ObjectiveTo characterize the changes of metabolites of Blumea balsamifera in the process of sweating by non-targeted metabolomics， and to investigate the influence of sweating processing on the constituents of B. balsamifera. MethodsUltra performance liquid chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap-MS） metabolomics was used to identify the metabolites in no sweating group（F1）， sweating 2 d group（F2） and sweating 4 d group（F3）， the differences of metabolites between the groups were compared by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， and differential metabolites were screened according to the variable importance in the projection（VIP） value>1 and P<0.05， and the pathway enrichment of the differential metabolites was analyzed by Kyoto Encyclopedia of Genes and Genomes（KEGG）. ResultsThe results of PCA and OPLS-DA showed a clear distinction between the three groups of samples， indicating significant differences in the compositions of the three groups of samples. A total of 433 differential metabolites were screened between the F1 and F2， with 154 up-regulated and 279 down-regulated， the significant up-regulated metabolites were tangeritin， 5-O-demethylnobiletin and so on， while the metabolites with significant down-regulation included alternariol， fortunellin， etc. A total of 379 differential metabolites were screened between the F2 and F3， with 150 up-regulated and 229 down-regulated， the significant up-regulated metabolites were isoimperatorin， helianyl octanoate and so on， and the significant down-regulated metabolites were hovenoside I， goyasaponin Ⅲ， etc. KEGG pathway enrichment analysis showed that tyrosine metabolism， isoquinoline alkaloid biosynthesis， phenylalanine， tyrosine and tryptophan biosynthesis， tryptophan metabolism， valine， leucine and isoleucine biosynthesis， pantothenate and coenzyme A biosynthesis may be the key pathways affecting metabolite differences of B. balsamifera after sweating treatment. ConclusionSweating can reduce the content of endophytic mycotoxins in B. balsamifera and has a great impact on the synthesis and metabolic pathways of total flavonoids and auxin. This study can provide a reference for the process research on the sweating conditions of B. balsamifera.

This study analyzed the epidemiological characteristics and trends of respiratory syncytial virus (RSV) infections among inpatients with acute respiratory infections (ARI) in a children′s hospital in Shenzhen City inpatients from 2020 to 2023. From January 2020 to December 2023, multiple reverse transcription polymerase chain reaction (RT-PCR) combined with capillary electrophoresis fragment analysis technology was used to detect the nucleic acids of 12 respiratory pathogens, including RSV, in hospitalized children diagnosed with ARI. The patients were divided into six age groups: 0 to <6 months, 6 months to <1 year, 1 to <2 years, 2 to <5 years, 5 to <10 years, and 10 to <18 years. A total of 53 033 children were tested, including 6 830 RSV positive cases, with an overall positivity rate of 12.88%. The annual RSV positivity rates from 2020 to 2023 were 20.04%, 16.18%, 4.89%, and 13.33%, respectively, with statistically significant differences between the years ( χ2=1 185.994, P<0.001). The positive rate of RSV detection decreased with increasing age across all years (all P trend<0.05). From 2020 to 2023, the proportion of RSV-positive cases aged 2 to 5 years and older showed an increasing trend ( P trend<0.001 for all years). Compared to 2023, the median age of RSV-infected children was lower in 2020 ( Z=7.826, P<0.001) and 2021 ( Z=6.106, P<0.001). The proportion of severe infections requiring ICU admission did not change significantly across all years ( χ2=0.179, P=0.981). The RSV epidemic season in 2020 mainly occurred during 28-43 weeks, and in 2021, it spanned from 22-43 weeks. However, in 2022, the season was delayed until the 49th week and lasted for three weeks. In 2023, the seasonal epidemic appeared earlier, starting in the 14th week and lasting for 28 weeks. From 2020 to 2023, the rate of RSV co-infections with other pathogens (mycoplasma pneumoniae, human parainfluenza virus, human bocavirus, human coronavirus, human metapneumovirus, and influenza A) significantly increased (all P trend<0.01). In conclusion, the epidemiological characteristics of RSV infections in Shenzhen Children′s Hospital changed from 2020 to 2023. In 2022, there were only delayed, low-intensity and short-lived seasonal epidemics. However, in 2023, there was an earlier and prolonged epidemic, with increased infections in children aged 2 to 5 years and older and a rise in co-infections, while the proportion of severe infections requiring ICU admission remained unchanged.

The working principle of Bausch&Lomb BL11110 phacoemulsification system was described.Three cases of typical faults of the phacoemulsification system were introduced,and the causes were analyzed,then the maintenance measures were given accordingly.References were provided for diagnosing and eliminating the faults of the phacoemulsification system.[Chinese Medical Equipment Journal,2025,46(4):118-120]

Objective A scoping review of domestically and internationally published studies on finite element analysis(FEA)based on three-dimensional(3D)human body model in preventing pressure ulcer(PU)was conducted,aiming to provide new directions for improving the prevention strategies of pressure ulcer.Methods We conducted a systematic search in both Chinese and English medical databases,including PubMed,Embase,CINAHL,Web of Science,Cochrane Library,Sinomed,CNKI,Wanfang and VIP,and engineering database(Engineering Village Compen-dex).The search period was from the inception of each database to July 29,2024.The information was extracted,and the results were analyzed and standardized for reporting.Results A total of 30 studies were included.The general methods of FEA based on 3D human body model include establishing geometric model,meshing,defining material properties,loading and setting boundary conditions,and solving equations.According to the contents of studies,they could be categorized into 4 distinct application domains,including identification of risk groups(n=9),position management(n=9),preventive dressings(n=10)and supportive surfaces(n=7).Conclusion FEA based on 3D human body model provides a foundation to PU biomechanical mechanism research and a scientific basis to the supplement and optimization of clinical prevention.Future studies should integrate clinical problems with simulations and further optimize simulations techniques and protocols.

The working principle of Bausch&Lomb BL11110 phacoemulsification system was described.Three cases of typical faults of the phacoemulsification system were introduced,and the causes were analyzed,then the maintenance measures were given accordingly.References were provided for diagnosing and eliminating the faults of the phacoemulsification system.[Chinese Medical Equipment Journal,2025,46(4):118-120]

Objective To analyze differentially expressed proteins(DEPs)in the hippocampal tissue of an amyloid-beta 1-42(Aβ1-42)-induced Alzheimer's disease(AD)rat model using Tandem mass tag(TMT)-based quantitative proteomics,followed by bioinformatic analysis to explore potential AD mechanisms.Methods Twelve male Sprague-Dawley(SD)rats were randomly assigned to a control group(n=6)and a model group(n=6).The AD model was established by bilateral hippocampal injection of Aβ1-42 in the model group,while the control group received an equivalent volume of saline.Cognitive function was assessed using the novel object recognition test,and hippocampal Aβ deposition was detected by immunofluorescence.DEPs were identified using TMT-based proteomics and subsequently analyzed via Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and protein-protein interaction(PPI)network analysis.Key DEPs were validated using parallel reaction monitoring(PRM)technology.Results The model group exhibited a significantly lower novel object recognition index(P<0.01)and significantly increased hippocampal Aβ deposition(P<0.01)compared to the control group.Proteomic analysis identified 183 DEPs(87 upregulated,96 downregulated).GO analysis revealed that DEPs were primarily enriched in processes such as amyloid-beta binding and ion transmembrane transport.KEGG analysis indicated significant enrichment in 42 pathways,including dopaminergic synapse,glutamatergic synapse,cholinergic synapse,and long-term potentiation.Ten core DEPs were identified from the PPI network,and PRM validation confirmed expression trends consistent with the TMT results.Conclusion Aβ1-42-induced AD involves the synergistic action of multiple targets,biological processes,and pathways.The activation of glutamatergic and dopaminergic synaptic signaling pathways,mediated by core DEPs(e.g.,Th、D1、VGLUT2、GluN2A、GluA1、GluA3、Shank1、DARPP-32、PKC-δ、PKC-α、PKA C-β、CaMKⅡα、PTK2B),likely represents a key molecular mechanism in this AD model,providing a basis for identifying potential therapeutic targets.

Near infrared spectroscopy(NIRS)analysis technology has become an important process analysis tool in industrial and agricultural production,and has been widely used for qualitative and quantitative analysis in the fields of tobacco,agriculture,and pharmaceuticals.To address issues such as poor generalization ability and low prediction accuracy in NIRS modeling,a two-dimensional convolutional neural network(2DCNN)quantitative analysis model based on competitive adaptive reweighted sampling(CARS)and Gramian angular difference field(GADF)(CARS-GADF-2DCNN)was proposed.CARS-GADF-2DCNN used the CARS method to select an optimal wavelength set from the full spectrum,then employed GADF to encode the selection results into two-dimensional images,and finally used 2DCNN for prediction analysis.The 2DCNN model consisted of convolutional layers,parallel convolution modules,flattening layer,and fully connected layers.Simulation experiments were conducted on three public near-infrared(NIR)spectral datasets encompassing soil,tablet,and grain datasets to evaluate the CARS-GADF-2DCNN model.The results demonstrated that,compared to the one-dimensional convolutional neural network(1DCNN),the GADF-2DCNN model achieved 16.74％,23.40％,and 7.13％improvement in prediction accuracy for the soil,tablet,and grain datasets,respectively.Compared to GADF-2DCNN,VCPA-GADF-2DCNN,and IRIV-GADF-2DCNN models,the CARS-GADF-2DCNN model further improved prediction accuracy.For the soil dataset,prediction accuracy improved by 39.00％,30.78％and 4.13％;for the tablet dataset,the improvements were 9.52％,6.94％and 2.56％;for the grain dataset,the improvements were 20.57％,9.85％and 15.66％.In conclusion,CARS-GADF-2DCNN effectively selected the optimal wavelength subset from near infrared spectra,and revealed the latent features between different wavelengths.CARS-GADF-2DCNN addresses the issues of high complexity in prediction models and low prediction accuracy in near infrared spectral modeling,and could be effectively applied to near infrared spectral prediction analysis of different substances.

This study analyzed the epidemiological characteristics and trends of respiratory syncytial virus (RSV) infections among inpatients with acute respiratory infections (ARI) in a children′s hospital in Shenzhen City inpatients from 2020 to 2023. From January 2020 to December 2023, multiple reverse transcription polymerase chain reaction (RT-PCR) combined with capillary electrophoresis fragment analysis technology was used to detect the nucleic acids of 12 respiratory pathogens, including RSV, in hospitalized children diagnosed with ARI. The patients were divided into six age groups: 0 to <6 months, 6 months to <1 year, 1 to <2 years, 2 to <5 years, 5 to <10 years, and 10 to <18 years. A total of 53 033 children were tested, including 6 830 RSV positive cases, with an overall positivity rate of 12.88%. The annual RSV positivity rates from 2020 to 2023 were 20.04%, 16.18%, 4.89%, and 13.33%, respectively, with statistically significant differences between the years ( χ2=1 185.994, P<0.001). The positive rate of RSV detection decreased with increasing age across all years (all P trend<0.05). From 2020 to 2023, the proportion of RSV-positive cases aged 2 to 5 years and older showed an increasing trend ( P trend<0.001 for all years). Compared to 2023, the median age of RSV-infected children was lower in 2020 ( Z=7.826, P<0.001) and 2021 ( Z=6.106, P<0.001). The proportion of severe infections requiring ICU admission did not change significantly across all years ( χ2=0.179, P=0.981). The RSV epidemic season in 2020 mainly occurred during 28-43 weeks, and in 2021, it spanned from 22-43 weeks. However, in 2022, the season was delayed until the 49th week and lasted for three weeks. In 2023, the seasonal epidemic appeared earlier, starting in the 14th week and lasting for 28 weeks. From 2020 to 2023, the rate of RSV co-infections with other pathogens (mycoplasma pneumoniae, human parainfluenza virus, human bocavirus, human coronavirus, human metapneumovirus, and influenza A) significantly increased (all P trend<0.01). In conclusion, the epidemiological characteristics of RSV infections in Shenzhen Children′s Hospital changed from 2020 to 2023. In 2022, there were only delayed, low-intensity and short-lived seasonal epidemics. However, in 2023, there was an earlier and prolonged epidemic, with increased infections in children aged 2 to 5 years and older and a rise in co-infections, while the proportion of severe infections requiring ICU admission remained unchanged.

Objective A scoping review of domestically and internationally published studies on finite element analysis(FEA)based on three-dimensional(3D)human body model in preventing pressure ulcer(PU)was conducted,aiming to provide new directions for improving the prevention strategies of pressure ulcer.Methods We conducted a systematic search in both Chinese and English medical databases,including PubMed,Embase,CINAHL,Web of Science,Cochrane Library,Sinomed,CNKI,Wanfang and VIP,and engineering database(Engineering Village Compen-dex).The search period was from the inception of each database to July 29,2024.The information was extracted,and the results were analyzed and standardized for reporting.Results A total of 30 studies were included.The general methods of FEA based on 3D human body model include establishing geometric model,meshing,defining material properties,loading and setting boundary conditions,and solving equations.According to the contents of studies,they could be categorized into 4 distinct application domains,including identification of risk groups(n=9),position management(n=9),preventive dressings(n=10)and supportive surfaces(n=7).Conclusion FEA based on 3D human body model provides a foundation to PU biomechanical mechanism research and a scientific basis to the supplement and optimization of clinical prevention.Future studies should integrate clinical problems with simulations and further optimize simulations techniques and protocols.