Long non-coding RNAs as promising targets for controlling disease vector mosquitoes.

Hematophagous female mosquitoes are important vectors of numerous devastating human diseases, posing a major public health threat. Effective prevention and control of mosquito-borne diseases rely considerably on progress in understanding the molecular mechanisms of various life activities, and accordingly, the molecules that regulate the various life activities of mosquitoes are potential targets for implementing future vector control strategies. Many long non-coding RNAs (lncRNAs) have been identified in mosquitoes and significant progress has been made in determining their functions. Here, we present a comprehensive overview of the research advances on mosquito lncRNAs, including their molecular identification, function, and interaction with other non-coding RNAs, as well as their synergistic regulatory roles in mosquito life activities. We also highlight the potential roles of competitive endogenous RNAs in mosquito growth and development, as well as in insecticide resistance and virus-host interactions. Insights into the biological functions and mechanisms of lncRNAs in mosquito life activities, viral replication, pathogenesis, and transmission will contribute to the development of novel drugs and safe vaccines.

Inquiry lipaseoring the mechanism of pancreatic lipase inhibition by isovitexin based on multispectral method and enzyme inhibition assay.

Isovitexin is a main natural flavonoid component in various plants. Currently, the inhibitory effect of isovitexin on pancreatic lipase (PL) and its mechanism have not been elucidated yet. In the present study, we investigated the inhibitory effect of isovitexin on PL, as well as its interaction mechanism, using enzyme inhibition methods, spectroscopic analysis, and molecular simulations. Results showed that isovitexin possessed significant PL inhibitory activity, with IC50 values of 0.26 ± 0.02 mM. The interaction between isovitexin and PL was dominated by static quenching, and mainly through hydrogen bonding and hydrophobic interaction forces. Analysis of fluorescence spectroscopy confirmed that isovitexin binding altered the conformation of the PL. Circular dichroism (CD) spectrum indicated that isovitexin altered the secondary structure of PL by decreasing the α-helix content and increasing the ß-fold content. Molecular simulations further characterize the conformational changes produced by the interaction between isovitexin with PL. The performed study may provide a new insight into the inhibitory mechanism of isovitexin as a novel PL inhibitor.

Dynamic Profiling and Prediction of Antibody Response to SARS-CoV-2 Booster-Inactivated Vaccines by Microsample-Driven Biosensor and Machine Learning.

Knowledge of the antibody response to the third dose of inactivated SARS-CoV-2 vaccines is crucial because it is the subject of one of the largest global vaccination programs. This study integrated microsampling with optical biosensors to profile neutralizing antibodies (NAbs) in fifteen vaccinated healthy donors, followed by the application of machine learning to predict antibody response at given timepoints. Over a nine-month duration, microsampling and venipuncture were conducted at seven individual timepoints. A refined iteration of a fiber optic biolayer interferometry (FO-BLI) biosensor was designed, enabling rapid multiplexed biosensing of the NAbs of both wild-type and Omicron SARS-CoV-2 variants in minutes. Findings revealed a strong correlation (Pearson r of 0.919, specificity of 100%) between wild-type variant NAb levels in microsamples and sera. Following the third dose, sera NAb levels of the wild-type variant increased 2.9-fold after seven days and 3.3-fold within a month, subsequently waning and becoming undetectable after three months. Considerable but incomplete evasion of the latest Omicron subvariants from booster vaccine-elicited NAbs was confirmed, although a higher number of binding antibodies (BAbs) was identified by another rapid FO-BLI biosensor in minutes. Significantly, FO-BLI highly correlated with a pseudovirus neutralization assay in identifying neutralizing capacities (Pearson r of 0.983). Additionally, machine learning demonstrated exceptional accuracy in predicting antibody levels, with an error level of <5% for both NAbs and BAbs across multiple timepoints. Microsample-driven biosensing enables individuals to access their results within hours of self-collection, while precise models could guide personalized vaccination strategies. The technology's innate adaptability means it has the potential for effective translation in disease prevention and vaccine development.

Minimally Invasive Hypoglossal Nerve Stimulator Enabled by ECG Sensor and WPT to Manage Obstructive Sleep Apnea.

A hypoglossal nerve stimulator (HGNS) is an invasive device that is used to treat obstructive sleep apnea (OSA) through electrical stimulation. The conventional implantable HGNS device consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68% accuracy, achieved through the utilization of a convolutional neural network (CNN) algorithm. With a skin thickness of 5 mm and a receiving coil diameter of 9 mm, the power conversion efficiency was measured as 31.8%. The implantable device, on the other hand, is composed of a front-end CMOS power management module (PMM), a binary-phase-shift-keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 mm2 (excluding PADs), demonstrated a power conversion efficiency of 77.5% when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2 V, 1.8 V, and 3.1 V). Within the data receiver component, a low-power BPSK demodulator was ingeniously incorporated, consuming only 42 µW when supplied with a voltage of 0.7 V. The performance was achieved through the implementation of the self-biased phase-locked-loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5 bit programmable range spanning from 0 to 2.4 mA. The functionality of the proposed ECG- and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing the trauma and space requirements.

Heterogeneous-Nucleation Biosensor for Long-Term Collection and Mask-Based Self-Detection of SARS-CoV-2.

The effective control of infectious diseases, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, depends on the availability of rapid and accurate monitoring techniques. However, conventional SARS-CoV-2 detection technologies do not support continuous self-detection and may lead to cross-infection when utilized in medical institutions. In this study, we introduce a prototype of a mask biosensor designed for the long-term collection and self-detection of SARS-CoV-2. The biosensor utilizes the average resonance Rayleigh scattering intensity of Au nanocluster-aptamers. The inter-mask surface serves as a medium for the long-term collection and concentration enhancement of SARS-CoV-2, while the heterogeneous-nucleation nanoclusters (NCs) contribute to the exceptional stability of Au NCs for up to 48 h, facilitated by the adhesion of Ti NCs. Additionally, the biosensors based on Au NC-aptamers exhibited high sensitivity for up to 1 h. Moreover, through the implementation of a support vector machine classifier, a significant number of point signals can be collected and differentiated, leading to improved biosensor accuracy. These biosensors offer a complementary wearable device-based method for diagnosing SARS-CoV-2, with a limit of detection of 103 copies. Given their flexibility, the proposed biosensors possess tremendous potential for the continuous collection and sensitive self-detection of SARS-CoV-2 variants and other infectious pathogens.

Machine Learning Techniques for Effective Pathogen Detection Based on Resonant Biosensors.

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism.

Combined analysis of the proteome and metabolome provides insight into microRNA-1174 function in Aedes aegypti mosquitoes.

BACKGROUND: Pathogenic viruses can be transmitted by female Aedes aegypti (Ae. aegypti) mosquitoes during blood-meal acquisition from vertebrates. Silencing of mosquito- and midgut-specific microRNA (miRNA) 1174 (miR-1174) impairs blood intake and increases mortality. Determining the identity of the proteins and metabolites that respond to miR-1174 depletion will increase our understanding of the molecular mechanisms of this miRNA in controlling blood-feeding and nutrient metabolism of mosquitoes. METHODS: Antisense oligonucleotides (antagomirs [Ant]) Ant-1174 and Ant-Ct were injected into female Ae. aegypti mosquitoes at 12-20 h posteclosion, and depletion of miR-1174 was confirmed by reverse transcription quantitative real-time PCR (RT-qPCR). Ant-1174-injected and control mosquitoes were collected before the blood meal at 72 h post-injection for tandem mass tag-based proteomic analysis and liquid chromatography-tandom mass spectrometry non-target metabolomic analysis to identify differentially expressed proteins and metabolites, respectively. RNA interference (RNAi) using double-stranded RNA (dsRNA) injection was applied to investigate the biological roles of these differentially expressed genes. The RNAi effect was verified by RT-qPCR and western blotting assays. Triglyceride content and ATP levels were measured using the appropriate assay kits, following the manufacturers' instructions. Statistical analyses were conducted with GraphPad7 software using the Student's t-test. RESULTS: Upon depletion of mosquito- and midgut-specific miR-1174, a total of 383 differentially expressed proteins (DEPs) were identified, among which 258 were upregulated and 125 were downregulated. Functional analysis of these DEPs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment suggested that miR-1174 plays important regulatory roles in amino acid metabolism, nucleotide metabolism, fatty acid metabolism and sugar metabolism pathways. A total of 292 differential metabolites were identified, of which 141 were upregulated and 151 were downregulated. Integrative analysis showed that the associated differential proteins and metabolites were mainly enriched in a variety of metabolic pathways, including glycolysis, citrate cycle, oxidative phosphorylation and amino acid metabolism. Specifically, the gene of one upregulated protein in miR-1174-depleted mosquitoes, purine nucleoside phosphorylase (PNP; AAEL002269), was associated with the purine, pyrimidine and niacin-nicotinamide metabolism pathways. PNP knockdown seriously inhibited blood digestion and ovary development and increased adult mortality. Mechanically, PNP depletion led to a significant downregulation of the vitellogenin gene (Vg); in addition, some important genes in the ecdysone signaling and insulin-like peptide signaling pathways related to ovary development were affected. CONCLUSIONS: This study demonstrates differential accumulation of proteins and metabolites in miR-1174-depleted Ae. aegypti mosquitoes using proteomic and metabolomic techniques. The results provide functional evidence for the role of the upregulated gene PNP in gut physiological activities. Our findings highlight key molecular changes in miR-1174-depleted Ae. aegypti mosquitoes and thus provide a basis and novel insights for increased understanding of the molecular mechanism involved in a lineage-specific miRNA in mosquito vectors.

Versatile Tetrasilane for Time-Controlled Palladium-Catalyzed Divergent Synthesis of Silacycles via C-H Activation.

Transition-metal-catalyzed intermolecular annulation of silicon reagents with organic molecules is still underdeveloped due to the scarcity of silicon reagent types and their diverse reactivity. Herein, a readily accessible silicon reagent (octamethyl-1,4-dioxacyclohexasilane) has been developed for divergent synthesis of silacycles via time-controlled palladium-catalyzed cascade C-H silacyclization. This protocol enables the rapid and selective transformation of acrylamides into spirosilacycles with different ring sizes, including benzodioxatetrasilecines, benzooxadisilepines, and benzosiloles, in moderate to good yields through a time switch. Notably, the tetrasilane reagent can also be utilized for C-H silacyclization of 2-halo-N-methacryloylbenzamides and 2-iodobiphenyls, leading to diverse fused silacycles. Furthermore, several synthetic transformations of products are achieved. A series of mechanistic studies demonstrate the transformation relationships and possible pathways among ten-, seven-, and five-membered silacycles.

Catalytic Asymmetric Dehydrogenative Si-H/N-H Coupling: Synthesis of Silicon-Stereogenic Silazanes.

Despite growing progress in the construction of silazanes, the catalytic asymmetric synthesis of silicon-stereogenic silazanes is significantly less explored and remains a considerable challenge. Herein, we report a highly enantioselective synthesis of silicon-stereogenic silazanes via catalytic dehydrogenative coupling of dihydrosilanes with anilines. The reaction readily produces a wide range of chiral silazanes and bis-silazanes in excellent yields and stereoselectivities (up to 99% ee). Further utility of this process is demonstrated by the construction of polycarbosilazanes featuring configurational main chain silicon-stereogenic chirality. In addition, the straightforward transformation of the enantioenriched silazanes delivers various chiral silane compounds in a stereospecific fashion, illustrating their potential utilities as synthons for the synthesis of novel silicon-containing functional molecules.

LncRNA-MALAT1: A Key Participant in the Occurrence and Development of Cancer.

LncRNAs are a group of non-coding RNA transcripts with lengths of over 200 nucleotides and can interact with DNA, RNA, and proteins to regulate gene expression of malignant tumors in human tissues. LncRNAs participate in vital processes, such as chromosomal nuclear transport in the cancerous site of human tissue, activation, and the regulation of proto-oncogenes, the differentiation of immune cells, and the regulation of the cellular immune system. The lncRNA metastasis-associated lung cancer transcript 1 (MALAT1) is reportedly involved in the occurrence and development of many cancers and serves as a biomarker and therapeutic target. These findings highlight its promising role in cancer treatment. In this article, we comprehensively summarized the structure and functions of lncRNA, notably the discoveries of lncRNA-MALAT1 in different cancers, the action mechanisms, and the ongoing research on new drug development. We believe our review would serve as a basis for further research on the pathological mechanism of lncRNA-MALAT1 in cancer and provide evidence and novel insights into its application in clinical diagnoses and treatments.

Public Expenditure and Green Total Factor Productivity: Evidence from Chinese Prefecture-Level Cities.

Whilst effective public expenditure policies are essential for transforming the traditional factor-driven economy into a green and innovation-driven economy, the impacts of public expenditure's size and composition on green economic development have not been comprehensively investigated. This paper attempts to fill this research gap. Based on the data of Chinese prefecture-level cities from 2010 to 2018, we first measure green total factor productivity (GTFP), the proxy variable for green development, and briefly analyze its spatial-temporal trends. Then, using the dynamic panel models, dynamic panel mediation models, and dynamic panel threshold models, we evaluate how public expenditure affects GTFP. The main findings are fourfold: (1) there is a significant inverted U-shaped relationship between the expenditure size and GTFP. (2) The expansion of social expenditures and science and technology (S&T) and environmental protection expenditures play an important role in stimulating green growth, while economic expenditures and administrative expenditures have adverse effects. (3) Public expenditure mainly promotes green development through four channels: human capital accumulation, technological innovation, environmental quality improvement, and labor productivity increase. (4) The expenditure composition influences the turning point of the inverted U-shaped relationship. Based on these findings, we propose some targeted policy suggestions to promote green development.

Multichannel Synthetic Preictal EEG Signals to Enhance the Prediction of Epileptic Seizures.

Epilepsy is a chronic neurological disorder affecting 1% of people worldwide, deep learning (DL) algorithms-based electroencephalograph (EEG) analysis provides the possibility for accurate epileptic seizure (ES) prediction, thereby benefiting patients suffering from epilepsy. To identify the preictal region that precedes the onset of seizure, a large number of annotated EEG signals are required to train DL algorithms. However, the scarcity of seizure onsets leads to significant insufficiency of data for training the DL algorithms. To overcome this data insufficiency, in this paper, we propose a preictal artificial signal synthesis algorithm based on a generative adversarial network to generate synthetic multichannel EEG preictal samples. A high-quality single-channel architecture, determined by visual and statistical evaluations, is used to train the generators of multichannel samples. The effectiveness of the synthetic samples is evaluated by comparing the ES prediction performances without and with synthetic preictal sample augmentation. The leave-one-seizure-out cross validation ES prediction accuracy and corresponding area under the receiver operating characteristic curve evaluation improve from 73.0% and 0.676 to 78.0% and 0.704 by 10× synthetic sample augmentation, respectively. The obtained results indicate that synthetic preictal samples are effective for enhancing ES prediction performance.

Synthesis of Si-Stereogenic Silanols by Catalytic Asymmetric Hydrolytic Oxidation.

Despite growing progress in the construction of chiral organosilicon compounds, the catalytic asymmetric synthesis of silicon-stereogenic silanols is less explored and remains a considerable challenge. Herein, we report the first enantioselective construction of silicon-stereogenic silanols by the catalytic asymmetric hydrolytic oxidation of dihydrosilanes. This practical procedure features ambient reaction conditions, high atom economy, good functional-group compatibility, and H2 as the only by-product, and produces a wide range of valuable chiral silanols and bis-silanols in decent yields with excellent chemo- and stereoselectivity.

Economic Development, Fiscal Ecological Compensation, and Ecological Environment Quality.

Focusing on the exploration of the important role of fiscal ecological compensation in green development, this paper incorporates fiscal ecological compensation into the analytical framework of green development. Based on samples of data from county areas in China in 2017 and 2018, this paper empirically examines the shape of the green development routes in county areas in China. On this basis, this paper explores the impact and mechanism of fiscal ecological compensation on the green development path in China. The empirical results show that there is a nonlinear, N-shaped relationship between economic development and the ecological environment in China within the range of the sample examined. Fiscal ecological compensation has a direct governance effect on the ecological environment of deterring ecological damage and providing financial compensation. Fiscal ecological compensation has an indirect impact on the ecological management of different regions by influencing economic development. Therefore, while focusing on transforming the economic development model, local governments should adopt policy instruments such as expanding the coverage of financial ecological compensation, deepening the design of the financial ecological compensation system, and systematically evaluating the effects of financial ecological compensation policies. The government should further improve and optimize the fiscal eco-compensation system in order to help China's green and high-quality development.

Me3SiSiMe2(O n Bu): a disilane reagent for the synthesis of diverse silacycles via Brook- and retro-Brook-type rearrangement.

Herein, a readily available disilane Me3SiSiMe2(O n Bu) has been developed for the synthesis of diverse silacycles via Brook- and retro-Brook-type rearrangement. This protocol enables the incorporation of a silylene into different starting materials, including acrylamides, alkene-tethered 2-(2-iodophenyl)-1H-indoles, and 2-iodobiaryls, via the cleavage of Si-Si, Si-C, and Si-O bonds, leading to the formation of spirobenzosiloles, fused benzosiloles, and π-conjugated dibenzosiloles in moderate to good yields. Preliminary mechanistic studies indicate that this transformation is realized by successive palladium-catalyzed bis-silylation and Brook- and retro-Brook-type rearrangement of silane-tethered silanols.

Palladium-Catalyzed [4 + 3] or [2 + 2 + 3] Annulation via C-H Activation and Subsequent Decarboxylation: Access to Heptagon-Embedded Polycyclic Aromatic Hydrocarbons.

The construction of a seven-membered ring in the polycyclic aromatic hydrocarbon skeleton remains a notoriously difficult but attractive challenge. Herein a novel palladium-catalyzed [4 + 3] decarboxylative annulation of 2-iodobiphenyls with 2-(2-halophenyl)acrylic acids is reported, which provides an efficient approach for assembling various tribenzo[7]annulenes via a C-H activation and decarboxylation process. Moreover, tribenzo[7]annulenes can be also synthesized via a [2 + 2 + 3] decarboxylative annulation strategy by employing readily available 1,2-halobenzenes, phenylboronic acids, and 2-(2-halophenyl)acrylic acids.

NBE-Controlled Palladium-Catalyzed Interannular Selective C-H Silylation: Access to Divergent Silicon-Containing 1,1'-Biaryl-2-Acetamides.

A novel palladium-catalyzed interannular selective C-H silylation of 1,1'-biaryl-2-acetamides is described. The combination of palladium catalyst with copper oxidant enables meta- or ortho-selective C-H silylation by employing hexamethyldisilane as a trimethylsilyl source, which relies on the control of NBE derivatives as a switch, thus providing straightforward access to divergent silicon-containing 1,1'-biaryl-2-acetamides.

Palladium/Norbornene Chemistry: Synthesis of Norbornene-Containing Arylsilanes Involving Double C-Si Bond Formation.

A novel palladium-catalyzed three-component cascade reaction of aryl halides with norbornene and hexamethyldisilane has been described, which allows the simultaneous construction of two C-Si bonds and one C-C bond. The method achieves ortho C-H functionalization of aryl halides through the formation of the five-membered palladacycle, leading to norbornene-containing arylsilanes.

Palladium-Catalyzed Tandem Reaction of Three Aryl Iodides Involving Triple C-H Activation.

A novel palladium-catalyzed tandem reaction of N-(2-iodoaryl)acrylamides with two aryl iodides for the synthesis of spirooxindole has been achieved. The reaction underwent the process of triple C-H activation and four C-C bond formations based on the double trapping of transient spirocyclic palladacycles which are obtained through remote C-H activation.

Measurement and calculation of surface tension of molten Sn-Bi alloy.

The surface tension of molten Sn-Bi (mole fraction X(Bi) = 0.455) alloy has been determined by the sessile drop method at oxygen partial pressure (P(O2)) of 1.0x10(-6) MPa and different temperatures. The experimental results have been analyzed and discussed, and the positive temperature coefficient of surface tension of molten Sn-Bi alloy has been elucidated. The surface tension of this molten alloy has also been obtained by calculation using STCBE based on Butler's equation and thermodynamic data. The experimental results agree well with the calculation values.