Application of computer vision and deep learning models to automatically classify medically important mosquitoes in North Borneo, Malaysia.

Mosquito-borne diseases have emerged in North Borneo in Malaysia due to rapid changes in the forest landscape, and mosquito surveillance is key to understanding disease transmission. However, surveillance programmes involving sampling and taxonomic identification require well-trained personnel, are time-consuming and labour-intensive. In this study, we aim to use a deep leaning model (DL) to develop an application capable of automatically detecting mosquito vectors collected from urban and suburban areas in North Borneo, Malaysia. Specifically, a DL model called MobileNetV2 was developed using a total of 4880 images of Aedes aegypti, Aedes albopictus and Culex quinquefasciatus mosquitoes, which are widely distributed in Malaysia. More importantly, the model was deployed as an application that can be used in the field. The model was fine-tuned with hyperparameters of learning rate 0.0001, 0.0005, 0.001, 0.01 and the performance of the model was tested for accuracy, precision, recall and F1 score. Inference time was also considered during development to assess the feasibility of the model as an app in the real world. The model showed an accuracy of at least 97%, a precision of 96% and a recall of 97% on the test set. When used as an app in the field to detect mosquitoes with the elements of different background environments, the model was able to achieve an accuracy of 76% with an inference time of 47.33 ms. Our result demonstrates the practicality of computer vision and DL in the real world of vector and pest surveillance programmes. In the future, more image data and robust DL architecture can be explored to improve the prediction result.

Genome-wide analysis of long non-coding RNAs in adult tissues of the melon fly, Zeugodacus cucurbitae (Coquillett).

BACKGROUND: Long non-coding RNAs (lncRNAs) are involved in many fundamental biological processes, such as transcription regulation, protein degradation, and cell differentiation. Information on lncRNA in the melon fly, Zeugodacus cucurbitae (Coquillett) is currently limited. RESULTS: We constructed 24 RNA-seq libraries from eight tissues (midgut, Malpighian tubules, fat body, ovary, and testis) of Z. cucurbitae adults. A total of 3124 lncRNA transcripts were identified. Among those, 1464 were lincRNAs, 1037 were intronic lncRNAs, 301 were anti-sense lncRNAs, and 322 were sense lncRNAs. The majority of lncRNAs contained two exons and one isoform. Differentially expressed lncRNAs were analyzed between tissues, and Malpighian tubules versus testis had the largest number. Some lncRNAs exhibited strong tissue specificity. Specifically expressed lncRNAs were identified and filtered in tissues of female and male Z. cucurbitae based on their expression levels. Four midgut-specific lncRNAs were validated by quantitative real-time polymerase chain reaction (RT-qPCR), and the data were consistent with RNA-seq data. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of targets of midgut-specific lncRNAs indicated an enrichment of the metabolic process. CONCLUSIONS: This was the first systematic identification of lncRNA in the melon fly. Expressions of lncRNAs in multiple adult tissues were evaluated by quantitative transcriptomic analysis. These qualitative and quantitative analyses of lncRNAs, especially the tissue-specific lncRNAs in Z. cucurbitae, provide useful data for further functional studies.

DOCK7-ANGPTL3 SNPs and their haplotypes with serum lipid levels and the risk of coronary artery disease and ischemic stroke.

BACKGROUND: Little is known about the association of the dedicator of cytokinesis 7 (DOCK7 rs1748195) and angiopoietin like 3 (ANGPTL3 rs12563308) single nucleotide polymorphisms (SNPs) and their haplotypes with serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese populations. This study aimed to detect such association in a Southern Chinese Han population. METHODS: This study included 1728 subjects (CAD, 568; IS, 539; and controls, 621). Genotypes of the two SNPs were determined by the Snapshot technology. RESULTS: The genotypic and allelic frequencies of the rs1748195 SNP were different between CAD patients and controls (P < 0.05 for each), the rs1748195G allele frequency was higher in CAD patients than in controls (27.6% vs. 23.6%, P = 0.024). The genotypic frequencies of the rs12563308 SNP were also different between CAD patients and controls (P = 0.021). The rs1748195 SNP was associated with an increased risk of CAD after controlling for potential confounders and Bonferroni correction (P < 0.025 considered statistically significant; Recessive: OR = 1.79, 95% CI = 1.04-3.06, P = 0.017; Log-additive: OR = 1.27, 95% CI = 1.02-1.57, P = 0.014), whereas the rs12563308 SNP was associated with a decreased risk of CAD (Dominant: OR = 0.69, 95% CI = 0.45-0.94, P = 0.011; Log-additive: OR = 0.73, 95% CI = 0.49-0.89, P = 0.009). The rs1748195 SNP was also associated with an increased risk of severity to coronary artery atherosclerosis (Dominant: OR = 1.45, 95% CI = 1.07-2.11, P = 0.017; Log-additive: OR = 1.35, 95% CI = 1.09-1.82, P = 0.013). The interactions of SNP-environment on serum lipid levels and the risk of severity to coronary artery atherosclerosis, CAD and IS were noted. The rs1748195G-rs12563308T haplotype was associated with an increased angiographic severity to coronary artery atherosclerosis (OR = 1.46, 95% CI = 1.05-2.03), and the risk of CAD (OR = 1.37, 95% CI = 1.08-1.74). The interactions of haplotype-hypertension on the risk of CAD and haplotype-drinking on the risk of CAD/IS were observed. CONCLUSIONS: These results suggest that the DOCK-ANGPTL3 SNPs and their haplotypes were associated with the angiographic severity to coronary artery atherosclerosis and the risk of CAD and IS in the Southern Chinese Han population.

A New Feature Extraction Method of Near-Infrared Spectra Based on the Addition of Historical Data.

In traditional qualitative analysis of near-infrared (NIR) spectra, the stability of recognition models is decreased when new varieties of samples are added into the model. In order to improve the robustness of the model, a new feature extraction method based on the addition of historical data was put forward. The NIR training samples will be collected first, after that the historical data of the same species is added to constitute a larger and richer dataset. Then, the pretreated data of these training samples is projected to the feature space, which is constructed by feature extraction using partial least squares (PLS) based on the above dataset. Subsequently, orthogonal linear discriminant analysis (OLDA) is employed to extract features of the projected data. 18 varieties of corn seeds were taken as study subject, the comparative experiments with and without historical data are implemented respectively, and then the biomimetic pattern recognition (BPR) method is applied to verify the efficiency of the method proposed. The results suggest that the method adopted can improve the robustness of recognition model more effectively compared with the method without historical data. It maintains the high correct recognition ratios when new varieties are added into the model. Besides that, the recognition effect on test sets of the different days remains the same basically in the condition of same PLS dimensions. Therefore, the dimension of feature extraction can be set to some fixed values in recognition software. In this way, it can keep out of the trouble of manually modifying the optimal PLS parameter in recognition software if new varieties need to be added into the model. The experiment results of the thesis manifested the effectiveness of the proposed method.

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

[Study on spectral calibration of discrimination of corn variety using near-infrared spectra based on DS algorithm].

From the perspective of calibration, the present paper studies the model stability problem in qualitative analysis of NIR. Aiming at the issue of model failure caused by different data acquisition time, 13 varieties of corn were used as experimental material, and learning from the idea of model calibration transfer between the two instruments in quantitative analysis of NIR, the DS (direct standardization) algorithm was used to calibrate the spectra acquired at different times with the same instrument, that made the varieties identification model established one time able to be applied to identify the test data at different acquisition time. First, transfer set was selected from the master spectrum set by Kennard/Stone algorithm, the corresponding number spectrums in slave spectrum set were selected, and then DS algorithm was applied to transfer set to calculate the transformation function between the two sets of data. Finally, the remaining slave spectrums were transformed so that they could apply to the model. This study does some experiment to discuss the impact of the number of transfer set and the location of calibration on the calibration results. Respectively, the experiment results were analyzed from two aspects, one is the correct discrimination rate in qualitative analysis, and the other is the distribution distance between master spectrums and slave spectrums before and after calibration. The experiment results indicate that this approach is effective to solve the spectra drift produced by sampling over time, can bring higher recognition rate on different sampling time test sets, also improves the robustness and application scope of the identification model, and the experiment results also indicate that the best result can be obtained with calibration locating after feature extraction.

Comparative analyses of the transcriptome among three development stages of Zeugodacus tau larvae (Diptera: Tephritidae).

Studying differences in transcriptomes across various development stages of insects is necessary to uncover the physiological and molecular mechanism underlying development and metamorphosis. We here present the first transcriptome data generated under Illumina Hiseq platform concerning Zeugodacus tau (Walker) larvae from Nanchang, China. In total, 11,702 genes were identified from 9 transcriptome libraries of three development stages of Z. tau larvae. 7219 differentially expressed genes (DEGs) were screened out from the comparisons between each two development stages of Z. tau larvae, and their roles in development and metabolism were analyzed. Comparative analyses of transcriptome data showed that there are 5333 DEGs between 1-day and 7-day old larvae, consisting of 1609 up-regulated and 3724 down-regulated genes. Expressions of DEGs were more abundant in L7 than in L1 and L3, which might be associated with metamorphosis. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested the enrichment of metabolic process. KOG annotation further confirmed that 20-hydroxyecdysone (20E) pathway related genes Cyp4ac1_1, Cyp4aa1, Cyp313a4_3 were critical for the biosynthesis, transport, and catabolism of secondary metabolites and lipid transport and metabolism. Expression patterns of 8 DEGs were verified using quantitative real-time PCR (RT-qPCR). This study elucidated the DEGs and their roles underlying three development stages of Z. tau larvae, which provided valuable information for further functional genomic research.

Do we really need closed-suction drainage in total hip arthroplasty? A meta-analysis.

PURPOSE: The clinical use of closed-suction drainage, which aims to reduce postoperative wound haematomas and infection, is common. This study was performed to determine whether closed-suction drainage is safe and effective in promoting wound healing and reducing blood loss and other complications compared with no-drainage in total hip arthroplasty. METHODS: The literature search was based on PubMed, the Cochrane Library, MEDLINE, and EMBASE. The data were evaluated using the generic evaluation tool designed by the Cochrane Bone, Joint and Muscle Trauma Group, and then analysed using RevMan 5.0. Twenty randomised controlled trials involving 3,186 patients were included in our analysis. RESULTS: The results of our meta-analysis indicate that closed-suction drainage reduces the requirement for dressing reinforcement, but increases the rate of homologous blood transfusion. No significant difference was observed in the incidence of infection, blood loss, changes in haemoglobin and haematocrit, functional assessment, or other complications when the drainage group was compared with the no-drainage group. CONCLUSIONS: Our results of the comparison between closed-suction drainage and no drainage in THA have indicated that the routine use of closed-suction drainage for elective total hip arthroplasty may be of more harm than benefit.

Comparative multi-tissue analyses identify testis-specific serine/threonine protein kinase (TSSK) genes involved in male fertility in the melon fly Zeugodacus cucurbitae.

BACKGROUND: Zeugodacus cucurbitae is an agricultural pest species with robust reproductive capabilities capable of causing extensive damage. The advent of novel male fertility-related pest control strategies has been an area of active entomological research focused on the sterile insect technique (SIT) strategy. RESULTS: RNA-sequencing analyses were conducted using 16 tissue samples from adult male Z. cucurbitae, leading to the identification of 5338 genes that were differentially expressed between the testes and three other analyzed tissue types. Of these genes, 808 exhibited high levels of testis expression. A quantitative polymerase chain reaction (qPCR) approach was used to validate the expression of ten of these genes selected at random, including ZcTSSK1 and ZcTSSK3, which are testis-specific serine/threonine protein kinase (TSSK) genes. Evaluation via a loss-of-function-based knockdown assay showed that the down-regulation of either of these two genes in males was associated with significantly decreased egg hatching rates. In situ hybridization analyses revealed the expression of both of these transcripts in the transformation zone, and significant decreases in Z. cucurbitae sperm numbers were observed following double-stranded RNA treatment. Together, these results suggested that inhibiting ZcTSSK1 and ZcTSSK3 expression was sufficient to alter male fertility in Z. cucurbitae. CONCLUSION: These transcriptional sequencing results provide a foundation for further efforts to clarify the regulators of Z. cucurbitae male fertility. These preliminary analyses of the functions of ZcTSSK family genes as regulators of spermatogenesis underscore their importance in the processes integral to male fecundity and their potential as targets for pest control efforts centered on the genetic manipulation of males. © 2023 Society of Chemical Industry.

Public Awareness, Perception, and Knowledge of Bed Bug Infestation Prevalence in Iraq.

Background: Bed bugs are blood-feeding insects and are an important urban pest. Bed bugs are nocturnal insects and hide in cracks in walls and beds during the day. The study aims to: (1) determine the bed bugs species that infest Iraq, their infestation source, and their distribution; (2) determine the level of awareness and concern regarding bed bugs among the Iraqi community. Methods: Between 2020 and 2021, a survey of bed bug infestation dynamics was conducted in 18 infested sites located in major cities across eight governorates. The 23-item online survey was distributed over social media to Iraqi citizens between June and July 2022 to survey on their familiarity with bed bug habitat, medical significance, transmission, prevention, control measures, and concerns. Results: There were a total of 1104 bed bugs collected. Based on the morphological characteristics, bed bugs collected from eight Iraqi governorates are identified as Cimex hemipterus. Besides, a high rate of bed bug infestation was observed in workers' dormitories. The online questionnaire was answered by 1843 respondents and based on the feedback, most respondents (55.3%) have no awareness of bed bug infestations, while around 43.8% are somewhat concerned about bed bug infestations in Iraq. Conclusion: Only tropical bed bugs, C. hemipterus were found in all sampled sites. Bed bug infestations are mainly caused by migrant workers and the reuse of second-hand furniture and clothing. The results suggest that the Iraqi government should organize more proper demonstrations on bed bug awareness for the public.

[Research on the parameter drift problem of near infrared spectra based corn variety discrimination technology].

Aiming to differentiate 13 varieties of corn, present paper proposes an effective approach to solving the parameter drift problem of spectrum instruments. Remarkable drift has been found among the inter-day data when using the identical spectrum instrument to acquire sample data at different times, modeling with the intra-day data, and testing with the rest. The correct recognition rate is reduced to only 7.69% in the condition of severe drift. To tackle this problem, this paper proposes a supervised feature-based inter-day combination modeling approach, at first, the representative sample data acquired at multiple times will be selected to make up the modeling set, and then the PLS+LDA algorithm will be applied to extract the feature of varieties which is independent on instrument parameter drift, and finally BPR will be used to identify the varieties. The experiment results indicate that this approach is effective to rectify the data drift at different times, can bring higher recognition rate, and also shows its stability in practice.

Expression and Role of Vitellogenin Genes in Ovarian Development of Zeugodacus cucurbitae.

Vitellogenin (Vg) genes encode the major egg yolk protein precursor in arthropods. In this study, four Vgs were identified in Zeugodacus cucurbitae (Coquillett). Sequence analysis showed that four ZcVgs had the conserved Vg domain. Phylogenetic analysis indicated that four ZcVgs were homologous to the Vgs of Tephritidae insects. The temporal and spatial expression patterns of ZcVgs were analyzed by quantitative real-time polymerase chain reaction (RT-qPCR), and the four ZcVgs showed high expression levels in female adults, especially in the fat body. The expression of ZcVg1 and ZcVg3 was down-regulated by a low dosage (0.5 µg) of 20-hydroxyecdysone (20E), and ZcVg2, ZcVg3, and ZcVg4 were up-regulated by a high dosage (1.0 and 2.0 µg) of 20E. The expression of ZcVg1 and ZcVg2 was up-regulated by 5 µg of juvenile hormone (JH), while all of the ZcVgs were down-regulated by a low and high dosage of JH. Expression of ZcVgs was down-regulated after 24 h of starvation and recovered to normal after nutritional supplementation. After micro-injection of the gene-specific double-stranded RNA, the ZcVgs' expression was significantly suppressed, and ovarian development was delayed in Z. cucurbitae females. The results indicate that RNA interference of reproduction-related genes is a potential pest control method that works by manipulating female fertility.

[Application of DPLS-based LDA in corn qualitative near infrared spectroscopy analysis].

NIR technology is a rapid, nondestructive and user-friendly method ideally suited for Qualitative analysis. In this paper the authors present the use of discriminant partial least Squares (DPLS)-based linear discriminant analysis (LDA) in corn qualitative near infrared spectroscopy analysis. Firstly, a training set including 30 corn varieties (each variety has 20 samples) was used to build the DPLS regression model, and 28 principal components (DPLS-PCs) were obtained from original spectrum. Secondly, the DPLS-PCs scores of the training set were extracted as DPLS features. Thirdly, LDA was applied to the DPLS features, determining 26 principal components (LDA-PCs). A test sample was first projected onto the DPLS-PCs and then onto the LDA-PCs, and finally 26 DPLS+LDA features were obtained. The recognition results were obtained by minimum distance classifier. DPLS+LDA method achieved 96.18% recognition rate, while traditional DPLS regression method and DPLS feature extraction method only achieved 85.38% and 95.76% recognition rate respectively. The experiment results indicated that DPLS +LDA method is with better generalization ability compared with traditional DPLS regression method and NIRS analysis by DPLS+LDA method is an efficient way to discriminate corn species.

[DFT feature analysis of corn varieties based on near infrared spectra].

The present paper develops a new approach to the analyse of corn based on discrete Fourier transform (DFT). The experiment data is of 37 varieties of corn seed with the Fourier transform near infrared spectrometer in the wave number range from 4 000 to 12 000 cm(-1). Analyse of the origin data found that as the wave number increases, the data noise also increases. Firstly, the paper defines a calculation method of interspecific and intraspecific differences Qm to measure the effectiveness of feature selection. Secondly, Qm was used to analyse the original data and DFT-section data. Experimental results show that by choosing data of DFT with wave number range from 4 000 to 7 085 cm(-1), the mean value and the peak value of the the Qm curve markedly improved relative to the full band original data. The mean value was enhanced from the original 4.804 9 to 8.513 8, and the max of the peak value was enhanced from the original 35.924 0 to 60.821 6, while the min of the peak value was enhanced from the original 2.891 8 to 3.741 5. Data feature points (Qm value of large point) are more concentrated than the original data after DFT. Such a result is most conducive to extracting the characteristics of corn seed.

[Study on discrimination of varieties of corn using near-infrared spectroscopy based on GA and LDA].

A new method for the fast discrimination of varieties of corn based on near-infrared spectroscopy using genetic algorithm and linear discriminant analysis (LDA) was proposed. First, data of NIS of 37 varieties of corn was collected, second, genetic algorithm used for choosing the feature band of spectrum, then PCA and LDA were used to extract features, and finally corn seeds were classified. The result showed that GA could remove noise band effectively and improve the generalization ability of LDA. A large number of redundant data was removed to simplify the computing, which resulted in the data dimension reduction from 2075 to 233. For the 300 samples of test set one, the average correct recognition rate and average correct rejection rate attained 99.30% for both, and the average correct recognition rate of 73.33% varieties of corn attained for 100%. For the 175 samples of test set 2 (all of whose varieties had not been trained), the average correct recognition rate attained 99.65%. The run time is shorter and the correct rate is higher compared to the common method of PCA.

Identification and Expression Characterization of ATP-Binding Cassette (ABC) Transporter Genes in Melon Fly.

The ATP-binding cassette (ABC) transporter is a protein superfamily that transports specific substrate molecules across lipid membranes in all living species. In insects, ABC transporter is one of the major transmembrane protein families involved in the development of xenobiotic resistance. Here, we report 49 ABC transporter genes divided into eight subfamilies (ABCA-ABCH), including seven ABCAs, seven ABCBs, 10 ABCCs, two ABCDs, one ABCE, three ABCFs, 16 ABCGs, and three ABCHs according to phylogenetic analysis in Zeugodacus cucurbitae, a highly destructive insect pest of cucurbitaceous and other related crops. The expressions level of 49 ABC transporters throughout various developmental stages and within different tissues were evaluated by quantitative transcriptomic analysis, and their expressions in response to three different insecticides were evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). These ABC transporter genes were widely expressed at developmental stages but most highly expressed in tissues of the midgut, fat body and Malpighian tube. When challenged by exposure to three insecticides, abamectin, ß-cypermethrin, and dinotefuran, the expressions of ZcABCB7 and ZcABCC2 were significantly up-regulated. ZcABCB1, ZcABCB6, ZcABCB7, ZcABCC2, ZcABCC3, ZcABCC4, ZcABCC5, and ZcABCC7 were significantly up-regulated in the fat body at 24 h after ß-cypermethrin exposure. These data suggest that ZcABCB7 and ZcABCC2 might play key roles in xenobiotic metabolism in Z. cucurbitae. Collectively, these data provide a foundation for further analysis of ABCs in Z. cucurbitae.

[A frequency selection method of NIR spectroscopy for discrimination of maize seed varieties].

A frequency selection method of NIR spectroscopy was proposed in the present paper for discrimination of maize seed varieties. A criterion function was defined to evaluate the discriminative ability of NIR spectroscopy at different frequencies, and then features of maize seed varieties were extracted accordingly for further processing. By eliminating correlation between features at different frequencies, the selected features are guaranteed to contain as much information of inter-variety difference as possible. Also, features with larger variances are preferred to suppress the impact of noise. Experiment results demonstrate that our frequency selection method can achieve high recognition rate with less spectroscopy features than traditional methods. Specifically, a recognition rate as high as 94.16% can be attained with NIR spectroscopy with only 30 frequencies. Simulation results show that recognition rate of NIR spectroscopy at selected frequencies is stable with small disturbance of frequencies, which verifies the robustness of the authors' method.

[Feature analysis and discrimination of varieties of corn based on near infrared spectra].

A new method for the discrimination of varieties of corn was proposed based on the data set of near-infrared spectroscopy range from 4 000 to 12 000 cm(-1) of corn seed varieties. Principal component analysis (PCA) method was used to study the feature of the data, and the authors found that the near-infrared spectroscopy of corn seed varieties has a clear feature of zonal distribution, so the correlativity between the change in the distribution of the principal component and the discrimination result was studied, according to which the normalized principal component analysis (NPCA) method was proposed. Besides, principal direction biomimetic pattern recognition (PBPR) was proposed according to the feature, which got a better discrimination result. The average correct recognition rate attained 97.67% for test set I, and the average correct rejection rate attained 98.40%, with 13 of the 30 varieties reaching the correct recognition rate of 100%; The average correct rejection rate attained 98.90% for the test set II , and 11 of the 30 varieties reached the correct rejection rate of 100%. It was proved that the method had a high correct discrimination rate.

[Influence of Secondary Organic Coating on Hygroscopicity of a Sodium Chloride Core: Based on Mircro-scale Single Particle Analysis].

The hygroscopicity of atmospheric particulate matter can determine its optical behaviors, cloud condensation nuclei activity, and heterogeneous chemical reaction on the surface. However, the effect of secondary organic matter on the hygroscopicity of inorganic salts is still rarely studied. In this study, a 2 L gas-phase flow tube was used to stimulate the oxidation process of α-pinene. NaCl particles at the end of the flow tube served as seeds to absorb the product of α-pinene oxidation. The absorption times were 11, 15, and 20 h. Transmission electron microscopy results show that this system could produce particles with typical core-shell structure, and that the thickness of the organic shell would be thicker with longer collection time. Results from individual particle hygroscopic systems indicate that the organic shell can affect the deliquescent point of NaCl (pure NaCl deliquesces at 77%):for 11 h collection time, the NaCl core began to deliquesce at 75.5% relative humidity, and completely deliquesced at 78%; for 15 h collection time, the deliquescent range of the NaCl core was 75%-78.5%; and the deliquescent range was 76%-83% for the NaCl core with 20 h collection time. Furthermore, the organic shell could affect the hygroscopic growth of the NaCl core:the growth factor of the NaCl core with 11 h, 15 h, and 20 h collection time was 2.5, 2.3, and 1.8, respectively. These results indicate that:① the secondary organic shell could cause water absorption of the NaCl core in advance:② the organic shell could postpone the completely deliquescent point of the NaCl core, and this effect is more obvious with a thicker organic shell; ③ the organic shell could restrain the hygroscopic growth factor of the NaCl core. This study suggests that it is necessary to consider the influence of secondary organic matter on inorganic salts when studying the hygroscopic properties of atmospheric particles in climate models and field observations.

Genome-wide gene expression profiling of the melon fly, Zeugodacus cucurbitae, during thirteen life stages.

The melon fly, Zeugodacus cucurbitae (Coquillett), is an important destructive pest worldwide. Functional studies of the genes associated with development and reproduction during different life stages are limited in Z. cucurbitae. There have yet to be comprehensive transcriptomic resources for genetic and functional genomic studies to identify the molecular mechanisms related to its development and reproduction. In this study, we comprehensively sequenced the transcriptomes of four different developmental stages: egg, larva, pupa, and adults. Using the Illumina RNA-Seq technology, we constructed 52 libraries from 13 stages with four biological replicates in each and generated 435.61 Gb clean reads. We comprehensively characterized the transcriptomes with high-coverage mapping to the reference genome. A total of 13,760 genes were mapped to the reference genome, and another 4481 genes were characterized as new genes. Finally, 14,931 genes (81.85%) were functionally annotated against six annotation databases. This study provides the first comprehensive transcriptome data of all developmental stages of Z. cucurbitae, and will serve as a valuable resource for future genetic and functional studies.