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Oncogenes are increasingly recognized as important factors in the development and progression of cancer. Holliday Junction Recognition Protein (HJURP) is a highly specialized mitogenic protein that is a chaperone protein of histone H3. The HJURP gene is located on chromosome 2q37.1 and is involved in nucleosome composition in the mitotic region, forming a three-dimensional crystal structure with Centromere Protein A (CENP-A) and the histone 4 complex. HJURP is involved in the recruitment and assembly of centromere and kinetochore and plays a key role in stabilizing the chromosome structure of tumor cells, and its dysfunction may contribute to tumorigenesis. In the available studies HJURP is upregulated in a variety of cancer tissues and cancer cell lines and is involved in tumor proliferation, invasion, metastasis and immune response. In an in vivo model, overexpression of HJURP in most cancer cell lines promotes cell proliferation and invasiveness, reduces susceptibility to apoptosis, and promotes tumor growth. In addition, upregulation of HJURP was associated with poorer prognosis in a variety of cancers. These properties suggest that HJURP may be a possible target for the treatment of certain cancers. Various studies targeting HJURP as a prognostic and therapeutic target for cancer are gradually attracting interest and attention. This paper reviews the functional and molecular mechanisms of HJURP in a variety of tumor types with the aim of providing new targets for future cancer therapy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Yuan, Chu, Jiang, Zhao, Su, Huo and Zhang.)

Aims: Microorganisms in fermentation pits (FPs) play key roles for Chinese-strong-aromatic-liquor (CSAL) production. However, the microbial community in the FPs is still poorly understood. Here, the aim of this study was to reveal the diversity and potential functions of microbiota in FPs., Methods and Results: Sequencing-by-synthesis-based metagenomic sequencing and annotation results revealed that the microbiota of FPs was primarily composed of Firmicutes (54·6%), Euryarchaeota (15·3%), Bacteroidetes (10·1%), Gammaproteobacteria (5·8%), Opisthokonta (5·7%) and Unclassified_Bacteria (2·3%). And 133 genera were identified as the dominant genera of this fermentative food. Lactobacillus, Sedimentibacter, Syntrophomonas, Methanoculleus, Methanobacterium, Bacillus, Clostridium, Galactomyces, Candida, Pichia, Penicillium and Aspergillus were defined as active populations for biosynthesizing the characteristic volatile compounds of CSAL. The study also revealed that the microbial community structures changed significantly with different cellar ages and over different geographical regions. (i) The presence of Bacteroidetes was the most distinctive feature that characterized the different FPs ages. (ii) Distinct contents of Gammaproteobacteria and Euryarchaeota were observed at different positions in the FPs. (iii) Euryarchaeota markedly contributed to the generation of the character of the liquors with distinct geographical associations., Conclusions: This study demonstrated that the changes of microbial communities determined the different quality characteristics of CSAL., Significance and Impact of the Study: This research contributes to a deeper understanding of the FPs microbial composition and shows a new microbial resource for biotechnological applications., (© 2019 The Society for Applied Microbiology.)

A minimally-disruptive portable electrochemical system is constructed by combining a hand-held syringe as reservoir with disposable screen-printed electrodes (SPEs) modified with a simple and efficient yeast/Co 3 O 4 /Au material for lead determination by a square-wave voltammetry (SWV) method. Not only can it preserve the operation and advantages of the conventional electrochemical procedure, but it also integrates sampling, filtering and analysis to make the determination of lead convenient and effective at higher and lower concentration levels. This is the first report of a microbial biosensor based on active yeast crosslinked to Co 3 O 4 /Au particles using glutaraldehyde as the crosslinking agent. The determination process is simplified by introducing a fiber filter and takes only 150 s with the developed system, which illustrates its simplicity, speed and detection accuracy. Also, the design shows a wide log-linear dynamic range (LDR) from 10 -8 to 10 -14  g·L -1 , with a limit of detection (LOD) of 3.45 × 10 -15  g·L -1 (S/N = 3). Additionally, the proposed system was used to determine lead in blood samples, which demonstrated the potential of this biosensor for use in practical applications. Furthermore, this study provides a basis for the development of microscale blood devices for lead measurement., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this work, a simple room-temperature phosphorescence (RTP) method was first proposed to detect adriamycin, by using a functional material of Mn doped ZnS quantum dots (Mn-ZnS QDs) composited with poly(diallyldimethylammonium chloride) (PDDA). After PDDA was associated to the Mn-ZnS QDs, the RTP intensity was significantly enhanced. As a result, Mn-ZnS QDs/PDDA nanoassemblies greatly improve the adriamycin detection ability of QDs and provide an important method for developing more effective and sensitive adriamycin detection sensor. The method based upon RTP has a linear range from 0.5 to 64.0 μM with a detection limit (3σ/s) for adriamycin of 0.45 μM. The developed method was further successfully applied to detect adriamycin in human serum samples (diluted 50 times) with satisfactory results, and the recovery ranged from 98.3 to 101.3.

In recent years, optical colorimetric sensor arrays have demonstrated beneficial features, including rapid response, high selectivity, and high specificity; as a result, it has been extensively applied in food inspection and chemical studies, among other fields. There are instruments in the current market available for the preparation of an optical colorimetric sensor array, but it lacks the corresponding research of the preparation mechanism. Therefore, in connection with the main features of this kind of sensor array such as consistency, based on the preparation method of contact spotting, combined with a capillary fluid model, Washburn equation, Laplace equation, etc., this paper develops a diffusion model of an optical colorimetric sensor array during its preparation and sets up an optical colorimetric sensor array preparation system based on this diffusion model. Finally, this paper compares and evaluates the sensor arrays prepared by the system and prepared manually in three aspects such as the quality of array point, response of array, and response result, and the results show that the performance index of the sensor array prepared by a system under this diffusion model is better than that of the sensor array of manual spotting, which meets the needs of the experiment.

Herein, we have developed a simple, sensitive and paper-based colorimetric sensor for the selective detection of Chromium (Ⅵ) ions (Cr (VI)). Silanization-titanium dioxide modified filter paper (STCP) was used to trap bovine serum albumin capped gold nanoparticles (BSA-Au NPs), leading to the fabrication of BSA-Au NPs decorated membrane (BSA-Au NPs/STCP). The BSA-Au NPs/STCP operated on the principle that BSA-Au NPs anchored on the STCP were gradually etched by Cr (VI) as the leaching process of gold in the presence of hydrobromic acid (HBr) and hence induced a visible color change. Under optimum conditions, the paper-based colorimetric sensor showed clear color change after reaction with Cr (VI) as well as with favorable selectivity to a variety of possible interfering counterparts. The amount-dependent colorimetric response was linearly correlated with the Cr (VI) concentrations ranging from 0.5µM to 50.0µM with a detection limit down to 280nM. Moreover, the developed cost-effective colorimetric sensor has been successfully applied to real environmental samples which demonstrated the potential for field applications., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In this work, maltodextrin-grafted-cinnamic acid (MD-g-CA) was synthesised and used as wall material to improve the stability of purple sweet potato anthocyanins (PSPa) via microencapsualtion. MD-g-CA was prepared through esterification in a two-step convenient synthesis procedure and characterised using infra-red (IR) spectroscopy. The IR data indicated the typical ester carbonyl stretching at around 1721 cm -1 . Moreover, MD-g-CA could give about 40% inhibition of DPPH radical and present excellent UV-absorption, which were notably better than that of native MD. Maltodextrin (MD) and MD-g-CA were used to prepare PSPa microcapsules by spray drying. The stability of PSPa was evaluated by UV-Vis analysis. The microcapsules produced by MD-g-CA showed a spheres-like appearance with some cracks. Storage tests revealed that the degradation rate of PSPa embedded by MD-g-CA was much lower than that of free PSPa under the same condition. Thus, MD-g-CA could be used as an effective wall material to improve stability of anthocyanins.

In this paper, a novel, simple, rapid, and low-cost detection device for lung cancer related Volatile Organic Compounds (VOCs) was constructed. For this task, a sensor array based on cross-responsive mechanism was designed. A special gas chamber was made to insure sensor array exposed to VOCs sufficiently and evenly, and FLUENT software was used to simulate the performance of the gas chamber. The data collection and processing system was used to detect fluorescent changes of the sensor arrays before and after reaction, and to extract unique patterns of the tested VOCs. Four selected VOCs, p-xylene, styrene, isoprene, and hexanal, were detected by the proposed device. Unsupervised pattern recognition methods, hierarchical cluster analysis and principal component analysis, were used to analyze data. The results showed that the methods could 100% discriminate the four VOCs. What is more, combined with artificial neural network, the correct rate of quantitative detection was up to 100%, and the device obtained responses at concentrations below 50 ppb. In conclusion, the proposed detection device showed excellent selectivity and discrimination ability for the VOCs related to lung cancer. Furthermore, our preliminary study demonstrated that the proposed detection device has brilliant potential application for early clinical diagnosis of lung cancer.

A new colorimetric sensor array was developed for the discrimination of 12 high-alcoholic Chinese base liquors from Luzhou Co., Ltd., and 15 commercial Chinese liquor of different brands as well as flavor types. Seventeen volatile compounds within four chemical groups were determined as markers in the base liquor by GC-MS analysis and factor analysis method (FAM). A specialized colorimetric sensor array composed of 20 sensitive dots was fabricated accordingly to obtain sensitive interaction with different types of volatile markers. Discrimination of the liquor samples was subsequently performed using chemometric and statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). The results suggested that facile identification of either base liquors with high-alcoholic volume or commercial liquors of the same flavor types could be achieved by analysis of the color change profiles. The response of the sensor improved significantly in comparison with those that rely on nonspecific interactions, and no misclassification was observed for both liquor samples using two chemometric methods. Besides, it was also found that the discrimination is closely related to the characteristic flavor compounds (esters, aldehydes, and acids) and alcoholic strength in liquors, and its performance was even comparable with that of GC-MS.

The complex microbiota of pit mud of solid-state fermentation reactors used for the production of Chinese liquor is responsible for producing one of the oldest distillates in the world. We apply a deep-sequencing approach to characterize the microbiota from pits that have been in use for up to 440 years., (Copyright © 2014 Guo et al.)

A plant-esterase extracted from wheat flour and purified with a PEG1000/NaH(2)PO(4) aqueous two-phase system was characterized for its catalytic characteristics. The optimal condition for plant-esterase to catalyze 1-naphthyl acetate was at 30°C, pH 6.5. It kept stability at 20°C during 120 min and at pH 5.5 during 60 h. The effects of metal ions, chemical modification reagents and pesticides on plant-esterase activity were investigated. It was found that Ba(2+) and Pb(2+) at concentrations of 20 mM significantly inhibited the activity of plant-esterase while Mg(2+), Ca(2+) and Fe(2+) at the same concentration enhanced the enzyme activity. Chemical modification reagents significantly influenced the activity of plant-esterase. Particularly, PMSF (4.5 mM) and N-bromosuccinimide (11 mM) inhibited by 5.40-19.87% of the enzyme activity. It is implied that serine and tryptophan are related to the enzyme activity. Plant-esterase were displayed concentration-dependent inhibition by dichlorvos, carbofuran and carbendazim (IC50 = 0.31-63.12 ppm). All these results indicated that catalytic efficiency of plant-esterase strongly depends on reaction conditions, activity effectors and amino acid residues at the active site. It makes meaningful guidance on further design of sensing material in monitoring pesticides.

With a colorimetric sensor array comprising chemoresponsive dyes, a simple, rapid, and cost-effective integrated system for differentiating low-concentration gases was described. The system could be used to identify gases by detecting the color change information of the chemoresponsive dyes based on porphyrins before and after reaction with the target gas; the colorimetric sensor array images were collected by a charge coupled device and processed with image analysis to get the color changes of the dyes in the array. Temperature, humidity, and flux of the chamber could be detected and displayed on the personal computer screen. A low-concentration [30-210 ppb (parts per 10(9))] NH(3) was detected by the system. This prototype successfully differentiated four concentration levels of NH(3) in less than 1 min. Pattern recognition methods, such as the backpropagation neural network and the radial basis function neural network, validated the effect of the developed sensor system both with 100% classification with feature vectors at single time point as inputs.