A hybrid quantum-classical classification model based on branching multi-scale entanglement renormalization ansatz.

Tensor networks are emerging architectures for implementing quantum classification models. The branching multi-scale entanglement renormalization ansatz (BMERA) is a tensor network known for its enhanced entanglement properties. This paper introduces a hybrid quantum-classical classification model based on BMERA and explores the correlation between circuit layout, expressiveness, and classification accuracy. Additionally, we present an autodifferentiation method for computing the cost function gradient, which serves as a viable option for other hybrid quantum-classical models. Through numerical experiments, we demonstrate the accuracy and robustness of our classification model in tasks such as image recognition and cluster excitation discrimination, offering a novel approach for designing quantum classification models.

Effect of Acupuncture on Neurogenic Claudication Among Patients With Degenerative Lumbar Spinal Stenosis : A Randomized Clinical Trial.

BACKGROUND: Acupuncture may improve degenerative lumbar spinal stenosis (DLSS), but evidence is insufficient. OBJECTIVE: To investigate the effect of acupuncture for DLSS. DESIGN: Multicenter randomized clinical trial. (ClinicalTrials.gov: NCT03784729). SETTING: 5 hospitals in China. PARTICIPANTS: Patients with DLSS and predominantly neurogenic claudication pain symptoms. INTERVENTION: 18 sessions of acupuncture or sham acupuncture (SA) over 6 weeks, with 24-week follow-up after treatment. MEASUREMENTS: The primary outcome was change from baseline in the modified Roland-Morris Disability Questionnaire ([RMDQ] score range, 0 to 24; minimal clinically important difference [MCID], 2 to 3). Secondary outcomes were the proportion of participants achieving minimal (30% reduction from baseline) and substantial (50% reduction from baseline) clinically meaningful improvement per the modified RMDQ. RESULTS: A total of 196 participants (98 in each group) were enrolled. The mean modified RMDQ score was 12.6 (95% CI, 11.8 to 13.4) in the acupuncture group and 12.7 (CI, 12.0 to 13.3) in the SA group at baseline, and decreased to 8.1 (CI, 7.1 to 9.1) and 9.5 (CI, 8.6 to 10.4) at 6 weeks, with an adjusted difference in mean change of -1.3 (CI, -2.6 to -0.03; P = 0.044), indicating a 43.3% greater improvement compared with SA. The between-group difference in the proportion of participants achieving minimal and substantial clinically meaningful improvement was 16.0% (CI, 1.6% to 30.4%) and 12.6% (CI, -1.0% to 26.2%) at 6 weeks. Three cases of treatment-related adverse events were reported in the acupuncture group, and 3 were reported in the SA group. All events were mild and transient. LIMITATION: The SA could produce physiologic effects. CONCLUSION: Acupuncture may relieve pain-specific disability among patients with DLSS and predominantly neurogenic claudication pain symptoms, although the difference with SA did not reach MCID. The effects may last 24 weeks after 6-week treatment. PRIMARY FUNDING SOURCE: 2019 National Administration of Traditional Chinese Medicine "Project of building evidence-based practice capacity for TCM-Project BEBPC-TCM" (NO. 2019XZZX-ZJ).

External fistula internalization - Endoscopic ultrasound guided stent implantation between stomach and fistula in the treatment of refractory pancreatic cutaneous fistula.

Pancreatic cutaneous fistula is a complex condition, making it challenging to achieve favorable outcomes with conservative medical treatment. Surgical interventions often entail surgical risks and postoperative complications. Here, we present a case involving endoscopically guided stent placement between the stomach and the fistula. By internalizing the fistula, patients can potentially remove the external drainage tube, offering a novel endoscopic treatment approach for such cases.

Complement factor I knockdown inhibits colon cancer development by affecting Wnt/ß-catenin/c-Myc signaling pathway and glycolysis.

BACKGROUND: Colon cancer (CC) occurrence and progression are considerably influenced by the tumor microenvironment. However, the exact underlying regulatory mechanisms remain unclear. AIM: To investigate immune infiltration-related differentially expressed genes (DEGs) in CC and specifically explored the role and potential molecular mechanisms of complement factor I (CFI). METHODS: Immune infiltration-associated DEGs were screened for CC using bioinformatics. Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines. Stable CFI-knockdown HT29 and HCT116 cell lines were constructed, and the diverse roles of CFI in vitro were assessed using CCK-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice. Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting. RESULTS: Six key immune infiltration-related DEGs were screened, among which the expression of CFI, complement factor B, lymphoid enhancer binding factor 1, and SRY-related high-mobility-group box 4 was upregulated, whereas that of fatty acid-binding protein 1, and bone morphogenic protein-2 was downregulated. Furthermore, CFI could be used as a diagnostic biomarker for CC. Functionally, CFI silencing inhibited CC cell proliferation, migration, invasion, and tumor growth. Mechanistically, CFI knockdown downregulated the expression of key glycolysis-related proteins (glucose transporter type 1, hexokinase 2, lactate dehydrogenase A, and pyruvate kinase M2) and the Wnt pathway-related proteins (ß-catenin and c-Myc). Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/ß-catenin/c-Myc pathway. CONCLUSION: The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/ß-catenin/c-Myc pathway, indicating that it could serve as a promising target for therapeutic intervention in CC.

Lomitapide repurposing for treatment of malignancies: A promising direction.

The development of novel drugs from basic science to clinical practice requires several years, much effort, and cost. Drug repurposing can promote the utilization of clinical drugs in cancer therapy. Recent studies have shown the potential effects of lomitapide on treating malignancies, which is currently used for the treatment of familial hypercholesterolemia. We systematically review possible functions and mechanisms of lomitapide as an anti-tumor compound, regarding the aspects of apoptosis, autophagy, and metabolism of tumor cells, to support repurposing lomitapide for the clinical treatment of tumors.

Temporal changes in plasma metabolic signatures to predict immune response of antiretroviral therapy among people living with HIV.

Antiretroviral therapy (ART) is an effective treatment for people living with HIV (PLHIVs), requiring an extended period to achieve immune reconstitution. Metabolic alterations induced by ART are crucial for predicting long-term therapeutic responses, yet comprehensive investigation through large-scale clinical studies is still lacking. Here, we collected plasma samples from 108 PLHIVs to the untargeted plasma metabolomics study, based on the longitudinal metabolomics design. Cross-sectional analyzes were performed at pre- and post-ART to explore the metabolic transformation induced by the therapy. Subsequently, delta values between pre- and post-ART measurements were calculated to quantify metabolic alterations. Then, the optimal set of metabolic traits and clinical signatures were further identified and applied to construct random forest model for predicting the future therapeutic responses to ART. We found distinct ART-induced metabolic transformation among PLHIVs. After confounder-adjustments, five metabolites exhibited significant associations with future immune response: tetracosatetraenoic acid (24:4n-6) (pre-ART) (odds ratio [OR]: 0.978, 95% confidence interval [CI]: 0.955~0.997), 1-(3,4-dihydroxyphenyl)-5-hydroxy-3-decanone (pre-ART) (OR: 1.298, 95% CI: 1.061~1.727), beta-PC-M6 (change) (OR: 0.967, 95% CI: 0.938~0.993), d-Galactaro-1,4-lactone (change) (OR: 1.032, 95% CI: 1.007~1.063), Annuionone C (change) (OR: 1.100, 95% CI: 1.030~1.190). The addition of plasma metabolites to clinical markers accurately predicted immune response to ART with an area under curve of 0.91. Notably, most disrupted metabolites were significantly correlated with blood lipids, suggesting that metabolic transformation might contribute to dyslipidemia among PLHIVs. This study highlights the distinct metabolic transformation post-ART among PLHIVs and reveals the potential role of metabolic transformation as key determinants of ART efficacy.

Correlation between type 2 diabetes mellitus remission and intrapancreatic fat deposition.

BACKGROUND: Intrapancreatic fat deposition (IPFD) exerts a significant negative impact on patients with type 2 diabetes mellitus (T2DM), accelerates disease deterioration, and may lead to impaired ß-cell quality and function. AIM: To investigate the correlation between T2DM remission and IPFD. METHODS: We enrolled 80 abdominally obese patients with T2DM admitted to our institution from January 2019 to October 2023, including 40 patients with weight loss-induced T2DM remission (research group) and 40 patients with short-term intensive insulin therapy-induced T2DM remission (control group). We comparatively analyzed improvements in IPFD [differential computed tomography (CT) values of the spleen and pancreas and average CT value of the pancreas]; levels of fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPBG), and insulin; and homeostasis model assessment of insulin resistance (HOMA-IR) scores. Correlation analysis was performed to explore the association between T2DM remission and IPFD. RESULTS: After treatment, the differential CT values of the spleen and pancreas, FBG, 2hPBG, and HOMA-IR in the research group were significantly lower than those before treatment and in the control group, and the average CT value of the pancreas and insulin levels were significantly higher. Correlation analysis revealed that the greater the T2DM remission, the lower the amount of IPFD. CONCLUSION: T2DM remission and IPFD are inversely correlated.

[Evaluation of a modified maxillary protraction appliance for the treatment of patients with skeletal Class â ¢ malocclusion associated with crowding].

PURPOSE: To investigate the efficacy of a modified maxillary protraction appliance in patients of skeletal Class Ⅲ with crowding. METHODS: Forty patients with skeletal Class Ⅲ malocclusion were divided into two groups, with 20 patients in each group. The experimental group had molar in a neutral or distal relationship and applied a modified maxillary protraction appliance, while the control group had molar mesial relationship and applied a conventional maxillary protraction appliance. Lateral cephalometric radiographs were taken before and after treatment in both groups for comparison. SPSS 22.0 software package was used for data analysis. RESULTS: The angle measurements taken before and after treatment showed a significant increase in SNA, ANB, SN-MP and U4-SN(P＜0.01), while SNB decreased(P＜0.01) in both groups. SN-OL changes were statistically different before and after treatment in the experimental group(P＜0.05). The sagittal measurements before and after treatment in both groups showed significant alterations in all(P＜0.05) but the length of the maxillary arch in both groups. For vertical measurements, U1-PP, L1-MP, U4-SN, U6-SN, and ANS-ME all increased (P＜0.05), while the changes of U4-PP and U6-PP in the two groups before and after treatment were statistically different(P＜0.05). Compared with the control group, the experimental group had a significantly increased maxillary arch length, a more remote location at U6, and a less variable molar relationship after treatment(P＜0.01). The two groups showed a variable amount of cephalometric measurements before and after treatment: the experimental group had a significant increase in maxillary arch length, a more remote position at U6, and a smaller change in molar relationship compared to the control group(P＜0.01). CONCLUSIONS: The modified maxillary protraction appliance showed good results for maxillary protraction and pushing the molar distally in patients with skeletal Class Ⅲ with crowding at neutral or distal molar relationship.

Advanced gene nanocarriers/scaffolds in nonviral-mediated delivery system for tissue regeneration and repair.

Tissue regeneration technology has been rapidly developed and widely applied in tissue engineering and repair. Compared with traditional approaches like surgical treatment, the rising gene therapy is able to have a durable effect on tissue regeneration, such as impaired bone regeneration, articular cartilage repair and cancer-resected tissue repair. Gene therapy can also facilitate the production of in situ therapeutic factors, thus minimizing the diffusion or loss of gene complexes and enabling spatiotemporally controlled release of gene products for tissue regeneration. Among different gene delivery vectors and supportive gene-activated matrices, advanced gene/drug nanocarriers attract exceptional attraction due to their tunable physiochemical properties, as well as excellent adaptive performance in gene therapy for tissue regeneration, such as bone, cartilage, blood vessel, nerve and cancer-resected tissue repair. This paper reviews the recent advances on nonviral-mediated gene delivery systems with an emphasis on the important role of advanced nanocarriers in gene therapy and tissue regeneration.

CKIP-1-Loaded Cartilage-Affinitive Nanoliposomes Reverse Osteoarthritis by Restoring Chondrocyte Homeostasis.

Osteoarthritis (OA) is a chronic joint disease characterized by cartilage imbalance and disruption of cartilage extracellular matrix secretion. Identifying key genes that regulate cartilage differentiation and developing effective therapeutic strategies to restore their expression is crucial. In a previous study, we observed a significant correlation between the expression of the gene encoding casein kinase-2 interacting protein-1 (CKIP-1) in the cartilage of OA patients and OA severity scores, suggesting its potential involvement in OA development. To test this hypothesis, we synthesized a chondrocyte affinity plasmid, liposomes CKIP-1, to enhance CKIP-1 expression in chondrocytes. Our results demonstrated that injection of CAP-Lipos-CKIP-1 plasmid significantly improved OA joint destruction and restored joint motor function by enhancing cartilage extracellular matrix (ECM) secretion. Histological and cytological analyses confirmed that CKIP-1 maintains altered the phosphorylation of the signal transduction molecule SMAD2/3 of the transforming growth factor-ß (TGF-ß) pathway by promoting the phosphorylation of the 8T, 416S sit. Taken together, this work highlights a novel approach for the precise modulation of chondrocyte phenotype from an inflammatory to a noninflammatory state for the treatment of OA and may be broadly applicable to patients suffering from other arthritic diseases.

Unexpected finding: a patient with choledocholithiasis found mass at the lower end of common bile duct.

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Extracellular Vesicles Derived from Neutrophils Accelerate Bone Regeneration by Promoting Osteogenic Differentiation of BMSCs.

The reconstruction of bone defects has been associated with severe challenges worldwide. Nowadays, bone marrow mesenchymal stem cell (BMSC)-based cell sheets have rendered this approach a promising way to facilitate osteogenic regeneration in vivo. Extracellular vesicles (EVs) play an essential role in intercellular communication and execution of various biological functions and are often employed as an ideal natural endogenous nanomedicine for restoring the structure and functions of damaged tissues. The perception of polymorphonuclear leukocytes (neutrophils, PMNs) as indiscriminate killer cells is gradually changing, with new evidence suggesting a role for these cells in tissue repair and regeneration, particularly in the context of bone healing. However, the role of EVs derived from PMNs (PMN-EVs) in bone regeneration remains largely unknown, with limited research being conducted on this aspect. In the current study, we investigated the effects of PMN-EVs on BMSCs and the underlying molecular mechanisms as well as the potential application of PMN-EVs in bone regeneration. Toward this end, BMSC-based cell sheets with integrated PMN-EVs (BS@PMN-EVs) were developed for bone defect regeneration. PMN-EVs were found to significantly enhance the proliferation and osteogenic differentiation of BMSCs in vitro. Furthermore, BS@PMN-EVs were found to significantly accelerate bone regeneration in vivo by enhancing the maturation of the newly formed bone in rat calvarial defects; this is likely attributable to the effect of PMN-EVs in promoting the expression of key osteogenic proteins such as SOD2 and GJA1 in BMSCs. In conclusion, our findings demonstrate the crucial role of PMN-EVs in promoting the osteogenic differentiation of BMSCs during bone regeneration. Furthermore, this study proposes a novel strategy for enhancing bone repair and regeneration via the integration of PMN-EVs with BMSC-based cell sheets.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma.

AIMS: To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance. METHODS: We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated. RESULTS: 147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy. CONCLUSION: The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Use of MRI Radiomics Models in Evaluating the Low HER2 Expression in Breast Cancer.

OBJECTIVE: To investigate the magnetic resonance imaging (MRI) radiomics models in evaluating the human epidermal growth factor receptor 2(HER2) expression in breast cancer.

Materials and Methods: The MRI data of 161 patients with invasive ductal carcinoma (non-special type) of breast cancer were retrospectively collected, and the MRI radiomics models were established based on the MRI imaging features of the fat suppression T2 weighted image (T2WI) sequence, dynamic contrast-enhanced (DCE)-T1WIsequence and joint sequences. The T-test and the least absolute shrinkage and selection operator (LASSO) algorithm were used for feature dimensionality reduction and screening, respectively, and the random forest (RF) algorithm was used to construct the classification model.

Results: The model established by the LASSO-RF algorithm was used in the ROC curve analysis. In predicting the low expression state of HER2 in breast cancer, the radiomics models of the fat suppression T2WI sequence, DCE-T1WI sequence, and the combination of the two sequences showed better predictive efficiency. In the receiver operating characteristic (ROC) curve analysis for the verification set of low, negative, and positive HER2 expression, the area under the ROC curve (AUC) value was 0.81, 0.72, and 0.62 for the DCE-T1WI sequence model, 0.79, 0.65 and 0.77 for the T2WI sequence model, and 0.84, 0.73 and 0.66 for the joint sequence model, respectively. The joint sequence model had the highest AUC value.

Conclusions: The MRI radiomics models can be used to effectively predict the HER2 expression in breast cancer and provide a non-invasive and early assistant method for clinicians to formulate individualized and accurate treatment plans.

The neural mechanism of communication between graduate students and advisers in different adviser-advisee relationships.

Communication is crucial in constructing the relationship between students and advisers, ultimately bridging interpersonal interactions. Only a few studies however explore the communication between postgraduate students and advisers. To fill the gaps in the empirical researches, this study uses functional near-infrared spectroscopy (FNIRS) techniques to explore the neurophysiology differences in brain activation of postgraduates with different adviser-advise relationships during simulated communication with their advisers. Results showed significant differences in the activation of the prefrontal cortex between high-quality and the low-quality students during simulating and when communicating with advisers, specifically in the Broca's areas, the frontal pole, and the orbitofrontal and dorsolateral prefrontal cortices. This further elucidated the complex cognitive process of communication between graduate students and advisers.

Investigating the Impact of Gut Microbiota on Gout Through Mendelian Randomization.

Background: The relationship between gout and gut microbiota has attracted significant attention in current research. However, due to the diverse range of gut microbiota, the specific causal effect on gout remains unclear. This study utilizes Mendelian randomization (MR) to investigate the causal relationship between gut microbiota and gout, aiming to elucidate the underlying mechanism of microbiome-mediated gout and provide valuable guidance for clinical prevention and treatment. Materials and Methods: The largest genome-wide association study meta-analysis conducted by the MiBioGen Consortium (n=18,340) was utilized to perform a two-sample Mendelian randomization investigation on aggregate statistics of intestinal microbiota. Summary statistics for gout were utilized from the data released by EBI. Various methods, including inverse variance weighted, weighted median, weighted model, MR-Egger, and Simple-mode, were employed to assess the causal relationship between gut microbiota and gout. Reverse Mendelian randomization analysis revealed a causal association between bacteria and gout in forward Mendelian randomization analysis. Cochran's Q statistic was used to quantify instrumental variable heterogeneity. Results: The inverse variance weighted estimation revealed that Rikenellaceae exhibited a slight protective effect on gout, while the presence of Ruminococcaceae UCG_011 is associated with a marginal increase in the risk of gout. According to the reverse Mendelian Randomization results, no significant causal relationship between gout and gut microbiota was observed. No significant heterogeneity of instrumental variables or level pleiotropy was detected. Conclusion: Our MR analysis revealed a potential causal relationship between the development of gout and specific gut microbiota; however, the causal effect was not robust, and further research is warranted to elucidate its underlying mechanism in gout development. Considering the significant association between diet, gut microbiota, and gout, these findings undoubtedly shed light on the mechanisms of microbiota-mediated gout and provide new insights for translational research on managing and standardizing treatment for this condition.

Improving the classification of multiple sclerosis and cerebral small vessel disease with interpretable transfer attention neural network.

As an autoimmune-mediated inflammatory demyelinating disease of the central nervous system, multiple sclerosis (MS) is often confused with cerebral small vessel disease (cSVD), which is a regional pathological change in brain tissue with unknown pathogenesis. This is due to their similar clinical presentations and imaging manifestations. That misdiagnosis can significantly increase the occurrence of adverse events. Delayed or incorrect treatment is one of the most important causes of MS progression. Therefore, the development of a practical diagnostic imaging aid could significantly reduce the risk of misdiagnosis and improve patient prognosis. We propose an interpretable deep learning (DL) model that differentiates MS and cSVD using T2-weighted fluid-attenuated inversion recovery (FLAIR) images. Transfer learning (TL) was utilized to extract features from the ImageNet dataset. This pioneering model marks the first of its kind in neuroimaging, showing great potential in enhancing differential diagnostic capabilities within the field of neurological disorders. Our model extracts the texture features of the images and achieves more robust feature learning through two attention modules. The attention maps provided by the attention modules provide model interpretation to validate model learning and reveal more information to physicians. Finally, the proposed model is trained end-to-end using focal loss to reduce the influence of class imbalance. The model was validated using clinically diagnosed MS (n=112) and cSVD (n=321) patients from the Beijing Tiantan Hospital. The performance of the proposed model was better than that of two commonly used DL approaches, with a mean balanced accuracy of 86.06 % and a mean area under the receiver operating characteristic curve of 98.78 %. Moreover, the generated attention heat maps showed that the proposed model could focus on the lesion signatures in the image. The proposed model provides a practical diagnostic imaging aid for the use of routinely available imaging techniques such as magnetic resonance imaging to classify MS and cSVD by linking DL to human brain disease. We anticipate a substantial improvement in accurately distinguishing between various neurological conditions through this novel model.

Lipidomic Comparisons of Whole Cream Buttermilk Whey and Cheese Whey Cream Buttermilk of Caprine Milk.

Buttermilk is a potential material for the production of a milk fat globule membrane (MFGM) and can be mainly classified into two types: whole cream buttermilk and cheese whey cream buttermilk (WCB). Due to the high casein micelle content of whole cream buttermilk, the removal of casein micelles to improve the purity of MFGM materials is always required. This study investigated the effects of rennet and acid coagulation on the lipid profile of buttermilk rennet-coagulated whey (BRW) and buttermilk acid-coagulated whey (BAW) and compared them with WCB. BRW has significantly higher phospholipids (PLs) and ganglioside contents than BAW and WCB. The abundance of arachidonic acid (ARA)- and eicosapentaenoic acid (EPA)-structured PLs was higher in WCB, while docosahexaenoic acid (DHA)-structured PLs were higher in BRW, indicating that BRW and WCB intake might have a greater effect on improving cardiovascular conditions and neurodevelopment. WCB and BRW had a higher abundance of plasmanyl PL and plasmalogen PL, respectively. Phosphatidylcholine (PC) (28:1), LPE (20:5), and PC (26:0) are characteristic lipids among BRW, BAW, and WCB, and they can be used to distinguish MFGM-enriched whey from different sources.