OBJECTIVE: To investigate the clinical efficacy of lengthened proximal femoral nail antirotation (PFNA) and InterTan in the treatment of subtrochanteric femur fractures in the elderly. METHODS: A retrospective analysis was performed on the data of 65 elderly patients diagnosed with subtrochanteric femoral fractures who met the inclusion criteria between October 2016 and January 2022. The enrolled patients were categorized into two groups according to the type of internal fixation used: the lengthened proximal femoral nail antirotation(PFNA) group and the InterTan group. There were 32 patients in the PFNA group, comprising 20 males and 12 females, with ages ranging from 60 to 85 years old with an average of (69.3±6.7 ) years old. Among these patients, 15 patients resulted from traffic accidents and 17 patients were caused by falls. According to the Seinsheimer classification system, there were 11 patients as type Ⅱ, 14 patients as type Ⅲ, 6 patients as type Ⅳ, and 1 patient as type Ⅴ. The InterTan group comprised 33 patients, including 20 males and 13 females, aged from 60 to 85 years old with an average of (69.8±7.8 ) years old. Of these, 15 patients resulted from traffic accidents, while 18 patients were caused by falls. According to the Seinsheimer classification system, 10 patients as type Ⅱ, 15 patients as type Ⅲ, 7 patients as type Ⅳ, and 1 patient as type Ⅴ. The intraoperative blood loss, operative duration, and fracture healing time were recorded and compared between two groups. The quality of fracture reduction was assessed using Chang's criteria. Additionally, the Harris hip score was utilized to evaluate hip function in both groups at 3 months postoperatively and at the final follow-up. RESULTS: All patients were followed up for a period ranging from 10 to 20 months with an average of (14.6±4.5) months. No statistically significant differences were observed between two groups in terms of operation time, intraoperative blood loss, quality of fracture reduction, or reduction methods (P>0.05). Three months after the surgery, the Harris hip score in the InterTan group was 80.0(78.0, 83.5) points, which was significantly higher than that in the PFNA group, which recorded a score of 77.5(75.0, 81.8) points. This difference was statistically significant (P<0.05). At the final follow-up, the Harris hip score in the InterTan group was 80.0(76.5, 87.0), while that in the PFNA group was 78.0(74.3, 82.8). No statistically significant difference was observed between two groups (P>0.05). CONCLUSION The use of lengthened PFNA and InterTan in the treatment of elderly subtrochanteric femur fractures can both achieve good treatment results, with the advantages of simple operation, firm fixation, and low failure rate of internal fixation. The lengthened InterTan can achieve better hip function than PFNA.
Humans ; Male ; Female ; Aged ; Aged, 80 and over ; Bone Nails ; Retrospective Studies ; Hip Fractures/surgery* ; Middle Aged ; Fracture Fixation, Intramedullary/instrumentation* ; Fracture Fixation, Internal/methods* ; Femoral Fractures/surgery*

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Background and aims:Primary sclerosing cholangitis(PSC)is an autoimmune liver disease characterized by complex pathogenesis and limited available therapeutic options.The mechanisms underlying the development and progression of PSCs remain unclear.Liver X receptor beta(LXR-β)is recognized to modulate lipid metabolism and immune response,but its specific involvement in the PSC has not been elucidated.Here,we explored the role and mechanism of LXR-β in PSC induced by 3,5-diethoxycarbonyl-1,4-dihydro-2,4,6-collidine(DDC).Methods:CRISPR-Cas9 technology was applied to generate Abcb4(coding MDR2,next named as Mdr2),Nr1h2(coding LXR-β,next named as Lxrβ),and Rag2(coding RAG2)knockout mice.DDC was used to induce PSC.Hematoxylin and eosin and Sirius red staining were used to assess the extent of hepatic injury and fibrosis.Flow cytometry was used to observe immune cell subsets.Results:We observed a declining trend in hepatic Lxrβ in the PSC model.Unexpectedly,Lxrβ knockout failed to modulate DDC-induced PSC pathogenesis.Concomitantly,assessment of the influence of Rag2 deficiency on PSC progression revealed the absence of aggravated or alleviated hepatic injury or fibrosis in the Rag2-/-DDC mice.However,Lxrβ depletion intensified DDC-induced PSC in the Rag2-/-mice,with more abundant infiltrative inflammatory cells and more severe liver fibrosis.Compared with Rag2-/-DDC mice,Lxrβ-/-Rag2-/-DDC mice had higher serum ALT and AST levels and mRNA expression of proinflammatory and profibrotic genes.Flow cytometry showed that LXR-β deficiency resulted in a diminished population of hepatic innate immune cells.Conclusion:This study indicated innate immune cell LXR-β deficiency can exacerbate hepatic injury and fibrosis in murine models of PSC suggesting that LXR-β may regulate the function of innate immunity in the fibrotic advancement of PSC.

Objective:To examine the near-complete genomic analysis of norovirus (NoV) subtype GⅡ.17 [P17] outbreaks in Beijing Chaoyang District from 2014 to 2024.Methods:Data and specimens related to outbreaks of the NoV aggregation in Beijing′s Chaoyang District from 2014 to 2024 were collected. The NoV was identified using real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR). Specimens with positive nucleic acid were amplified by standard PCR, whole genome sequencing and evolutionary analysis. Amino acid site variations were compared.Results:In Chaoyang District, from 2014 to 2024, a total of 637 aggregated outbreaks caused by the NoV infection were reported, of which 584 were successfully typed. The epidemic caused by the GⅡ.17 [P17] subtype accounted for 8.79% (56/637), which was the dominant epidemic gene subtype in 2014-2015, sporadic in 2016-2019, reappeared in 2022, and significantly increased in 2024 (27.27%, 24/88). Outbreaks caused by the GⅡ.17 [P17] subtype occurred mainly from October to December, with the main sites of occurrence in primary schools and kindergartens. This study yielded 53 near-complete genome sequences of the GⅡ.17 [P17] subtype from 46 incidents in Chaoyang District. The GⅡ.17 [P17] subtype sequences of Chaoyang District from 2014 to 2024 were segmented into three subgroups on the evolutionary tree, with sequences from 2014 to 2019, 2022 to April 2024, and May to December 2024 clustered into the d, e, and b subgroups, respectively. In the VP1 region′s P2 area, particularly at the HBGA binding site, subgroups b and e exhibited mutations in 22 and two sites, while subgroups b and e showed mutations in four and one sites, predominantly in the RdRp region.Conclusion:The outbreak caused by the NoV GⅡ.17 [P17] subtype in Chaoyang District from 2014 to 2024 continues, with a significant increase in 2024, and it becomes the dominant gene subtype from October to December. The sequence formation of the NoV GⅡ.17 [P17] subtype in Chaoyang District from January to April 2022 and from May to December 2024 shows two different evolutions, with specific mutation sites, requiring continuous monitoring of the NoV GⅡ.17 [P17] subtype.

Objective:To examine the near-complete genomic analysis of norovirus (NoV) subtype GⅡ.17 [P17] outbreaks in Beijing Chaoyang District from 2014 to 2024.Methods:Data and specimens related to outbreaks of the NoV aggregation in Beijing′s Chaoyang District from 2014 to 2024 were collected. The NoV was identified using real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR). Specimens with positive nucleic acid were amplified by standard PCR, whole genome sequencing and evolutionary analysis. Amino acid site variations were compared.Results:In Chaoyang District, from 2014 to 2024, a total of 637 aggregated outbreaks caused by the NoV infection were reported, of which 584 were successfully typed. The epidemic caused by the GⅡ.17 [P17] subtype accounted for 8.79% (56/637), which was the dominant epidemic gene subtype in 2014-2015, sporadic in 2016-2019, reappeared in 2022, and significantly increased in 2024 (27.27%, 24/88). Outbreaks caused by the GⅡ.17 [P17] subtype occurred mainly from October to December, with the main sites of occurrence in primary schools and kindergartens. This study yielded 53 near-complete genome sequences of the GⅡ.17 [P17] subtype from 46 incidents in Chaoyang District. The GⅡ.17 [P17] subtype sequences of Chaoyang District from 2014 to 2024 were segmented into three subgroups on the evolutionary tree, with sequences from 2014 to 2019, 2022 to April 2024, and May to December 2024 clustered into the d, e, and b subgroups, respectively. In the VP1 region′s P2 area, particularly at the HBGA binding site, subgroups b and e exhibited mutations in 22 and two sites, while subgroups b and e showed mutations in four and one sites, predominantly in the RdRp region.Conclusion:The outbreak caused by the NoV GⅡ.17 [P17] subtype in Chaoyang District from 2014 to 2024 continues, with a significant increase in 2024, and it becomes the dominant gene subtype from October to December. The sequence formation of the NoV GⅡ.17 [P17] subtype in Chaoyang District from January to April 2022 and from May to December 2024 shows two different evolutions, with specific mutation sites, requiring continuous monitoring of the NoV GⅡ.17 [P17] subtype.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Objective To evaluate the ability of the ratio of peripheral blood white blood cell(WBC)counts to platelet counts to predict the onset of radiation-induced thymic lymphoma(TL)in a mouse model.Methods Mice were subjected to fractionated total-body irradiation(TBI)to established a TL model before the changes of the WBC-to-platelet ratio during the development and progression of TL were investigated.Four-week-old male C57BL/6J mice were randomized into the normal(non-irradiation)group and radiation exposure group that was subjected to 1.8 Gy TBI once weekly for four consecutive weeks.The survival and TL-incidence of those two groups were compared within 370 days of TBI.Histomorphology and hematoxylin & eosin(H&E)staining of the thymus were used for definite diagnosis of TL while flow cytometry was adopted to detect the frequency changes of T cells in the thymus,bone marrow and spleen.Peripheral blood(PB)cell counts were measured to analyze the changes of peripheral hemogram during TL pathogenesis.Results No mice in the normal group were diagnosed with TL while 83％of the irradiated mic suffered from TL within 370 days of fractionated TBI(P＜0.0001).Using histopathologic technology,medium-sized tumor cells were observed in the thymus of irradiated mice diagnosed with TL.Cytometric analysis showed decreased frequencies of CD4 mono-positive cells and increased frequencies of CD8 mono-positive cells in the thymus,bone marrow and spleen of mice diagnosed with TL.PB analysis displayed a significant increase in the WBC-to-platelet ratio one week prior to the TL-caused death in the irradiated mice(P＜0.01).Conclusion Elevation of the peripheral blood WBC-to-platelet ratio can help predict the onset of IR-induced TL of mice.

Objective:To investigate the clinical and genetic characteristics of a case of primary ciliary dyskinesia(PCD).Methods:We collected the clinical data on a case of PCD treated in the Department of Reproductive Medicine of Linyi People's Hospi-tal in July 2020,detected the genes of the patient by whole-exome sequencing(WES),verified the candidate mutations by Sanger se-quencing,and predicted the protein structure of the mutant gene by SWISS-MODEL.Results:The proband was found with the clini-cal phenotypes of chronic rhinitis,bronchiectasis,visceral transposition and male infertility.WES revealed a homozygous frameshift variation of c.12890dup(p.N4297Kfs*13)in exon 74 of the DNAH5 gene,which led to the premature termination of polypeptide chain synthesis and affected the gene function.SWISS-MODEL prediction showed that some of the amino acid residues were deleted af-ter mutation,resulting in a 3D conformational change of the protein.This variation was not recorded in the ClinVar,gnomAD and OMIM databases and,according to the relevant guidelines of the American College of Genetics and Genomics,was classified as a path-ogenic variation(PVS1+PM2_P+PM3_P).Conclusion:The homozygous variation of the DNAH5 gene c.12890dup(p.N4297Kfs*13)may be the cause of the clinical phenotype of this case of PCD,and the above findings have enriched the variation spectrum of the DNAH5 gene.

This study was aimed at understanding the Blastocystis,Enteroc ytozoon bieneusi,Cryptosporidium spp.,Gi-ardia duodenalis,and Pentatrichomonas hominis infection status in Chinese Milu deer(Elaphurus davidianus)in various prov-inces of China.A total of 81 fecal samples were collected from Beijing,Inner Mongolia,Hebei,and Hubei.PCR was used to detect the protozoans,and their subtypes and zoonoticity were determined through sequence and phylogenetic analyses.PCR re-sults indicated an infection prevalence of 40.74％,19.75％,and 8.64％for Blastocystis,E.bieneusi,and Cryptosporidium spp.,respectively,whereas G.duodenalis and P.hominis was not detected.Only one subtype of Cryptosporidium spp.(Cryptosporidium deer genotype)was detected.Four E.biene-usi genotypes were detected:HLJD-V,MWC-d1,BEB6,and CGC2.Five Blastocystis ST types were found:ST10,ST14,ST21,ST23,and ST25.Cryptosporidium spp.,E.bieneusi,and Blastocystis infections were prevalent,and zoonotic subtypes or genotypes of E.bieneusi and Blastocystis were i-dentified.The prevention and control of intestinal protozoa in Chinese Milu deer would support population health and is im-portant for public health.

This study was aimed at understanding the Blastocystis,Enteroc ytozoon bieneusi,Cryptosporidium spp.,Gi-ardia duodenalis,and Pentatrichomonas hominis infection status in Chinese Milu deer(Elaphurus davidianus)in various prov-inces of China.A total of 81 fecal samples were collected from Beijing,Inner Mongolia,Hebei,and Hubei.PCR was used to detect the protozoans,and their subtypes and zoonoticity were determined through sequence and phylogenetic analyses.PCR re-sults indicated an infection prevalence of 40.74％,19.75％,and 8.64％for Blastocystis,E.bieneusi,and Cryptosporidium spp.,respectively,whereas G.duodenalis and P.hominis was not detected.Only one subtype of Cryptosporidium spp.(Cryptosporidium deer genotype)was detected.Four E.biene-usi genotypes were detected:HLJD-V,MWC-d1,BEB6,and CGC2.Five Blastocystis ST types were found:ST10,ST14,ST21,ST23,and ST25.Cryptosporidium spp.,E.bieneusi,and Blastocystis infections were prevalent,and zoonotic subtypes or genotypes of E.bieneusi and Blastocystis were i-dentified.The prevention and control of intestinal protozoa in Chinese Milu deer would support population health and is im-portant for public health.