Spatial profiling of ovarian carcinoma and tumor microenvironment evolution under neoadjuvant chemotherapy.

PURPOSE: Immune tumor microenvironment (iTME) determines ovarian cancer development. This study investigates changes in HLA-I expression, CD8+/Foxp3 ratio, CD8+ cells and coregulators density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes. EXPERIMENTAL DESIGN: Multiplexed immune profiling and cell clustering analysis was performed on paired matched OC samples to characterize the iTME at diagnosis and under NACT from patients enrolled in the CHIVA trial (NCT01583322). RESULTS: Several immune cells (IC) subsets and immune coregulators were quantified pre-/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA-1+ enriched tumors were associated with -better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into 4 subsets: high Binf, enriched in B clusters; high Tinf, low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors segregated into 3 clusters: high BinfTinf, low Tinf and desert. The high BinfTinf, more diverse in IC composition encompassing T, B and NK cell, correlated with improved survival. PD-L1 was rarely expressed, while TIM-3, LAG- and IDO-1 were more prevalent. CONCLUSIONS: Several iTMEs exist during tumor evolution and NACT impact on iTME is heterogeneous. Clustering analysis of patients, unravels several IC subsets within OC and can guide future personalized approaches. Targeting different checkpoints such as TIM-3, LAG-3 and IDO-1, more prevalent than PD-L1, could more effectively harness anti-tumor immunity in this anti-PD-L1 resistant malignancy.

Dnmt3b ablation affects fracture repair process by regulating apoptosis.

PURPOSE: Previous studies have shown that DNA methyltransferase 3b (Dnmt3b) is the only Dnmt responsive to fracture repair and Dnmt3b ablation in Prx1-positive stem cells and chondrocyte cells both delayed fracture repair. Our study aims to explore the influence of Dnmt3b ablation in Gli1-positive stem cells in fracture healing mice and the underlying mechanism. METHODS: We generated Gli1-CreERT2; Dnmt3bflox/flox (Dnmt3bGli1ER) mice to operated tibia fracture. Fracture callus tissues of Dnmt3bGli1ER mice and control mice were collected and analyzed by X-ray, micro-CT, biomechanical testing, histopathology and TUNEL assay. RESULTS: The cartilaginous callus significantly decrease in ablation of Dnmt3b in Gli1-positive stem cells during fracture repair. The chondrogenic and osteogenic indicators (Sox9 and Runx2) in the fracture healing tissues in Dnmt3bGli1ER mice much less than control mice. Dnmt3bGli1ER mice led to delayed bone callus remodeling and decreased biomechanical properties of the newly formed bone during fracture repair. Both the expressions of Caspase-3 and Caspase-8 were upregulated in Dnmt3bGli1ER mice as well as the expressions of BCL-2. CONCLUSIONS: Our study provides an evidence that Dnmt3b ablation Gli1-positive stem cells can affect fracture healing and lead to poor fracture healing by regulating apoptosis to decrease chondrocyte hypertrophic maturation.

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions' correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.

Protective effects of Shensuitongzhi formula on intervertebral disc degeneration via downregulation of NF-κB signaling pathway and inflammatory response.

Low back pain (LBP) is a common orthopedic disease over the world. Lumbar intervertebral disc degeneration (IDD) is regarded as an important cause of LBP. Shensuitongzhi formula (SSTZF) is a drug used in clinical treatment for orthopedic diseases. It has been found that SSTZF can have a good treatment for IDD. But the exact mechanism has not been clarified. The results showed that SSTZF protects against LSI-induced degeneration of cartilage endplates and intervertebral discs. Meanwhile, SSTZF treatment dramatically reduces the expression of inflammatory factor as well as the expression of catabolism protein and upregulates the expression of anabolism protein in LSI-induced mice. In addition, SSTZF delayed the progression of LSI-induced IDD via downregulation the level of NF-κB signaling key gene RELA and phosphorylation of key protein P65 in endplate chondrocytes. Our study has illustrated the treatment as well as the latent mechanism of SSTZF in IDD.

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA.

Aucubin Alleviates Intervertebral Disc Degeneration by Repressing NF-κB-NLRP3 Inflammasome Activation in Endplate Chondrocytes.

Background: Intervertebral disc degeneration (IDD) is a prevalent degenerative disease and often recognized as the primary cause of lower back pain (LBP). Aucubin (Au) is a natural compound with anti-inflammatory properties in various diseases. The present study aimed to confirm the therapeutic effect of Au on IDD and explore its potential mechanism in vivo and in vitro. Methods: The process of IDD was simulated using the lumbar spine instability (LSI) model. In vivo, the therapeutic effect of Au on LSI-induced mice was evaluated by micro-CT and histomorphometry. Additionally, immunohistochemistry was applied to detect the cartilage metabolism and inflammasome activation in endplate. In vitro, the cytotoxicity of Au on ATDC5 cells was detected by Cell Counting Kit-8 (CCK-8), and the biological effects of Au were evaluated by Quantitative Real-time PCR (qRT-PCR) and Western blotting. Results: Micro-CT analysis showed that Au administration significantly alleviated LSI-induced disc volume narrowing and endplate cartilage degeneration, which was further supported by Alcian Blue Hematoxylin/Orange G (ABH/OG) staining. Immunohistochemistry results verified that Au could increase the expression of Col2α1 and Aggrecan, reduce the expression of Mmp-13, and attenuate the degradation of the endplate extracellular matrix (ECM). Mechanistically, we found that Au treatment, both in vivo and in vitro, significantly inhibited NF-κB-NLRP3 inflammasome activation in chondrocytes as determined by the decreased expression of p-P65, NLRP3, and Caspase-1. Discussion: Taken together, our findings have demonstrated for the first time that Au treatment ameliorated the degeneration of cartilage endplates in IDD may by inhibiting NF-κB-NLRP3 inflammasome activation in chondrocytes and provided a potential candidate for the treatment of IDD.

Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab-bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study.

BACKGROUND: Clinical benefits of atezolizumab plus bevacizumab (atezolizumab-bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and the development of biomarkers is needed to improve therapeutic strategies. The atezolizumab-bevacizumab response signature (ABRS), assessed by molecular biology profiling techniques, has been shown to be associated with progression-free survival after treatment initiation. The primary objective of our study was to develop an artificial intelligence (AI) model able to estimate ABRS expression directly from histological slides, and to evaluate if model predictions were associated with progression-free survival. METHODS: In this multicentre retrospective study, we developed a model (ABRS-prediction; ABRS-P), which was derived from the previously published clustering-constrained attention multiple instance learning (or CLAM) pipeline. We trained the model fit for regression analysis using a multicentre dataset from The Cancer Genome Atlas (patients treated by surgical resection, n=336). The ABRS-P model was externally validated on two independent series of samples from patients with hepatocellular carcinoma (a surgical resection series, n=225; and a biopsy series, n=157). The predictive value of the model was further tested in a series of biopsy samples from a multicentre cohort of patients with hepatocellular carcinoma treated with atezolizumab-bevacizumab (n=122). All samples in the study were from adults (aged ≥18 years). The validation sets were sampled between Jan 1, 2008, to Jan 1, 2023. For the multicentre validation set, the primary objective was to assess the association of high versus low ABRS-P values, defined relative to cross-validation median split thresholds in the first biopsy series, with progression-free survival after treatment initiation. Finally, we performed spatial transcriptomics and matched prediction heatmaps with in situ expression profiles. FINDINGS: Of the 840 patients sampled, 641 (76%) were male and 199 (24%) were female. Across the development and validation datasets, hepatocellular carcinoma risk factors included alcohol intake, hepatitis B and C virus infections, and non-alcoholic steatohepatitis. Using cross-validation in the development series, the mean Pearson's correlation between ABRS-P values and ABRS score (mean expression of ABRS genes) was r=0·62 (SD 0·09; mean p<0·0001, SD<0·0001). The ABRS-P generalised well on the external validation series (surgical resection series, r=0·60 [95% CI 0·51-0·68], p<0·0001; biopsy series, r=0·53 [0·40-0·63], p<0·0001). In the 122 patients treated with atezolizumab-bevacizumab, those with ABRS-P-high tumours (n=74) showed significantly longer median progression-free survival than those with ABRS-P-low tumours (n=48) after treatment initiation (12 months [95% CI 7-not reached] vs 7 months [4-9]; p=0·014). Spatial transcriptomics showed significantly higher ABRS score, along with upregulation of various other immune effectors, in tumour areas with high ABRS-P values versus areas with low ABRS-P values. INTERPRETATION: Our study indicates that AI applied on hepatocellular carcinoma digital slides is able to serve as a biomarker for progression-free survival in patients treated with atezolizumab-bevacizumab. This approach could be used in the development of inexpensive and fast biomarkers for targeted therapies. The combination of AI heatmaps with spatial transcriptomics provides insight on the molecular features associated with predictions. This methodology could be applied to other cancers or diseases and improve understanding of the biological mechanisms that drive responses to treatments. FUNDING: Institut National du Cancer, Fondation ARC, China Scholarship Council, Ligue Contre le Cancer du Val de Marne, Fondation de l'Avenir, Ipsen, and Fondation Bristol Myers Squibb Pour la Recherche en Immuno-Oncologie.

Amygdalin Delays Cartilage Endplate Degeneration and Improves Intervertebral Disc Degeneration by Inhibiting NF-κB Signaling Pathway and Inflammatory Response.

Background: Intervertebral disc degeneration (IDD) is a major cause of lower back pain (LBP), in which inflammatory is frequently involved. Amygdalin (AMD) is a naturally occurring compound that exerts anti-fibrotic, anti-inflammatory, analgesic, and immunomodulatory effects in various diseases. The purpose of this study was to investigate the therapeutic effects and molecular mechanisms of AMD on Lumbar spine instability (LSI)-induced IDD in mice. Methods: In this study, we first explored the effects of AMD in vivo, and then further explored the mechanism of its effects both in vivo and in vitro. Ten-week-old male C57BL/6J mice were administrated with AMD. At 10 weeks after LSI, spinal were collected for tissue analyses, including histology, micro-CT, and immunohistochemistry for Col2, Mmp-13, TNF-α, and p-P65. Additionally, we also evaluated the mRNA and protein expression level of p-P65 and p-IKBα after being treated with AMD in vitro. Results: Histological staining, micro-CT and immunohistochemical analysis showed that AMD treatment significantly inhibited the expression of TNF-α and Mmp-13, increased the expression of Col2 as well as attenuated the calcification of cartilage endplates, eventually to delayed the progression of IDD. Meanwhile, in vivo and in vitro fluorescence imaging revealed that AMD markedly inhibited the AMD significantly inhibited the LSI-induced increase in TNF-α expression and P65and IKBα phosphorylation. Discussion: Our findings suggest that AMD partly inhibits the activation of NF-κB signaling pathway to reduce the release of inflammatory mediators and delay the degeneration of cartilage endplate in IDD model mice. Therefore, AMD may be a potential candidate for the treatment of IDD.

Glucocorticoid-induced activation of NOX/ROS/NF-κB signaling in MSCs contributes to the development of GONFH.

BACKGROUND: This study aimed to investigate the pathogenic factors of glucocorticoids (GCs)-induced osteonecrosis of the femoral head (GONFH) and its underlying pathogenesis in vivo and in vitro. METHODS: Radiographical (µCT) scanning, histopathological, immunohistochemical, reactive oxygen species (ROS) and tunel staining were conducted on GONFH patients and rats. ROS, tunel, flow cytometry, alkaline phosphatase, Oil red O staining, reverse transcription­quantitative PCR and western blotting were applied to elucidate the exact pathogenesis mechanism. RESULTS: Clinical and animal studies demonstrated increased levels of ROS, aggravated oxidative stress (OS) microenvironment, augmented apoptosis and imbalance in osteogenic/lipogenic in the GONFH group compared to the control group. The fate of mesenchymal stem cells (MSCs) directed by GCs is a crucial factor in determining GONFH. In vitro studies further revealed that GCs promote excessive ROS production through the expression of NOX family proteins, leading to a deterioration of the OS microenvironment in MSCs, ultimately resulting in apoptosis and imbalance in osteogenic/lipogenic differentiation. Furthermore, our results confirmed that the NOX inhibitor-diphenyleneiodonium chloride and the NF-κB inhibitor-BAY 11-7082 ameliorated apoptosis and osteogenic/lipogenic differentiation imbalance of MSCs induced by an excess of GCs. CONCLUSION: We demonstrated for the first time that the aggravation of the OS microenvironment in MSCs caused by high doses of GCs leading to apoptosis and differentiation imbalance is a crucial factor in the pathogenesis of GONFH, mediated through activating the NOX/ROS/NF-κB signaling pathway.

Chondroprotective Mechanism of Eucommia ulmoides Oliv.-Glycyrrhiza uralensis Fisch. Couplet Medicines in Knee Osteoarthritis via Experimental Study and Network Pharmacology Analysis.

Background: Knee osteoarthritis (KOA) is the primary prevalent disabling joint disorder among osteoarthritis (OA), and there is no particularly effective treatment at the clinic. Traditional Chinese medicine (TCM) herbs, such as Eucommia ulmoides Oliv. and Glycyrrhiza uralensis Fisch. (E.G.) couplet medicines, have been reported to exhibit beneficial health effects on KOA, exact mechanism of E.G. nevertheless is not fully elucidated. Purpose: We assess the therapeutic effects of E.G. on KOA and explore its underlying molecular mechanism. Methods: UPLC-Q-TOF/MS technique was used to analyze the active chemical constituents of E.G. The destabilization of the medial meniscus model (DMM) was employed to evaluate the chondroprotective action of E.G. in KOA mice using histomorphometry, µCT, behavioral testing and immunohistochemical staining. Additionally, network pharmacology and molecular docking were used to predict potential targets for anti-KOA activities of E.G., which was further verified through in vitro experiments. Results: In vivo studies have shown that E.G. could significantly ameliorate DMM-induced KOA phenotypes including subchondral bone sclerosis, cartilage degradation, gait abnormality and thermal pain reaction sensibility. E.G. treatment could also promote extracellular matrix synthesis to protect articular chondrocytes, which was indicated by Col2 and Aggrecan expressions, as well as reducing matrix degradation by inhibiting MMP13 expression. Interestingly, network pharmacologic analysis showed that PPARG might be a therapeutic center. Further study proved that E.G.-containing serum (EGS) could up-regulate PPARG mRNA level in IL-1ß-induced chondrocytes. Notably, significant effects of EGS on the increment of anabolic gene expressions (Col2, Aggrecan) and the decrement of catabolic gene expressions (MMP13, Adamts5) in KOA chondrocytes were abolished due to the silence of PPARG. Conclusion: E.G. played a chondroprotective role in anti-KOA by inhibiting extracellular matrix degradation, which might be related to PPARG.

Glycyrrhizic acid alters the hyperoxidative stress-induced differentiation commitment of MSCs by activating the Wnt/ß-catenin pathway to prevent SONFH.

This study aimed to examine the in vivo and in vitro therapeutic effects of glycyrrhizic acid (GA) on steroid-induced osteonecrosis of the femoral head (SONFH), which is caused by the overuse of glucocorticoids (GCs). Clinically, we identified elevated oxidative stress (OS) levels and an imbalance in osteolipogenic homeostasis in SONFH patients compared to femoral neck fracture (FNF) patients. In vivo, we established experimental SONFH in rats via lipopolysaccharides (LPSs) combined with methylprednisolone (MPS). We showed that GA and Wnt agonist-S8320 alleviated SONFH, as evidenced by the reduced microstructural and histopathological alterations in the subchondral bone of the femoral head and the decreased levels of OS in rat models. In vitro, GA reduced dexamethasone (Dex)-induced excessive NOX4 and OS levels by activating the Wnt/ß-catenin pathway, thereby promoting the osteogenic differentiation of mesenchymal stem cells (MSCs) and inhibiting lipogenic differentiation. In addition, GA regulated the expression levels of the key transcription factors downstream of this pathway, Runx2 and PPARγ, thus maintaining osteolipogenic homeostasis. In summary, we demonstrated for the first time that GA modulates the osteolipogenic differentiation commitment of MSCs induced by excessive OS through activating the Wnt/ß-catenin pathway, thereby ameliorating SONFH.

Chemical profiling and identification of anti-osteoporosis chemical-markers of Cinnamomum cassia (L.) presl extracts using GC-MS and spectrum-activity analyses.

Cinnamomum cassia (L.) Presl (cinnamon), an important folk medicine is widely used to prevent osteoporosis for long time in China. Our study aimed to investigate the anti-osteoporosis activity and mechanisms of cinnamon extracts obtained by supercritical CO2 extraction (SFE) and identify activity associated chemical components by gas chromatography-mass spectrometry. The cinnamon SFE exhibited superior anti-osteoporosis efficacy in an ovariectomised mice model to common alcohol extracts. It could induce calcified nodules and ALP activity, upregulate the mRNA expression of ALP, BMP-2, and RUNX2 in MC3T3-E1 cells. The major chemical classes of cinnamon extracts were alcohol esters (28.2%), and terpenes (16.1%). The spectrum-activity analysis indicated that the potential chemical-markers of extracts could be (E)-Cinnamaldehyde, γ-Sitosterol, and (Z, Z)-9,12-Octadecadienoic acid, which could induce the proliferation and ALP activity in MC3T3-E1 cells. Our study revealed the promising applications of the cinnamon SFE in prevention of osteoporosis, and identified its anti-osteoporosis associated compounds.

An Intelligent Correlation Real-Time Analysis Method for the Mechanical Properties of Members in Super-Span Valve Hall Grid Structure Hoisting Process.

The mechanical performance analysis of the members is the primary basis for evaluating the hoisting quality and safety of the valve hall grid structure. Ordinarily, manual analysis of monitoring data and on-site experience inspection are employed to structural judgment, but it is challenging to evaluate the correlation of the various members and the overall safety of a valve hall. In this paper, an intelligent correlation real-time analysis method based on a BPNN (Back Propagation Neural Network) for the mechanical properties of members is proposed to intelligently control the safety of valve hall grid structure hoisting. The correlation between the mechanical properties of multi-points in the grid structure is used to model the target measuring points. In addition, an intelligent real-time analysis system is used to manage and apply the mechanical property correlation and abnormality of members in real-time. Then, the model is applied to a super-span valve hall in South China, and the application effect is good. The mechanical property correlation model can accurately reflect the mechanical state of the valve hall grid structure hoisting process. Simultaneously, it can effectively pinpoint hidden dangers and locate risk members. It provides a new reference for the normal operation and maintenance of a super-span valve hall grid.

18F-FDG PET as an imaging biomarker for the response to FGFR-targeted therapy of cancer cells via FGFR-initiated mTOR/HK2 axis.

Rationale: The overall clinical response to FGFR inhibitor (FGFRi) is far from satisfactory in cancer patients stratified by FGFR aberration, the current biomarker in clinical practice. A novel biomarker to evaluate the therapeutic response to FGFRi in a non-invasive and dynamic manner is thus greatly desired. Methods: Six FGFR-aberrant cancer cell lines were used, including four FGFRi-sensitive ones (NCI-H1581, NCI-H716, RT112 and Hep3B) and two FGFRi-resistant ones (primary for NCI-H2444 and acquired for NCI-H1581/AR). Cell viability and tumor xenograft growth analyses were performed to evaluate FGFRi sensitivities, accompanied by corresponding 18F-fluorodeoxyglucose (18F-FDG) uptake assay. mTOR/PLCγ/MEK-ERK signaling blockade by specific inhibitors or siRNAs was applied to determine the regulation mechanism. Results: FGFR inhibition decreased the in vitro accumulation of 18F-FDG only in four FGFRi-sensitive cell lines, but in neither of FGFRi-resistant ones. We then demonstrated that FGFRi-induced transcriptional downregulation of hexokinase 2 (HK2), a key factor of glucose metabolism and FDG trapping, via mTOR pathway leading to this decrease. Moreover, 18F-FDG PET imaging successfully differentiated the FGFRi-sensitive tumor xenografts from primary or acquired resistant ones by the tumor 18F-FDG accumulation change upon FGFRi treatment. Of note, both 18F-FDG tumor accumulation and HK2 expression could respond the administration/withdrawal of FGFRi in NCI-H1581 xenografts correspondingly. Conclusion: The novel association between the molecular mechanism (FGFR/mTOR/HK2 axis) and radiological phenotype (18F-FDG PET uptake) of FGFR-targeted therapy was demonstrated in multiple preclinical models. The adoption of 18F-FDG PET biomarker-based imaging strategy to assess response/resistance to FGFR inhibition may benefit treatment selection for cancer patients.

N-Butanol Extract of Modified You-Gui-Yin Attenuates Osteoclastogenesis and Ameliorates Osteoporosis by Inhibiting RANKL-Mediated NF-κB Signaling.

Postmenopausal Osteoporosis (PMOP) is the most prevalent primary osteoporosis, attributable to an imbalance in osteoblast and osteoclast activity. Modified You-Gui-Yin (MYGY), a traditional Chinese herbal formula, is able to effectively treat PMOP, while the critical components and pharmacological mechanisms of MYGY are still unclear. In this study, we aimed to investigate the therapeutic effects and underlying mechanisms of N-butanol extract of MYGY (MYGY-Nb) in ovariectomized (OVX)-induced osteoporosis mice. Histological staining and micro-computed tomography (µCT) analysis showed that MYGY-Nb was more effective in the suppression of OVX-induced bone loss than MYGY original formula. Subsequently, liquid chromatography and mass spectrometry analysis identified 16 critical compounds of MYGY-Nb and some of them are reported to affect osteoclast functions. Furthermore, in vivo and in vitro experiments demonstrated that MYGY-Nb significantly attenuated osteoclastogenesis by down-regulating RANKL-mediated NF-κB signaling. In conclusion, our study indicated that MYGY-Nb suppresses NF-κB signaling and osteoclast formation to mitigate bone loss in PMOP, implying that MYGY-Nb and its compounds are potential candidates for development of anti-PMOP drugs.

Case Report: First Documented Hip Arthroplasty on Chinese Patient with Ochronotic Arthropathy.

Alkaptonuria (AKU) is a rare autosomal recessive disorder caused by homogentisc acid (HGA) accumulation, the deposition of which in the joints usually causes ochronotic arthropathy. With no specific therapy for AKU currently, total joint arthroplasty in ochronotic arthropathy is applied to relieve the symptoms. A 63-year-old female patient came to our Orthopedic Surgery Department in 2019, complaining of severe limitation of movement and pain in the right hip for more than one year. A right total hip arthroplasy (THA) was performed due to the ineffective conservative therapy. At a follow-up of more than 15 months, the woman had full mobility with no complaining of pains. Since there is no relevant case reported about THA therapy for Chinese AKU patients, this report provides a feasible scheme, which makes clinical data more comprehensive.

Col9a2 gene deletion accelerates the degeneration of intervertebral discs.

As an essential component of the extracellular matrix (ECM) in cartilage, the α2 chain of type IX collagen (Col9a2), has been implicated in human intervertebral disc degeneration (IVDD). However, the precise role of the Col9a2 gene in the pathogenesis of IVDD has remained elusive. In the present study, the spines of Col9a2-deficient (Col9a2-/-) mice were systematically analyzed and compared with wild-type control mice using micro-CT (µCT), histomorphology, immunofluorescence, immunohistochemistry and reverse transcription-quantitative PCR (RT-qPCR). µCT analysis revealed that endplate (EP) osteochondral remodeling in the Col9a2-/- group was accompanied by a significant increase in EP porosity. Likewise, histopathological staining at 12 weeks revealed that the Col9a2-/- mice exhibited a marked early-stage IVDD phenotype, including EP sclerosis, calcification and annulus fibrosus rupture. The immunofluorescence results indicated that Col9a2 was extensively expressed in the IVDs, whereas it was barely detectable in Col9a2-/- mice. Immunohistochemical and RT-qPCR analyses demonstrated that the expression levels of Col2a1 and Aggrecan in the IVDs of Col9a2-/- mice were significantly decreased. In addition, the levels of Mmp13, ADAM metallopeptidase with thrombospondin type 1 motif 5, Col10a1 and Runx family transcription factor 2 were significantly elevated. These results suggested that deletion of the Col9a2 gene led to osteochondral remodeling of cartilage EP and suppressed ECM synthesis, accelerating matrix degradation and chondrocyte hypertrophy in the IVD tissue.

Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology.

BACKGROUND & AIMS: Patients with hepatocellular carcinoma (HCC) displaying overexpression of immune gene signatures are likely to be more sensitive to immunotherapy, however, the use of such signatures in clinical settings remains challenging. We thus aimed, using artificial intelligence (AI) on whole-slide digital histological images, to develop models able to predict the activation of 6 immune gene signatures. METHODS: AI models were trained and validated in 2 different series of patients with HCC treated by surgical resection. Gene expression was investigated using RNA sequencing or NanoString technology. Three deep learning approaches were investigated: patch-based, classic MIL and CLAM. Pathological reviewing of the most predictive tissue areas was performed for all gene signatures. RESULTS: The CLAM model showed the best overall performance in the discovery series. Its best-fold areas under the receiver operating characteristic curves (AUCs) for the prediction of tumors with upregulation of the immune gene signatures ranged from 0.78 to 0.91. The different models generalized well in the validation dataset with AUCs ranging from 0.81 to 0.92. Pathological analysis of highly predictive tissue areas showed enrichment in lymphocytes, plasma cells, and neutrophils. CONCLUSION: We have developed and validated AI-based pathology models able to predict the activation of several immune and inflammatory gene signatures. Our approach also provides insights into the morphological features that impact the model predictions. This proof-of-concept study shows that AI-based pathology could represent a novel type of biomarker that will ease the translation of our biological knowledge of HCC into clinical practice. LAY SUMMARY: Immune and inflammatory gene signatures may be associated with increased sensitivity to immunotherapy in patients with advanced hepatocellular carcinoma. In the present study, the use of artificial intelligence-based pathology enabled us to predict the activation of these signatures directly from histology.

A three-dimensional intelligent engineering management and control system for the construction of a long-span valve hall project based on a microservice architecture.

Three-dimensional intelligent engineering management and control systems (EMCS) based on the browser/server (B/S) model are an important part of intelligent engineering development. These systems are used for solving the difficulties encountered in engineering management with frequent cross-specialties and are vital tools for data exchange and service sharing among multiple departments. Currently, most engineering management and control systems are based on service-oriented architectures (SOAs). The integration mechanism and high coupling of SOAs leads to the reduction in system expansibility, service quality and service safety of the engineering system, making it difficult for these architectures to serve the construction of long-span valve hall engineering. To address these concerns, the management and application technology of the multidisciplinary data of valve hall engineering based on a microservice architecture (MSA) is proposed to improve the management efficiency of engineering data. A 3D integration modeling method for valve hall engineering structures and geological environments is proposed to establish the topological association between engineering structures and geological environments, without increasing the amount of model data required. A 3D intelligent engineering management and control technology for the entire process of the construction of long-span valve hall engineering is proposed, which realizes the entire process simulation and control of engineering construction based on WebGL technology. Accordingly, a three-dimensional intelligent engineering management and control system for the entire construction process of a long-span valve hall project in Southeast China is established, which can effectively manage and apply the data, display and analyze the three-dimensional model, and control and make decisions regarding the construction schedule. This study provides support for the construction of "smart engineering", promotes information communication and transmission between different project units, and speeds up the transformation from traditional construction management relying on drawings to three-dimensional intelligent construction management based on cloud services.