Comparative transcriptomic and metabolomics analysis of modified atmosphere responses in Tribolium castaneum (Coleoptera: Tenebrionidae).

Modified atmosphere is effective in controlling Tribolium castaneum Herbst, but it has adaptations. Comprehending the potential mechanism of resistance to T. castaneum in a modified atmosphere will help advance related management methods. This study conducted a comparative transcriptomic and metabolomic analysis to understand the physiological mechanism of T. castaneum in adapting to CO2 stress. Results showed that there were a large number of differentially expressed genes (DEGs) in T. castaneum treated with different concentrations of CO2. Gene ontology (GO) analysis revealed significant enrichment of DEGs mainly in binding, catalytic activity, cell, membrane, membrane part, protein-containing complex, biological regulation, and cellular and metabolic process. Kyoto Encyclopedia of Genes and Genomes analysis showed that different treatments had different effects on the metabolic pathways of T. castaneum. DEGs induced by 25% CO2 were involved in arginine and proline metabolism, and 50% air + 50% CO2 treatment affected most kinds of metabolic pathways, mainly the signal transduction pathway, including PI3K-Akt signaling pathway, AMPK signaling pathway, neurotrophin signaling pathway, insulin signaling pathway, and thyroid hormone signaling. Ribosome and DNA replication were enriched under high CO2 stress (75% and 95%). The metabolomics revealed that different concentrations of CO2 treatments might inhibit the growth of T. castaneum through acidosis, or they may adapt to anoxic conditions through histamine and N-acetylhistamine. Multiple analyses have shown significant changes in histamine and N-acetylhistamine levels, as well as their associated genes, with increasing CO2 concentration. In conclusion, this study comprehensively revealed the molecular mechanism of T. castaneum responding to CO2 stress and provided the basis for an effectively modified atmosphere in the T. castaneum.

Ductal Hyperkeratinization and Acinar Renewal Abnormality: New Concepts on Pathogenesis of Meibomian Gland Dysfunction.

Meibomian gland dysfunction (MGD) is a functional and morphological disorder of the meibomian glands which results in qualitative or quantitative alteration in meibum secretion and is the major cause of evaporative dry eye (EDE). EDE is often characterized by tear film instability, increased evaporation, hyperosmolarity, inflammation, and ocular surface disorder. The precise pathogenesis of MGD remains elusive. It has been widely considered that MGD develops as a result of ductal epithelial hyperkeratinization, which obstructs the meibomian orifice, halts meibum secretion, and causes secondary acinar atrophy and gland dropout. Abnormal self-renewal and differentiation of the acinar cells also play a significant role in MGD. This review summarizes the latest research findings regarding the possible pathogenesis of MGD and provides further treatment strategies for MGD-EDE patients.

Application of ultrasound technology in the field of solid-state fermentation: increasing peptide yield through ultrasound-treated bacterial strain.

BACKGROUND: The increase of peptide yield contributed to reducing the usage of antibiotics in solid-state fermented feed. Ultrasound technology is used in the field of liquid-state fermentation to improve yield of fermented products but has not been utilized in the field of solid-state fermentation (SSF). The main objective of this study was to investigate the feasibility of improving peptide yield in SSF products through ultrasound-treated bacterial strain. RESULTS: The highest peptides content in soybean meal SSF products reached 153.28 mg g-1 , which increased by 15.05% compared with the control. This content value was acquired through treating the bacteria of Bacillus amyloliquefaciens by ultrasound before inoculating into soybean meal under the optimized mode and parameters (simultaneous dual-frequency ultrasound mode, frequency combination of 40/60 kHz, total power density of 40 W L-1 , time of 20 min, pulse-on and pulse-off times of 40 and 60 s, delayed inoculation time of 0 h). Fermenting with ultrasound-treated bacterial strain can effectively increase peptide yield, biomass and protease activity of soybean meal fermented products during the SSF prophase. After treating by ultrasound, the latent phase and logarithmic phase of the bacterial strain shortened by 1 and 3 h while the generation time reduced by 23.64%. In qualitative test of protease activity, diameter ratio (DR) value of ultrasound-treated bacterial cells enlarged by 12.0% compared with the control. CONCLUSION: Peptide yield of soybean meal SSF products can be improved through ultrasound-treated bacterial inoculum, which attributed to the promoting effect of ultrasound treatment on growth activity and protease production capability of bacterial cells. © 2021 Society of Chemical Industry.

Role of Chitin Deacetylase 1 in the Molting and Metamorphosis of the Cigarette Beetle Lasioderma serricorne.

Chitin deacetylases (CDAs) are chitin-modifying enzymes known to play vital roles in insect metamorphosis and development. In this study, we identified and characterized a chitin deacetylase 1 gene (LsCDA1) from the cigarette beetle Lasioderma serricorne. LsCDA1 contains a 1614 bp open reading frame encoding a protein of 537 amino acids that includes domain structures typical of CDAs. LsCDA1 was mainly expressed in the late larval and late pupal stages. In larval tissues, the highest level of LsCDA1 was detected in the integument. The expression of LsCDA1 was induced by 20-hydroxyecdysone (20E) in vivo, and it was significantly suppressed by knocking down the expression of ecdysteroidogenesis genes and 20E signaling genes. RNA interference (RNAi)-aided silencing of LsCDA1 in fifth-instar larvae prevented the larval-pupal molt and caused 75% larval mortality. In the late pupal stage, depletion of LsCDA1 resulted in the inhibition of pupal growth and wing abnormalities, and the expression levels of four wing development-related genes (LsDY, LsWG, LsVG, and LsAP) were dramatically decreased. Meanwhile, the chitin contents of LsCDA1 RNAi beetles were significantly reduced, and expressions of three chitin synthesis pathway genes (LsTRE1, LsUAP1, and LsCHS1) were greatly decreased. The results suggest that LsCDA1 is indispensable for larval-pupal and pupal-adult molts, and that it is a potential target for the RNAi-based control of L. serricorne.

Insulin signaling pathway in the oriental fruit fly: The role of insulin receptor substrate in ovarian development.

Insulin signaling pathways have integral roles in regulating organ growth and body size of insects. Here, we identified and characterized six insulin signaling pathway components-InR, IRS, PI3K92E, PI3K21B, Akt, and PDK-from Bactrocera dorsalis. Quantitative real-time polymerase chain reaction was used to establish gene expression profiles for the insulin signaling pathway components for different developmental stages and tissues, and in response to 20-hydroxyecdysone (20E) and starvation. IRS, PI3K92E, and PI3K21B were highly expressed in the head, while InR, Akt, and PDK were most abundant in Malpighian tubules. Both IRS and PI3K92E were highly expressed during the larval-pupal and pupal-adult transition, while the remaining four genes were highly expressed only during the pupal-adult transition. Following initial exposure to 20E, the expression levels of most genes were significantly decreased. However, the expression levels of IRS, PI3K92E, and PI3K21B were significantly increased at 8 and 12h post-treatment compared with the control. Moreover, we found that most insulin signaling pathway genes in B. dorsalis were up-regulated in response to starvation, but decreased when re-fed. On the contrary, transcript levels of PI3K21B decreased significantly during starvation. Furthermore, injection of IRS dsRNA into adult females significantly reduced IRS transcript levels. Suppression of IRS expression inhibited ovarian development, and the average ovary size was reduced by 33% compared with the control. This study provides new insight into the roles of insulin signaling pathway components in B. dorsalis, and demonstrates an important role for IRS in ovarian development.

Two Chitin Biosynthesis Pathway Genes in Bactrocera dorsalis (Diptera: Tephritidae): Molecular Characteristics, Expression Patterns, and Roles in Larval-Pupal Transition.

Glucose-6-phosphate isomerase (G6PI) and UDP-N-acetylglucosamine pyrophosphorylase (UAP), two key components in the chitin biosynthesis pathway, are critical for insect growth and metamorphosis. In this study, we identified the genes BdG6PI and BdUAP from the oriental fruit fly, Bactrocera dorsalis (Hendel). The open reading frames (ORFs) of BdG6PI (1,491 bp) and BdUAP (1,677 bp) encoded 496 and 558 amino acid residues, respectively. Multiple sequence alignments showed that BdG6PI and BdUAP had high amino acid sequence identity with other insect homologues. Quantitative real-time polymerase chain reaction (qPCR) analysis indicated that BdG6PI was mainly expressed in the early stages of third-instar larvae and adults, while significantly higher expression of BdUAP was observed in adults. Both transcripts were expressed highly in the Malpighian tubules, but only slightly in the tracheae. The expression of both BdG6PI and BdUAP was significantly up-regulated by 20-hydroxyecdysone exposure and down-regulated by starvation. Moreover, injection of double-stranded RNAs of BdG6PI and BdUAP into third-instar larvae significantly reduced the corresponding gene expressions. Additionally, silencing of BdUAP resulted in 65% death and abnormal phenotypes of larvae, while silencing of BdG6PI had a slight effect on insect molting. These findings provide some data on the roles of BdG6PI and BdUAP in B. dorsalis and demonstrate the potential role for BdUAP in larval-pupal transition.

Multilayer Online Sequential Reduced Kernel Extreme Learning Machine-Based Modeling for Time-Varying Distributed Parameter Systems.

A significant number of industrial dynamic processes belong to time-varying distributed parameter systems (DPSs). To develop an accurate approximation model for these systems, it is critical to capture their time-varying behavior and strong nonlinearity. In this article, a multilayer online sequential reduced kernel extreme learning machine (ML-OSRKELM)-based online spatiotemporal modeling approach is developed for such DPSs. First, ML-OSRKELM stacks multiple online sequential reduced kernel extreme learning machine autoencoders (OSRKELM-AEs) to create a deep network, which can translate the spatiotemporal domain into a low-dimensional time domain. Then, an online sequential reduced kernel extreme learning machine (OS-RKELM) is employed to construct a dynamic temporal model. Finally, after obtaining time coefficients from the time domain, OS-RKELM is also used to reconstruct the original spatiotemporal domain. By using the kernel trick and the support vector selection strategy, the proposed method can remove redundant information while maintaining satisfactory nonlinear learning performance. Furthermore, the designed sequential update scheme can update the model parameters with real-time data, which makes it a promising method for capturing time-varying dynamics. Experiments and simulations on a lithium-ion battery's thermal process confirm the excellent performance and validity of the proposed model.

MicroR-9c-5p and novel-mir50 co-target Akt to regulate Lasioderma serricorne reproduction.

High fecundity is a common characteristic of insect pests which increases the difficulty of population control. Serine/threonine kinase Akt is an indispensable component of the insulin signaling pathway. Silencing of LsAkt severely hinders reproduction in Lasioderma serricorne, a stored product insect pest. However, the post-transcriptional pathway of LsAkt in L. serricorne remains unknown. This study identified 2 binding sites of miR-9c-5p and novel-mir50 in the coding sequences of LsAkt. The expression profiles of 2 microRNAs (miRNAs) and LsAkt displayed an opposite pattern during the adult stages. Luciferase reporter assay showed that novel-mir50 and miR-9c-5p could downregulate the expression of LsAkt. Overexpression of miR-9c-5p and novel-mir50 by injection of mimics inhibited the expression of LsAkt and reduced oviposition, decreased egg hatchability, and blocked ovarian development. It also decreased the expression of genes involved in ovarian development (LsVg and LsVgR) and the nutritional signaling pathway (LsTOR, LsS6K, and Ls4EBP), and reduced the phosphorylation of Akt. Conversely, injection of miR-9c-5p and novel-mir50 inhibitors induced the expressions of LsAkt, LsVg, LsVgR, LsTOR, LsS6K, and Ls4EBP, enhanced Akt phosphorylation level, and accelerated ovarian development. Injection of bovine insulin downregulated the expression of miR-9c-5p and novel-mir50 and upregulated the LsAkt expression. It also rescued the reproductive development defects associated with miR-9c-5p/novel-mir50 overexpression, forming a positive regulatory loop of insulin signaling. These results indicate that miR-9c-5p/novel-mir50 regulates the female reproduction of L. serricorne by targeting Akt in response to insulin signaling. The data also demonstrate the effects of the insulin/miRNA/Akt regulatory axis in insect reproduction.

Disruption of microRNA pathway core genes inhibits molting and reproduction of the cigarette beetle, Lasioderma serricorne.

BACKGROUND: MicroRNA (miRNA) pathway genes have been widely reported to participate in several physiological events in insect lifecycles. The cigarette beetle Lasioderma serricorne is an economically important storage pest worldwide. However, the functions of miRNA pathway genes in L. serricorne remain to be clarified. Herein, we investigated the function of molting and reproduction of the miRNA pathway in L. serricorne. RESULTS: LsDicer-1, LsArgonaute-1, LsLoquacious and LsExportin-5 were universally expressed in adults, whereas LsPasha and LsDrosha were mainly expressed in the pupae. The genes presented different patterns in various tissues. Silencing of LsDicer-1, LsArgonaute-1, LsDrosha and LsExportin-5 resulted in a high proportion of wing deformities and molting defects. Silencing of LsDicer-1, LsArgonaute-1, LsPasha and LsLoquacious affected the development of the ovary and the maturation of oocytes, resulting in a significant decrease in fecundity. Further investigation revealed that the decreases in LsDicer-1 and LsArgonaute-1 expression destroyed follicular epithelia and delayed vitellogenesis and oocyte development. In addition, the expression levels of several miRNAs (let-7, let-7-5p, miR-8-3p, miR-8-5p, miR-9c-5p, miR-71, miR-252-5p, miR-277-3p, miR-263b and Novel-miR-50) were decreased significantly after knockdown of these miRNA pathway core genes, indicating that they played important roles in regulating miRNA-mediated gene expression. CONCLUSION: The results indicate that miRNA pathway genes play important roles in the molting, ovarian development and female fecundity of L. serricorne, and thus are potentially suitable target genes for developing an RNAi strategy against a major pest of stored products. © 2024 Society of Chemical Industry.

Functional analysis of nuclear receptor genes in molting and metamorphosis of the cigarette beetle, Lasioderma serricorne.

Nuclear receptors (NRs) are ligand-regulated transcription factors that are important for the normal growth and development of insects. However, systematic function analysis of NRs in the molting process of Lasioderma serricorne has not been reported. In this study, we identified and characterized 16 NR genes from L. serricorne. Spatiotemporal expression analysis revealed that six NRs were mainly expressed in 3-d-old 4th-instar larvae; five NRs were primarily expressed in 5-d-old adults and four NRs were predominately expressed in prepupae. All the NRs were highly expressed in epidermis, fat body and foregut. RNA interference (RNAi) experiments revealed that knockdown of 15 NRs disrupted the larva-pupa-adult transitions and caused 64.44-100 % mortality. Hematoxylin-eosin staining showed that depletion of 12 NRs prevented the formation of new cuticle and disrupted apolysis of old cuticle. Silencing of LsHR96, LsSVP and LsE78 led to newly formed cuticle that was thinner than the controls. The 20E titer and chitin content significantly decreased by 17.67-95.12 % after 15 NR dsRNA injection and the gene expression levels of 20E synthesis genes and chitin metabolism genes were significantly reduced. These results demonstrated that 15 NR genes are essential for normal molting and metamorphosis of L. serricorne by regulating 20E synthesis and chitin metabolism.

A novel scoring system based on sIL-2R for predicting IVIG resistance in Chinese children with KD.

OBJECTIVE: This study aimed to develop a novel scoring system utilizing circulating interleukin (IL) levels to predict resistance to intravenous immunoglobulin (IVIG) in Chinese patients with Kawasaki disease (KD). We further compared this scoring system against six previously established scoring methods to evaluate its predictive performance. METHODS: A retrospective analysis was conducted on KD patients who were treated at the cardiovascular medical ward of our institution from January 2020 to December 2022. Six scoring systems (Egami, Formosa, Harada, Kobayashi, Lan and Yang) were analyzed, and a new scoring system was developed based on our data. RESULTS: In our study, 521 KD patients were recruited, 42 of whom (8.06%) were identified as resistant to IVIG. Our study indicated that IVIG-resistant KD patients were at an increased risk for the development of coronary arterial lesions (CALs) (P = 0.001). The evaluation of IVIG resistance using various scoring systems revealed differing levels of sensitivity and specificity, as follows: Egami (38.10% and 88.52%), Formosa (95.24% and 41.13%), Harada (78.57% and 43.22%), Kobayashi (66.67% and 74.95%), Lan (66.67% and 73.49%), and Yang (69.05% and 77.24%). Our novel scoring system utilizing sIL-2R demonstrated the highest sensitivity and specificity of 69.29% and 83.91%, respectively, and calibration curves indicated a favorable predictive accuracy of the model. CONCLUSION: Our newly developed scoring system utilizing sIL-2R demonstrated superior predictive performance in identifying IVIG resistance among Chinese patients with KD.

Molecular cloning, characterization and mRNA expression of a chitin synthase 2 gene from the oriental fruit fly, Bactrocera dorsalis (Diptera: Tephritidae).

Chitin synthase (CHS), a potential target for eco-friendly insecticides, plays an essential role in chitin formation in insects. In this study, a full-length cDNA encoding chitin synthase 2 (BdCHS2) was cloned and characterized in the oriental fruit fly, Bactrocera dorsalis. The BdCHS2 cDNA had 4417 nucleotides, containing an open reading frame of 4122 nucleotides, which encoded 1373 amino acid residues with a predicted molecular weight of 158.5 kDa. Phylogenetic analysis with other insect CHSs suggested that BdCHS2 belongs to insect CHS2. The BdCHS2 transcript was predominately found in midgut but was detected at low levels in fat body, Malpighian tubules, integument, and trachea. Moreover, BdCHS2 was expressed in all developmental stages, and highly expressed in the feeding stages. There was a positive relationship between BdCHS2 expression and total chitin content during development. Furthermore, both the gene expression and chitin content in midgut decreased when the insect was fed for 24 h, then starved for 24 h, while they increased dramatically and rapidly under the condition of starvation for 24 h then feeding for 24 h. These results suggest that BdCHS2 may play an important role in regulating chitin content of the midgut, and subsequently affect the growth and development of B. dorsalis.

Transcriptional regulation of a chitinase gene by 20-hydroxyecdysone and starvation in the oriental fruit fly, Bactrocera dorsalis.

Insect chitinases are hydrolytic enzymes that are required for the degradation of glycosidic bonds of chitin. In this study, we identified and characterized a full-length cDNA of the chitinase gene (BdCht2) in the oriental fruit fly, Bactrocera dorsalis. The cDNA contains an open reading frame (ORF) of 1449 bp that encodes 483 amino acid residues and 126- and 296-bp non-coding regions at the 5'- and 3'-ends, respectively. The BdCht2 genome has four exons and three introns. The predicted molecular mass of the deduced BdCht2 is approximately 54.3 kDa, with an isoelectric point of 5.97. The 977 bp 5' flanking region was identified and the transcription factor binding sites were predicted. Bioinformatic analyses showed that the deduced amino acid sequence of BdCht2 had 34%-66% identity to that of chitinases identified in other insect species. Quantitative real-time PCR (qPCR) analyses indicated that BdCht2 was mainly expressed during the larval-pupal and pupal-adult transitions. The tissue-specific expression showed that the highest expression was in the integument, followed by the fat body and other tissues. Moreover, the expression of BdCht2 was upregulated significantly upon 20-hydroxyecdysone (20E) at different dose injections after 8 h compared to that of the control. Starvation also increased the expression of BdCht2 in the third-instar larvae and was suppressed again by re-feeding the insects. These results suggest that BdCht2 plays an important role in the molting process of B. dorsalis larvae and can be regulated by 20E.

Energy optimisation for the combination of turning and drilling features using differential evolution.

Cutting parameter optimisation is an effective way to realise energy-efficient machining. In previous studies, the cutting parameters of machining features of turning, milling, grinding, drilling, hobbing, and threading were optimised to decrease energy consumed by machine tools, and considerable energy savings were achieved. However, the energy consumption (EC) for each feature was separately optimised without systematic consideration of the negative effects on the EC for other features. The total EC for all features together probably increases. Hence, the trade-off amongst the reductions of EC for each feature needs to be jointly optimised. In our study, the external turning and drilling features are selected as examples to be combined. As a key novel contribution, we propose the integrated dimensional and cutting parameter optimisation problem about minimising the EC of Machine Tools for the combination of Turning and Drilling features (EMT-TD). In terms of optimisation, differential evolution (DE) is adopted to minimise the EMT-TD. According to case studies, DE obtained the optimal solutions within a computation time of 1 second. The optimal solutions achieved savings of 5.41%, 10.85%, and 7.19% of EMT-TD and savings of 2.23%, 5.90%, and 2.73% of machining time for three typical cases, respectively.

Energy benchmark for energy-efficient path planning of the automated guided vehicle.

The automated guided vehicle (AGV) is a piece of promising advanced transport equipment that has been widely used in flexible manufacturing systems to increase productivity and automation. Previous studies about the AGV focused on improving the capacities of perception, navigation, and anti-collision as well as reducing the transport time, cost, and distance, but insufficient attention was paid to the energy consumption (EC) reduction of AGV. The energy benchmark is recognised as an effective analytical methodology and management tool that can improve energy efficiency. Nonetheless, research on the energy benchmark for the AGV is lacking. To finish a transport task, many AGV path plans are feasible, and we develop an energy benchmark to evaluate each path plan and select the energy-saving one. We also establish a dynamic rating system of energy efficiency which is consistent with the energy-saving potentials of the transport task. The case study shows that the transport EC is reduced by 10.98 %, validating the proposed energy benchmark methodology. In addition, the effects of AGV path plans on the EC of machine tools at the workstations are analysed. Lastly, we explore the relationship between the energy efficiency of AGV path plans and the locations of workstations.

Comparison of chromatographic conditions for the targeted tandem mass spectrometric determination of 354 mammalian metabolites.

Metabolomics is becoming increasingly popular in livestock research, but no single analytical method can cover the entire metabolome. As such, we compared similar and complementary chromatographic methods with respect to analyte coverage and chromatographic properties of mammalian metabolites. We investigated 354 biologically relevant primary metabolites from 19 compound classes including amino acids, bile acids, biogenic amines, carboxylic acids, lipids, nucleotides and sugars. A total of 2063 selected reaction monitoring transitions were optimized on a triple quadrupole mass spectrometer. We then determined the retention profiles and peak parameters of our compounds using an anion exchange chromatography (AIC), three reversed-phase (RP) and three hydrophilic interaction liquid chromatography (HILIC) methods. On average, HILIC methods covered 54% of all metabolites with retention factors >1, while average RP coverage was 41%. In contrast to RP, HILIC methods could also retain polar metabolites such as amino acids and biogenic amines. Carboxylic acids, nucleotides, and sugar related compounds were best separated by AIC or zwitterionic pHILIC with alkaline eluents. Combining two complementary HILIC and RP methods increased the library coverage to 92%. By further including important short chain fatty acids, a combination of HILIC, RP and AIC methods achieved a coverage of 97%. The resulting dataset of LC and MS/MS parameters will facilitate the development of tailor-made quantitative targeted LC-MS/MS methods to investigate the mammalian metabolome.

A novel loss-of-function mutation in NRAP is associated with left ventricular non-compaction cardiomyopathy.

Background: The nebulin-related-anchoring protein (NRAP) gene encodes actin-associated ankyrin. Few studies reported the association of the NRAP gene with cardiomyopathy. Thus, the genetic role of this gene in cardiomyopathy remains to be investigated. Methods: The clinical data of the rare case of left ventricular non-compaction (LVNC) were collected and analyzed. Whole-exome sequencing (WES) was performed on related family members. Western blot was used to detect the effect of mutation on the NRAP protein expression. The effect of the c.259delC variant on myocardial development was further evaluated in a zebrafish model. Results: A novel homozygous frameshift mutation c.259delC of NRAP was found in the proband with LVNC. It was found that c.259delC decreased the expression of NRAP by Western blot. In the zebrafish model, the heart development was affected while knocking out the NRAP gene, which showed pericardial edema. The pathological manifestations were uneven hypertrophy, disordered arrangement of cardiomyocytes, enlarged intercellular space, and loose muscle fibers. RNA-sequencing (RNA-seq) showed that the expression of genes related to heart development decreased significantly, and the NRAP gene mutation could participate in biological processes (BPs) such as myocardial contraction, cell adhesion, myosin coarse filament assembly of striated muscle, myosin complex composition, and muscle α-actin binding. Conclusion: We identified a rare case of LVNC associated with a novel homozygous NRAP frameshift variant. This study further strengthened the evidence linking mutations in the NRAP gene with LVNC, providing a new clue for further study of LVNC. NRAP may be one of the pathogenic genes of cardiomyopathy.

Locally Weighted Principal Component Analysis-Based Multimode Modeling for Complex Distributed Parameter Systems.

Global principal component analysis (PCA) has been successfully introduced for modeling distributed parameter systems (DPSs). In spite of the merits, this method is not feasible due to parameter variations and multiple operating domains. A novel multimode spatiotemporal modeling method based on the locally weighted PCA (LW-PCA) method is developed for large-scale highly nonlinear DPSs with parameter variations, by separating the original dataset into tractable subsets. This method implements the decomposition by making full use of the dependence among subset densities. First, the spatiotemporal snapshots are divided into multiple different Gaussian components by using a finite Gaussian mixture model (FGMM). Once the components are derived, a Bayesian inference strategy is then applied to calculate the posterior probabilities of each spatiotemporal snapshot belonging to each component, which will be regarded as the local weights of the LW-PCA method. Second, LW-PCA is adopted to calculate each locally weighted snapshot matrix, and the corresponding local spatial basis functions (SBFs) can be generated by the PCA method. Third, all the local temporal models are estimated using the extreme learning machine (ELM). Thus, the local spatiotemporal models can be produced with local SBFs and corresponding temporal model. Finally, the original system can be approximated using the sum form of each local spatiotemporal model. Unlike global PCA, which uses global SBFs to construct a global spatiotemporal model, LW-PCA approximates the original system by multiple local reduced SBFs. Numerical simulations verify the effectiveness of the developed multimode spatiotemporal model.

Accurate Forecasting of Emergency Department Arrivals With Internet Search Index and Machine Learning Models: Model Development and Performance Evaluation.

BACKGROUND: Emergency department (ED) overcrowding is a concerning global health care issue, which is mainly caused by the uncertainty of patient arrivals, especially during the pandemic. Accurate forecasting of patient arrivals can allow health resource allocation in advance to reduce overcrowding. Currently, traditional data, such as historical patient visits, weather, holiday, and calendar, are primarily used to create forecasting models. However, data from an internet search engine (eg, Google) is less studied, although they can provide pivotal real-time surveillance information. The internet data can be employed to improve forecasting performance and provide early warning, especially during the epidemic. Moreover, possible nonlinearities between patient arrivals and these variables are often ignored. OBJECTIVE: This study aims to develop an intelligent forecasting system with machine learning models and internet search index to provide an accurate prediction of ED patient arrivals, to verify the effectiveness of the internet search index, and to explore whether nonlinear models can improve the forecasting accuracy. METHODS: Data on ED patient arrivals were collected from July 12, 2009, to June 27, 2010, the period of the 2009 H1N1 pandemic. These included 139,910 ED visits in our collaborative hospital, which is one of the biggest public hospitals in Hong Kong. Traditional data were also collected during the same period. The internet search index was generated from 268 search queries on Google to comprehensively capture the information about potential patients. The relationship between the index and patient arrivals was verified by Pearson correlation coefficient, Johansen cointegration, and Granger causality. Linear and nonlinear models were then developed with the internet search index to predict patient arrivals. The accuracy and robustness were also examined. RESULTS: All models could accurately predict patient arrivals. The causality test indicated internet search index as a strong predictor of ED patient arrivals. With the internet search index, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the linear model reduced from 5.3% to 5.0% and from 24.44 to 23.18, respectively, whereas the MAPE and RMSE of the nonlinear model decreased even more, from 3.5% to 3% and from 16.72 to 14.55, respectively. Compared with each other, the experimental results revealed that the forecasting system with extreme learning machine, as well as the internet search index, had the best performance in both forecasting accuracy and robustness analysis. CONCLUSIONS: The proposed forecasting system can make accurate, real-time prediction of ED patient arrivals. Compared with the static traditional variables, the internet search index significantly improves forecasting as a reliable predictor monitoring continuous behavior trend and sudden changes during the epidemic (P=.002). The nonlinear model performs better than the linear counterparts by capturing the dynamic relationship between the index and patient arrivals. Thus, the system can facilitate staff planning and workflow monitoring.

A review of physiological resistance to insecticide stress in Nilaparvata lugens.

Insecticides are widely used in agriculture as effective means to control pests. However, pests have not been completely mitigated with the increased use of insecticides. Instead, many side effects have arisen, especially the '3Rs' (resistance, resurgence, and residue). The brown planthopper, Nilaparvata lugens, is one of the most threatening rice pests. The main insecticides for controlling N. lugens belong to organochlorine, organophosphorus, carbamate, neonicotinoid and pyrethroid groups. However, metabolic enzymes, including cytochrome P450s, esterases, glutathione-S-transferases, and ATP-binding cassette transporters, effectively promote the detoxification of insecticides. Besides, mutations of neurological target sites, such as acetylcholinesterase, nicotinic acetylcholine, γ-aminobutyric acid receptor, and ryanodine receptor, result in insensitivity to insecticides. Here, we review the physiological metabolic resistance in N. lugens under insecticide stress to provide a theoretical basis for identifying and developing more effective and harmless insecticides.