ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

A deep learning-based method for recognizing the minutiae in fingerprint,as well as a Python programming-based evaluation system for quantifying the evidence value of fingerprint was proposed.Firstly,latent fingerprints,which were developed using a series of fluorescent nanomaterials synthesized by chemical methods,were used as unknown fingerprint(UKFP),while ink impressed fingerprints were used as known fingerprint(KFP).Then,the bifurcations and terminations in minutiae were recognized using the improved YOLOv8 deep learning model.After that,the similarity index(Sim.)of UKFP vs KFP were calculated by analyzing the angle similarity factor(α)and the curve similarity factor(β)between UKFP and KFP,meanwhile,the sensitivity index(Sen.)were calculated by analyzing the fineness factor(γ)between UKFP and KFP.The evidence value(EV)of fingerprint was thus obtained by the combination of Sim.and Sen..The calculation formulas for above evaluation factors(i.e.α,β and γ),evaluation indexes(i.e.Sim.and Sen.),and EV were also put forward.Finally,the evaluation system for quantifying the evidence value of fingerprint was established,the feasibility and reliability of this system were verified,and the external factors that impacted on Sim.,Sen.,and EV were investigated in detail.The Python-based evaluation system for quantifying the evidence value of fingerprint could achieve the goals objectively,comprehensively,accurately and efficiently,exhibiting easy operability,high efficiency,responsiveness and reliability.This research was expected to provide beneficial references for quantitatively evaluating and thoroughly developing the evidence value.

In this study,an ON/OFF type micro-valve with a sandwich(glass-silicon-glass)structure was designed and fabricated based on the micro-electro-mechanical system(MEMS)technique.The deformable membrane of this micro-valve was prepared on the silicon on insulator(SOI)substrate and sealed using Si-Si bonding and anodic bonding methods.The micro-valve had high-temperature stability and was suitable for integration with other gas chromatography components.The deformable membrane with a thickness of 10 μm was processed on the top silicon of the SOI substrate.The flow control of the micro-valve could be achieved by changing the driving pressure applied to the deformable membrane to deform it.Compared with polymer membranes,the deformable membrane prepared on the top layer silicon of SOI had better temperature stability and could be released using the deep reactive ion etching technique after silicon-silicon bonding,avoiding deformation during the preparation process.In addition,due to the small gap between the membrane and the inlet/outlet holes,the dead volume of the microvalve was very small.The test results indicated that the micro-valve achieved flow control and ON/OFF functions with good repeatability.

A monolithic integrated gas chromatography chip,consisting of a micro gas chromatography column(μGCC)and a micro helium discharge ionization detector(μHDID)was proposed.The chip was fabricated using micro electromechanical system(MEMS)technique,and its sensitivity was improved from two aspects.On one hand,open tubular column was selected as the separation device,and the auxiliary helium channel width of μHDID was modulated based on the microchannel width of the μGCC to match the flow rates of μHDID and μGCC.On the other hand,the electrode structure inside the μHDID collection zone was optimized,a bias electrode group around the collection electrode was constructed,and the ion collection efficiency was improved.After coating HKUST-1 as the stationary phase,the monolithic integrated gas chromatography chip could achieve baseline separation and detection of light hydrocarbon gas mixture(methane,ethane,propane,andn-butane),with a detection limit for propane as low as 25 pg.The chip could carried out test under temperature-programmed conditions,with a resolution of 9.24 for ethane and propane.

The influence of material properties on fingerprint development effects were systematically studied.Firstly,carbon dots/NaYF4 and Cu nanoclusters/starch nanocomposites respectively possessing different fluorescent intensities and dual fluorescent colors,as well as NaYF4 micro-/nano-materials exhibiting different morphologies,sizes,and surface properties were chemically synthesized and further used for latent fingerprint development.Then,the developing effects were comprehensively evaluated by visual analysis combining with spectral characterization and Python-based calculation.Finally,the influences of material properties on latent fingerprint development were quantitatively evaluated from three dimensions including contrast,sensitivity,and selectivity.The fluorescence properties of developing materials and substrates could significantly affect the developing contrast,namely,the stronger the developing signal,the higher the contrast;the weaker the background noise,the higher the contrast.The sizes and morphologies of the developing materials could respectively influence the quantity and quality of developed minutiae,and significantly affect the developing sensitivity,namely,the smaller the particle size of developing materials,the more the quantity of developed minutiae and the higher the sensitivity;the smaller the surface area of developing materials,the higher the quality of developed minutiae and the higher the sensitivity.The surface properties together with the sizes and morphologies of developing materials could influence their adsorption performances,and significantly affect the developing selectivity,namely,the stronger the specific adsorption of developing materials with fingerprint substance,and the weaker the non-specific adsorption of developing materials with substrate,the higher the selectivity.Moreover,the fingerprint development using the materials with suitable surface area and appropriate mass would have a high selectivity.