Background/Aims: Biliary tract cancer (BTC) frequently harbors KRAS mutations, which are associated with resistance to traditional treatment and a poor prognosis. Synthetic lethality (SL) strategy may provide other targets of KRAS. Therefore, we aim to identify and validate potential therapeutic targets of KRAS for the treatment of BTC via SL. Methods: The dependency (DepMap) projects were used to predict the synthetic lethal gene of KRAS. FDA-approved anticancer drug library was applied to screen potential drugs effective against KRAS-mutant BTC. Furthermore, the synthetic lethal effects or corresponding mechanisms of potential genes and drugs on BTC were investigated using KRAS-mutant and KRAS-wild type BTC cell lines, patient-derived xenografts (PDX), and KRAS oncogene-driven tumor models, as well as other KRAS-mutant cancer cell lines. Results: Initially, we discovered that the loss of GATA2 reduced the viability of KRAS-mutant but not KRAS-wild-type BTC. Subsequently, the drug library screened out disulfiram, which primarily exerts a synthetic lethal effect by inhibiting interleukin-1β (IL-1β) in KRAS-mutant BTC. Mechanistically, GATA2 specifically enhanced the transcription of IL-1β to promote NF-κB signaling in KRAS-mutant BTC. IL-1β inhibition phenocopied GATA2 deficiency, leading to reduced KRAS-mutant BTC viability. These synthetically lethal effects were confirmed using PDX, a KRAS oncogene-driven tumor model, as well as in other KRAS-mutant cancer cell lines. Conclusions In summary, these results indicate that inhibiting GATA2/IL1β could be a therapeutic strategy in KRAS-mutant BTC and potentially other cancers.

[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.

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 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.

Objectives:To investigate the application effect of a self-designed transpedicular intravertebral bone grafting device in percutaneous pedicle screw fixation for thoracolumbar fractures,and to evaluate its safety and the role in preventing the"shell"phenomenon.Methods:A retrospective analysis was performed on 49 patients with thoracolumbar fractures who underwent percutaneous pedicle screw fixation combined with intravertebral bone grafting at our hospital from January 2018 to January 2023.Among them,25 patients were treated with a self-designed transpedicular intavertebral bone grafting device[Self-designed device group:8 males,17 females,aged 48.0±9.7 years;Body mass index(BMI)21.6±2.7kg/m2;T11 3 cases,T12 9 cases,L17 cases,L2 6 cases;Thoracolumbar injury classification and severity(TLICS)score 4.3±0.5;AO classification:A3 18 cases,A4 7 cases].The other 24 patients were treated with a conventional technique bone grafting funnel(Conventional technique group:11 males,13 females,aged 48.2±10.7 years;Body mass index 21.4±2.7kg/m2;T11 6 cases,T12 6 cases,L1 8 cases,L2 4 cases;TLICS score 4.3±0.5;AO classification:A3 17 cases,A4 7 cases).There were no statistically significant differences between the two groups in age,gender ratio,body mass index,fracture level,AO classification,or TLICS score(P＞0.05).The total operativetime,graft implantation time,fluoroscopy frequency during bone grafting,intraoperative blood loss,hospital stay,and in-traoperative complications were compared between the two groups.Low back pain was assessed using visual analogue scale(VAS)score,lumbar function was evaluated using Oswestry disability index(ODI)and Japanese Orthopaedic Association(JOA)score preoperatively,at 3 months and 1 year postoperatively.The local kyphotic angle(LKA)and anterior vertebral height ratio(AVHR)were measured and compared preoperatively,immediately postoperatively,at 3 months and 1 year postoperatively.Immediate postoperative CT scan was performed to determine bone graft distribution,assess iatrogenic injuries to the pedicle or anterior vertebral wall,and iden-tify the"shell"phenomenon.Follow-up CT at 1 year postoperatively was performed to evaluate bony fusion and the outcomes of the"shell"phenomenon.Results:All the patients successfully completed the surgery and were followed up for over 12 months(17.0±3.1 months).The self-designed device group was significantly lower in fluoroscopy frequency during bone grafting(11.0±1.5 vs.13.5±1.7,P＜0.05)and longer in graft implan-tation time(15.0±1.7min vs.12.7±1.9min,P＜0.05)than the conventional technique group,but there was no significant difference in total operative time between the two groups(P＞0.05).In the conventional technique group,3 cases(12.5％)had pedicle injuries,9 cases(37.5％)had anterior vertebral wall injuries,and 12 cases(50.0％)had bone graft material leakage;In contrast,the self-designed device group had no pedicle or ante-rior wall injuries,and there were 4 cases(16％)of bone graft leakage.The difference in complication rates be-tween the two groups was statistically significant(P＜0.05).Both groups showed significant improvement in LKA and AVHR immediately postoperatively,at 3 months,and at 1 year compared to preoperative values(P＜0.05).VAS score,ODI,and JOA score also significantly improved at 3 months and 1 year postoperatively compared to preoperative scores(P＜0.05).The"shell"phenomenon occurred in 5 cases in the self-designed device group,with 1 case healed at the 1-year follow-up,which occurred in 8 cases in the conventional technique group,with 2 cases healed at 1 year,and the difference was no statistically significant(P＞0.05).Conclusions:The application of the self-designed minimally invasive transpedicular vertebral bone grafting device in percu-taneous pedicle screw fixation combined with vertebral bone grafting for thoracolumbar fractures can reduce intraoperative fluoroscopy frequency and complications,therefore to improve surgical safety.

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.

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.

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.

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.