1.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
2.In situ Analytical Techniques for Membrane Protein Interactions
Zi-Yuan KANG ; Tong YU ; Chao LI ; Xue-Hua ZHANG ; Jun-Hui GUO ; Qi-Chang LI ; Jing-Xing GUO ; Hao XIE
Progress in Biochemistry and Biophysics 2025;52(5):1206-1218
Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
4.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
5.Potential utility of albumin-bilirubin and body mass index-based logistic model to predict survival outcome in non-small cell lung cancer with liver metastasis treated with immune checkpoint inhibitors.
Lianxi SONG ; Qinqin XU ; Ting ZHONG ; Wenhuan GUO ; Shaoding LIN ; Wenjuan JIANG ; Zhan WANG ; Li DENG ; Zhe HUANG ; Haoyue QIN ; Huan YAN ; Xing ZHANG ; Fan TONG ; Ruiguang ZHANG ; Zhaoyi LIU ; Lin ZHANG ; Xiaorong DONG ; Ting LI ; Chao FANG ; Xue CHEN ; Jun DENG ; Jing WANG ; Nong YANG ; Liang ZENG ; Yongchang ZHANG
Chinese Medical Journal 2025;138(4):478-480
6.Targeting WEE1: a rising therapeutic strategy for hematologic malignancies.
Hao-Bo LI ; Thekra KHUSHAFA ; Chao-Ying YANG ; Li-Ming ZHU ; Xing SUN ; Ling NIE ; Jing LIU
Acta Physiologica Sinica 2025;77(5):839-854
Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, are hazardous diseases characterized by the uncontrolled proliferation of cancer cells. Dysregulated cell cycle resulting from genetic and epigenetic abnormalities constitutes one of the central events. Importantly, cyclin-dependent kinases (CDKs), complexed with their functional partner cyclins, play dominating roles in cell cycle control. Yet, efforts in translating CDK inhibitors into clinical benefits have demonstrated disappointing outcomes. Recently, mounting evidence highlights the emerging significance of WEE1 G2 checkpoint kinase (WEE1) to modulate CDK activity, and correspondingly, a variety of therapeutic inhibitors have been developed to achieve clinical benefits. Thus, WEE1 may become a promising target to modulate the abnormal cell cycle. However, its function in hematologic diseases remains poorly elucidated. In this review, focusing on hematologic malignancies, we describe the biological structure of WEE1, emphasize the latest reported function of WEE1 in the carcinogenesis, progression, as well as prognosis, and finally summarize the therapeutic strategies by targeting WEE1.
Humans
;
Protein-Tyrosine Kinases/physiology*
;
Hematologic Neoplasms/drug therapy*
;
Cell Cycle Proteins/antagonists & inhibitors*
;
Nuclear Proteins/antagonists & inhibitors*
;
Cyclin-Dependent Kinases
;
Molecular Targeted Therapy
;
Animals
7.Effect of Chaihu Jia Longgu Muli Decoction on apoptosis in rats with heart failure after myocardial infarction through IκBα/NF-κB pathway.
Miao-Yu SONG ; Cui-Ling ZHU ; Yi-Zhuo LI ; Xing-Yuan LI ; Gang LIU ; Xiao-Hui LI ; Yan-Qin SUN ; Ming-Yuan DU ; Lei JIANG ; Chao-Chong YUE
China Journal of Chinese Materia Medica 2025;50(8):2184-2192
This study aims to explore the protective effect of Chaihu Jia Longgu Muli Decoction on rats with heart failure after myocardial infarction, and to clarify its possible mechanisms, providing a new basis for basic research on the mechanism of classic Chinese medicinal formula-mediated inflammatory response in preventing and treating heart failure induced by apoptosis after myocardial infarction. A heart failure model after myocardial infarction was established in rats by coronary artery ligation. The rats were divided into sham group, model group, and low, medium, and high-dose groups of Chaihu Jia Longgu Muli Decoction, with 10 rats in each group. The low-dose, medium-dose, and high-dose groups of Chaihu Jia Longgu Muli Decoction were given 6.3, 12.6, and 25.2 g·kg~(-1) doses by gavage, respectively. The sham group and model group were given an equal volume of distilled water by gavage once daily for four consecutive weeks. Cardiac function was assessed using color Doppler echocardiography. Myocardial pathology was detected by hematoxylin-eosin(HE) staining, apoptosis was measured by TUNEL assay, and mitophagy was observed by transmission electron microscopy. The levels of tumor necrosis factor-α(TNF-α), interleukin(IL)-1β, and N-terminal pro-B-type natriuretic peptide(NT-proBNP) in serum were detected by enzyme-linked immunosorbent assay(ELISA). The expression of apoptosis-related proteins B-cell lymphoma 2(Bcl-2), Bcl-2-associated X protein(Bax), and cleaved caspase-3 was detected by Western blot. Additionally, the expression of phosphorylated nuclear transcription factor-κB(NF-κB) p65(p-NF-κB p65)(upstream) and nuclear factor kappa B inhibitor alpha(IκBα)(downstream) in the NF-κB signaling pathway was assessed by Western blot. The results showed that compared with the sham group, left ventricular ejection fraction(LVEF) and left ventricular short axis shortening(LVFS) in the model group were significantly reduced, while left ventricular end diastolic diameter(LVEDD) and left ventricular end systolic diameter(LVESD) increased significantly. Myocardial tissue damage was severe, with widened intercellular spaces and disorganized cell arrangement. The apoptosis rate was increased, and mitochondria were enlarged with increased vacuoles. Levels of TNF-α, IL-1β, and NT-proBNP were elevated, indicating an obvious inflammatory response. The expression of pro-apoptotic factors Bax and cleaved caspase-3 increased, while the anti-apoptotic factor Bcl-2 decreased. The expression of p-NF-κB p65 was upregulated, and the expression of IκBα was downregulated. In contrast, the Chaihu Jia Longgu Muli Decoction groups showed significantly improved of LVEF, LVFS and decreased LVEDD, LVESD compared to the model group. Myocardial tissue damage was alleviated, and intercellular spaces were reduced. The apoptosis rate decreased, mitochondrial volume decreased, and the levels of TNF-α, IL-1β, and NT-proBNP were lower. The expression of pro-apoptotic factors Bax and cleaved caspase-3 decreased, while the expression of the anti-apoptotic factor Bcl-2 increased. Additionally, the expression of p-NF-κB p65 decreased, while IκBα expression increased. In summary, this experimental study shows that Chaihu Jia Longgu Muli Decoction can reduce the inflammatory response and apoptosis rate in rats with heart failure after myocardial infarction, which may be related to the regulation of the IκBα/NF-κB signaling pathway.
Animals
;
Apoptosis/drug effects*
;
Drugs, Chinese Herbal/administration & dosage*
;
Rats
;
Myocardial Infarction/physiopathology*
;
Male
;
NF-kappa B/genetics*
;
Heart Failure/etiology*
;
Rats, Sprague-Dawley
;
Signal Transduction/drug effects*
;
NF-KappaB Inhibitor alpha/genetics*
;
Humans
;
Tumor Necrosis Factor-alpha/genetics*
8.Studies on pharmacological effects and chemical components of different extracts from Bawei Chenxiang Pills.
Jia-Tong WANG ; Lu-Lu KANG ; Feng ZHOU ; Luo-Bu GESANG ; Ya-Na LIANG ; Guo-Dong YANG ; Xiao-Li GAO ; Hui-Chao WU ; Xing-Yun CHAI
China Journal of Chinese Materia Medica 2025;50(11):3035-3042
The medicinal materials of Bawei Chenxiang Pills(BCPs) were extracted via three methods: reflux extraction by water, reflux extraction by 70% ethanol, and extraction by pure water following reflux extraction by 70% ethanol, yielding three extracts of ST, CT, and CST. The efficacy of ST(760 mg·kg~(-1)), CT(620 mg·kg~(-1)), and CST(1 040 mg·kg~(-1)) were evaluated by acute myocardial ischemia(AMI) and p-chlorophenylalanine(PCPA)-induced insomnia in mice, respectively. Western blot was further utilized to investigate their hypnosis mechanisms. The main chemical components of different extracts were identified by the UPLC-Q-Exactive-MS technique. The results showed that CT and CST significantly increased the ejection fraction(EF) and fractional shortening(FS) of myocardial infarction mice, reduced left ventricular internal dimension at end-diastole(LVIDd) and left ventricular internal dimension at end-systole(LVIDs). In contrast, ST did not exhibit significant effects on these parameters. In the insomnia model, CT significantly reduced sleep latency and prolonged sleep duration, whereas ST only prolonged sleep duration without shortening sleep latency. CST showed no significant effects on either sleep latency or sleep duration. Additionally, both CT and ST upregulated glutamic acid decarboxylase 67(GAD67) protein expression in brain tissue. A total of 15 main chemical components were identified from CT, including 2-(2-phenylethyl) chromone and 6-methoxy-2-(2-phenylethyl) chromone. Six chemical components including chebulidic acid were identified from ST. The results suggested that chromones and terpenes were potential anti-myocardial ischemia drugs of BCPs, and tannin and phenolic acids were potential hypnosis drugs. This study enriches the pharmacological and chemical research of BCPs, providing a basis and reference for their secondary development, quality standard improvement, and clinical application.
Animals
;
Drugs, Chinese Herbal/isolation & purification*
;
Mice
;
Male
;
Sleep Initiation and Maintenance Disorders/physiopathology*
;
Humans
;
Myocardial Infarction/drug therapy*
;
Myocardial Ischemia/drug therapy*
9.Clinical application of three-dimensional printing technology combined with customized bone plate in the treatment of acetabulum fracture.
Yan-Chao ZANG ; Quan-Yong ZHAO ; Li YANG ; Jin-Zeng ZUO ; Wei QI ; Wei-Dong LIANG ; Jie XING
China Journal of Orthopaedics and Traumatology 2025;38(2):203-207
OBJECTIVE:
To explore the application value and clinical effect of 3D printing combined with customized bone plate in the treatment of acetabular fracture.
METHODS:
From June 2020 to June 2022, 11 patients with acetabular fractures underwent preoperative planning using 3D printing technology and were treated with customized bone plates including 8 males and 3 females, aged 25 to 66 years old. The fractures were classified according to Letournel-Judet:4 posterior wall fractures, 2 T-type fractures, 2 transverse posterior wall fractures, 2 double column fractures, and 1 anterior column with posterior semi-transverse fractures. The operative time, intraoperative blood loss, intraoperative fluoroscopy times, postoperative drainage volume, postoperative fracture healing time, and hip function score were recorded and analyzed.
RESULTS:
The operation time of 11 patients was 80 to 150 min, intraoperative blood volume was 150 to 700 ml, fluoroscopy frequency was 2 to 6, postoperative drainage flow was 60 to 195 ml, and the fracture healing time was 2.5 to 6.0 months. Fracture reduction was evaluated according to Matta score:anatomical reduction in 3 cases and satisfactory reduction in 8 cases. Eleven patients were followed up for 7 to 18 months. The hip Merle d'Aubigne function scores were excellent in 6 cases, good in 3 cases, fair in 1 case and poor in 1 case. Incision fat liquefaction occurred in 1 case and obturator nerve traction in 1 case.
CONCLUSION
The application of 3D printing technology combined with customized bone plates in the treatment of acetabular fracture is effective. In addition, the printed model can provide the operator with the results of the three-dimensional shape of the fracture, which is convenient for surgical reduction and effectively improves the efficiency of surgery.
Humans
;
Female
;
Male
;
Middle Aged
;
Acetabulum/surgery*
;
Printing, Three-Dimensional
;
Adult
;
Aged
;
Bone Plates
;
Fractures, Bone/surgery*
;
Fracture Fixation, Internal/methods*
10.Biomechanical study and clinical application of two osteotomy guide methods in media open wedge high tibial osteotomy operation.
Chao QI ; Xiao-Ming LI ; Dong-Hui GUO ; Qiu-Ling SHI ; Yun-Chao ZHAO ; Jun DONG ; Zheng-Xin MENG ; Xing-Yue WANG
China Journal of Orthopaedics and Traumatology 2025;38(7):698-704
OBJECTIVE:
To explore the effectiveness and feasibility of two osteotomy guides in medial open wedge high tibial osteotomy (MOWHTO).
METHODS:
Clinical data of 103 patients who underwent routine MOWHTO surgery between January 2020 and December 2022 were collected for retrospective analysis. The patients were divided into two groups based on the method of osteotomy guide plate. The control group of 51 patients received traditional osteotomy guide plate technique, including 17 males and 34 females, aged from 48 to 68 years old with an average of(57.93±4.82) years old, with a disease duration ranged from 1 to 8 years with an average of (4.89±1.49) years. The observation group of 52 patients received personalized osteotomy guide plate technique, including 23 males and 29 females, aged from 48 to 69 with an average of (58.22±5.10) years, with a disease duration ranged from 1 to 9 years with an average of(5.10±1.55) years. The perioperative indicators, complications, and knee joint recovery rate were statistically analyzed for both groups, as well as the preoperative and postoperative coagulation function, fibrinogen (FIB), D-dimer (D-D), gait parameters (step frequency, step length, step speed), biomechanical indicators, weight bearing line (WBL), medial proximal tibial angle (MPTA), joint line conergence angle (JLCA), and anterior cruciate ligament (ACL) function (body width, tibial anterior displacement).
RESULTS:
All patients were followed up for 6 months. The intraoperative blood loss, operation time, and number of fluoroscopic views in the observation group were (358.58±93.76) ml, (84.42±8.17) min, and (2.00±0.44) times, respectively, which were all less than those in the control group (465.55±105.38) ml, (96.53±10.51) min, and (6.31±0.58) times (P<0.05). Three days after surgery, the FIB and D-D levels in the observation group were (4.21±0.48) g·L-1 and (204.47±35.59) μg·L-1, respectively, which were both lower than those in the control group (5.56±0.57) g·L-1 and (311.12±42.23) μg·L-1 (P<0.05). Three months after surgery, the step frequency, step length, and step speed in the observation group were (1.89±0.23) steps·s-1, (0.57±0.15) m, and (0.99±0.11) m·s-1, respectively, which were all higher than those in the control group (1.80±0.18) steps·s-1, (0.50±0.14) m, and (0.95±0.09) m·s-1 (P<0.05). Three months after surgery, the WBL and MPTA in the observation group were (45.53±4.41)% and (87.03±8.15)°, respectively, which were both higher than those in the control group (38.38±4.36)% and (83.68±8.50)°, and the JLCA was (2.36±0.24)°, which was lower than that in the control group (2.61±0.33)° (P<0.05). The ACL body width during internal fixation removal was (5.60±0.51) mm, which was greater than that in the control group (5.08±0.56) mm, and the tibial migration was (5.70±0.42) mm, which was less than that in the control group (6.33±0.48) mm (P<0.05). There was no significant difference in the incidence of complications between the two groups (P>0.05). Six months after surgery, there was no significant difference in the recovery rate of knee joint between the two groups (P>0.05).
CONCLUSION
The application of personalized osteotomy guide technique in MOWHTO can help improve knee biomechanics and ACL function, and has less effect on coagulation function and no increase in complications.
Humans
;
Male
;
Female
;
Osteotomy/methods*
;
Middle Aged
;
Tibia/physiopathology*
;
Aged
;
Biomechanical Phenomena
;
Retrospective Studies
;
Osteoarthritis, Knee/physiopathology*

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