AIM:A strain was isolated and identified as the H3N8 subtype of the avian influenza virus from a sick chicken at a farm in Yangjiang,Guangdong Province,named A/chicken/Yangjiang/552/2023(abbreviated as YJ/552).The aim of this research is to determine its genetic evolution,biological properties and pathogenicity in hamsters.This study may provide a theoretical strategy for preventing and treating the H3N8 subtype avian influenza virus-induced epidemic.METHODS:A strain of H3N8 avian influenza virus from chickens was characterised by phylogenetic analy-sis,antigenic diversity,receptor-binding specificity,neuraminidase activity,replication,and transmission in hamsters and a systematic pathological analysis was conducted.RESULTS:This novel avian influenza virus was generated through complex recombination of Eurasian avian H3 genes,North American avian N8 genes and six internal genes of H9N2 sub-type AIV.The cleavage site of the outer protein,HA,was PEKQTR↓GLF,which is characteristic of the low pathogenic avian influenza virus.The HA gene of YJ/552 exhibited the highest nucleotide homology with A/China/ZMD-22-2/2022(H3N8)at 99.09%,while the NA gene showed the highest homology with A/chicken/Dongguan/879/2022(H3N8)at 99.01%.This strain preferentially binds to avian-type receptors and could bind to human-type receptors.This virus could effectively replicate in the trachea and lungs of inoculated and contact hamsters.CONCLUSION:YJ/552 is a recombi-nant H3N8 avian influenza virus replicated in the upper respiratory system and transmitted in hamsters.This study pro-vides data support for the early warning and prevention of H3 subtype avian influenza viruses.

Objective:To develop a deep learning-based artificial intelligence system for assessing image quality in early pregnancy ultrasound，and to evaluate its performance in anatomical structure identification and quality control.Methods:A retrospective study was conducted by collecting 17 910 static ultrasound images of 8 quality-control planes from fetuses at 11 to 13 +6 weeks of gestation who underwent routine first-trimester ultrasound examinations at the First Affiliated Hospital of Sun Yat-sen University from June 2018 to June 2024. The dataset was divided into a training set（12 536 images），a test set（3 582 images），and a validation set（1 792 images）in a 7∶2∶1 ratio to develop a prenatal-screening artificial intelligence system（PSAIS）and to evaluate its performance in the automatic recognition and quality control of standard planes during early pregnancy. The average precision and mean average precision（mAP）were used to measure the model's ability to recognize the anatomical structures on each plane. Intraclass correlation coefficient（ICC）and Kappa statistics were used to assess the consistency between PSAIS and expert-level sonographers in both plane image quality assessment and standardization. The efficiency of PSAIS was also compared to manual quality control. Results:In the test set，the mAP values for recognizing the anatomical structures of the 8 quality-control planes all exceeded 0.800. In the validation set，PSAIS demonstrated moderate to good agreement with two experts in image quality evaluation：the ICC ranged from 0.713 to 0.843 for one expert and 0.678 to 0.788 for the other，while the Kappa values ranged from 0.590 to 0.768 and 0.530 to 0.702，respectively. In terms of plane standardization scoring，PSAIS showed particularly high agreement with expert ratings on the transventricular view（compliance rate 94.6%，Kappa=0.860）and the four-chamber cardiac view with blood flow（compliance rate 94.1%，Kappa=0.778），with agreement above 70% for the remaining planes. Compared with manual quality-control，PSAIS significantly increased processing speed：the total processing time was only 413 seconds，markedly less than the 77 008 seconds and 94 918 seconds required for manual QC（ P<0.001）. Conclusions:The PSAIS system performs well in recognizing and controlling the quality of standard ultrasound planes in early pregnancy，demonstrating high consistency with expert evaluations and significantly improved processing efficiency. It has potential application value in enhancing the quality and efficiency of early pregnancy screening.

Objective:To investigate the incidence, clinical characteristics, and impact of spontaneous portosystemic shunt (SPSS) in patients with liver cirrhosis combined with hepatic encephalopathy (HE).Methods:The basic clinical and follow-up data were retrospectively analyzed for patients diagnosed with cirrhosis combined with HE at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2017 to December 2022. The patients were divided into large and small SPSS groups and a control group based on the results of abdominal enhanced CT or MRI.The clinical characteristics and outcome differences were compared among the three groups. Kaplan-Meier survival curves were used to compare HE-free survival time and overall survival time among the three groups. The log-rank test was used to compare the differences between groups. Cox regression analysis was used to identify the relevant risk factors affecting HE-free survival time and overall survival time.Results:A total of 223 cases with liver cirrhosis combined with HE were enrolled, including 150 in the SPSS and 73 in the control groups. The incidence rate of SPSS was 67.3% (150/223). The group was divided into small SPSS (79/150, 52.7%) and large SPSS group (71/150, 47.3%) according to the cross-sectional area of the diversion channel. The HE-free survival was shorter in the small and large SPSS groups compared with the control group (35.5 months in the small SPSS group and 21.3 months in the large SPSS group; P<0.001). The HE-free survival time was shorter in the large SPSS than with small SPSS group ( P=0.003). The overall survival time in the small SPSS group and the large SPSS group was shorter compared with the control group (small SPSS group: 39.4 months, large SPSS group: 52.9 months; P<0.001). There was no statistically significant difference in overall survival time between the small SPSS and large SPSS groups ( P=0.700). Cox regression analysis showed that SPSS was an independent risk factor affecting patients' HE-free survival time and overall survival time ( P<0.05). Conclusion:SPSS is more common in patients with liver cirrhosis combined with HE. Patients who combined with SPSS showed significant reductions in both HE-free survival time and overall survival time, especially evident in those with combined large SPSS.

AIM:A strain was isolated and identified as the H3N8 subtype of the avian influenza virus from a sick chicken at a farm in Yangjiang,Guangdong Province,named A/chicken/Yangjiang/552/2023(abbreviated as YJ/552).The aim of this research is to determine its genetic evolution,biological properties and pathogenicity in hamsters.This study may provide a theoretical strategy for preventing and treating the H3N8 subtype avian influenza virus-induced epidemic.METHODS:A strain of H3N8 avian influenza virus from chickens was characterised by phylogenetic analy-sis,antigenic diversity,receptor-binding specificity,neuraminidase activity,replication,and transmission in hamsters and a systematic pathological analysis was conducted.RESULTS:This novel avian influenza virus was generated through complex recombination of Eurasian avian H3 genes,North American avian N8 genes and six internal genes of H9N2 sub-type AIV.The cleavage site of the outer protein,HA,was PEKQTR↓GLF,which is characteristic of the low pathogenic avian influenza virus.The HA gene of YJ/552 exhibited the highest nucleotide homology with A/China/ZMD-22-2/2022(H3N8)at 99.09%,while the NA gene showed the highest homology with A/chicken/Dongguan/879/2022(H3N8)at 99.01%.This strain preferentially binds to avian-type receptors and could bind to human-type receptors.This virus could effectively replicate in the trachea and lungs of inoculated and contact hamsters.CONCLUSION:YJ/552 is a recombi-nant H3N8 avian influenza virus replicated in the upper respiratory system and transmitted in hamsters.This study pro-vides data support for the early warning and prevention of H3 subtype avian influenza viruses.

Objective:To develop a deep learning-based artificial intelligence system for assessing image quality in early pregnancy ultrasound，and to evaluate its performance in anatomical structure identification and quality control.Methods:A retrospective study was conducted by collecting 17 910 static ultrasound images of 8 quality-control planes from fetuses at 11 to 13 +6 weeks of gestation who underwent routine first-trimester ultrasound examinations at the First Affiliated Hospital of Sun Yat-sen University from June 2018 to June 2024. The dataset was divided into a training set（12 536 images），a test set（3 582 images），and a validation set（1 792 images）in a 7∶2∶1 ratio to develop a prenatal-screening artificial intelligence system（PSAIS）and to evaluate its performance in the automatic recognition and quality control of standard planes during early pregnancy. The average precision and mean average precision（mAP）were used to measure the model's ability to recognize the anatomical structures on each plane. Intraclass correlation coefficient（ICC）and Kappa statistics were used to assess the consistency between PSAIS and expert-level sonographers in both plane image quality assessment and standardization. The efficiency of PSAIS was also compared to manual quality control. Results:In the test set，the mAP values for recognizing the anatomical structures of the 8 quality-control planes all exceeded 0.800. In the validation set，PSAIS demonstrated moderate to good agreement with two experts in image quality evaluation：the ICC ranged from 0.713 to 0.843 for one expert and 0.678 to 0.788 for the other，while the Kappa values ranged from 0.590 to 0.768 and 0.530 to 0.702，respectively. In terms of plane standardization scoring，PSAIS showed particularly high agreement with expert ratings on the transventricular view（compliance rate 94.6%，Kappa=0.860）and the four-chamber cardiac view with blood flow（compliance rate 94.1%，Kappa=0.778），with agreement above 70% for the remaining planes. Compared with manual quality-control，PSAIS significantly increased processing speed：the total processing time was only 413 seconds，markedly less than the 77 008 seconds and 94 918 seconds required for manual QC（ P<0.001）. Conclusions:The PSAIS system performs well in recognizing and controlling the quality of standard ultrasound planes in early pregnancy，demonstrating high consistency with expert evaluations and significantly improved processing efficiency. It has potential application value in enhancing the quality and efficiency of early pregnancy screening.

Objective:To investigate the incidence, clinical characteristics, and impact of spontaneous portosystemic shunt (SPSS) in patients with liver cirrhosis combined with hepatic encephalopathy (HE).Methods:The basic clinical and follow-up data were retrospectively analyzed for patients diagnosed with cirrhosis combined with HE at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2017 to December 2022. The patients were divided into large and small SPSS groups and a control group based on the results of abdominal enhanced CT or MRI.The clinical characteristics and outcome differences were compared among the three groups. Kaplan-Meier survival curves were used to compare HE-free survival time and overall survival time among the three groups. The log-rank test was used to compare the differences between groups. Cox regression analysis was used to identify the relevant risk factors affecting HE-free survival time and overall survival time.Results:A total of 223 cases with liver cirrhosis combined with HE were enrolled, including 150 in the SPSS and 73 in the control groups. The incidence rate of SPSS was 67.3% (150/223). The group was divided into small SPSS (79/150, 52.7%) and large SPSS group (71/150, 47.3%) according to the cross-sectional area of the diversion channel. The HE-free survival was shorter in the small and large SPSS groups compared with the control group (35.5 months in the small SPSS group and 21.3 months in the large SPSS group; P<0.001). The HE-free survival time was shorter in the large SPSS than with small SPSS group ( P=0.003). The overall survival time in the small SPSS group and the large SPSS group was shorter compared with the control group (small SPSS group: 39.4 months, large SPSS group: 52.9 months; P<0.001). There was no statistically significant difference in overall survival time between the small SPSS and large SPSS groups ( P=0.700). Cox regression analysis showed that SPSS was an independent risk factor affecting patients' HE-free survival time and overall survival time ( P<0.05). Conclusion:SPSS is more common in patients with liver cirrhosis combined with HE. Patients who combined with SPSS showed significant reductions in both HE-free survival time and overall survival time, especially evident in those with combined large SPSS.

OBJECTIVE: To investigate the mechanism of nucleolin (NCL) involved in lymphoma proliferation by regulating thymidine kinase 1 (TK1). METHODS: Twenty-three patients with diffuse large B-cell lymphoma (DLBCL) were selected and divided into initial treatment group (14 cases) and relapsed/refractory group (9 cases). Serum TK1 and C23 protein in peripheral blood mononuclear cells were detected. Cell models of CA46-NCL-KD (CA46-NCL-knockdown) and CA46-NCL-KNC (CA46-NCL-knockdown negative control) were established by lentivirus vector mediated transfection in Burkitt lymphoma cell line CA46. The half maximal inhibitory concentration (IC₅₀) of CA46-NCL-KD, CA46-NCL-KNC, and CA46 to adriamycin were detected by cell proliferation assay (MTS). The expression of NCL mRNA and protein in CA46-NCL-KD and CA46-NCL-KNC cells were dectected by Q-PCR and Western blot, respectively. The cell cycle of CA46-NCL-KD, CA46-NCL-KNC, and CA46 cells were detected by flow cytometry. The expression of TK1 protein in CA46-NCL-KD and CA46-NCL-KNC cells was detected by an enhanced chemiluminescence (ECL) dot blot assay. RESULTS: The level of serum TK1 in the initial treatment group was 0.43(0-30-1.01) pmol/L, which was lower than 10.56(2.19-14.99) pmol/L in the relapsed/refractory group (P<0-01), and the relative expression level of NCL protein in peripheral blood was also significantly lower. The IC₅₀ of CA46-C23-KD cells to adriamycin was (0.147±0.02) μg/ml, which was significantly lower than (0.301±0.04) μg/ml of CA46-C23-KNC cells and (0.338±0.05) μg/ml of CA46 cells (P<0.05). Compared with CA46-NCL-KNC cells, the expression of NCL mRNA and protein, TK1 protein decreased in CA46-NCL-KD cells, and the proportion of S phase and G₂/M phase also decreased, while G0/G1 phase increased in cell cycle. CONCLUSION The increased expression of NCL in DLBCL and CA46 cells indicates low sensitivity to drug. NCL may participate in regulation of lymphoma proliferation by affecting TK1 expression, thereby affecting the drug sensitivity.
Humans ; Leukocytes, Mononuclear/metabolism* ; Apoptosis ; Cell Line, Tumor ; Lymphoma ; Thymidine Kinase/pharmacology* ; Doxorubicin/pharmacology* ; Cell Division ; RNA, Messenger/genetics*

OBJECTIVE: To analyze the influence of serum homocysteine (Hcy) levels to the prognosis of newly diagnosed multiple myeloma (MM) patients, and to explore related factors affecting the prognosis of the patients. METHODS: The clinical pathological data of 180 newly diagnosed MM patients treated in our hospital from March 2013 to February 2015 were collected, and the patients were divided into high and low Hcy groups based on the median Hcy. The survival curves of the patients in the two groups were drawn to compare the differences of the survival; univariate and multivariate survival analysis was used to observe the influence of serum cysteine to the prognosis of newly diagnosed MM patients; the clinicopathological data of the patients with high and low Hcy in the two groups was compared, Pearson test was used to further analyzes the relationship between Hcy and different factors, and explores the related factors of Hcy affecting the prognosis of the patients. RESULTS: The median survival times of patients in the high and low Hcy groups were 32 (5-59) and 41 (7-71) months, respectively. The 3-year survival rate of the patients in high Hcy group was significantly lower than those in low Hcy group, and the difference shows statistically significant (P<0.05). The results of univariate survival analysis showed that the OS of newly diagnosed MM patients whom with advanced age, high bone disease grade, high-level bone marrow plasma cell count, LDH, C-reactive protein, Cr, β CONCLUSION Serum Hcy level has a correlation trend with the survival of newly diagnosed MM, which is affected by factors such as Hb.
Bone Marrow Cells ; Homocysteine ; Humans ; Multiple Myeloma ; Prognosis ; Risk Factors

BACKGROUND: The basis of individualized treatment should be individualized mortality risk predictive information. The present study aimed to develop an online individual mortality risk predictive tool for acute-on-chronic liver failure (ACLF) patients based on a random survival forest (RSF) algorithm. METHODS: The current study retrospectively enrolled ACLF patients from the Department of Infectious Diseases of The First People's Hospital of Foshan, Shunde Hospital of Southern Medical University, and Jiangmen Central Hospital. Two hundred seventy-six consecutive ACLF patients were included in the present study as a model cohort (n = 276). Then the current study constructed a validation cohort by drawing patients from the model dataset based on the resampling method (n = 276). The RSF algorithm was used to develop an individual prognostic model for ACLF patients. The Brier score was used to evaluate the diagnostic accuracy of prognostic models. The weighted mean rank estimation method was used to compare the differences between the areas under the time-dependent ROC curves (AUROCs) of prognostic models. RESULTS: Multivariate Cox regression identified hepatic encephalopathy (HE), age, serum sodium level, acute kidney injury (AKI), red cell distribution width (RDW), and international normalization index (INR) as independent risk factors for ACLF patients. A simplified RSF model was developed based on these previous risk factors. The AUROCs for predicting 3-, 6-, and 12-month mortality were 0.916, 0.916, and 0.905 for the RSF model and 0.872, 0.866, and 0.848 for the Cox model in the model cohort, respectively. The Brier scores were 0.119, 0.119, and 0.128 for the RSF model and 0.138, 0.146, and 0.156 for the Cox model, respectively. The nonparametric comparison suggested that the RSF model was superior to the Cox model for predicting the prognosis of ACLF patients. CONCLUSIONS The current study developed a novel online individual mortality risk predictive tool that could predict individual mortality risk predictive curves for individual patients. Additionally, the current online individual mortality risk predictive tool could further provide predicted mortality percentages and 95% confidence intervals at user-defined time points.
Acute-On-Chronic Liver Failure ; Humans ; Prognosis ; Proportional Hazards Models ; ROC Curve ; Retrospective Studies

Objective: Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear. Methods: A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( Results: Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks. Conclusion Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.
Adult ; Aged ; COVID-19/virology* ; China/epidemiology* ; Comorbidity ; Female ; Humans ; Male ; Middle Aged ; Retrospective Studies ; Severity of Illness Index ; Treatment Outcome