Episodic memory, our ability to recall past experiences, is supported by structures in the medial temporal lobe (MTL) particularly the hippocampus, and its interactions with fronto-parietal brain regions. Understanding how these brain regions coordinate to encode, consolidate, and retrieve episodic memories remains a fundamental question in cognitive neuroscience. Non-invasive brain stimulation (NIBS) methods, especially transcranial magnetic stimulation (TMS), have advanced episodic memory research beyond traditional lesion studies and neuroimaging by enabling causal investigations through targeted magnetic stimulation to specific brain regions. This review begins by delineating the evolving understanding of episodic memory from both psychological and neurobiological perspectives and discusses the brain networks supporting episodic memory processes. Then, we review studies that employed TMS to modulate episodic memory, with the aim of identifying potential cortical regions that could be used as stimulation sites to modulate episodic memory networks. We conclude with the implications and prospects of using NIBS to understand episodic memory mechanisms.
Humans ; Memory, Episodic ; Transcranial Magnetic Stimulation/methods* ; Brain/physiology* ; Nerve Net/physiology* ; Mental Recall/physiology* ; Neural Pathways/physiology*

Objective:To analyze the epidemiological, etiological and genetic characteristics of influenza virus in Shandong Province during 2023-2024.Methods:The surveillance data of influenza-like illness (ILI) in sentinel hospitals in Shandong from 2023 to 2024 were collected and analyzed. The isolated influenza strains with hemagglutination titers ≥8 were selected for antigenicity analysis, drug susceptibility test, gene sequencing and evolutionary analysis.Results:From 2023 to 2024, the positive rate of influenza virus in Shandong was 8.51% (23 663/277 995), the highest positive rate was in the age group of 5-14 years (15.78%, 6 073/38 478), and the highest positive rate was in the 49 th week (35.86%, 2 264/6 313). Both antigenicity analysis and evolutionary analysis showed that the A(H1N1)pdm09 subtype and B(Victoria) strain had good matching effect and close evolutionary distance with the 2023-2024 surveillance year vaccine strain. The A(H3N2) subtype strain did not have a high matching effect with the 2023-2024 vaccine strain and had a long evolutionary distance, but had a close evolutionary distance with the 2024-2025 vaccine strain. Drug susceptibility test showed that oseltamivir sensitivity of influenza A(H1N1)pdm09 strain decreased greatly, and the amino acid site mutation of neuraminidase was H275Y. Conclusions:In the 2023-2024 surveillance year, the peak of influenza virus epidemic in Shandong was mainly occurred in winter and spring, and the age group of 5-14 years was the focus of prevention and control. The dominant strain was subtype A(H3N2), which had poor matching effect with the vaccine strain in the 2023-2024 surveillance year. One A(H1N1)pdm09 resistant strain was found in the drug resistance monitoring work. Follow-up prevention and control work should be strengthen the surveillance for the epidemiological characteristics, genetic variation and drug resistance of influenza viruses, timely understand the epidemic trend and mutation of influenza viruses, timely discover drug-resistant strains of influenza viruses, promote influenza vaccination, and improve of influenza prevention and control.

Objective:To analyze the respiratory virus infection status and epidemiological characteristics of influenza-like illness (ILI) cases in Shandong Province during the 2020 -2021 influenza surveillance year. Methods:According to the National Influenza Surveillance Plan (2017 version), throat swab samples of ILI cases were collected from 14 surveillance sentinel hospitals in Shandong Province. Nucleic acid was extracted from all samples. Real-time fluorescence quantitative PCR (RT-PCR) was utilized to detect six common viruses, including human metapneumovirus (HMPV), human parainfluenza virus (HPIV) types 1, 2 and 3, respiratory syncytial virus (RSV), and adenovirus (ADV). Subsequently, the obtained detection results were analyzed.Results:A total of 2 386 specimens were collected, with a detection rate of 24.22% (578). Six viruses were detected, with detection rates of 6.75% (162 cases) for HMPV, 5.87% (140 cases) for RSV, 3.56% (85 cases) for HPIV3, 3.14% (75 cases) for HPIV2, 2.98% (71 cases) for HPIV1, and 2.77% (66 cases) for ADV. There was no significant difference in detection rates between genders, but a notable variation among different age groups ( P<0.001). The highest detection rate was observed in individuals aged 0-4 years (31.94%), followed by those aged≥60 years (26.06%). The prevalence of six viruses showed a monthly variation, with the detection rate of HMPV being higher in December and HPIV1 being higher in February. HPIV2, HPIV3, RSV, and ADV had higher detection rates in November. The co-detection rate of multiple viruses was 0.80%, with RSV being the most common pathogen involved in co-detection, primarily in individuals aged 0-4 years. Conclusion:The detection of six multiple pathogens in ILI cases in Shandong Province is dominated by HMPV, RSV and HPIV3. The prevalence of respiratory viruses varies by age and time.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This study investigated the epidemic status of H3N2 influenza virus and the genetic evolution characteristics of hemagglutinin(HA)and neuraminidase(NA)of H3N2 subtype influenza viruses isolated in Shandong Province during 2023-2024,to understand their compatibility with vaccine strains and drug resistance status.A total of 25 H3N2 subtype influenza virus strains were randomly selected from the strains isolated by the influenza surveillance network laboratory.The HA and NA genes were sequenced with the vaccine strains recommended by the WHO as a reference.Monitoring of sensitivity to oseltamivir and zanamivir was conducted through neuraminidase inhibition experiments.The H3N2 influenza viruses in Shandong Province belonged to the 3C.2a1b.2a.2a.3a.1 clade.Nucleotide sequence analysis revealed that the HA1 and NA genes were closely related to the WHO-recommended vaccine strain A/Darwin/9/2021 for the current season,with homology rates of 97.8%-98.2%and 98.9%-99.3%,respectively.Amino acid sequence analysis indicated 22 amino acid sequence variations in the HA1 protein,and antigenic drift was detected in 8 strains.A glycosylation site was added at position 94 of the HA protein in all 25 strains.Variations occurred in the NA antigenic determinants of some strains.Neuraminidase inhibition experiments indicated that all tested influenza viruses were sensitive to oseltamivir and zanamivir.Some differences in HA and NA proteins were observed between the monitored strains and vaccine strains.Continued monitoring of the molecular evolution characteristics of influenza viruses is necessary to understand the risk of influenza outbreaks,and their effects on the effectiveness of influenza vaccines and therapeutic drugs.

Objective:To analyze the epidemiological, etiological and genetic characteristics of influenza virus in Shandong Province during 2023-2024.Methods:The surveillance data of influenza-like illness (ILI) in sentinel hospitals in Shandong from 2023 to 2024 were collected and analyzed. The isolated influenza strains with hemagglutination titers ≥8 were selected for antigenicity analysis, drug susceptibility test, gene sequencing and evolutionary analysis.Results:From 2023 to 2024, the positive rate of influenza virus in Shandong was 8.51% (23 663/277 995), the highest positive rate was in the age group of 5-14 years (15.78%, 6 073/38 478), and the highest positive rate was in the 49 th week (35.86%, 2 264/6 313). Both antigenicity analysis and evolutionary analysis showed that the A(H1N1)pdm09 subtype and B(Victoria) strain had good matching effect and close evolutionary distance with the 2023-2024 surveillance year vaccine strain. The A(H3N2) subtype strain did not have a high matching effect with the 2023-2024 vaccine strain and had a long evolutionary distance, but had a close evolutionary distance with the 2024-2025 vaccine strain. Drug susceptibility test showed that oseltamivir sensitivity of influenza A(H1N1)pdm09 strain decreased greatly, and the amino acid site mutation of neuraminidase was H275Y. Conclusions:In the 2023-2024 surveillance year, the peak of influenza virus epidemic in Shandong was mainly occurred in winter and spring, and the age group of 5-14 years was the focus of prevention and control. The dominant strain was subtype A(H3N2), which had poor matching effect with the vaccine strain in the 2023-2024 surveillance year. One A(H1N1)pdm09 resistant strain was found in the drug resistance monitoring work. Follow-up prevention and control work should be strengthen the surveillance for the epidemiological characteristics, genetic variation and drug resistance of influenza viruses, timely understand the epidemic trend and mutation of influenza viruses, timely discover drug-resistant strains of influenza viruses, promote influenza vaccination, and improve of influenza prevention and control.

This study investigated the epidemic status of H3N2 influenza virus and the genetic evolution characteristics of hemagglutinin(HA)and neuraminidase(NA)of H3N2 subtype influenza viruses isolated in Shandong Province during 2023-2024,to understand their compatibility with vaccine strains and drug resistance status.A total of 25 H3N2 subtype influenza virus strains were randomly selected from the strains isolated by the influenza surveillance network laboratory.The HA and NA genes were sequenced with the vaccine strains recommended by the WHO as a reference.Monitoring of sensitivity to oseltamivir and zanamivir was conducted through neuraminidase inhibition experiments.The H3N2 influenza viruses in Shandong Province belonged to the 3C.2a1b.2a.2a.3a.1 clade.Nucleotide sequence analysis revealed that the HA1 and NA genes were closely related to the WHO-recommended vaccine strain A/Darwin/9/2021 for the current season,with homology rates of 97.8%-98.2%and 98.9%-99.3%,respectively.Amino acid sequence analysis indicated 22 amino acid sequence variations in the HA1 protein,and antigenic drift was detected in 8 strains.A glycosylation site was added at position 94 of the HA protein in all 25 strains.Variations occurred in the NA antigenic determinants of some strains.Neuraminidase inhibition experiments indicated that all tested influenza viruses were sensitive to oseltamivir and zanamivir.Some differences in HA and NA proteins were observed between the monitored strains and vaccine strains.Continued monitoring of the molecular evolution characteristics of influenza viruses is necessary to understand the risk of influenza outbreaks,and their effects on the effectiveness of influenza vaccines and therapeutic drugs.

Objective:To analyze the respiratory virus infection status and epidemiological characteristics of influenza-like illness (ILI) cases in Shandong Province during the 2020 -2021 influenza surveillance year. Methods:According to the National Influenza Surveillance Plan (2017 version), throat swab samples of ILI cases were collected from 14 surveillance sentinel hospitals in Shandong Province. Nucleic acid was extracted from all samples. Real-time fluorescence quantitative PCR (RT-PCR) was utilized to detect six common viruses, including human metapneumovirus (HMPV), human parainfluenza virus (HPIV) types 1, 2 and 3, respiratory syncytial virus (RSV), and adenovirus (ADV). Subsequently, the obtained detection results were analyzed.Results:A total of 2 386 specimens were collected, with a detection rate of 24.22% (578). Six viruses were detected, with detection rates of 6.75% (162 cases) for HMPV, 5.87% (140 cases) for RSV, 3.56% (85 cases) for HPIV3, 3.14% (75 cases) for HPIV2, 2.98% (71 cases) for HPIV1, and 2.77% (66 cases) for ADV. There was no significant difference in detection rates between genders, but a notable variation among different age groups ( P<0.001). The highest detection rate was observed in individuals aged 0-4 years (31.94%), followed by those aged≥60 years (26.06%). The prevalence of six viruses showed a monthly variation, with the detection rate of HMPV being higher in December and HPIV1 being higher in February. HPIV2, HPIV3, RSV, and ADV had higher detection rates in November. The co-detection rate of multiple viruses was 0.80%, with RSV being the most common pathogen involved in co-detection, primarily in individuals aged 0-4 years. Conclusion:The detection of six multiple pathogens in ILI cases in Shandong Province is dominated by HMPV, RSV and HPIV3. The prevalence of respiratory viruses varies by age and time.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To characterize and analyze the genetic variation of hemagglutinin (HA) of influenza A (H1N1) pdm09 subtype virus in Shandong Province, and explore the genetic variation patterns for providing reference for influenza monitoring, epidemic prevention and control, and vaccine strain selection.Methods:HA gene sequences of the recommended strains of influenza vaccine from 2009 to 2024 and the representative strains of each branch were downloaded from the GISAID Influenza Data Platform, and were phylogenetically analyzed and characterized in terms of amino acid site variation with the HA gene sequences of 298 influenza A (H1N1) virus strains isolated from Shandong Province. A phylogenetic tree was constructed using the maximum likelihood (ML) method of the IQ-TREE online tool, and the amino acid site variants were viewed using MegAlign software. The potential glycosylation sites of the HA gene were predicted using the NetNGlyc 1.0 online software.Results:The HA gene homology of the 298 influenza A (H1N1) viruses isolated in Shandong Province ranged from 91.2% to 100.0%. The evolutionary branches were gradually distantly related over time, but the direction of evolution was roughly the same as that in other provinces. Amino acid mutations in the HA occurred every year and most were found in the antigenic determinants.Conclusions:The HA genes of influenza viruses isolated in Shandong Province from 2009 to 2024 are still in the process of continuous evolution, and continuous monitoring of the epidemiological trends and the evolutionary directions of influenza viruses is essential for early warning of influenza virus pandemics.