TransConv: Transformer Meets Contextual Convolution for Unsupervised Domain Adaptation.

Unsupervised domain adaptation (UDA) aims to reapply the classifier to be ever-trained on a labeled source domain to a related unlabeled target domain. Recent progress in this line has evolved with the advance of network architectures from convolutional neural networks (CNNs) to transformers or both hybrids. However, this advance has to pay the cost of high computational overheads or complex training processes. In this paper, we propose an efficient alternative hybrid architecture by marrying transformer to contextual convolution (TransConv) to solve UDA tasks. Different from previous transformer based UDA architectures, TransConv has two special aspects: (1) reviving the multilayer perception (MLP) of transformer encoders with Gaussian channel attention fusion for robustness, and (2) mixing contextual features to highly efficient dynamic convolutions for cross-domain interaction. As a result, TransConv enables to calibrate interdomain feature semantics from the global features and the local ones. Experimental results on five benchmarks show that TransConv attains remarkable results with high efficiency as compared to the existing UDA methods.

Designed Synthesis of Compartmented Bienzyme Biocatalysts Based on Core-Shell Zeolitic Imidazole Framework Nanostructures.

For complex cascade biocatalysis, multienzyme compartmentalization helps to optimize substrate transport channels and promote the orderly and tunable progress of step reactions. Herein, a simple and general synthesis strategy is proposed for the construction of a multienzyme biocatalyst by compartmentalizing glucose oxidase and horseradish peroxidase (GOx and HRP) within core-shell zeolite imidazole frameworks (ZIF)-8@ZIF-8 nanostructures. Owing to the combined effects of biomimetic mineralization and the fine regulation of the ZIF-8 growth process, the uniform shell encloses the seed (core) surface by epitaxial growth, and the bienzyme system is accurately localized in a controlled manner. The versatility of this strategy is also reflected in ZIF-67. Meanwhile, with the ability to covalently bind divalent metal ions, lithocholic acid (LCA) is used as a competitive ligand to improve the pore structure of the ZIF from a single micropore to a hierarchical micro/mesopore network, which greatly increases mass transfer efficiency. Furthermore, the multienzyme cascade reaction is exemplified by the oxidation of o-phenylenediamine (OPD). The findings show that the bienzyme assembly strategy significantly affects the biocatalytic efficiency mainly by influencing the utilization efficiency of the intermediate (Hydrogen peroxide, H2 O2 ) between the step reactions. This study sheds new light on facile synthetic routes to constructing in vitro multienzyme biocatalysts.

Target recognition initiated self-dissociation based DNA nanomachine for sensitive and accurate MicroRNA (miRNA) detection.

As a valuable biomarker for various tumor, sensitive and reliable quantitative determination of microRNA (miRNA) is crucial for both disease diagnosis and cancer treatment. Herein, we depict a novel simple and sensitive miRNA detection approach by exploiting an elegantly designed target recognition initiated self-dissociation based DNA nanomachine. In this nanomachine, target recognition assists the formation of active DNAzyme secondary conformation, and the active DNAzyme generates a nicking site in H probe, initiating the self-assembly of H probe. With the reflexed sequences as primer, dual signal recycles are formed under the cooperation of DNA polymerase and Nb.BbvCI. Eventually, the method exhibits a high sensitivity with the limit of detection as low as 12 fM. In addition, the method is also demonstrated with a high selectivity that can distinguish one mismatched base pair. We believe the established approach can be a robust tool for the early-diagnosis of a variety of cancers and also in anticancer drug development.

Synthesis and antibacterial activity of novel 2­fluoro ketolide antibiotics with 11,12­quinoylalkyl side chains.

A series of novel 2­fluoro ketolide antibiotics with 11,12­quinoylalkyl side chains derived from telithromycin and cethromycin were designed and synthesized. The corresponding targets 2a-o were tested for their in vitro activities against a series of macrolide-sensitive and macrolide-resistant pathogens. Some of them showed a similar antibacterial spectrum and comparable or slightly better activity to telithromycin. Among them, compounds 2g and 2k, displayed excellent activities against macrolide-sensitive and macrolide-resistant pathogens.

Improving Multiple Pedestrian Tracking in Crowded Scenes with Hierarchical Association.

Recently, advances in detection and re-identification techniques have significantly boosted tracking-by-detection-based multi-pedestrian tracking (MPT) methods and made MPT a great success in most easy scenes. Several very recent works point out that the two-step scheme of first detection and then tracking is problematic and propose using the bounding box regression head of an object detector to realize data association. In this tracking-by-regression paradigm, the regressor directly predicts each pedestrian's location in the current frame according to its previous position. However, when the scene is crowded and pedestrians are close to each other, the small and partially occluded targets are easily missed. In this paper, we follow this pattern and design a hierarchical association strategy to obtain better performance in crowded scenes. To be specific, at the first association, the regressor is used to estimate the positions of obvious pedestrians. At the second association, we employ a history-aware mask to filter out the already occupied regions implicitly and look carefully at the remaining regions to find out the ignored pedestrians during the first association. We integrate the hierarchical association in a learning framework and directly infer the occluded and small pedestrians in an end-to-end way. We conduct extensive pedestrian tracking experiments on three public pedestrian tracking benchmarks from less crowded to crowded scenes, demonstrating the proposed strategy's effectiveness in crowded scenes.

An Organ-Specific Metabolite Annotation Approach for Ambient Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations of a Whole Mouse Body.

Rapid and accurate metabolite annotation in mass spectrometry imaging (MSI) can improve the efficiency of spatially resolved metabolomics studies and accelerate the discovery of reliable in situ disease biomarkers. To date, metabolite annotation tools in MSI generally utilize isotopic patterns, but high-throughput fragmentation-based identification and biological and technical factors that influence structure elucidation are active challenges. Here, we proposed an organ-specific, metabolite-database-driven approach to facilitate efficient and accurate MSI metabolite annotation. Using data-dependent acquisition (DDA) in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to generate high-coverage product ions, we identified 1620 unique metabolites from eight mouse organs (brain, liver, kidney, heart, spleen, lung, muscle, and pancreas) and serum. Following the evaluation of the adduct form difference of metabolite ions between LC-MS and airflow-assisted desorption electrospray ionization (AFADESI)-MSI and deciphering organ-specific metabolites, we constructed a metabolite database for MSI consisting of 27,407 adduct ions. An automated annotation tool, MSIannotator, was then created to conduct metabolite annotation in the MSI dataset with high efficiency and confidence. We applied this approach to profile the spatially resolved landscape of the whole mouse body and discovered that metabolites were distributed across the body in an organ-specific manner, which even spanned different mouse strains. Furthermore, the spatial metabolic alteration in diabetic mice was delineated across different organs, exhibiting that differentially expressed metabolites were mainly located in the liver, brain, and kidney, and the alanine, aspartate, and glutamate metabolism pathway was simultaneously altered in these three organs. This approach not only enables robust metabolite annotation and visualization on a body-wide level but also provides a valuable database resource for underlying organ-specific metabolic mechanisms.

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed t-SNE of Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue.

The role of diet in renal cell carcinoma incidence: an umbrella review of meta-analyses of observational studies.

BACKGROUND: Evidence associating diet with the incidence of renal cell carcinoma (RCC) is inconclusive. We aimed to summarize evidence associating dietary factors with RCC incidence and assess the strength and validity of this evidence. METHODS: We conducted an umbrella review of systematic reviews or meta-analyses (SRoMAs) that assessed the association between diet and RCC incidence. Through April 2021, PubMed, Web of Science, Embase, The Cochrane Library, Scopus, and WCRF were searched. Two independent reviewers selected studies, extracted data, and appraised the quality of SRoMAs. According to credibility assessment criteria, evidence can be divided into five categories: convincing (class I), highly suggestive (class II), suggestive (class III), weak (class IV), and nonsignificant (class V). RESULTS: Twenty-nine meta-analyses were obtained after screening. After excluding 7 overlapping meta-analyses, 22 meta-analyses including 502 individual studies and 64 summary hazard ratios for RCC incidence were included: dietary patterns or dietary quality indices (n = 6), foods (n = 13), beverages (n = 4), alcohol (n = 7), macronutrients (n =15), and micronutrients (n =19). No meta-analyses had high methodological quality. Five meta-analyses exhibited small study effects; one meta-analysis showed evidence of excess significance bias. No dietary factors showed convincing or highly suggestive evidence of association with RCC in the overall analysis. Two protective factors had suggestive evidence (vegetables (0.74, 95% confidence interval 0.63 to 0.86) and vitamin C (0.77, 0.66 to 0.90)) in overall analysis. One protective factor had convincing evidence (moderate drinking (0.77, 0.70 to 0.84)) in Europe and North America and one protective factor had highly suggestive evidence (cruciferous vegetables (0.78, 0.70 to 0.86)) in North America. CONCLUSIONS: Although many meta-analyses have assessed associations between dietary factors and RCC, no high-quality evidence exists (classes I and II) in the overall analysis. Increased intake of vegetables and vitamin C is negatively associated with RCC risk. Moderate drinking might be beneficial for Europeans and North Americans, and cruciferous vegetables might be beneficial to North Americans, but the results should be interpreted with caution. More researches are needed in the future. TRIAL REGISTRATION: PROSPERO CRD42021246619.

Design, synthesis, and preclinical evaluation of a novel bifunctional macrocyclic chelator for theranostics of cancers.

PURPOSE: This study was to design and synthesize a novel bifunctional chelator, named Dar, primarily validated by conjugating to tumor targeting motifs, labeled with radiometals, and performed preclinical evaluation of tumor imaging and cancer therapy in murine tumor models. METHOD: The designed Dar was synthesized and characterized by X-ray crystallography, 1H/13C NMR, and mass spectrometry. Dar-PSMA-617 was conjugated and radiolabeled with 68Ga, 177Lu, and 89Zr. The in vivo behavior of 68 Ga/89Zr-labeled Dar-PSMA-617 were evaluated using micro-PET imaging and biodistribution from image quantitation and tissue radioactivity counting, with 68Ga/89Zr-labeled NOTA/DOTA/DFO-PSMA-617 analogs as controls, respectively. The [177Lu]-Dar-PSMA-617, with [177Lu]-DOTA-PSMA-617 as control, was evaluated in competitive cell uptake, tumor cell internalization, and efflux studies. The treatment efficacy of [177Lu]Lu-Dar-PSMA-617, with [177Lu]Lu-DOTA-PSMA-617 as control, was evaluated in PSMA-positive LNCaP tumor-bearing mice. In addition, the ability of Dar for radiolabeling nanobody was tested by conjugating Dar to KN035 nanobody. The resultant [89Zr]Zr-Dar-KN035 nanobody, with [89Zr]Zr-DFO-KN035 as control, was evaluated by micro-PET imaging and biodistribution in a mouse model bearing MC38&MC38-hPD-L1 colon cancer. RESULTS: 68Ga, 89Zr, and 177Lu-radiolabeled Dar-PSMA-617 complexes were able to be produced under mild condition with high radiochemical yield and purity successfully. [177Lu]Lu-Dar-PSMA-617 had higher cellular uptake yet similar internalization and efflux properties in LNCaP cells, as compared to [177Lu]Lu-DOTA-PSMA-617. Micro-PET images demonstrated significantly higher tumor uptake of [68Ga]Ga-Dar-PSMA-617, than that of the analog [68Ga]Ga-DOTA-PSMA-617. The tumor uptake values of [68Ga]Ga-Dar-PSMA-617 at multiple time points are comparable to that of [68Ga]Ga-NOTA-PSMA-617, although a higher and persistently prolonged kidney retention was resulted in during the study period. The Dar chelator can also successfully mediate the radiolabeling with 89Zr, while the resultant [89Zr]Zr-Dar-PSMA-617 demonstrated a similar biodistribution with [89Zr]Zr-DFO-PSMA-617 measured at 96 h p.i. The treatment with [177Lu]Lu-Dar-PSMA-617 significantly inhibited the tumor growth, showing much better efficacy than that of [177Lu]Lu-DOTA-PSMA-617 at the same injected radioactivity and mass dose. Dar was covalently linked to KN035 nanobody and enabled radiolabeling with 89Zr in high yield and radiochemical purity at room temperature. The resultant [89Zr]Zr-Dar-KN035, with [89Zr]Zr-DFO-KN035 as control, demonstrated superior tumor uptake and detection capability in PET imaging studies. CONCLUSION: The Dar, as a novel bifunctional chelator for medicating the labeling of radiometals onto tumor targeting carriers, was successfully synthesized and chemically characterized. Test radiolabeling, on PSMA-617 and a nanobody as tool targeting molecule carriers, demonstrated the Dar has potential as a universal bifunctional chelator for radiolabeling various radiometals (at least 68Ga, 177Lu, and 89Zr tested) commonly used for clinical imaging and therapy. Using a novel Dar chelator results in altered in vivo behavior of the carriers even though labeled with the same nuclide. This capability makes Dar an alternative to the existing choices for radiolabeling new carrier molecules with various radiometals, especially the radiometals with large radius.

Spatially resolved metabolomics to discover tumor-associated metabolic alterations.

Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.

Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning.

Currently, most Graph Structure Learning (GSL) methods, as a means of learning graph structure, improve the robustness of GNN merely from a local view by considering the local information related to each edge and indiscriminately applying the mechanism across edges, which may suffer from the local structure heterogeneity of the graph (i.e., the uneven distribution of inter-class connections over nodes). To overcome the drawbacks, we extract the graph structure as a learnable parameter and jointly learn the structure and common parameters of GNN from the global view. Excitingly, the common parameters contain the global information for nodes features mapping, which is also crucial for structure optimization (i.e., optimizing the structure relies on global mapping information). Mathematically, we apply a generic structure extractor to abstract the graph structure and transform GNNs in the form of learning structure and common parameters. Then, we model the learning process as a novel bi-level optimization, i.e., Generic Structure Extraction with Bi-level Optimization for Graph Structure Learning (GSEBO), which optimizes GNN parameters in the upper level to obtain the global mapping information and graph structure is optimized in the lower level with the global information learned from the upper level. We instantiate the proposed GSEBO on classical GNNs and compare it with the state-of-the-art GSL methods. Extensive experiments validate the effectiveness of the proposed GSEBO on four real-world datasets.

Enhanced On-Tissue Chemical Derivatization with Hydrogel Assistance for Mass Spectrometry Imaging.

The improvement of on-tissue chemical derivatization for mass spectrometry imaging (MSI) of low-abundance and/or poorly ionizable functional molecules in biological tissue without delocalization is challenging. Here, we developed a novel hydrogel-assisted chemical derivatization (HCD) approach coupled with airflow-assisted desorption electrospray ionization (AFADESI)-MSI, allowing for enhanced visualization of inaccessible molecules in biological tissues. The derivatization reagent Girard's P (GP) reagent was creatively packaged into a hydrogel to form HCD blocks that have reactivity to carbonyl compounds as well as the feasibility of "cover/uncover" contact mode with tissue sections. The HCD blocks provided a favorable liquid microenvironment for the derivatization reaction and reduced matrix effects from derivatization reagents and tissue without obvious molecular migration, thus improving the derivatization efficiency. With this methodology, unusual carbonyl metabolites, including 166 fatty aldehydes (FALs) and 100 oxo fatty acids (FAs), were detected and visualized in rat brain, kidney, and liver tissue. This study provides a new approach to enhance chemical labeling for in situ tissue submetabolome profiling and improves our knowledge of the molecular histology and complex metabolism of biological tissues.

Mapping Metabolic Networks in the Brain by Ambient Mass Spectrometry Imaging and Metabolomics.

Metabolic networks and their dysfunction in the brain are closely associated with central nervous function and many psychogenic diseases. Thus, it is of utmost importance to develop a high-throughput imaging method for metabolic network mapping. Here, we developed a metabolic network mapping method to discover the metabolic contexts and alterations with spatially resolved information from the microregion of the brain by ambient-air flow-assisted desorption electrospray ionization mass spectrometry imaging and metabolomics analysis, which can be performed without any chemical derivatization, labels, or complex sample pretreatment. This method can map hundreds of different polar functional metabolites involved in multiple metabolic pathways, including not only neurotransmitters but also purines, organic acids, polyamines, cholines, and carbohydrates, in the rat brain. These high-coverage metabolite profile and microregional distribution information constitute complex networks that regulate advanced functions in the central nervous system. Moreover, this methodology was further used to discover not only the dysregulated metabolites but also the brain microregions involved in the pathology of a scopolamine-treated Alzheimer's model. Furthermore, this methodology was demonstrated to be a powerful visualizing tool that could offer novel insight into the metabolic events and provide spatial information about these events in central nervous system diseases.

E3 ubiquitin ligase PJA1 regulates lung adenocarcinoma apoptosis and invasion through promoting FOXR2 degradation.

Among all lung cancer cases, lung adenocarcinoma (LAC) represents nearly 40% and remains the leading cause of cancer deaths worldwide. Although the combination therapy of surgical treatment with radiotherapy, chemotherapy, and immunotherapy, has been used to treat LAC, unfortunately, high recurrence rates and poor survival remain. Therefore, novel prognostic markers and new targets for molecular targeted therapy in LAC is urgently needed. Fork-head box R2 (FOXR2) plays a key role in a wide range of cellular processes, including cellular proliferation, invasion, differentiation, and apoptosis, and it has been reported to be implicated in progression of LAC, thus inhibition of FOXR2 may be a novel targeting therapy for lung cancer. This current study found that E3 ligase PJA1 regulates ubiquitin-mediated degradation of FOXR2 and predicts good outcome of patients with LAC. In addition, it was showed force expression of PJA1 significantly inhibited LAC cells invasion and induced apoptosis in vitro through inactivating Wnt/ß-catenin signaling pathway. In short, our findings reveal that PJA1 could be a potential diagnostic and prognostic biomarkers and the PJA1- FOXR2 axis could be served as a promising target for LAC therapy.

Biotechnology and bioengineering of pullulanase: state of the art and perspectives.

Pullulanase (EC 3.2.1.41) is a starch-debranching enzyme in the α-amylase family and specifically cleaves α-1,6-glycosidic linkages in starch-type polysaccharides, such as pullulan, ß-limited dextrin, glycogen, and amylopectin. It plays a key role in debranching and hydrolyzing starch completely, thus bring improved product quality, increased productivity, and reduced production cost in producing resistant starch, sugar syrup, and beer. Plenty of researches have been made with respects to the discovery of either thermophilic or mesophilic pullulanases, however, few examples meet the demand of industrial application. This review presents the progress made in the recent years from the first aspect of characteristics of pullulanases. The heterologous expression of pullulanases in different microbial hosts and the methods used to improve the expression effectiveness and the regulation of enzyme production are also described. Then, the function evolution of pullulanases from a protein engineering view is discussed. In addition, the immobilization strategy using novel materials is introduced to improve the recyclability of pullulanases. At the same time, we indicate the trends in the future research to facilitate the industrial application of pullulanases.

RNF115-mediated ubiquitination of p53 regulates lung adenocarcinoma proliferation.

Lung adenocarcinoma (LAC) represents approximately 40% of all lung cancer cases and is the leading cause of cancer-associated mortality worldwide. Although combined treatment, including radiotherapy, chemotherapy, surgical treatment and immunotherapy, has been used in treating LAC, the five-year survival rate of patients with LAC has not significantly improved. Therefore, it is vital for cancer research to investigate novel prognostic markers and new targets for molecular targeted therapy in LAC. TP53 is an important tumor suppressor gene and is frequently inactivated in lung cancer, thus upregulation or activation of p53 may be a novel targeted therapy for LAC. The present study found that RNF115 mediates ubiquitination of p53 and predicts poor prognosis of patients with LAC. Functionally, it was demonstrated that disruption of RNF115 significantly inhibited cell viability in vitro through inducing G1 phase arrest of LAC cells, which reduced tumor growth in an xenograft model. Taken together, these results suggest that RNF115 could be a novel prognostic biomarker and the RNF115-p53 axis may be a potential target for LAC therapy.

"Sandwich" mesh reconstruction of female giant urethral diverticulum: a case report.

BACKGROUND: There is no consensus between urologists on the diagnosis and treatment of female urethral diverticula. Once the diagnosis has been established, the most common treatment approach is surgical excision and reconstruction. Whether a staged procedure or simultaneous management is more appropriate for treating concomitant urethral diverticula and stress urinary incontinence remains controversial. CASE PRESENTATION: A 63-year-old woman was hospitalized for repeated frequent urination, urgent urination, odynuria, and dysuria accompanied by intermittent overflow urinary incontinence for over 10 years. She had a 5 year history of urinary stress incontinence prior to onset of these symptoms and had had four urethral caruncles resected on four separate occasions. There was visible leakage of urine when abdominal pressure was increased during physical examination and urodynamic studies. Additionally, turbid urine was discharged when the anterior vaginal wall was squeezed. Cystourethrography showed circumferential filling with contrast and multiple bladder diverticulae in the mid plane of the pubic symphysis. Urethrocystoscopy showed an orifice to a diverticulum at 7 o'clock in the proximal urethra, into which an F19.8 urethroscope could be inserted, enabling examination of most of the diverticulae. The urethral diverticulae were resected, followed by mesh reconstruction of the urethra. During a 20-month follow-up, the treatment outcomes were satisfactory. CONCLUSION: We here report a case of a giant circumferential urethral diverticulum combined with stress urinary incontinence that was successfully managed by an uncommon surgical reconstructive technique: a minimally invasive "Sandwich" mesh repair procedure utilizing synthetic mesh wrap in the midurethral region.

[Electrolytic drinking water improves the metabolism of uric acid in the SD rats with hyperuricemia].

OBJECTIVE: To investigate the effects of electrolytic drinking water on the hyperuricemia and the potential mechanism. METHODS: The 6-week-old SD rats were induced as the animal model with hyperuricemia by yeast extract(10 g/kg) and adenine(100 g/kg) gavage(twice per day) combined with oxygen oxazine acid potassium(300 mg/kg, the 1~(st), 5~(th) and 10~(th )day) i. p. Then the rats were supplied electrolytic drinking water in different dosages(1 mL, 2 mL and 3 mL) by gavage for 7 days. Weight was measured at regular intervals. The 24-hour urine was sampled by metabolic cage for the measurements of uric acid, creatinine and urea nitrogen levels. The parameters for the uric acid clearance were calculated. The serum was sampled after execution for the determination of serum uric acid, creatinine. The activities of xanthine oxidase and adenine dehydrogenase were detected. The morphological measurements of stomach and kidney were completed. RESULTS: The hyperuricemia model was successfully induced by this method. In the intervention, the pH of urine was significantly elevated along with the electrolytic drinking water intake(P<0. 01). The excretion of uric acid in the rats with hyperuricemia was significantly increased while administrated with electrolytic drinking water. The effects of improving uric acid excretion were enhanced along with the intake of electrolytic drinking water. The levels of serum uric acid(group Model, Model+Treatment 1, Model+Treatment 2 and Model+Treatment 3: 693. 7 µmol/L, 668. 1 µmol/L, 642. 5 µmol/L, 633. 1 µmol/L), urine uric acid(5740. 0 µmol/L, 5894. 1 µmol/L, 5562. 3 µmol/L, 5083. 2 µmol/L) and urea nitrogen(11. 40 mmol/L, 10. 47 mmol/L, 9. 54 mmol/L, 8. 93 mmol/L) were significantly decreased in the model rats with high dose intervention(P<0. 05). Clearance of uric acid was obviously increased(9. 27%, 10. 40%, 10. 44%, 11. 13%, P<0. 05). However, no pathological change was observed among the three groups with intervention. CONCLUSION: The electrolytic drinking water intake is benefit for the excretion of uric acid of hyperuricemia rat. Enhancing alkalization of urine is considered as the important mechanism of the beneficial effects.

Virtual Calibration Quantitative Mass Spectrometry Imaging for Accurately Mapping Analytes across Heterogenous Biotissue.

It is highly challenging to quantitatively map multiple analytes in biotissues without specific chemical labeling. Quantitative mass spectrometry imaging (QMSI) has this potential but still poses technical issues for its variant ionization efficiency across a complicated, heterogeneous biomatrices. Herein, a self-developed air-flow-assisted desorption electrospray ionization (AFADESI) is introduced to present a proof of concept method, virtual calibration (VC) QMSI. This method screens and utilizes analyte response-related endogenous metabolite ions from each mass spectrum as native internal standards (IS). Through machine-learning-based regression and clustering, tissue-specific ionization variation can be automatically recognized, predicted, and normalized region by region or pixel by pixel. Therefore, the quantity of analytes can be accurately mapped across highly structural biosamples including whole body, kidney, brain, tumor, etc. VC-QMSI has the advantages of simple sample preparation without laborious isotopic IS synthesis, extrapolation for those unknown tissues or regions without previous investigation, and automatic spatial recognition without histological guidance. This strategy is suitable for mass spectrometry imaging using a variety of in situ ionization techniques. It is believed that VC-QMSI has wide applicability for drug candidate's discovery, molecular mechanism elucidation, biomarker validation, and clinical diagnosis.

Synthesis and Antibacterial Activity of Novel 4″-O-desosaminyl clarithromycin derivatives with 11, 12-arylalkyl side chains.

A series of novel 4″-O-desosaminyl clarithromycin derivatives with 11, 12-arylalkyl side chains was synthesized by coupling 6-deoxy-desosamine donors (18, 19) with 4″-OH of compounds 5a-c. The activities of the target compounds were tested against a series of macrolide-sensitive and macrolide-resistant pathogens. Some of them showed activities against macrolide sensitive and resistant pathogens, and compounds 21d and 21e displayed significant improvement of activities against resistant pathogens.