Objective: To investigate the current status of iron metabolism among apheresis donors in Guangzhou and analyze the improvement effects of health education on iron deficiency in frequent apheresis donors. Methods: Using a generalized linear mixed model (GLMM), a 180-day follow-up was conducted on 261 eligible apheresis donors at the Guangzhou Blood Center from January to July 2024. Hemoglobin (Hb), serum ferritin (SF), unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), and transferrin saturation (TS) were selected as outcome variables. The effects of gender, age group, and number of donations within 180 days on these outcomes were analyzed and modeled. A general linear model (GLM) with repeated measures was applied to 55 donors who received health education interventions, comparing changes in Hb and iron metabolism-related indicators before and after follow-up and health education. Results: No significant difference in Hb levels was observed between first-time and regular apheresis donors, but SF levels were significantly higher in first-time donors (F=6.195, P<0.05). The GLMM revealed that female donors exhibited more significant reductions in Hb (T=-12.546) and SF (T=-5.829)(P<0.05 for both). Age group showed no interactive effects on Hb or SF changes. While number of donations within 180 days had no interactive effect on Hb, SF levels significantly decreased with increased number of donations (using ≥9 donations as the reference group; P<0.05 for all groups). After health education, Hb levels remained unchanged, but SF increased compared to pre-intervention levels (mean difference: -18.571, P<0.05), though a declining trend persisted compared to baseline (mean difference from baseline to post-intervention: 23.068,P<0.05). Conclusion: Female and number of donations are primary factors contributing to SF reduction in apheresis donors. Health education interventions promote SF recovery. Extending donation intervals and reinforcing iron deficiency-related health education may improve iron status in donors.

Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

Although symptomatic treatment is widely applied in clinical practice， it is often regarded as a relatively low-level therapeutic method. Based on Traditional Chinese Medicine （TCM） state theory， the macroscopic， mesoscopic， and microscopic characterization parameters of TCM symptomatology are horizontally integrated， the full life cycle of states （pre-disease， incipient disease， manifest disease， post-disease） is vertically covered， and the cognitive system of "symptoms" is reconstructed from multiple dimensions. Accordingly， the application approach of symptomatic treatment at different state stages is proposed： implementing preventive intervention in the pre-disease state， strengthening the interception of disease progression in the incipient disease state， regulating dynamic development and treatment in the manifest disease state， and formulating a staged diagnosis and treatment strategy which focuses on functional rehabilitation in the post-disease state.

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.

To develop vaccines for the prevention and control of porcine circovirus 2d genotype(PCV2d)and pseudorabies virus(PRV),the PCV2d ORF2 gene was amplified by PCR,and cloned into the BamH Ⅰ site of PRV transfer plasmid pG vector harboring the enhanced green fluorescent protein(EGFP)gene.The resulting recombinant transfer plasmid pG-PCV2d-EGFP was transfect-ed into ST cells infected with the three gene deleted PRV variant strain gE-/g-/TK-PRV NY to generate a recombinant virus rPRV-PCV2d-EGFP+,and then the EGFP gene was knocked out to harvest the rPRV-PCV2d using gene-editing technology termed CRISPR/Cas9 system.The recom-binant virus rPRV-PCV2d had similar genetic stability to the parental PRV as indicated by PCR and one-step growth curve test,and the expression of PCV2d capsid(Cap)protein was validated by Western blot.In animal experiment,higher PCV2-specific ELISA antibodies and detectable PCV2-specific neutralizing antibodies could be elicited in mice immunized with the recombinant vi-rus rPRV-PCV2d compared to commercial PCV2 inactivated vaccine.rPRV-PCV2d significantly re-duced the PCV2d loads in tissues such as the heart,liver and spleen of mice following virulent PCV2d challenge.Moreover,rPRV-PCV2d elicits PRV-specific immune responses in mice and can prevent PRV virulent infection in mice,indicating the recombinant virus rPRV-PCV2d has strong immunogenicity.

[Objective] To analyze the influencing factors of repeat blood donor lapsing using a zero-inflated poisson regression model (ZIP). [Methods] The blood donation behavior of 12 498 whole blood donors from 2020 was tracked until December 31, 2023. The factors influencing the frequency of blood donations in a given year was analyzed using ZIP, and donors with 0 blood donation in that year were considered to have lapsed. The changes in relevant influencing factors associated with each blood donation were measured and modeled for analysis. [Results] The zero-inflated part of ZIP showed that the risk of lapsing of male blood donors was 2.24 times that of female blood donors (OR 95% CI:1.864-2.696, P<0.001); the risk of lapsing of the 35-44 age group and over 45 age group was respectively 40% (OR 95% CI:0.455-0.790, P<0.001) and 61%(OR 95% CI:0.268-0.578, P<0.001) lower than that of the under 25 age group; the risk of lapsing for those who have donated blood twice and ≥3 times was respectively 50% (OR 95% CI:0.405-0.609, P<0.001) and 81% (OR 95% CI:0.154-0.225, P<0.001) lower than that of first-time donors; the risk of lapsing of those with junior high or high school education was 1.2 times that of those with a college degree or higher (OR 95% CI:1.033-1.384, P<0.05); the risk of lapsing for the divorced group was 2.02 times that of the married group (OR 95% CI:1.445-2.820, P<0.001); the risk of lapsing for those with an income (Yuan) of 10 000 to 50 000, 50 000 to 100 000 and more than 100 000 was respectively 0.67 (OR 95% CI:0.552-0.818, P<0.001), 0.72 (OR 95% CI:0.591-0.884, P=0.002) and 0.67 (OR 95% CI:0.535-0.834, P<0.001) times that of those with an income (Yuan) of less than 10 000. The results of the Poisson part are consistent with the results of the zero-inflated part in terms of age and education level. [Conclusion] Blood donor lapsing is overall related to factors such as gender, age, donation frequency, education, marital status and family income. It's essential to care for those blood donors prone to lapse to retain more regular blood donors.

Objective To establish a rat model of acclimatization to motion sickness(MS)induced by rotational stimulation.Methods To determine the stimulation conditions of MS,SD rats were divided into a static control group(SCG)and a single rotation stimulation group(SRG)before being subjected to the motion sickness index(MSI)measurement,open-field experiment and Morris water maze experiment after rotational stimulation to verify the feasibility of MS being induced in rats.Morris water maze experiments were performed to find out whether rotational stimulation could be used to induce MS in rats.During experiments on acclimatization,the SD rats were divided into the control group(Ctrl),one day of rotational stimulation group(Day1),three days of continuous rotational stimulation group(Day3),and seven days of continuous rotational stimulation group(Day7)before the changes in the MSI and behavior of these rats were recorded so as to explore the relationship between continuous stimulation and MS acclimatization in rats.Results After rotational stimulation,the rats showed a significant increase in the number of fecal pellets(P<0.0001)and in the MSI(P<0.0001)compared with the SCG.In the open field experiment,the rats showed a significant decrease in the spontaneous activity time(AT)(P<0.0001),total spontaneous activity distance(TD)(P<0.001)and distance moved by the center point per second(DMCPS)(P<0.001).The time taken to climb onto the platform(latency to find the platform,LP)(P<0.0001)and the total distance to the platform(distance to the platform,DP)(P<0.001)were significantly increased during the Morris water maze experiment.Acclimatization experiments revealed a significant increase in MSI and in the number of fecal pellets in the Day1 and Day3 groups of rotational stimulation compared to the Ctrl group(P<0.0001).AT(P<0.01),TD(P<0.05)and DMCPS(P<0.01)were significantly decreased,while LP and DP were significantly increased(P<0.0001),but there was no statistically significant difference in indices compared with the Day7 group(P>0.05).Conclusion Sinusoidal stimulation can induce MS in rats,and twice-a-day,continuous rotational stimulation for seven days can lead to acclimatization.The rat MS model can be assessed via behavioral experiments.

Real-time, noninvasive programmed death-ligand 1 (PD-L1) testing using molecular imaging has enhanced our understanding of the immune environments of neoplasms and has served as a guide for immunotherapy. However, the utilization of radiotracers in the imaging of human brain tumors using positron emission tomography/computed tomography (PET/CT) remains limited. This investigation involved the synthesis of [¹⁸F]AlF-NOTA-PCP2, which is a novel peptide-based radiolabeled tracer that targets PD-L1, and evaluated its imaging capabilities in orthotopic glioblastoma (GBM) models. Using this tracer, we could noninvasively monitor radiation-induced PD-L1 changes in GBM. [¹⁸F]AlF-NOTA-PCP2 exhibited high radiochemical purity (>95%) and stability up to 4 h after synthesis. It demonstrated specific, high-affinity binding to PD-L1 in vitro and in vivo, with a dissociation constant of 0.24 nM. PET/CT imaging, integrated with contrast-enhanced magnetic resonance imaging, revealed significant accumulation of [¹⁸F]AlF-NOTA-PCP2 in orthotopic tumors, correlating with blood-brain barrier disruption. After radiotherapy (15 Gy), [¹⁸F]AlF-NOTA-PCP2 uptake in tumors increased from 9.51% ± 0.73% to 12.04% ± 1.43%, indicating enhanced PD-L1 expression consistent with immunohistochemistry findings. Fractionated radiation (5 Gy × 3) further amplified PD-L1 upregulation (13.9% ± 1.54% ID/cc) compared with a single dose (11.48% ± 1.05% ID/cc). Taken together, [¹⁸F]AlF-NOTA-PCP2 may be a valuable tool for noninvasively monitoring PD-L1 expression in brain tumors after radiotherapy.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.