Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS.

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.202, p < 0.01). Global spatial autocorrelation analysis indicated significant positive spatial autocorrelation in influenza incidence rates from 2016 and from 2018 to 2023 (Moran's I > 0, P < 0.05). Local spatial autocorrelation analysis further revealed clustering patterns in different regions, with high-high clustering and low-high clustering predominating in northern Xinjiang, and low-low clustering predominating in southern Xinjiang. Hotspot analysis indicated a progressive rise in the number of influenza incidence hotspots, primarily concentrated in northern Xinjiang, particularly in Urumqi, Ili Kazakh Autonomous Prefecture, and Hotan Prefecture. Standard deviation ellipse analysis and the trajectory of influenza incidence gravity center migration showed that the transmission range of influenza in Xinjiang has been expanding, with the epidemic center gradually moving northward. The spatiotemporal heterogeneity of influenza incidence in Xinjiang highlights the need for differentiated and precise influenza prevention and control strategies in different regions to address the changing trends in influenza prevalence.

Stabilization effect of nano-SiO2@iron-phosphorus on ferrallisols, calcareous soil and organic soil heavily polluted by heavy metals: A fast reaction curing stabilization process.

The remediation of soil pollution by heavy metals (HMs) presents a significant challenge in environmental restoration. Stabilization remediation technology has proven effective in treating HMs contaminated soil. However, its development is constrained by drawbacks such as slow reaction kinetics and low adsorption capacity. This research synthesized a nano-SiO2@iron­phosphorus (FPOH) material by SiO32- encapsulating the iron-phosphate precipitate obtained from Fe ion and phosphate. In addition, this research applied this material to ferrallisols, calcareous soils and organic soils with three different levels of high pollution by Cd, Pb, Cu and Zn. The experimental results indicate that all experimental soils stabilized rapidly within 1 day and met the requirements of remediation engineering standards (ChinaMEE HJ 1282-2023). Analysis of the possible mechanisms suggests that the FPOH material effectively fills voids with phosphate mineral formation, preventing the secondary release of HMs. During the stabilization process, FPOH involves the adsorption of free ions and small organic molecules in the soil, which does not affect its high reactivity. The development and utilization of FPOH offer valuable insights for soil stabilization remediation.

Clinical significance of serum soluble scavenger receptor CD163 in patients with lupus nephritis.

BACKGROUND: The soluble CD163 (sCD163) was elevated in systemic lupus erythematosus (SLE) patients. PURPOSE: To study whether serum sCD163 could be used to predict the occurrence and prognosis of lupus nephritis (LN). RESEARCH DESIGN: The recruited patients were classified into different groups according to standard identification criteria. STUDY SAMPLE: The patients with LN. DATA COLLECTION AND ANALYSIS: 11 indices were analyzed and compared in SLE and LN patients. Furthermore, the level of serum sCD163 was detected using an enzyme-linked immunosorbent assay. Meanwhile, the receiver operating characteristic analysis was performed to evaluate the prediction effect of sCD163. Additionally, spearman correlation analysis of serum sCD163 with indices was conducted. RESULTS: There were six positive indices and one negative risk factor correlated to LN. sCD163 was elevated in LN patients and could be used to diagnose LN. Importantly, sCD163 was increased in LN patients with a heavy SLE disease activity index. Finally, it was revealed that the level of sCD163 was higher in the LN patients with no response than that with complete or partial response, which also could predict the prognosis of LN. CONCLUSIONS: Serum sCD163 was elevated in LN patients than in SLE patients, which could be used to predict the occurrence and prognosis of LN.

Surveillance of avian influenza viruses in Hebei Province of China from 2021 to 2023: Identification of a novel reassortant H3N3.

Avian influenza remains a global public health concern for its well-known point mutation and genomic segment reassortment, through which plenty of serum serotypes are generated to escape existing immune protection in animal and human populations. Some occasional cases of human infection of avian influenza viruses (AIVs) since 2020 posed a potential pandemic risk through human-to-human transmission. Both east-west and north-south migratory birds fly through and linger in the Hebei Province of China as a stopover habitat, providing an opportunity for imported AIVs to infect the local poultry and for viral gene reassortment to generate novel stains. In this study, we collected more than 6000 environmental samples (mostly feces) in Hebei Province from 2021 to 2023. Samples were screened using real-time RT-PCR, and virus isolation was performed using the chick embryo culture method. We identified 10 AIV isolates, including a novel reassortant H3N3 isolate. Sequencing analysis revealed these AIVs are highly homologous to those isolated in the Yellow River Basin. Our findings supported that AIVs keep evolving to generate new isolates, necessitating a continuous risk assessment of local avian influenza in wild waterfowl in Hebei, China.

Diversity of Fungal Community and Its Constraints in the Yifeng Lithium Mines, Eastern China.

It is well accepted that biodiversity and ecosystem functions are strongly shaped by environmental conditions; however, relatively little is known about how they depend on the mineralogical assemblage of local environments, especially in mines. This study aims to reveal the diversity characteristics of the fungal community in the surface of granite lithium ores and their weathering products sampled from the Yifeng lithium mines in Jiangxi Province, eastern China. According to the analysis of internal transcribed spacer1 (ITS1) high-throughput sequencing, significant differences in fungal community diversity on the surface of lithium ores and their weathering products have been revealed. The operational taxonomic unit (OTU) of the ore surface and its weathering products ranged from 280 to 624, which may depend on the mineral composition as well as the degree of weathering. The community composition of each sample was significantly different at the phylum level, especially between the weathering products in Ascomycota and Basidiomycota. Although Ascomycota and Basidiomycota were the dominant fungal communities in all samples, each sample has its own distinctive fungi. The trophic modes of the fungi were more complex than that of the bacteria. 10 different fungal trophic modes and 25 dominant functional fungal groups were disclosed, and the saprophytic community was found to be the dominant group. These fungi could accelerate the decomposition of environmental organic matter in the environment by producing hydrolases and oxidases. Chytridiomycota with the function of producing and regulating secondary metabolites were the representative fungi in all samples. Our findings would provide theoretical basis and research clues for understanding the relationship between weathering of granite lithium and fungal communities.

Construction of an interface interaction in a g-C3N4/CdS/NiS for photoreforming of plastic and clean hydrogen regeneration.

Converting plastics into organic matter by photoreforming is an emerging way to deal with plastic pollution and produce valuable organic matter. Water shortage can be alleviated by using seawater resources. To solve these problems, we synthesize a ternary heterostructure composite g-C3N4/CdS/NiS. Heterojunctions are formed between graphitized carbon nitride (g-C3N4), cadmium sulfide (CdS) and nickel sulfide (NiS), which effectively improve the problem of fast charge recombination of pure g-C3N4 and CdS. The results of the g-C3N4/CdS/NiS photocatalytic tests show that the hydrogen production rates in seawater and pure water for 5 h are 30.44 and 25.79 mmol/g/h, respectively. In stability test, the hydrogen production rate of the g-C3N4/CdS/NiS in seawater and pure water is similar. This suggests that seawater can replace pure water as a source of hydrogen. While H2 is generated, the lactate obtained by polylactic acid (PLA) hydrolysis is oxidized to form small organic compounds such as formate, acetate and pyruvate. Our study shows that g-C3N4/CdS/NiS can not only use seawater as a hydrogen source to produce H2, but also photoreformate plastics dissolved in seawater into valuable small organic molecules. This has a positive impact on the production and use of clean energy, as well as on plastic pollution and water scarcity.

One-Pot Synthesis of Color-Tunable Narrow-Bandwidth Ag-In-Ga-Zn-S Semiconductor Nanocrystals for Quantum-Dot Light-Emitting Diodes.

I-III-VI type semiconductor nanocrystals (NCs) have attracted considerable attention due to their environmental friendly nature and large-scale tunable emission. Herein, we report the successful synthesis of full-spectrum (470 to 614 nm) Ag-In-Ga-Zn-S (AIGZS) NCs by precisely regulating the In/Ga ratios using a facile one-pot method. Intriguingly, the photoluminescence (PL) peak width exhibits a continuous narrowing trend with extended reaction time, ultimately reaching a full width at half-maximum (fwhm) of 34 nm for green AIGZS NCs. Furthermore, the exciton relaxation dynamics of AIGZS NCs were systematically investigated using time-resolved photoluminescence and femtosecond transient absorption spectroscopy. Remarkably, we successfully fabricated blue, green, and red quantum-dot light-emitting diodes (QLEDs), forecasting the potential of AIGZS NCs with high color purity for applications in full-spectrum QLEDs.

DLK1 promoted ischemic angiogenesis through notch1 signaling in endothelial progenitor cells.

Delta like non-canonical Notch ligand 1 (DLK1), as a member of epidermal growth factor-like family, plays a critical role in somatic growth, tissue development and possibly tissue renewal. Though previous studies had indicated that DLK1 contributed to adipogenesis and myogenesis, it's still controversial whether DLK1 affects angiogenesis and how it interacts with Notch signaling with numerous conflicting reports from different models. Based on our preliminary finding that DLK1 expression was up-regulated in mice ischemic gastrocnemius and in the border zone of infarcted myocardium, we administered either recombinant DLK1 (rDLK1) or PBS in C57BL/6 mice after establishment of hindlimb ischemia (HLI) and myocardial infarction (MI), respectively. Exogenous rDLK1 administration significantly improved both blood perfusion of mice ischemic hindlimbs and muscle motor function on the 3rd, 7th day after HLI, by promoting neovascularization. Similar effect on neovascularization was verified in mice on the 28th day after MI as well as improvement of cardiac failure. Correspondingly, the number of CD34+KDR+ cells, indicated as endothelial progenitor cells (EPCs), was significantly in mice ischemic gastrocnemius by rDLK1 administration, which was abrogated by DAPT as the specific inhibitor of Notch intracellular domain (NICD). Furthermore, bone marrow mononuclear cells were obtained from C57BL/6 mice and differentiated to EPCs ex vivo. Incubation with rDLK1 triggered Notch1 mRNA and NICD protein expressions in EPCs as exposed to hypoxia and serum deprivation, promoting EPCs proliferation, migration, anti-apoptosis and tube formation. Otherwise, rDLK1 incubation significantly decreased intracellular and mitochondrial reactive oxygen species, increased ATP content and mitochondrial membrane potential, downregulated short isoform of OPA-1 expression whereas upregulated mitofusin (-1, -2) expression in EPCs by Notch1 signaling, which were all abrogated by DAPT. In summary, the present study unveils the pro-angiogenesis and its mechanism of rDLK1 through activation of Notch1 signaling in endothelial progenitor cells.

Replicon-Based Typing About IncG Plasmids and Molecular Characterization of Five IncG Plasmids Carrying Carbapenem Resistance Gene bla KPC-2.

Purpose: To investigate the genetic diversity of IncG plasmids, we have proposed a typing scheme based on replicon repA and performed comparative genomic analysis of five IncG plasmids from China. Methods: p30860-KPC, p116965-KPC, pA1705-KPC, pA1706-KPC and pNY5520-KPC total in five IncG plasmids from clinical isolates of Pseudomonas and Enterobacteriaceae, respectively, were fully sequenced and were compared with the previously collected reference plasmid p10265-KPC. Results: Based on phylogeny, IncG-type plasmids are divided into IncG-I to IncG-VIII, the five plasmids belong to IncG-VIII. A detailed sequence comparison was then presented that the IncG plasmid involved accessory region I (Tn5563a/b/c/d/e), accessory region II (ISpa19), and accessory region III (bla KPC-2-region). Expect for the pNY5520-KPC, the rest of the plasmids had the same backbone structure as the reference one. Within the plasmids, insertion sequences Tn5563d and Tn5563e were identified, a novel unknown insertion region was found in Tn5563b/c/d/e. In addition, Tn6376b and Tn6376c were newly designated in the study. Conclusion: The data presented here including a typing scheme and detailed genetic comparison which provide an insight into the diversification and evolution history of IncG plasmids.

Deep learning-based automated scan plane positioning for brain magnetic resonance imaging.

Background: Manual planning of scans in clinical magnetic resonance imaging (MRI) exhibits poor accuracy, lacks consistency, and is time-consuming. Meanwhile, classical automated scan plane positioning methods that rely on certain assumptions are not accurate or stable enough, and are computationally inefficient for practical application scenarios. This study aims to develop and evaluate an effective, reliable, and accurate deep learning-based framework that incorporates prior physical knowledge for automatic head scan plane positioning in MRI. Methods: A deep learning-based end-to-end automated scan plane positioning framework has been developed for MRI head scans. Our model takes a three-dimensional (3D) pre-scan image input, utilizing a cascaded 3D convolutional neural network to detect anatomical landmarks from coarse to fine. And then, with the determined landmarks, accurate scan plane localization can be achieved. A multi-scale spatial information fusion module was employed to aggregate high- and low-resolution features, combined with physically meaningful point regression loss (PRL) function and direction regression loss (DRL) function. Meanwhile, we simulate complex clinical scenarios to design data augmentation strategies. Results: Our proposed approach shows good performance on a clinically wide range of 229 MRI head scans, with a point-to-point absolute error (PAE) of 0.872 mm, a point-to-point relative error (PRE) of 0.10%, and an average angular error (AAE) of 0.502°, 0.381°, and 0.675° for the sagittal, transverse, and coronal planes, respectively. Conclusions: The proposed deep learning-based automated scan plane positioning shows high efficiency, accuracy and robustness when evaluated on varied clinical head MRI scans with differences in positioning, contrast, noise levels and pathologies.

Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets.

Background: Pre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood. Methods: In this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis. The GSE75010 and GSE74341 datasets from the GEO database were obtained and merged for differential analysis. A weighted gene co-expression network analysis (WGCNA) was constructed based on macrophage content, and machine learning methods were employed to identify key genes. Immunoinfiltration analysis completed by the CIBERSORT method, R package "ClusterProfiler" to explore functional enrichment of these intersection genes, and potential drug predictions were conducted using the CMap database. Lastly, independent analysis of protein levels, localization, and quantitative analysis was performed on placental tissues collected from both preeclampsia patients and healthy control groups. Results: We identified 70 differentially expressed NETs genes and found 367 macrophage-related genes through WGCNA analysis. Machine learning identified three key genes: FNBP1L, NMUR1, and PP14571. These three key genes were significantly associated with immune cell content and enriched in multiple signaling pathways. Specifically, these genes were upregulated in PE patients. These findings establish the expression patterns of three key genes associated with M2 macrophage infiltration, providing potential targets for understanding the pathogenesis and treatment of PE. Additionally, CMap results suggested four potential drugs, including Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin, which may have the potential to reverse pre-eclampsia. Conclusion: Studying the expression levels of three key genes in pre-eclampsia provides valuable insights into the prevention and treatment of this condition. We propose that these genes play a crucial role in regulating the maternal-fetal immune microenvironment in PE patients, and the pathways associated with these genes offer potential avenues for exploring the molecular mechanisms underlying preeclampsia and identifying therapeutic targets. Additionally, by utilizing the Connectivity Map database, we identified drug targets like Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin as potential clinical treatments for preeclampsia.

Optical modification of nonlinear crystals for quasi-parametric chirped-pulse amplification.

Quasi-parametric chirped-pulse amplification (QPCPA), which features a theoretical peak power much higher than those obtained with Ti:sapphire laser or optical parametric chirped-pulse amplification, is promising for future ultra-intense lasers. The doped rare-earth ion used for idler dissipation is critical for effective QPCPA, but is usually not compatible with traditional crystals. Thus far, only one dissipative crystal of Sm3+-doped yttrium calcium oxyborate has been grown and applied. Here we introduce optical means to modify traditional crystals for QPCPA applications. We theoretically demonstrate two dissipation schemes by idler frequency doubling and sum-frequency generation with an additional laser. In contrast to absorption dissipation, the proposed nonlinear dissipations ensure not only high signal efficiency but also high small-signal gain. The demonstrated ability to optically modify crystals will facilitate the wide application of QPCPA.

Enhancing guided bone regeneration with cross-linked collagen-conjugated xenogeneic bone blocks and membrane fixation: A preclinical in vivo study.

OBJECTIVE: To determine whether combining cross-linked (CL) collagen-integrated xenogeneic bone blocks stabilized with the fixation of resorbable collagen membranes (CM) can enhance guided bone regeneration (GBR) in the overaugmented calvarial defect model. MATERIALS AND METHODS: Four circular defects with a diameter of 8 mm were prepared in the calvarium of 13 rabbits. Defects were randomly assigned to receive one of the following treatments: (i) non-cross-linked (NCL) porcine-derived collagen-embedded bone block covered by a CM without fixation (NCL + unfix group); (ii) NCL bone block covered by CM with fixation using bone-tack (NCL + fix group); (iii) cross-linked (CL) porcine-derived collagen-embedded bone block covered by CM without fixation (CL + unfix group); and (iv) CL bone block covered by CM with fixation using bone-tack fixation (CL + fix group). The efficacy of GBR was assessed through histological and molecular analyses after 2 and 8 weeks. RESULTS: At 2 weeks, there were no significant differences in histologically measured areas of newly formed bone among the groups. At 8 weeks, however, the CL + fix group exhibited a larger area of new bone (5.08 ± 1.09 mm2, mean ± standard deviation) compared to the NCL + unfix (1.62 ± 0.42 mm2; p < .0083), NCL + fix (3.97 ± 1.39 mm2) and CL + unfix (2.55 ± 1.04 mm2) groups. Additionally, the expression levels of tumour necrosis factor-alpha, fibroblast growth factor-2, vascular endothelial growth factor, osteocalcin and calcitonin receptor were significantly higher in the CL + fix group compared to the other three groups (p < .0083). CONCLUSION: Cross-linked bone blocks stabilized with collagen membrane fixation can significantly enhance GBR.

Highly Efficient Flexible Photodetectors Based on Pb-Free CsBi3I10 Perovskites.

Perovskites have made remarkable advancements in optoelectronics owing to their high light absorption coefficient, tunable bandgap, and long charge diffusion. Nonetheless, the practical applications of Pb-based perovskites have been hindered by the instability and toxicity of Pb, especially in flexible electronics, which require high biosecurity and low toxicity. Hence, the development of stable Pb-free perovskite materials has gained increasing attention. In this study, we synthesized stable CsBi3I10 Pb-free perovskites outside the glovebox and improved the optoelectronic and mechanical performances of the CsBi3I10-based flexible devices through polyvinylcarbazole (PVK) doping. Flexible photodetectors with the device structure of PET/ITO/PEDOT:PSS/CsBi3I10:PVK/Au was fabricated. The results indicated that the introduction of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) reduced the surface roughness of the flexible PET substrate, while PVK doping further improved the surface smoothness of CsBi3I10 thin films, thereby enhancing the interfacial charge transportation. Moreover, PEDOT:PSS and PVK acted as stepwise hole transport layers in the photodetectors. The device demonstrated a maximum responsivity of 0.3 A/W, detectivity of 2.6 × 1011 Jones, and a response time of 102 µs at 650 nm. After subjecting it to 1000 bending tests, the light current retained 80% of its initial value. This study presents a universally applicable method for controlling the surface morphology of a flexible perovskite thin film.

Genetic Characteristics of Novel IncpSE5381-aadB Plasmids, Integrative and Mobilizable Elements, and Integrative and Conjugative Elements in Pseudomonas aeruginosa.

Purpose: Pseudomonas aeruginosa is a common causative bacteria in nosocomial infections. This study aims to describe the structure and evolutionary characteristics of mobile genetic elements (MGEs) carrying antibiotic resistance genes (ARGs) from P. aeruginosa and to conduct bioinformatics and comparative genomic analysis to provide a deeper understanding of the genetic characteristics and diversity of MGEs in P. aeruginosa. Methods: Fifteen clinical isolates of P. aeruginosa from China were collected and sequenced in this study, and 15 novel MGEs were identified. Together with four MGEs from GenBank, a total of 19 MGEs were used to perform detailed modular structure dissection and sequence comparison. Then, the biological experiments were carried out to verify the biological characteristics of these isolates and MEGs. Results: The novel MGEs identified in this study displayed diversification in modular structures, which showed complex mosaic natures. The seven types of 19 MGEs included in this study were divided into three groups: i) novel MGEs (firstly identified in this study): four IncpSE5381-aadB plasmids and three Tn7495-related integrative and mobilizable elements (IMEs); ii) newly defined MGEs (firstly designated in this study, but with previously determined sequences): four Tn7665-related IMEs; iii) novel transposons with reference prototypes identified in this study: two Tn6417-related integrative and conjugative elements (ICEs), two IS-based transposition units, two Tn501-related unit transposons, two Tn1403-related unit transposons. At least 36 ARGs involved in resistance to 11 different classes of antimicrobials and heavy metals were identified. Additionally, three novel blaOXA variants were identified. Antimicrobial susceptibility testing showed that these variants were resistant to some ß-lactamase antibiotics and blaOXA-1204 was additionally resistant to cephalosporins. Conclusion: The continuous evolution of ARG-carrying MGEs during transmission, leading to the emergence of novel MGEs or ARGs, which facilitates the spread of antibiotic resistance in P. aeruginosa and enhances the diversity of transmission modes of bacterial resistance.

The Inflammatory State of Follicular Fluid Combined with Negative Emotion Indicators can Predict Pregnancy Outcomes in Patients with PCOS.

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder syndrome with an incidence of 6% to 10% in women of reproductive age. Women with PCOS not only exhibit abnormal follicular development and fertility disorders, but also have a greater tendency to develop anxiety and depression. Our aim was to evaluate the ability of inflammatory factors in follicular fluid to predict embryonic developmental potential and pregnancy outcome and to construct a machine learning model that can predict IVF pregnancy outcomes based on indicators such as basic sex hormones, embryonic morphology, the follicular microenvironment, and negative emotion. In this study, inflammatory factors (CRP, IL-6, and TNF-α) in follicular fluid samples obtained from 225 PCOS and 225 non-PCOS women were detected via ELISA. For patients with PCOS, the levels of CRP and IL-6 in the follicular fluid in the pregnant group were significantly lower than those in the nonpregnant group. For non-patients with PCOS, only the level of IL-6 in the follicular fluid was significantly lower in the pregnant group than in the nonpregnant group. In addition, for both PCOS and non-patients with PCOS, compared with those in the pregnant group, patients in the nonpregnant group showed more pronounced signs of anxiety and depression. Finally, the factors that were significantly different between the two subgroups (pregnancy and nonpregnancy) of patients with or without PCOS were identified by an independent sample t test first and further analysed by multilayer perceptron (MLP) and random forest (RF) models to distinguish the two clinical pregnancy outcomes according to the classification function. The accuracy of the RF model in predicting pregnancy outcomes in patients with or without PCOS was 95.6% and 91.1%, respectively. The RF model is more suitable than the MLP model for predicting pregnancy outcomes in IVF patients. This study not only identified inflammatory factors that can affect embryonic development and assessed the anxiety and depression tendencies of PCOS patients, but also constructed an AI model that predict pregnancy outcomes through machine learning methods, which is a beneficial clinical tool.

Polymerase-Based Signal Delay for Temporally Regulating DNA Involved Reactions, Programming Dynamic Molecular Systems, and Biomimetic Sensing.

Complex temporal molecular signals play a pivotal role in the intricate biological pathways of living organisms, and cells exhibit the ability to transmit and receive information by intricately managing the temporal dynamics of their signaling molecules. Although biomimetic molecular networks are successfully engineered outside of cells, the capacity to precisely manipulate temporal behaviors remains limited. In this study, the catalysis activity of isothermal DNA polymerase (DNAP) through combined use of molecular dynamics simulation analysis and fluorescence assays is first characterized. DNAP-driven delay in signal strand release ranged from 100 to 102 min, which is achieved through new strategies including the introduction of primer overhangs, utilization of inhibitory reagents, and alteration of DNA template lengths. The results provide a deeper insight into the underlying mechanisms of temporal control DNAP-mediated primer extension and DNA strand displacement reactions. Then, the regulated DNAP catalysis reactions are applied in temporal modulation of downstream DNA-involved reactions, the establishment of dynamic molecular signals, and the generation of barcodes for multiplexed detection of target genes. The utility of DNAP-based signal delay as a dynamic DNA nanotechnology extends beyond theoretical concepts and achieves practical applications in the fields of cell-free synthetic biology and bionic sensing.

FTO promotes gastric cancer progression by modulating MAP4K4 expression via demethylation in an m6A-dependent manner.

Gastric cancer (GC) is a serious malignant tumour with a high mortality rate and a poor prognosis. Recently, emerging evidence has suggested that N6-methyladenosine (m6A) modification plays a crucial regulatory role in cancer progression. However, the exact role of m6A regulatory factors FTO in GC is unclear. First, the expression of m6A methylation-related regulatory factors in clinical samples and the clinical data of the corresponding patients were obtained from The Cancer Genome Atlas (TCGA-STAD) dataset, and correlation analysis between FTO expression and patient clinicopathological parameters was subsequently performed. qRT-PCR, immunohistochemistry (IHC) and western blotting (WB) were used to verify FTO expression in GC. CCK-8, EdU, flow cytometry and transwell assays were used to evaluate the effect of FTO on the behaviour of GC cells. Transcriptome sequencing and RNA immunoprecipitation analysis were used to explore the potential regulatory mechanisms mediated by FTO. FTO was highly expressed in GC tissues and cells, and high expression of FTO predicted a worse prognosis than low expression. Functionally, overexpression of FTO promoted the proliferation, migration and invasion of GC cells but inhibited cell apoptosis. Mechanistically, we found that FTO is upregulated in GC and promotes GC progression by modulating the expression of MAP4K4. Taken together, our findings provide new insights into the effects of FTO-mediated m6A demethylation and could lead to the development of new strategies for GC monitoring and aggressive treatment.

Research on Indoor Environment Prediction of Pig House Based on OTDBO-TCN-GRU Algorithm.

Temperature and humidity, along with concentrations of ammonia and hydrogen sulfide, are critical environmental factors that significantly influence the growth and health of pigs within porcine habitats. The ability to accurately predict these environmental variables in pig houses is pivotal, as it provides crucial decision-making support for the precise and targeted regulation of the internal environmental conditions. This approach ensures an optimal living environment, essential for the well-being and healthy development of the pigs. The existing methodologies for forecasting environmental factors in pig houses are currently hampered by issues of low predictive accuracy and significant fluctuations in environmental conditions. To address these challenges in this study, a hybrid model incorporating the improved dung beetle algorithm (DBO), temporal convolutional networks (TCNs), and gated recurrent units (GRUs) is proposed for the prediction and optimization of environmental factors in pig barns. The model enhances the global search capability of DBO by introducing the Osprey Eagle optimization algorithm (OOA). The hybrid model uses the optimization capability of DBO to initially fit the time-series data of environmental factors, and subsequently combines the long-term dependence capture capability of TCNs and the non-linear sequence processing capability of GRUs to accurately predict the residuals of the DBO fit. In the prediction of ammonia concentration, the OTDBO-TCN-GRU model shows excellent performance with mean absolute error (MAE), mean square error (MSE), and coefficient of determination (R2) of 0.0474, 0.0039, and 0.9871, respectively. Compared with the DBO-TCN-GRU model, OTDBO-TCN-GRU achieves significant reductions of 37.2% and 66.7% in MAE and MSE, respectively, while the R2 value is improved by 2.5%. Compared with the OOA model, the OTDBO-TCN-GRU achieved 48.7% and 74.2% reductions in the MAE and MSE metrics, respectively, while the R2 value improved by 3.6%. In addition, the improved OTDBO-TCN-GRU model has a prediction error of less than 0.3 mg/m3 for environmental gases compared with other algorithms, and has less influence on sudden environmental changes, which shows the robustness and adaptability of the model for environmental prediction. Therefore, the OTDBO-TCN-GRU model, as proposed in this study, optimizes the predictive performance of environmental factor time series and offers substantial decision support for environmental control in pig houses.