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 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.

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 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.

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.

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 develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.