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Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G

Lim WX, Chen Z

Med Biol Eng Comput, 2024 Aug;62(8):2571-2583.
PMID: 38649629 DOI: 10.1007/s11517-024-03093-0

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermore, the computational cost of inspecting each pixel is expensive because the number of pixels is high even at low resolution. In this work, we propose a hybrid image processing method. Simple Linear Iterative Clustering with Gaussian Filter (SLIC-G) for the purpose of overcoming pixel constraints. The SLIC-G image processing method is divided into two stages: (1) simple linear iterative clustering superpixel segmentation and (2) Gaussian smoothing operation. In such a way, a large number of new transformed datasets are generated and then used for model training. Finally, two performance evaluation metrics that are suitable for imbalanced diabetic retinopathy datasets were used to validate the effectiveness of the proposed SLIC-G. The results indicate that, in comparison to prior published works' results, the proposed SLIC-G shows better performance on image classification of class imbalanced diabetic retinopathy datasets. This research reveals the importance of image processing and how it influences the performance of deep learning networks. The proposed SLIC-G enhances pre-trained network performance by eliminating the local redundancy of an image, which preserves local structures, but avoids over-segmented, noisy clips. It closes the research gap by introducing the use of superpixel segmentation and Gaussian smoothing operation as image processing methods in diabetic retinopathy-related tasks.
Fulltext The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review

Lim WX, Chen Z, Ahmed A

Med Biol Eng Comput, 2022 Mar;60(3):633-642.
PMID: 35083634 DOI: 10.1007/s11517-021-02487-8

Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence of diabetes. There are challenges such as the dearth of ophthalmologists, healthcare resources, and facilities that are unable to provide patients with appropriate eye screening services. As a result, deep learning (DL) has the potential to play a critical role as a powerful automated diagnostic tool in the field of ophthalmology, particularly in the early detection of DR when compared to traditional detection techniques. The DL models are known as black boxes, despite the fact that they are widely adopted. They make no attempt to explain how the model learns representations or why it makes a particular prediction. Due to the black box design architecture, DL methods make it difficult for intended end-users like ophthalmologists to grasp how the models function, preventing model acceptance for clinical usage. Recently, several studies on the interpretability of DL methods used in DR-related tasks such as DR classification and segmentation have been published. The goal of this paper is to provide a detailed overview of interpretability strategies used in DR-related tasks. This paper also includes the authors' insights and future directions in the field of DR to help the research community overcome research problems.
Investigation on the association between serum lipid levels and periodontitis: a bidirectional Mendelian randomization analysis

Chen Z, Song J, Tang L

BMC Oral Health, 2023 Nov 02;23(1):827.
PMID: 37919698 DOI: 10.1186/s12903-023-03575-x

OBJECTIVE: Several research has considered the potential correlation between periodontitis and serum lipids. However, serum lipid profiles correlation with periodontitis remains largely unknown. The investigation objective was to examine periodontitis correlation with serum lipid levels using a bidirectional Mendelian randomization (MR) analysis.
METHODS: The study employed a bidirectional MR analysis with two samples, utilizing a freely accessible genome-wide association study (GWAS). Furthermore, the primary analysis employed the inverse variance weighted (IVW) method. To determine whether the lipid profiles were associated with periodontitis, a variety of sensitivity analyses (including MR-Egger regression, MR-PRESSO, and weighted median), as well as multivariable MR, were employed.
RESULTS: MR analysis performed by IVW did not reveal any relationship between periodontitis and low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), or total cholesterol (TC). It was also found that LDL, HDL, TG, and TC were not associated to periodontitis. Furthermore, the MR estimations exhibited consistency with other MR sensitivity and multivariate MR (MVMR) analyses. These results show that the correlation between serum lipid levels and periodontitis could not be established.
CONCLUSION: The finding indicates a negligible link between periodontitis and serum lipid levels were identified, despite previous observational studies reporting a link between periodontitis and serum lipid levels.
Fulltext Antimicrobial, antibiofilm and antitumor activities of essential oil of Agastache rugosa from Xinjiang, China

Haiyan G, Lijuan H, Shaoyu L, Chen Z, Ashraf MA

Saudi J Biol Sci, 2016 Jul;23(4):524-30.
PMID: 27298587 DOI: 10.1016/j.sjbs.2016.02.020

In the study, we evaluated chemical composition and antimicrobial, antibiofilm, and antitumor activities of essential oils from dried leaf essential oil of leaf and flower of Agastache rugosa for the first time. Essential oil of leaf and flower was evaluated with GC and GC-MS methods, and the essential oil of flower revealed the presence of 21 components, whose major compounds were pulegone (34.1%), estragole (29.5%), and p-Menthan-3-one (19.2%). 26 components from essential oil of leaf were identified, the major compounds were p-Menthan-3-one (48.8%) and estragole (20.8%). At the same time, essential oil of leaf, there is a very effective antimicrobial activity with MIC ranging from 9.4 to 42 μg ml(-1) and potential antibiofilm, antitumor activities for essential oils of flower and leaf essential oil of leaf. The study highlighted the diversity in two different parts of A. rugosa grown in Xinjiang region and other places, which have different active constituents. Our results showed that this native plant may be a good candidate for further biological and pharmacological investigations.
Fulltext A Novel Computational Method to Reduce Leaky Reaction in DNA Strand Displacement

Li X, Wang X, Song T, Lu W, Chen Z, Shi X

J Anal Methods Chem, 2015;2015:675827.
PMID: 26491602 DOI: 10.1155/2015/675827

DNA strand displacement technique is widely used in DNA programming, DNA biosensors, and gene analysis. In DNA strand displacement, leaky reactions can cause DNA signals decay and detecting DNA signals fails. The mostly used method to avoid leakage is cleaning up after upstream leaky reactions, and it remains a challenge to develop reliable DNA strand displacement technique with low leakage. In this work, we address the challenge by experimentally evaluating the basic factors, including reaction time, ratio of reactants, and ion concentration to the leakage in DNA strand displacement. Specifically, fluorescent probes and a hairpin structure reporting DNA strand are designed to detect the output of DNA strand displacement, and thus can evaluate the leakage of DNA strand displacement reactions with different reaction time, ratios of reactants, and ion concentrations. From the obtained data, mathematical models for evaluating leakage are achieved by curve derivation. As a result, it is obtained that long time incubation, high concentration of fuel strand, and inappropriate amount of ion concentration can weaken leaky reactions. This contributes to a method to set proper reaction conditions to reduce leakage in DNA strand displacement.
The rubber elongation factor of rubber trees (Hevea brasiliensis) is the major allergen in latex

Czuppon AB, Chen Z, Rennert S, Engelke T, Meyer HE, Heber M, et al.

J Allergy Clin Immunol, 1993 Nov;92(5):690-7.
PMID: 8227860

BACKGROUND: Allergy to latex-containing articles is becoming more and more important because it can result in unexpected life-threatening anaphylactic reactions in sensitized individuals.
METHODS: A protein of 58 kd with an isoelectric point of 8.45 was purified from raw latex and from latex gloves and identified as the major allergen, completely blocking specific IgE antibodies in the serum of latex-sensitized subjects. The allergen is a noncovalent homotetramer molecule, in which the 14.6 kd monomer was identified, by amino acid composition and sequence homologies of tryptic peptides, to be the rubber elongation factor found in natural latex of the Malaysian rubber tree.
RESULTS: Competitive immunoinhibition tests showed that the starch powder covering the finished gloves is the airborne carrier of the allergen, resulting in bronchial asthma on inhalation. The purified allergen can induce allergic reactions in the nanogram range.
CONCLUSION: The identification of the allergen (Hev b I) may help to eliminate it during the production of latex-based articles in the future.
Fulltext Characteristics Regarding Lift-Off Intersection of Pulse-Modulation Eddy Current Signals for Evaluation of Hidden Thickness Loss in Cladded Conductors

Li Y, Wang Y, Liu Z, Zainal Abidin IM, Chen Z

Sensors (Basel), 2019 Sep 23;19(19).
PMID: 31547499 DOI: 10.3390/s19194102

The cladded conductor is broadly utilized in engineering fields, such as aerospace, energy, and petrochemical; however, it is vulnerable to thickness loss occurring in the clad layer and nonconductive protection coating due to abrasive and corrosive environments. Such a flaw severely undermines the integrity and safety of the mechanical structures. Therefore, evaluating the thickness loss hidden inside cladded conductors via reliable nondestructive evaluation techniques is imperative. This paper intensively investigates the pulse-modulation eddy current technique (PMEC) for the assessment of thickness loss in a cladded conductor. An analytical model of the ferrite-cored probe is established for analyzing PMEC signals and characteristics of lift-off intersection (LOI) in testing signals. Experiments are conducted for evaluation of the thickness loss in cladded conductors. An inverse scheme based on LOI for estimation of the thickness-loss depth is proposed and further verified. Through simulations and experiments, it is found that the influences of the thickness loss in the clad layer and protective coating on the PMEC signals can be decoupled in virtue of the LOI characteristics. Based on LOI, the hidden thickness loss can be efficiently evaluated without much of a reduction in accuracy by using the PMEC probe for dedicated inspection of the cladded conductor.
Development and characterization of 33 microsatellite loci for the tiger frog Hoplobatrachus rugulosus (Wiegmann 1834) through transcriptome sequencing

Chen Z, Ding G, Wang Y, Xu J, Lin Z

J Genet, 2018 Nov 14;97(5):e147-e151.
PMID: 30574879

The tiger frog Hoplobatrachus rugulosus (Wiegmann 1834) is a large robust dicroglossid frog widely distributed in southern China, Malaysia, Myanmar, Vietnam and Thailand. The escaped bred tiger frog introduced from Thailand hybridized with Chinese native population may have affected the genetic diversity of local Chinese tiger frogs. However, previous microsatellite loci of this species do not offer enough information to construct the genetic map. Here, we reported 33 new microsatellite loci from transcriptome sequencing for H. rugulosus. Alleles ranged between 1 and 10 per locus and only one locus (HRT001) was monomorphic. The polymorphic information content, observed and expected heterozygosity were 0-0.794, 0-0.969 and 0-0.831, respectively. None of the loci was observed in linkage disequilibrium and two loci (HRT023 and HRT068) deviated from Hardy-Weinberg equilibrium after Bonferroni correction for multiple tests. These transcriptome-derived microsatellite markers will be usedto study the genetic divergence and construct the genetic map in H. rugulosus.
Fulltext Reference Frame Unification of IMU-Based Joint Angle Estimation: The Experimental Investigation and a Novel Method

Yi C, Jiang F, Yang C, Chen Z, Ding Z, Liu J

Sensors (Basel), 2021 Mar 05;21(5).
PMID: 33807746 DOI: 10.3390/s21051813

Inertial measurement unit (IMU)-based joint angle estimation is an increasingly mature technique that has a broad range of applications in clinics, biomechanics and robotics. However, the deviations of different IMUs' reference frames, referring to IMUs' individual orientations estimating errors, is still a challenge for improving the angle estimation accuracy due to conceptual confusion, relatively simple metrics and the lack of systematical investigation. In this paper, we clarify the determination of reference frame unification, experimentally study the time-varying characteristics of reference frames' deviations and accordingly propose a novel method with a comprehensive metric to unify reference frames. To be specific, we firstly define the reference frame unification (RFU) and distinguish it with drift correction that has always been confused with the term RFU. Secondly, we design a mechanical gimbal-based experiment to study the deviations, where sensor-to-body alignment and rotation-caused differences of orientations are excluded. Thirdly, based on the findings of the experiment, we propose a novel method to utilize the consistency of the joint axis under the hinge-joint constraint, gravity acceleration and local magnetic field to comprehensively unify reference frames, which meets the nonlinear time-varying characteristics of the deviations. The results on ten human subjects reveal the feasibility of our proposed method and the improvement from previous methods. This work contributes to a relatively new perspective of considering and improving the accuracy of IMU-based joint angle estimation.
Fisetin induces apoptosis in breast cancer MDA-MB-453 cells through degradation of HER2/neu and via the PI3K/Akt pathway

Guo G, Zhang W, Dang M, Yan M, Chen Z

J Biochem Mol Toxicol, 2019 Apr;33(4):e22268.
PMID: 30431692 DOI: 10.1002/jbt.22268

Overexpression of human epidermal growth factor receptor 2 (HER2) is observed in breast cancer. The major snag faced by the human population is the development of chemoresistance to HER2 inhibitors by advanced stage breast cancer cells. Moreover, recent researchers focussed on fisetin as an antiproliferative and chemotherapeutic agent. Therefore, this study was intended to analyze the effects of fisetin on HER2/neu-overexpressing breast cancer cell lines. Our results depicted that fisetin induced apoptosis of these cells by various mechanisms, such as inactivation of the receptor, induction of proteasomal degradation, decreasing its half-life, decreasing enolase phosphorylation, and alteration of phosphatidylinositol 3-kinase/Akt signaling.
Fulltext A localization strategy combined with transfer learning for image annotation

Chen Z, Rajamanickam L, Cao J, Zhao A, Hu X

PLoS One, 2021;16(12):e0260758.
PMID: 34879097 DOI: 10.1371/journal.pone.0260758

This study aims to solve the overfitting problem caused by insufficient labeled images in the automatic image annotation field. We propose a transfer learning model called CNN-2L that incorporates the label localization strategy described in this study. The model consists of an InceptionV3 network pretrained on the ImageNet dataset and a label localization algorithm. First, the pretrained InceptionV3 network extracts features from the target dataset that are used to train a specific classifier and fine-tune the entire network to obtain an optimal model. Then, the obtained model is used to derive the probabilities of the predicted labels. For this purpose, we introduce a squeeze and excitation (SE) module into the network architecture that augments the useful feature information, inhibits useless feature information, and conducts feature reweighting. Next, we perform label localization to obtain the label probabilities and determine the final label set for each image. During this process, the number of labels must be determined. The optimal K value is obtained experimentally and used to determine the number of predicted labels, thereby solving the empty label set problem that occurs when the predicted label values of images are below a fixed threshold. Experiments on the Corel5k multilabel image dataset verify that CNN-2L improves the labeling precision by 18% and 15% compared with the traditional multiple-Bernoulli relevance model (MBRM) and joint equal contribution (JEC) algorithms, respectively, and it improves the recall by 6% compared with JEC. Additionally, it improves the precision by 20% and 11% compared with the deep learning methods Weight-KNN and adaptive hypergraph learning (AHL), respectively. Although CNN-2L fails to improve the recall compared with the semantic extension model (SEM), it improves the comprehensive index of the F1 value by 1%. The experimental results reveal that the proposed transfer learning model based on a label localization strategy is effective for automatic image annotation and substantially boosts the multilabel image annotation performance.
Fulltext The complete chloroplast genome and phylogenetic analysis of Christella dentata (Forssk.) Brownsey & Jermy (Thelypteridaceae)

Xu G, Zhang C, Lee SY, Chen Z, Zeng X

Mitochondrial DNA B Resour, 2023;8(1):181-185.
PMID: 36713297 DOI: 10.1080/23802359.2023.2168114

Christella dentata (Forssk.) Brownsey & Jermy (Thelypteridaceae) is endemic to the tropical and subtropical regions of Africa, Asia, and Asia Pacific. In this study, the complete chloroplast genome sequence of C. dentata was assembled using next-generation sequencing data. The complete chloroplast genome was 151,662 bp in length and had a typical quadripartite structure, which consisted of a small single-copy region (21,776 bp) and a large single-copy region (82,624 bp) that were separated by a pair of inverted repeats (23,631 bp each). A total of 131 genes were predicted, including 89 protein coding (CDS), 34 tRNA, and eight rRNA genes. The overall GC content of the chloroplast genome was 42.48%. Based on the concatenated shared unique CDS sequence dataset, phylogenetic analysis using both the maximum-likelihood and the Bayesian inference methods revealed that C. dentata is placed within Thelypteridaceae and is closely related to Christella appendiculata. Such genetic information would be useful for studies on the evolution pattern in ferns. The availability of chloroplast genome sequence for the species also paves the way to resolving the complicated relationship among members of Christella.
Fulltext Characterization of the complete plastid genome and phylogenetic analysis of Oreocharis argyreia var. angustifolia (Gesneriaceae)

Xu G, Li Z, Chen Z, Lee SY, Kong X

Mitochondrial DNA B Resour, 2023;8(10):1137-1140.
PMID: 37928400 DOI: 10.1080/23802359.2023.2270207

Oreocharis argyreia var. angustifolia of Gesneriaceae is widely distributed in South China, including Guangdong, Guangxi, Hunan, and Jiangxi provinces. However, genetic information of this species is limited, further contributing to the taxonomic complications surrounding this species. Thus, in this study, we assembled and characterized the complete chloroplast genome of O. argyreia var. angustifolia as a genomic resource for future studies. The complete plastid genome was 154,675 bp in size, with a pair of inverted repeat regions of 25,329 bp each, separating the 85,977-bp large and 18,040-bp small single copy regions. A total of 131 genes were predicted, consisting of 86 protein-coding, 37 tRNA, and eight rRNA genes. The overall GC content was 37.6%. Phylogenetic analysis based on 79 shared unique CDS resulted in a fully resolved phylogenetic tree using both the maximum likelihood and Bayesian inference methods. Based on current circumscription, both methods indicated that Oreocharis is monophyletic; O. argyreia var. angustifolia diverged after O. chienii, which then followed by the divergence of the other three species included namely, O. continifolia, O. esquirolii, and O. mileensis. The genomic data obtained will be useful for future studies on the phylogenetics and evolution of Gesneriaceae.
Fulltext Exploring feature sparsity for out-of-distribution detection

Chen Q, Li K, Chen Z, Maul T, Yin J

Sci Rep, 2024 Nov 18;14(1):28444.
PMID: 39558072 DOI: 10.1038/s41598-024-79934-7

Out-of-distribution (OOD) detection is a crucial problem in practice, especially, for the safe deployment of machine learning models in industrial settings. Previous work has used free energy as a score function and proposed a fine-tuning method that utilized OOD data in the training phase of the classification model, which achieves a higher performance on the OOD detection task compared with traditional methods. One key drawback, however, is that the loss function parameters are highly dependent on involved datasets, which means it cannot be dynamically adapted and implemented in others settings; in other words, the general ability of the energy score is considerably limited. In this work, our point of departure is to enlarge distinguishability between in-distribution features and OOD data. Consequently, we present a simple yet effective sparsity-regularized (SR) tuning framework for this purpose. Our framework has two types of workflows depending on if external OOD data is available, the complexity of the original training loss is sharply reduced by adopting this modification, meanwhile, the adapted ability and detection performance are enhanced. Also, we contribute a mini dataset as a light and efficient alternative of the previous large-scale one. In the experiments, we verify the effectiveness of our framework in a wide range of typical datasets along with common network architectures.
NES-REBS: A novel nuclear export signal prediction method using regular expressions and biochemical properties

Wu T, Wang X, Zhang Z, Gong F, Song T, Chen Z, et al.

J Bioinform Comput Biol, 2016 06;14(3):1650013.
PMID: 27225342 DOI: 10.1142/S021972001650013X

A nuclear export signal (NES) is a protein localization signal, which is involved in binding of cargo proteins to nuclear export receptor, thus contributes to regulate localization of cellular proteins. Consensus sequences of NES have been used to detect NES from protein sequences, but suffer from poor predictive power. Some recent peering works were proposed to use biochemical properties of experimental verified NES to refine NES candidates. Those methods can achieve high prediction rates, but their execution time will become unacceptable for large-scale NES searching if too much properties are involved. In this work, we developed a novel computational approach, named NES-REBS, to search NES from protein sequences, where biochemical properties of experimental verified NES, including secondary structure and surface accessibility, are utilized to refine NES candidates obtained by matching popular consensus sequences. We test our method by searching 262 experimental verified NES from 221 NES-containing protein sequences. It is obtained that NES-REBS runs in 2-3[Formula: see text]mins and performs well by achieving precision rate 47.2% and sensitivity 54.6%.
Fulltext Structured caustic vector vortex optical field: manipulating optical angular momentum flux and polarization rotation

Chen RP, Chen Z, Chew KH, Li PG, Yu Z, Ding J, et al.

Sci Rep, 2015;5:10628.
PMID: 26024434 DOI: 10.1038/srep10628

A caustic vector vortex optical field is experimentally generated and demonstrated by a caustic-based approach. The desired caustic with arbitrary acceleration trajectories, as well as the structured states of polarization (SoP) and vortex orders located in different positions in the field cross-section, is generated by imposing the corresponding spatial phase function in a vector vortex optical field. Our study reveals that different spin and orbital angular momentum flux distributions (including opposite directions) in different positions in the cross-section of a caustic vector vortex optical field can be dynamically managed during propagation by intentionally choosing the initial polarization and vortex topological charges, as a result of the modulation of the caustic phase. We find that the SoP in the field cross-section rotates during propagation due to the existence of the vortex. The unique structured feature of the caustic vector vortex optical field opens the possibility of multi-manipulation of optical angular momentum fluxes and SoP, leading to more complex manipulation of the optical field scenarios. Thus this approach further expands the functionality of an optical system.
Fulltext 1H NMR-based metabolomics investigation of copper-laden rat: a model of Wilson's disease

Xu J, Jiang H, Li J, Cheng KK, Dong J, Chen Z

PLoS One, 2015;10(4):e0119654.
PMID: 25849323 DOI: 10.1371/journal.pone.0119654

Wilson's disease (WD), also known as hepatoleticular degeneration (HLD), is a rare autosomal recessive genetic disorder of copper metabolism, which causes copper to accumulate in body tissues. In this study, rats fed with copper-laden diet are used to render the clinical manifestations of WD, and their copper toxicity-induced organ lesions are studied. To investigate metabolic behaviors of 'decoppering' process, penicillamine (PA) was used for treating copper-laden rats as this chelating agent could eliminate excess copper through the urine. To date, there has been limited metabolomics study on WD, while metabolic impacts of copper accumulation and PA administration have yet to be established.
Sources and trends of oxidized and reduced nitrogen wet deposition in a typical medium-sized city of eastern China during 2010-2016

Cui J, Cui J, Peng Y, Yao D, Chan A, Chen Z, et al.

Sci Total Environ, 2020 Jun 27;744:140558.
PMID: 32711301 DOI: 10.1016/j.scitotenv.2020.140558

Fluxes and composition dynamics of atmospheric nitrogen deposition play key roles in better balancing economic development and ecological environment. However, there are some knowledge gaps and difficulties in urban ecosystems, especially for small and medium-sized cities. In this study, both flux and composition (ratio of NH4+-N to NO3--N, RN) of wet-deposited dissolved inorganic nitrogen (DIN, sum of NO3--N and NH4+-N) were estimated and sources were identified at a long-term urban observation station in Tongling, a typical medium-sized city in eastern China during 2010-2016, respectively. Results showed that wet-deposited DIN fluxes were 33.20 and 28.15 kgN ha-1 yr-1 in Tongling city during 2010-2011 and 2015-2016, respectively. Compared to these two periods, both DIN and NO3--N fluxes decreased by 15.2% and 31.8% for a series of NOx abatement measures applied effectively, respectively. At the same time, the NH4+-N flux remained stable and ranged from 19.53 to 20.62 kgN ha-1 yr-1, and the RN increased from 1.7 to 2.2. Seasonally, winds from the southwest and west-southwest with higher frequencies and speeds in spring and summer brought more NH4+-N and DIN wet deposition from an ammonia plant, which could threaten the safety of regional hydrosphere ecosystems. On the whole, the wet-deposited NH4+-N was threatening regional ecosystems of both the hydrosphere and forest. The wet-deposited DIN including NH4+-N in Tongling city stemmed mainly from a combined source of coal combustion and dust from Cu extraction and smelting, ammonia production, and roads. Therefore, production lines should be updated for Cu extraction and smelting industries, thermal power generations and the ammonia plant, old vehicles should be eliminated, and the use of new energy vehicles should be promoted for regional sustainable development and human health in the medium-sized city.
Real-time and visual sensing devices based on pH-control assembled lanthanide-barium nano-cluster

Liu M, Li H, Bai L, Zheng K, Zhao Z, Chen Z, et al.

J Hazard Mater, 2021 07 05;413:125291.
PMID: 33588337 DOI: 10.1016/j.jhazmat.2021.125291

Real-time and visual monitoring of pollutants in the air is of great importance since they are usually cannot be seen, smelled, or touched. Lanthanide nano-cluster is a kind of luminescent sensor for various species. However, controlling synthesis of lanthanide nano-cluster remains experimentally challenging. In this work, four series of lanthanide-barium (Ln-Ba) nano-clusters of Dy2Ba (1), Tb2Ba2 (2), Ln4Ba3 (Ln = Tb, 3a; Eu, 3b), Tb4Ba4 (4) were assembled through precisely controlling the pH of the reactant solutions. The work features the first example that the number of cluster's nuclei changes regularly with the pH. Moreover, investigation reveals that nano-cluster 3a is a highly selective and sensitive sensor towards acetylacetone (acac) and aniline. Interestingly, easy-to-use sensing devices of test paper, agarose gel, and five kinds of film on CaCO3, polyfoam, coin, mask, and wall that based on 3a were fabricated by facile methods. The seven sensing devices showed remarkable ability to sense aniline and acac vapors with visibility to the naked eyes. This is the first work on multiple real-time and visual sensing devices based on the lanthanide nano-cluster.
Genomic evaluations of Wolbachia and mtDNA in the population of coconut hispine beetle, Brontispa longissima (Coleoptera: Chrysomelidae)

Ali H, Muhammad A, Bala NS, Wang G, Chen Z, Peng Z, et al.

Mol Phylogenet Evol, 2018 10;127:1000-1009.
PMID: 29981933 DOI: 10.1016/j.ympev.2018.07.003

Wolbachia pipientis is a diverse, ubiquitous and most prevalent intracellular bacterial group of alpha-Proteobacteria that is concerned with many biological processes in arthropods. The coconut hispine beetle (CHB), Brontispa longissima (Gestro) is an economically important pest of palm cultivation worldwide. In the present study, we comprehensively surveyed the Wolbachia-infection prevalence and mitochondrial DNA (mtDNA) polymorphism in CHB from five different geographical locations, including China's Mainland and Taiwan, Vietnam, Thailand, Malaysia and Indonesia. A total of 540 sequences were screened in this study through three different genes, i.e., cytochrome oxidase subunit I (COI), Wolbachia outer surface protein (wsp) and multilocus sequencing type (MLST) genes. The COI genetic divergence ranges from 0.08% to 0.67%, and likewise, a significant genetic diversity (π = 0.00082; P = 0.049) was noted within and between all analyzed samples. In the meantime, ten different haplotypes (H) were characterized (haplotype diversity = 0.4379) from 21 different locations, and among them, H6 (46 individuals) have shown a maximum number of population clusters than others. Subsequently, Wolbachia-prevalence results indicated that all tested specimens of CHB were found positive (100%), which suggested that CHB was naturally infected with Wolbachia. Wolbachia sequence results (wsp gene) revealed a high level of nucleotide diversity (π = 0.00047) under Tajima's D test (P = 0.049). Meanwhile, the same trend of nucleotide diversity (π = 0.00041) was observed in Wolbachia concatenated MLST locus. Furthermore, phylogenetic analysis (wsp and concatenated MLST genes) revealed that all collected samples of CHB attributed to same Wolbachia B-supergroup. Our results strongly suggest that Wolbachia bacteria and mtDNA were highly concordant with each other and Wolbachia can affect the genetic structure and diversity within the CHB populations.

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