with 0.935 and 0.911 in the validation and test cohorts, respectively. In addition, it was found that tumor size and endoscopists’ experience were the most prominent features that significantly impacted the AutoML model’s performance in predicting the difficulty for ER of gGISTs.ConclusionThe AutoML model based on the GBM algorithm can accurately predict the difficulty for ER of gGISTs before surgery.

Background: Kidney renal clear cell carcinoma (KIRC) is a representative histologic subtype of renal cell carcinoma (RCC). RCC exhibits a strong immunogenicity with a prominent dysfunctional immune infiltration. Complement C1q C chain (C1QC) is a polypeptide in serum complement system and is involved in tumorigenesis and the modulation of tumor microenvironment (TME). However, researches have not explored the effect of C1QC expression on prognosis and tumor immunity of KIRC.Methods: The difference in a wide variety of tumor tissues and normal tissues in terms of the C1QC expression was detected using TIMER and TCGA portal databases, and further validation of protein expression of C1QC was conducted via Human Protein Atlas. Then, the associations of C1QC expression with clinicopathological data and other genes were studied with the use of UALCAN database. Subsequently, the association of C1QC expression with prognosis was predicted by searching the Kaplan-Meier plotter database. A protein-protein interaction (PPI) network with the Metascape database was built using STRING software, such that the mechanism underlying the C1QC function can be studied in depth. The TISCH database assisted in the evaluation of C1QC expression in different cell types in KIRC at the single-cell level. Moreover, the association of C1QC and the infiltration level of tumor immune cell was assessed using TIMER platform. The TISIDB website was selected to deeply investigate the Spearman correlation between C1QC and immune-modulator expression. Lastly, how C1QC affected the cell proliferation, migration, and invasion in vitro was assessed using knockdown strategies.Results: KIRC tissues had notably upregulated C1QC level in comparison with adjacent normal tissues, with showed a positive relevance to clinicopathological features including tumor stage, grade, and nodal metastasis, and a negative relevance to clinical prognosis in KIRC. C1QC knockdown inhibited KIRC cell proliferation, migration, and invasion, as indicated by the results of the in vitro experiment. Furthermore, functional and pathway enrichment analysis demonstrated that C1QC was involved in immune system-related biological processes. According to single-cell RNA analysis, C1QC exhibited a specific upregulation in macrophages cluster. Additionally, there was an obvious association of C1QC and a wide variety of tumor-infiltrating immune cells in KIRC. Also, high C1QC expression presented inconsistent prognosis in different enriched immune cells subgroups in KIRC. Immune factors might contribute to C1QC function in KIRC.Conclusion: C1QC is qualified to predict KIRC prognosis and immune infiltration biologically. Targeting C1QC may bring new hope for the treatment of KIRC.

The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancy history, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.

Summary: The oral microbiome has been implicated in a growing number of diseases; however, determinants of the oral microbiome and their roles remain elusive. Here, we investigated the oral (saliva and tongue dorsum) metagenome, the whole genome, and other omics data in a total of 4,478 individuals and demonstrated that the oral microbiome composition and its major contributing host factors significantly differed between sexes. We thus conducted a sex-stratified metagenome-genome-wide-association study (M-GWAS) and identified 11 differential genetic associations with the oral microbiome (psex-difference

Abstract The oral microbiota contains billions of microbial cells, which could contribute to diseases in many body sites. Challenged by eating, drinking, and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1915 individuals, for both the tongue dorsum (n = 2017) and saliva (n = 1915). We identified five genetic loci associated with oral microbiota at study-wide significance (p

Background: Infections of Staphylococcus aureus (S. aureus) often result in osteomyelitis, which is the acute or chronic infections of the bone marrow or bones. TNF-α is long recognized as a key factor contributing to the pathogenesis of osteomyelitis, but little is known about the underlying molecular mechanism. Methods: Expression levels of TNF-α, and several candidate genes, including endothelial nitric oxide synthase (eNOS), known to be downregulated by TNF-α were analysed in MC3T3-E1 cells with S. aureus infection and osteomyelitis patient blood. MicroRNA(miR)-129-5p was predicted and experimentally verified to target eNOS. Alizarin red sulfate (ARS) and alkaline phosphatase (ALP) staining assays were conducted on MC3T3-E1 cells with S. aureus infection to assess the role of TNF-α/miR-129-5p/eNOS on mineralization defect. Results: TNF-α and miR-129-5p were upregulated while eNOS was downregulated in MC3T3-E1 cells with S. aureus infection and osteomyelitis patients, showing inversely correlated expression profiles. MiR-129-5p directly binds to the 3′-UTR of eNOS mRNA to suppress eNOS expression in MC3T3-E1 cells. TNF-α blocker inhibited miR-129-5p and elevated eNOS expression, likely contributing to rescued mineralization defect in S. aureus-infected MC3T3-E1 cells. During S. aureus infection, upregulated TNF-α increases endogenous miR-129-5p expression, which in turn inhibits eNOS, contributing to osteomyelitis. Conclusion: Our study thereby proposes a novel signalling cascade involving TNF-α/miR-129-5p/eNOS in the pathogenesis of osteomyelitis, which may also serve as therapeutic targets.

ABSTRACT Little is unknown about the regulatory mechanisms underlying the pathogenesis of osteomyelitis induced by Staphylococcus aureus. Hypoxia-inducible factor-1α (HIF-1α) and transforming growth factor β1 (TGF-β1) were both upregulated in S. aureus-infected MC3T3-E1 cells and osteomyelitis patients. HIF-1α directly targets the hypoxia-responsive elements (HREs) of TGF-β1 mRNA to induce its expression. Silencing HIF-1α and TGF-β1, as well as treatment of hypoxia inhibitor IDF-11774, consistently elevated OPN and RUNX2 expression and alizarin Red S (ARS) and alkaline phosphatase (ALP) staining levels in MC3T3-E1 cells with S. aureus infection. S. aureus infection increased HIF-1α expression and serum TGF-β1 concentration in a mouse model of osteomyelitis. Hypoxia inhibitor IDF-11774 treatment reduced serum levels of interleukin (IL)-6, IL-1β, and C-reactive protein. Upon S. aureus infection, hypoxia was activated to trigger TGF-β1 upregulation through direct targeting of HRE on TGF-β1 mRNA by HIF-1α, eventually leading to osteomyelitis symptoms in terms of osteogenesis and mineralization deficiencies as well as elevated inflammation. This study hereby suggests a novel signaling cascade involving hypoxia/HIF-1α/TGF-β1 in osteomyelitis pathogenesis, which could potentially serve as a target for therapeutic measures. IMPORTANCE The pathogenesis of osteomyelitis induced by Staphylococcus aureus remains unclear. To develop therapeutic approaches for osteomyelitis, it is important to understand the molecular mechanisms of its pathogenesis. Our results suggests that hypoxia/HIF-1α/TGF-β1 signaling is involved in osteomyelitis pathogenesis. Thus, these findings highlight the potential of this signaling components as therapeutic targets for the treatment of osteomyelitis.

Abstract The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no

Summary: Biological age (BA) has been proposed to evaluate the aging status instead of chronological age (CA). Our study shows evidence that there might be multiple “clocks” within the whole-body system: systemic aging drivers/clocks overlaid with organ/tissue-specific counterparts. We utilize multi-omics data, including clinical tests, immune repertoire, targeted metabolomic molecules, gut microbiomes, physical fitness examinations, and facial skin examinations, to estimate the BA of different organs (e.g., liver, kidney) and systems (immune and metabolic system). The aging rates of organs/systems are diverse. People’s aging patterns are different. We also demonstrate several applications of organs/systems BA in two independent datasets. Mortality predictions are compared among organs' BA in the dataset of the United States National Health and Nutrition Examination Survey. Polygenic risk score of BAs constructed in the Chinese Longitudinal Healthy Longevity Survey cohort can predict the possibility of becoming centenarian.

Diabetes mellitus is a prevalent disease result in several complications, including bone problems. Previous studies have shown that microRNA (miR)-26a regulates glucose metabolism and plays a protective role in diabetes. However, whether miR-26a also affects bone quality in diabetes remains unknown. In the present study, we evaluated the potential effects of miR-26a on bone in diabetic mice. We administrated miR-26a in streptozotocin-induced diabetic mice. The metabolic parameters, bone quality, osteoblast and osteoclast markers, and insulin signaling activation were measured. miR-26a ameliorated insulin resistance and glucose tolerance, improved bone microarchitecture and quality, increased osteoblasts and bone formation, decreased osteoclasts, and promoted the insulin signaling pathway in diabetic mice. These effects were abolished in insulin receptor-compromised Col1a1-Insr+/– mice. In conclusion, miR-26a could ameliorate bone-specific insulin resistance and bone quality in diabetic mice, which depended on the insulin receptors on osteoblasts. Our findings highlight the potential of miR-26a as a therapeutic target for diabetes mellitus-related bone metabolism and diseases.

More than a decade of gut microbiome studies have a common goal of improving human health. However, while most of the disease studies have focused on the elderly or the middle-aged, a reference cohort for the gut microbiome in young individuals has been lacking. It is also not clear what other omics data need to be measured to better understand the gut microbiome. Here, we present a cohort including 2183 adults with high-depth metagenomic shotgun sequencing data for the fecal microbiome and other omics data. In this multiomic cohort, we observe a number of vitamins, hormones, amino acids, and trace elements that correlated with the gut microbiome. Many of the associations are validated in an additional cohort consisting of 1404 individuals. Our comprehensive data are poised to provide advice to future populations and mechanistic study designs to better understand and manage our gut microbiome.

Helicobacter pylori infection (HPI) is a prevalent infectious disease associated with gastric ulcer, gastric cancer, and many nongastrointestinal disorders. To identify genes that may serve as microbial markers for HPI, we performed shotgun metagenomic sequencing of fecal samples from 313 Chinese volunteers who had undergone a C14 breath test. Through comparing differences in intestinal microbial community structure between H. pylori‐positive and H. pylori‐negative individuals, we identified 58 HPI‐associated microbial species (P

Depression is becoming a major public health concern worldwide. Si-Ni-San (SNS) is a famous formula in Traditional Chinese Medicine (TCM) with potent antidepressant effects. However, the antidepressant mechanism of SNS has not been clearly elucidated. This study was performed to verify whether the antidepressant effects of SNS were related to its anti-inflammatory effects, the levels of brain-derived neurotrophic factor (BDNF) and Cytochrome P450 (CYP450) enzymatic activity. In our study, behavioral tests such as the forced swim test, sucrose preference test and open-field test were evaluated to ensure the establishment of depressive rats. The levels of IL-1β, IL-6, and TNF-α in the serum, liver, and hippocampus of rats were measured by enzyme-linked immunosorbent assays (ELISA). Furthermore, the key proteins NF-κB, BDNF, and TrkB were analyzed by Western blot (WB) analysis in the hippocampus. In addition, CYP450 enzymatic activity analysis was performed using LC-MS/MS in conjunction with drug and statistics (DAS 3.0) after oral administration of six probe drugs. Our results showed that SNS attenuated reserpine-induced increases in IL-1β, IL-6, and TNF-α expression in the serum, liver, and hippocampus. The levels of NF-κB, BDNF, and TrkB in the hippocampus of depressive rats were also altered. According to the pharmacokinetic parameters, SNS had moderate inhibitory effects in the reserpine-induced depression model on CYP1A2, CYP2D1, CYP2E1, and CYP3A2, but no significant metabolic changes to CYP2C6 and CYP2D2. These findings suggested that SNS has a protective effect on reserpine-induced depressive rats, which may be related to the improvement of the inflammatory factors, the level of BDNF and the activity of CYP450 enzymes.

In recent years, algae bloom phenomenon outbreaks frequently in large-scale water bodies during summer. At present, mechanical method is used to collect cyanobacteria and reduce volume. However, the characteristics of algae, namely high viscosity, small particle size and high moisture content, lead to poor efficiency of dehydration. In order to improve the dehydration efficiency of algae and achieve the purpose of volume reduction and dehydration, the dehydration performance of Microcystis aeruginosa was studied in this paper. Three filter aid agent, including Poly Aluminium Chloride (PAC), Montmorillonite and Diatomite were added to the algae solution to improve filterability of Microcystis aeruginosa. The results showed that all of three filter aid agent have positive effect on the algae filtration rate, specific resistance, compression index and dehydration efficiency. Compared with the other two filter aid agents, the filtration rate of Diatomite is relatively faster. Meanwhile dehydration performance is better as well. When the dosage of Diatomite was 10.0g/L, the filtration rate increased from 0.108 L/h to 0.504 L/h. In addition, the compression index was reduced from 0.710 to 0.594. The specific resistance was reduced from 7.62 × 1010 s2/g to 2.35 × 108 s2 /g while the water content was decreased from 86.5% to 66.4%.

Objective This study was performed to investigate the effects of age and sex on 10 salivary steroid hormones and analyze the correlations between salivary and plasma hormones. Methods The concentrations of 10 salivary steroid hormones in 1090 Chinese adult volunteers were examined using liquid chromatography–tandem mass spectrometry, and a related investigation was performed on the concentrations of salivary hormones in this population. Results The concentrations of androstenedione (A4), 17α-hydroxyprogesterone (17-OHP), aldosterone (ALD), cortisone (COR), corticosterone (CORT), cortisol (F), progesterone (P), and testosterone were significantly different between men and women (Student’s t-test). Differences in 17-OHP and ALD concentrations were highly significant between women in the follicular and luteal phases of their menstrual cycle (Student’s t-test). Five salivary steroid hormones (17-OHP, A4, CORT, COR, and F) significantly decreased with increasing age (Kruskal–Wallis test). A high linear correlation between salivary and plasma 17-OHP, P, A4, and F were observed with obvious sex-related differences (Pearson’s correlation, r > 0.7). Conclusions Our results provide important knowledge regarding the descriptive characteristics of salivary hormones in relation to age and sex and their correlations with plasma hormones.

High-energy charged particle radiography has been used for diagnostics of high-energy density matter, and electrons can serve as a promising radiographic probe that acts as a complement to commonly used proton probes. Here we report on an electron radiography experiment using 45 MeV electrons from an S-band photoinjector, where scattered electrons, after interacting with a sample, are collected and imaged by a quadrupole imaging system. We achieve a spatial resolution of a few microns (∼4 μm) and a thickness resolution of a few percent for a silicon target of 300–600 μm in thickness. With additional dark-field images captured by selecting electrons with large scattering angles, we show that complementary information for determining external details such as outlines, boundaries and defects can be obtained.

An efficient catalytic system was developed for the acetalization and ketalization of carbonyl compounds with polyhydric alcohols under mild solvent-free conditions. In the presence of 0.1 mol% CoCl2 and 0.2 mol% dimethylglyoxime at 70 °C under 5 KPa pressure for 1 h, 95.3% conversion of cyclohexanone and 100% selectivity of the corresponding cyclic ketal could be obtained, where TOF reached as high as 953 h−1. It is proposed that the in situ generated planartetracoordinate cobaloxime played the key role in the catalytic cycle and was responsible for the excellent catalytic performance.

Multicast support is a critical and desirable feature of wireless mesh network（WMN）.A distributed algorithm was presented based on pricing scheme by using Lagrange dual decomposition technique.According to the algorithm to joint optimizing rate allocation of flows and power consumption of links for forwarding data flows,to maximize the net utility.The price is associated with each individual network link,which reflects the traffic load on this link.The flow in turn collects the prices of all links on its multicast path and calculates the overall network price,then adjusts the stream-ing rate.The validity and effectiveness of the approach are demonstrated in simulations.

Hematopoietic stem cells (HSCs) express Mdr1a/lb and Bcrp1/Abcg2, which are members of the ATP binding cassette transporter family. Mice lacking both Mdr1-type genes (Mdr1a and Mdr1b) or Bcrp1 had normal hematopoietic development, but it has been unclear whether Mdr1a/1b and Bcrp1 play redundant roles in hematopoiesis. We generated a mouse model lacking both Mdr1a/1b and Bcrp1 expression (M-/-B-/-). The M-/-B-/- mice had normal numbers of peripheral blood cells, bone marrow colony-forming cells (CFCs) and colony-forming units-spleen (CFU-S), and demonstrated normal hematopoietic development. There was a near total elimination of side population (SP) cells in the bone marrow of M-/-B-/- mice compared to M+/+B-/- mice, primarily in the subpopulation lacking other HSC markers, which indicated that Mdr1a/1b was responsible for a small portion of SP cells that were mainly mature cells. Hematopoietic progenitor cells from the bone marrow of M-/-B-/- mice were more sensitive to mitoxantrone in vitro compared to either M-/-B+/+ or M+/+B-/- mice, suggesting that Mdr1a/1b and Bcrp1 may provide additive protection to HSCs against genotoxic agents. These studies demonstrate the lack of functional redundancy between these transporters for HSC development and further clarify their contributing role to the SP phenotype in HSCs and to intrinsic drug resistance within hematopoietic progenitor cells.