ObjectiveThe exacerbating trend of global population aging poses profound socioeconomic and public health challenges, making the comprehensive elucidation of biological aging mechanisms and the discovery of effective anti-aging interventions an urgent priority in the life sciences. Based on our previous serum metabolomics findings that dimethylglycine, an intermediate metabolite of amino acid metabolism naturally present in the human body, was significantly enriched in the serum of longevity families, this study aimed to systematically investigate the anti-aging effects of dimethylglycine both in living organisms and in controlled laboratory environments, and to preliminarily elucidate its underlying molecular mechanisms. While existing literature indicates that dimethylglycine possesses antioxidant and immunomodulatory properties, its direct anti-aging efficacy and the specific molecular pathways through which it operates remain largely unexplored. MethodsTo comprehensively evaluate the anti-aging properties of dimethylglycine, we utilized replicative senescent human embryonic lung fibroblasts, specifically the WI-38 cell line, as an experimental model in a controlled laboratory environment. Cell viability and safety were thoroughly assessed using Cell Counting Kit-8 and lactate dehydrogenase release assays across various concentrations of dimethylglycine. The impact of dimethylglycine on cellular senescence phenotypes, oxidative stress, and proliferative capacity was evaluated via senescence-associated beta-galactosidase staining, reactive oxygen species fluorescence detection, and 5-ethynyl-2'-deoxyuridine incorporation assays. Furthermore, the molecular alterations of senescence-associated secretory phenotype factors and core senescence signaling pathways were quantified using quantitative reverse transcription polymerase chain reaction for the messenger RNA levels of interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1, and enzyme-linked immunosorbent assay for the measurement of p16 and p21 protein expression levels. For the living organism model, the wild-type nematode Caenorhabditis elegans was used to evaluate systemic physiological effects. We conducted a comprehensive lifespan analysis at 20°C, heat stress resistance survival assays at 35℃, senescence-associated beta-galactosidase staining, lipofuscin accumulation tracking, intracellular reactive oxygen species measurement, and Oil Red O staining to ascertain systemic lipid accumulation. Additionally, network pharmacology bioinformatics tools, including PharmMapper and STRING databases, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were utilized to predict target pathways, alongside highly detailed molecular docking simulations utilizing SwissDock and Protein-Ligand Interaction Profiler to examine interactions with the cytochrome P450 family 2 subfamily C member 9 protein. ResultsThe experimental outcomes robustly demonstrate the potent anti-aging capabilities of dimethylglycine. At the cellular level, toxicity analyses firmly confirmed that dimethylglycine is highly safe; continuous treatment with 50 mol/L and 70 mol/L of dimethylglycine for 5 d did not induce any cellular membrane damage or cytotoxicity, but rather actively promoted cellular proliferation. Utilizing the optimal standardized concentration of 50 mol/L, dimethylglycine treatment significantly ameliorated senescent phenotypic markers in human embryonic lung fibroblasts, which was evidenced by a drastic and highly significant reduction in the senescence-associated beta-galactosidase positive cell percentage (P<0.000 1) and intracellular reactive oxygen species levels (P<0.000 1), alongside a marked increase in the 5-ethynyl-2'-deoxyuridine-positive proliferation rate (P=0.003 5). On a molecular expression scale, dimethylglycine significantly downregulated the messenger RNA expression of multiple core senescence-associated secretory phenotype inflammatory factors, including interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1. Concurrently, it effectively suppressed the protein expression of critical cell cycle arrest markers, diminishing p16 protein levels by 57.3% (P=0.000 4) and p21 protein levels by 27.2% (P=0.000 7). In the nematode Caenorhabditis elegans animal model, dimethylglycine significantly extended the mean lifespan from 20.402 d to an impressive 23.066 d (P<0.000 1) and notably enhanced overall survival rates under severe heat stress environmental conditions (P=0.017). Furthermore, systemic dimethylglycine intervention significantly mitigated age-related physiological decline by decreasing bodily lipofuscin accumulation (P<0.000 1), significantly reducing senescence-associated beta-galactosidase activity, lowering systemic reactive oxygen species fluorescence (P=0.008), and effectively alleviating overall fat accumulation (P<0.000 1). Mechanistically, extensive network pharmacology and Kyoto Encyclopedia of Genes and Genomes analyses strongly revealed that the potential targets of dimethylglycine are significantly enriched in fundamental drug metabolism and oxidative stress response pathways. Precision molecular docking simulations conclusively demonstrated that dimethylglycine forms highly stable structural interactions with the cytochrome P450 family 2 subfamily C member 9 protein, specifically highlighting the definitive formation of 5 stable hydrogen bonds involving serine 365, leucine 366, and serine 429 residues, as well as two critical salt bridge formations with arginine 97 and histidine 368 residues. It is additionally predicted to interact favorably with glutathione S-transferase family proteins. ConclusionDimethylglycine exhibits a profoundly significant and multifaceted anti-aging activity at both the cellular and entire living animal levels. By powerfully alleviating oxidative stress, heavily suppressing the core p16 and p21-dependent cellular senescence signaling pathways, and substantially mitigating the detrimental senescence-associated secretory phenotype, dimethylglycine effectively delays fundamental cellular senescence processes and drastically extends whole-organism lifespan. The biological mechanisms driving these robust protective effects are highly likely closely associated with its direct stable interactions with crucial metabolic and detoxifying enzyme systems, such as cytochrome P450 family 2 subfamily C member 9 and glutathione S-transferase family proteins, thereby systemically improving metabolic dysregulation and restoring critical redox homeostasis. This comprehensive study provides highly solid experimental evidence supporting dimethylglycine as a highly potent and safe potential anti-aging intervention agent, while simultaneously offering a clear molecular mechanistic explanation for the previously documented high abundance of dimethylglycine observed within exceptionally long-lived human populations.

"Clinical microbiology testing technology" is one of the core courses of medical laboratory science (MLS). Clinical microbiology testing enables quick and accurate identification of pathogens causing infectious diseases and provides guidance to the rational use of medications, thereby playing a key role in the diagnosis and treatment of infectious diseases. To address the evolving needs for intelligent testing and to nurture proficient microbiology technologists with self-learning abilities and advanced critical thinking skills, this course has undergone a series of reforms, focusing on content structure, method diversification, and the establishment of a skill-based assessment system. After three years of exploration and practice, an online-offline hybrid teaching mode aimed at improving students' thinking skills was developed. This teaching mode enhanced students' learning and logical thinking abilities and strengthened their professional training, serving as a reference for the reform of MLS courses.

Objective:To apply mass spectrometry as well as bioinformatics techniques to analyze HBV peptides derived from Pol and X proteins presented by human immortalized B lymphocytes(BLCLs),and to screen for effective T-cell epitopes,which lays the foundation for the development of therapeutic vaccines.Methods:The group has constructed a genome-wide expression plasmid containing 1.2-fold HBVC2 isoforms and transfected it into BLCLs by electro-transfection,isolated and identified HBV peptides by LC-MS/MS,bioinformatically predicted peptide sequences in terms of sensitization,antigenicity,toxicity,HLA molecular affinity,and the ability of peptide HLA-class Ⅰ complex to bind to specific T cells,and retrieved reported sequences.Results:HBV peptides from lysates of five immortalized B cells(BLCLs-1 to BLCLs-5)carrying HBVC2 subtype-expressing recombinants were analyzed,and 141 peptides with sequence lengths of no less than 8 amino acid residues(≥8 aa)were successfully isolated and identified,of which 133 were derived from Pol,and 8 from X proteins.The 141 HBV peptides were analyzed for sensitization,antigenicity and toxicity,and 50 antigenic,non-toxic and sensitizing HBV peptides(47 from Pol and 3 from X protein)were screened for affinity analysis with HLA-class Ⅰ and Ⅱ molecules and for prediction of the binding ability of the peptide HLA-class Ⅰ complexes to specific T cells.Among these peptides,37 had affinity to the corresponding genotypes of HLA-class Ⅰ and Ⅱ molecules.Finally,we obtained 37 peptides with antigenic,nontoxic,and sensitizing properties with IC50<500 nmol/L to HLA-class Ⅰ and Ⅱ molecules,which have affinitied to the corresponding genotypes but have not been reported,and can be continued to be explored as potential epitopes.Finally,15 HBV peptide hotspot core regions were formed by intra-and inter-strain common,contained,overlapping or neighboring sequence analysis of 141 peptides,with 7 core region sequences with antigenic,nontoxic,and sensitizing properties restricted to the corresponding geno-types.Peptides with affinity IC50<500 nmol/L had an affinity core sequence overlap of no less than 8 amino acids,and can be priori-tized for candidate T cell epitopes for subsequent studies.Conclusion:Peptides derived from Pol and X proteins have been successfully isolated and identified,and potential T cell epitopes have been screened.

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To investigate the differences in hippocampal subfield volumes and structural covariance network between participants with subjective cognitive decline (SCD) and healthy individuals, and to analyze the correlations of the volumes of the different subfields and altered covariance brain regions with memory function.Methods:A total of 57 SCD individuals(SCD group) and 44 normal controls(NC group) participants were assessed for memory function using composite scores from the auditory verbal learning test (AVLT) and the Wechsler memory scale visual reproduction (VR) test from June 2022 to October 2023.T1-weighted structural magnetic resonance imaging (MRI) data were collected from all participants, and hippocampal subfields, cortical regions, and subcortical nuclei were segmented using FreeSurfer to measure the gray matter volume of each structure. A structural covariance network was constructed based on the correlation of gray matter volumes across regions. Statistical analysis was performed using R 4.3.1 software. Inter-group differences in hippocampal subfield volumes were compared using multivariate analysis of covariance. Differences in structural covariance connectivity between groups were assessed using Z-test, while network topology differences were compared through permutation testing. Finally, partial correlation analysis was used to examine correlation of the volumes of the differential hippocampal subfields and covariance brain regions with memory function. Results:The SCD group exhibited significantly lower years of education, AVLT-immediate score, AVLT-delayed score, VR-immediate score, VR-delayed score, and memory function Z-score compared to the NC group ( t=2.064, 3.888, 2.622, 3.222, 4.761, 5.184, all P<0.05). The volumes of the right subiculum((387.75±55.20)mm 3, (352.70±70.25)mm 3), left presubiculum((263.12±38.52)mm 3, (239.79±46.02)mm 3), left subiculum((388.12±49.34)mm 3, (351.74±67.30)mm 3) and left CA1((571.01±80.01)mm 3, (526.51±98.80)mm 3) in the SCD group were smaller than the corresponding volumes in NC group ( F=9.139, 8.039, 11.207, 7.266, all P<0.05, FDR correction). Differences in structural covariance connectivity were found between the SCD and NC groups in the following pairs: right CA1-right subiculum, right CA1-left subiculum, right CA3-left parasubiculum and right hippocampus-amygdala transition area-left subiculum ( Z=-3.848, -3.896, -3.597, -3.895, all P<0.05, FDR correction).Partial correlation analysis revealed that in the SCD group, the volume of the left subiculum ( r=0.359, P=0.007), left CA1 ( r=0.430, P=0.001), right entorhinal cortex ( r=0.296, P=0.029), right middle temporal gyrus ( r=0.361, P=0.007), right parahippocampal gyrus ( r=0.313, P=0.021)were positively correlated with the total memory function score. Conclusion:Hippocampal subfields atrophy, as well as alterations in structural covariance network, have been found in SCD individuals. Furthermore, the decline in memory function may be closely associated with atrophy in hippocampal subfields and structurally covariant regions.

Objective::To compare the analgesic effects of ibuprofen administered orally via two modes combined with a conventional, patient-controlled intravenous analgesia pump on maternal pain after cesarean section (CS).Methods::This prospective, randomized, controlled study enrolled females who underwent CS from August 2022 to August 2023 at Peking University First Hospital, Beijing, China. Participants were randomly assigned to either an as-needed ibuprofen group (300 mg orally upon request) or a scheduled ibuprofen group (300 mg every 12 hours for 48 hours). The primary outcomes assessed were postoperative pain levels using the Wong-Baker Faces Pain Scale-Revised and cumulative oxycodone consumption at multiple time points up to 48 hours post-delivery. Secondary outcomes included recovery parameters (time to first flatus, ambulation, and lactation initiation), patient satisfaction with pain control, and postpartum depression scores evaluated by the Edinburgh Postnatal Depression Scale on postoperative day 3. Normally distributed data analyzed with t-tests; non-normal data with Mann-Whitney U tests; categorical variables with chi-square or Fisher’s exact tests (SPSS 26.0, P < 0.05). Results::After excluding 61 non-eligible cases, 339 patients were included (171 as-needed vs. 168 scheduled). The scheduled group showed significantly better pain control at 12 hours (4.00 (2.00-5.50) vs. 4.00 (4.00-6.00), P < 0.001), 24 hours (4.00 (2.00-4.00) vs. 4.00 (2.00-6.00), P < 0.001), and 36 hours (2.00 (2.00-4.00) vs. 4.00 (2.00-4.00), P < 0.001), and 48 hours (2.00 (2.00-4.00) vs. 2.00 (2.00-4.00), P = 0.004) post-delivery and lower levels of oxycodone consumption at 36 hours (10.20 (8.20-13.35) vs. 11.00 (8.80-14.40), P = 0.042) and 48 hours (12.40 (10.40-15.95) vs. 13.80 (11.00-16.00), P = 0.020) postpartum compared with those in the as-needed group. Additionally, the time to the return of bowel movements was shorter in the scheduled group than in the as-needed group (23.50 (16.94, 31.47) vs. 27.00 (19.88, 35.97), P = 0.004). Differences in post-delivery ambulation, lactation initiation, satisfaction levels, and depression scores were not significantly different between the two groups. Conclusion::The results of this study promote the use of ibuprofen (scheduled oral administration) combined with a conventional, patient-controlled intravenous analgesia pump for achieving better post-CS pain control than an as-needed dosage regimen.Registration::Chinese Clinical Trial Registry, ChiCTR2400082474.

Objective:To develop a scale on hospice care perception and attitude in family members of critically ill patients, so as to provide a valid tool for measuring the cognition and attitude level of hospice care among family members of critically ill patients.Methods:During May 2022 to 2023, an initial pool of scale entries was formed through the literature analysis method and group discussion. The scale′s first draft was formed by applying the Delphi correspondence method and a small sample pre-survey. The developed scale was administered to 98 family members of critically ill patients in Shandong Provincial Hospital Affiliated to Shandong First Medical University to test the reliability and validity of scale.Results:The results of exploratory factor analysis extracted 5 explanatory factors with a cumulative contribution rate of 77.65%. The developed Hospice Care Perceptions and Attitudes of Families of Critically Ill Patients Scale had 19 items. The content validity of 0.922 and a Cronbach alpha coefficient of 0.816 showed good validity and reliability.Conclusions:The scale has sufficient reliability and can be used to assess cognitive and attitudinal levels of hospice care in family members of critically ill patients.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To investigate the differences in hippocampal subfield volumes and structural covariance network between participants with subjective cognitive decline (SCD) and healthy individuals, and to analyze the correlations of the volumes of the different subfields and altered covariance brain regions with memory function.Methods:A total of 57 SCD individuals(SCD group) and 44 normal controls(NC group) participants were assessed for memory function using composite scores from the auditory verbal learning test (AVLT) and the Wechsler memory scale visual reproduction (VR) test from June 2022 to October 2023.T1-weighted structural magnetic resonance imaging (MRI) data were collected from all participants, and hippocampal subfields, cortical regions, and subcortical nuclei were segmented using FreeSurfer to measure the gray matter volume of each structure. A structural covariance network was constructed based on the correlation of gray matter volumes across regions. Statistical analysis was performed using R 4.3.1 software. Inter-group differences in hippocampal subfield volumes were compared using multivariate analysis of covariance. Differences in structural covariance connectivity between groups were assessed using Z-test, while network topology differences were compared through permutation testing. Finally, partial correlation analysis was used to examine correlation of the volumes of the differential hippocampal subfields and covariance brain regions with memory function. Results:The SCD group exhibited significantly lower years of education, AVLT-immediate score, AVLT-delayed score, VR-immediate score, VR-delayed score, and memory function Z-score compared to the NC group ( t=2.064, 3.888, 2.622, 3.222, 4.761, 5.184, all P<0.05). The volumes of the right subiculum((387.75±55.20)mm 3, (352.70±70.25)mm 3), left presubiculum((263.12±38.52)mm 3, (239.79±46.02)mm 3), left subiculum((388.12±49.34)mm 3, (351.74±67.30)mm 3) and left CA1((571.01±80.01)mm 3, (526.51±98.80)mm 3) in the SCD group were smaller than the corresponding volumes in NC group ( F=9.139, 8.039, 11.207, 7.266, all P<0.05, FDR correction). Differences in structural covariance connectivity were found between the SCD and NC groups in the following pairs: right CA1-right subiculum, right CA1-left subiculum, right CA3-left parasubiculum and right hippocampus-amygdala transition area-left subiculum ( Z=-3.848, -3.896, -3.597, -3.895, all P<0.05, FDR correction).Partial correlation analysis revealed that in the SCD group, the volume of the left subiculum ( r=0.359, P=0.007), left CA1 ( r=0.430, P=0.001), right entorhinal cortex ( r=0.296, P=0.029), right middle temporal gyrus ( r=0.361, P=0.007), right parahippocampal gyrus ( r=0.313, P=0.021)were positively correlated with the total memory function score. Conclusion:Hippocampal subfields atrophy, as well as alterations in structural covariance network, have been found in SCD individuals. Furthermore, the decline in memory function may be closely associated with atrophy in hippocampal subfields and structurally covariant regions.