ASPM stabilizes the NOTCH intracellular domain 1 and promotes oncogenesis by blocking FBXW7 binding in hepatocellular carcinoma cells

Notch signaling is aberrantly activated in approximately 30% of hepatocellular carcinoma (HCC), significantly contributing to tumorigenesis and disease progression. Expression of the major Notch receptor, NOTCH1, is upregulated in HCC cells and correlates with advanced disease stages, although the molecular mechanisms underlying its overexpression remain unclear. Here, we report that expression of the intracellular domain of NOTCH1 (NICD1) is upregulated in HCC cells due to antagonism between the E3-ubiquitin ligase F-box/WD repeat-containing protein 7 (FBXW7) and the large scaffold protein abnormal spindle-like microcephaly-associated protein (ASPM) isoform 1 (ASPM-i1). Mechanistically, FBXW7-mediated polyubiquitination and the subsequent proteasomal degradation of NICD1 are hampered by the interaction of NICD1 with ASPM-i1, thereby stabilizing NICD1 and rendering HCC cells responsive to stimulation by Notch ligands. Consistently, downregulating ASPM-i1 expression reduced the protein abundance of NICD1 but not its FBXW7-binding-deficient mutant. Reinforcing the oncogenic function of this regulatory module, the forced expression of NICD1 significantly restored the tumorigenic potential of ASPM-i1-deficient HCC cells. Echoing these findings, NICD1 was found to be strongly co-expressed with ASPM-i1 in cancer cells in human HCC tissues (P < 0.001). In conclusion, our study identifies a novel Notch signaling regulatory mechanism mediated by protein-protein interaction between NICD1, FBXW7, and ASPM-i1 in HCC cells, representing a targetable vulnerability in human HCC.

Repositioning VU-0365114 as a novel microtubule-destabilizing agent for treating cancer and overcoming drug resistance

Microtubule-targeting agents represent one of the most successful classes of anticancer agents. However, the development of drug resistance and the appearance of adverse effects hamper their clinical implementation. Novel microtubule-targeting agents without such limitations are urgently needed. By employing a gene expression-based drug repositioning strategy, this study identifies VU-0365114, originally synthesized as a positive allosteric modulator of human muscarinic acetylcholine receptor M5 (M5 mAChR), as a novel type of tubulin inhibitor by destabilizing microtubules. VU-0365114 exhibits a broad-spectrum in vitro anticancer activity, especially in colorectal cancer cells. A tumor xenograft study in nude mice shows that VU-0365114 slowed the in vivo colorectal tumor growth. The anticancer activity of VU-0365114 is not related to its original target, M5 mAChR. In addition, VU-0365114 does not serve as a substrate of multidrug resistance (MDR) proteins, and thus, it can overcome MDR. Furthermore, a kinome analysis shows that VU-0365114 did not exhibit other significant off-target effects. Taken together, our study suggests that VU-0365114 primarily targets microtubules, offering potential for repurposing in cancer treatment, although more studies are needed before further drug development.

Ginkgetin effectively mitigates collagen and AA-induced platelet activation via PLCγ2 but not cyclic nucleotide-dependent pathway in human

Platelets assume a pivotal role in the cardiovascular diseases (CVDs). Thus, targeting platelet activation is imperative for mitigating CVDs. Ginkgetin (GK), from Ginkgo biloba L, renowned for its anticancer and neuroprotective properties, remains unexplored concerning its impact on platelet activation, particularly in humans. In this investigation, we delved into the intricate mechanisms through which GK influences human platelets. At low concentrations (0.5-1 μM), GK exhibited robust inhibition of collagen and arachidonic acid (AA)-induced platelet aggregation. Intriguingly, thrombin and U46619 remained impervious to GK's influence. GK's modulatory effect extended to ATP release, P-selectin expression, intracellular calcium ([Ca2+ ]i) levels and thromboxane A2 formation. It significantly curtailed the activation of various signaling cascades, encompassing phospholipase Cγ2 (PLCγ2)/protein kinase C (PKC), phosphoinositide 3-kinase/Akt/glycogen synthase kinase-3β and mitogen-activated protein kinases. GK's antiplatelet effect was not reversed by SQ22536 (an adenylate cyclase inhibitor) or ODQ (a guanylate cyclase inhibitor), and GK had no effect on the phosphorylation of vasodilator-stimulated phosphoproteinSer157 or Ser239 . Moreover, neither cyclic AMP nor cyclic GMP levels were significantly increased after GK treatment. In mouse studies, GK notably extended occlusion time in mesenteric vessels, while sparing bleeding time. In conclusion, GK's profound impact on platelet activation, achieved through inhibiting PLCγ2-PKC cascade, culminates in the suppression of downstream signaling and, ultimately, the inhibition of platelet aggregation. These findings underscore the promising therapeutic potential of GK in the CVDs.

Structure-based development of a canine TNF-α-specific antibody using adalimumab as a template

The canine anti-tumor necrosis factor-alpha (TNF-α) monoclonal antibody is a potential therapeutic option for treating canine arthritis. The current treatments for arthritis in dogs have limitations due to side effects, emphasizing the need for safer and more effective therapies. The crystal structure of canine TNF-α (cTNF-α) was successfully determined at a resolution of 1.85 Å, and the protein was shown to assemble as a trimer, with high similarity to the functional quaternary structure of human TNF-α (hTNF-α). Adalimumab (Humira), a known TNF-α inhibitor, effectively targets and neutralizes TNF-α to reduce inflammation and has been used to manage autoimmune conditions such as rheumatoid arthritis. By comparing the structure of cTNF-α with the complex structure of hTNF-α and adalimumab-Fab, the epitope of adalimumab on cTNF-α was identified. The significant structural similarities of epitopes in cTNF-α and hTNF-α indicate the potential of using adalimumab to target cTNF-α. Therefore, a canine/human chimeric antibody, Humivet-R1, was created by grafting the variable domain of adalimumab onto a canine antibody framework derived from ranevetmab. Humivet-R1 exhibits potent neutralizing ability (IC50  = 0.05 nM) and high binding affinity (EC50  = 0.416 nM) to cTNF-α, comparable to that of adalimumab for both hTNF-α and cTNF-α. These results strongly suggest that Humivet-R1 has the potential to provide effective treatment for canine arthritis with reduced side effects. Here, we propose a structure-guided antibody design for the use of a chimeric antibody to treat canine inflammatory disease. Our successful development strategy can speed up therapeutic antibody discovery for animals and has the potential to revolutionize veterinary medicine.

Use of consecutive transcutaneous oxygen measurement when assessing the need for revascularization and association with the outcomes of ischemic diabetic ulcers

This study compared the ankle-brachial index (ABI) with transcutaneous oxygen pressure (TcPO2 ) in assessing peripheral vascular disease (PVD) prevalence in 100 diabetic foot ulcer (DFU) patients. Patients were categorized into vascular or nonvascular reconstruction groups and underwent both ABI and TcPO2 measurements four times over 6 months. Predictive validity for PVD diagnosis was analysed using the area under the receiver-operating characteristic curve (AUC). The study found TcPO2 to be a superior predictor of PVD than ABI. Among the DFU patients, 51 with abnormal TcPO2 values underwent vascular reconstruction. Only TcPO2 values showed significant pretreatment differences between the groups and increased post-reconstruction. These values declined over a 6-month follow-up, whereas ABI values rose. For those with end-stage renal disease (ESRD), TcPO2 values saw a sharp decrease within 3 months. Pre-reconstruction TcPO2 was notably lower in amputation patients versus limb salvage surgery patients. In conclusion, TcPO2 is more effective than ABI for evaluating ischemic limb perfusion and revascularization necessity. It should be prioritized as the primary follow-up tool, especially for ESRD patients.

Liaw's Ellipse Anteversion Method for Distinguishing Acetabular Component Retroversion from Anteversion on Plain Radiographs

Improper acetabulum component position is a significant risk factor for postoperative dislocation after total hip arthroplasty. Several radiographic two-dimensional methods exist for measuring acetabulum component anteversion, but they cannot distinguish between anteversion and retroversion. "Liaw's version," initially proposed as a simple mathematical standardized two-dimensional method, was modified to the computerized ellipse method, proving superior accuracy to traditional two-dimensional methods. In this article, we demonstrated its application in detecting and measuring retroverted acetabulum component. We obtained anteroposterior pelvis radiographs from a patient undergoing total hip arthroplasty on the day of surgery and 2 weeks postoperatively. The computerized ellipse method was used to measure the acetabulum component orientation. Upon comparison, the difference between θ assigned to be retroverted (9.52-8.56 = 0.96) is much smaller than the difference between θ assigned to be anteverted (23.81-18.86 = 4.95), leading us to determine retroversion. This was further confirmed by computed tomography at the 6-week follow-up. We propose that using the computerized ellipse method to measure Liaw's version can be a valuable tool in identifying acetabulum component retroversion on anteroposterior radiographs during routine postoperative follow-up and retrospective assessments of total hip arthroplasty patients.

A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning

INTRODUCTION

Pancreatic cancer is associated with poor prognosis. Considering the increased global incidence of diabetes cases and that individuals with diabetes are considered a high-risk subpopulation for pancreatic cancer, it is critical to detect the risk of pancreatic cancer within populations of person living = with diabetes. This study aimed to develop a novel prediction model for pancreatic cancer risk among patients with diabetes, using = a real-world database containing clinical features and employing numerous artificial intelligent approach algorithms.

METHODS

This retrospective observational study analyzed data on patients with Type 2 diabetes from a multisite Taiwanese EMR database between 2009 and 2019. Predictors were selected in accordance with the literature review and clinical perspectives. The prediction models were constructed using machine learning algorithms such as logistic regression, linear discriminant analysis, gradient boosting machine, and random forest.

RESULTS

The cohort consisted of 66,384 patients. The Linear Discriminant Analysis (LDA) model generated the highest AUROC of 0.9073, followed by the Voting Ensemble and Gradient Boosting machine models. LDA, the best model, exhibited an accuracy of 84.03%, a sensitivity of 0.8611, and a specificity of 0.8403. The most significant predictors identified for pancreatic cancer risk were glucose, glycated hemoglobin, hyperlipidemia comorbidity, antidiabetic drug use, and lipid-modifying drug use.

CONCLUSION

This study successfully developed a highly accurate 4-year risk model for pancreatic cancer in patients with diabetes using real-world clinical data and multiple machine-learning algorithms. Potentially, our predictors offer an opportunity to identify pancreatic cancer early and thus increase prevention and invention windows to impact survival in diabetic patients.

Salmonella YqiC exerts its function through an oligomeric state

Protein oligomerization occurs frequently both in vitro and in vivo, with specific functionalities associated with different oligomeric states. The YqiC protein from Salmonella Typhimurium forms a homotrimer through its C-terminal coiled-coil domain, and the protein is closely linked to the colonization and invasion of the bacteria to the host cells. To elucidate the importance of the oligomeric state of YqiC in vivo and its relation with bacterial infection, we mutated crucial residues in YqiC's coiled-coil region and confirmed the loss of trimer formation using chemical crosslinking and size exclusion chromatography coupled with multiple angle light scattering (SEC-MALS) techniques. The yqiC-knockout strain complemented with mutant YqiC showed significantly reduced colonization and invasion of Salmonella to host cells, demonstrating the critical role of YqiC oligomerization in bacterial pathogenesis. Furthermore, we conducted a protein-protein interaction study of YqiC using a pulled-down assay coupled with mass spectrometry analysis to investigate the protein's role in bacterial virulence. The results reveal that YqiC interacts with subunits of Complex II of the electron transport chain (SdhA and SdhB) and the β-subunit of F0 F1 -ATP synthase. These interactions suggest that YqiC may modulate the energy production of Salmonella and subsequently affect the assembly of crucial virulence factors, such as flagella. Overall, our findings provide new insights into the molecular mechanisms of YqiC's role in S. Typhimurium pathogenesis and suggest potential therapeutic targets for bacterial infections.

Machine learning approaches for predicting 5-year breast cancer survival: A multicenter study

The study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospitals in Taiwan. The study included female patients aged over 20 years who were diagnosed with primary breast cancer and had medical records in hospitals between January 1, 2009 and December 31, 2020. The data were divided into training and external testing datasets. Nine different machine learning algorithms were applied to develop the models. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. A total of 3914 patients were included in the study. The highest AUC of 0.95 was observed with the artificial neural network model (accuracy, 0.90; sensitivity, 0.71; specificity, 0.73; PPV, 0.28; NPV, 0.94; and F1-score, 0.37). Other models showed relatively high AUC, ranging from 0.75 to 0.83. According to the optimal model results, cancer stage, tumor size, diagnosis age, surgery, and body mass index were the most critical factors for predicting breast cancer survival. The study successfully established accurate 5-year survival predictive models for breast cancer. Furthermore, the study found key factors that could affect breast cancer survival in Taiwanese women. Its results might be used as a reference for the clinical practice of breast cancer treatment.

Determinants of the success in flap reconstruction-Outcome analysis of 120 flaps in 484 procedures for pressure injury

Pressure injury (PI) mainly occurs in bedridden older adults or those with physical limitations. Here, we aimed to determine the appropriate timing to conduct flap reconstruction in patients with PIs and identify factors affecting surgical outcomes. We retrospectively reviewed the data of all patients who received debridement or flap reconstruction surgery for PIs in our hospital from January 2016 to December 2021. The extracted data included patient demographics, surgical records, blood test results, vital signs, and flap outcomes. In total, 484 surgical procedures (364 debridements and 120 flaps) were performed on 216 patients. Serum albumin level of ≥2.5 g/dL remarkably increased the likelihood of complete wound healing (odds ratio [OR] = 4.12, P = .032) and reduced the risk of postoperative complications (OR = 0.26, P = .040). In contrast, advanced age (OR = 1.04, P = .045) and serum creatinine level ≥2 mg/dL (OR = 5.07, P = .016) increased the risk of postoperative complications. Thus, patients with a favourable nutrition status have a higher likelihood of achieving complete wound healing. By contrast, patients who are older and have serum creatinine ≥2 mg/dL and serum albumin <2.5 g/dL tend to develop more postoperative complications. Overall, thorough correction for patient inflammation, infection, anaemia, and malnutrition status can provide optimal flap surgery outcomes.

Personalized cancer avatars for patients with thymic malignancies: A pilot study with circulating tumor cell-derived organoids

BACKGROUND

Systemic therapy is the primary treatment for advanced thymic malignancies. However, there is an urgent need to improve clinical outcome. Personalized treatment based on predictive biomarkers is a potential approach to address this requirement. In this study, we aimed to show the correlation between drug sensitivity tests on CTCs-derived organoids and clinical response in patients with thymic malignancies. This approach carries the potential to create personalized cancer avatars and improve treatment outcome for patients.

METHODS

We previously reported potential treatment outcome prediction with patient-derived organoids (cancer avatars) in patients with pancreatic ductal adenocarcinoma. To further investigate the feasibility of this approach in advanced thymic malignancies, we conducted a study in which 12 patients were enrolled and 21 liquid biopsies were performed.

RESULTS

Cancer avatars were successfully derived in 16 out of 21 samples (success rate 76.2%). We found a sensitivity of 1.0 and specificity of 0.6 for drug sensitivity tests on the cancer avatars, and a two-tailed Fisher's exact test revealed a significant correlation between drug sensitivity tests and clinical responses (p = 0.0275).

CONCLUSION

This study supports the potential of circulating tumor cell-derived organoids to inform personalized treatment for advanced thymic malignancies. Further validation of this proof of concept finding is ongoing.

The change of clinical features and surgical outcomes in patients with pressure injury during the COVID-19 pandemic

This retrospective study aims to explore whether the COVID-19 pandemic altered patient conditions and surgery outcomes by studying 213 pressure injury (PI) patients who underwent surgery during 2016 to 2019 (pre-COVID) and 2020 to 2021 (COVID) in Taiwan. We extracted patient demographics, surgical and blood test records, preoperative vital signs, and flap surgery outcomes. In total, 464 surgeries were performed, including 308 pre-COVID and 156 COVID. During the COVID period, there were more patients presenting with dementia, and it had significantly more patients with >12 000 white blood cells/μL (24.03% vs 15.59%, P = 0.029), higher C-reactive protein levels (7.13 ± 6.36 vs 5.58 ± 5.09 mg/dL, P = 0.014), pulse rates (86.67 ± 14.76 vs 81.26 ± 13.66 beats/min, P < 0.001), and respiratory rates (17.87 ± 1.98 vs 17.31 ± 2.39 breaths/min, P = 0.009) but lower haemoglobin levels (9.75 ± 2.02 vs 10.43 ± 1.67 mg/dL, P < 0.001) preoperatively. There were no between-group differences in flap surgery outcomes but had fewer flap surgeries during COVID-19. Thus, PI patient condition was generally poor during the COVID-19 pandemic because of reduced access to medical treatment; this problem may be resolved through holistic care during a future pandemic or pandemic-like situation.

KI Essence extract (a spleen-tonifying formula) promotes neurite outgrowth, alleviates oxidative stress and hypomyelination, and modulates microbiome in maternal immune activation offspring

Mushrooms and Chinese traditional herbs have bioactive nutraceuticals with multiple therapeutic functions, including antioxidant and antibacterial activities and microbiome modulation properties. Mushroom-derived bioactive compounds are used in medicines for the treatment of neurological disorders with abnormal brain–gut–microbiome axis. This study examined the effects of KI Essence extract, a spleen-tonifying formula, on neurite growth, antioxidant activity, hypomyelination modulation, and the microbiome profile in lipopolysaccharide (LPS)-induced maternal immune activation (MIA) offspring. The KI Essence extract induced PC12 cell neurite growth by increasing extracellular signal–regulated kinase (ERK) phosphorylation, promoting 2,2′-diphenyl-1-picrylhydrazyl radical scavenging activity, reducing the level of tert-butylhydroperoxide–induced lipid peroxidation in brain homogenates, protecting PC12 cells from H2O2-induced cell death (through the inhibition of ERK phosphorylation), alleviating hypomyelination, and downregulating interleukin‐1β through LPS-activated microglia production; moreover, the numbers of Enterobacteriaceae, Actinobacteria, Peptostreptococcaceae, Erysipelotrichaceae, and Bifidobacterium bacteria in MIA offspring increased. In summary, the KI Essence extract promotes neurite outgrowth, alleviates oxidative stress and hypomyelination, and modulates microbiota dysbiosis in MIA offspring.

Potential of Cellular Therapy for ALS: Current Strategies and Future Prospects

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive upper and lower motor neuron (MN) degeneration with unclear pathology. The worldwide prevalence of ALS is approximately 4.42 per 100,000 populations, and death occurs within 3-5 years after diagnosis. However, no effective therapeutic modality for ALS is currently available. In recent years, cellular therapy has shown considerable therapeutic potential because it exerts immunomodulatory effects and protects the MN circuit. However, the safety and efficacy of cellular therapy in ALS are still under debate. In this review, we summarize the current progress in cellular therapy for ALS. The underlying mechanism, current clinical trials, and the pros and cons of cellular therapy using different types of cell are discussed. In addition, clinical studies of mesenchymal stem cells (MSCs) in ALS are highlighted. The summarized findings of this review can facilitate the future clinical application of precision medicine using cellular therapy in ALS.

Efficacy of Osteoporosis Medications for Patients With Chronic Kidney Disease: An Updated Systematic Review and Network Meta-Analysis

Background: Chronic kidney disease (CKD) is associated with bone and mineral metabolism. In this study we evaluated the comparative efficacies and safety of osteoporosis medications in patients with CKD or a history of kidney transplantation, and make recommendations for the best choice of osteoporosis treatment among patients with CKD or a history of kidney transplantation.

Methods: We systemically searched for randomized controlled trials published in PubMed, Embase, and Cochrane databases up to June 2020. Network-meta analysis was used to compare the relative effectiveness of different treatments. A random-effects model was used when heterogeneity was expected. The safety of different treatments was also evaluated in terms of reported major adverse events.

Results: A total of 17 studies with data from 10,214 patients who had stage 2–5 CKD, were receiving dialysis, or had a history of kidney transplantation were included in the network meta-analysis. Treatment with teriparatide, denosumab, alendronate, and raloxifene were all associated with a significantly reduced risk of fractures compared to treatment with placebos [teriparatide: odds ratio (OR) = 0.19, 95% confidence interval (CI): 0.10–0.35; denosumab: OR = 0.40, 95% CI: 0.27–0.58; alendronate: OR = 0.61, 95% CI: 0.40–0.92; raloxifene: OR = 0.52, 95% CI: 0.41–0.67]. The rank probability and the surface under the cumulative ranking (SUCRA) values suggested that teriparatide ranked the highest for improvement in vertebral bone mineral density (BMD) (SUCRA = 97.8%), whereas denosumab ranked the highest for improvement in femoral neck BMD (SUCRA = 88.3%).

Conclusion: Teriparatide and denosumab seem to be the most effective treatments for preventing bone loss and reducing the risk of fracture in our network comparison. However, because of the limitations and potential biases in the reviewed studies, there is still some uncertainty about the best treatment options for osteoporosis in patients with CKD or a history of kidney transplantation.

Systematic Review Registration: [PROSPERO], identifier [CRD42020209830].

Drug Repurposing for Atopic Dermatitis by Integration of Gene Networking and Genomic Information

Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.

Alcohol Consumption Moderated the Association Between Levels of High Blood Lead or Total Urinary Arsenic and Bone Loss

Metal exposure and lifestyle are important risk factors for osteoporosis. Our study aimed to investigate the association between red blood cell lead and cadmium, total urinary arsenic, and plasma selenium levels and bone mineral density (BMD). In addition, we explored whether alcohol and coffee consumption modified the association between BMD and metals and metalloids. In total, 437 participants who underwent adult or senile physical examinations were recruited. Bone loss was defined as a calcaneus BMD T-score of <-1. Blood cadmium and lead and plasma selenium levels were measured using inductively coupled plasma mass spectrometry. Levels of urinary arsenic species were determined using high-performance liquid chromatography-hydride generator-atomic absorption spectrometry. The total urinary arsenic level was defined as the sum of the levels of urinary arsenic species. The BMD T-scores decreased significantly with increasing blood lead levels. The BMD T-scores also showed a downward trend with increasing total urinary arsenic levels. The odds ratio (OR) and 95% confidence interval (CI) for bone loss in patients with blood lead levels >57.58 versus 35.74 μg/dL were 1.98 and 1.17-3.34. In addition, the greater the lead or arsenic exposure and alcohol intake was the higher the OR for bone loss with multivariate ORs of 2.57 (95% CI 1.45-4.56) and 2.96 (95% CI 1.67-5.22), respectively. To the best of our knowledge, this study is the first to demonstrate that high total urinary arsenic or blood lead levels and frequent or occasional alcohol consumption had a significant multiplicative interaction for increasing the OR for bone loss.