Development of artificial intelligence model for supporting implant drilling protocol decision making

Purpose: This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol using cone-beam computed tomography (CBCT) images. Methods: Anonymized CBCT images were obtained from 60 patients. For each case, after implant placement, images of the bone regions at the implant site were extracted from 20 slices of CBCT images. Based on the actual drilling protocol, the images were classified into three categories: protocols A, B, and C. A total of 1,200 images were divided into training and validation datasets (n = 960, 80%) and a test dataset (n = 240, 20%). Another 240 images (80 images for each type) were extracted from the 60 cases as test data. An AI model based on LeNet-5 was developed using these data sets. The accuracy, sensitivity, precision, F-value, area under the curve (AUC) value, and receiver operating curve were calculated. Results: The accuracy of the trained model is 93.8%. The sensitivity results for drilling protocols A, B, and C were 97.5%, 95.0%, and 85.0%, respectively, while those for protocols A, B, and C were 86.7%, 92.7%, and 100%, respectively, and the F values for protocols A, B, and C were 91.8%, 93.8%, and 91.9%, respectively. The AUC values for protocols A, B, and C are 98.6%, 98.6%, and 99.4%, respectively. Conclusions: The AI model established in this study was effective in predicting drilling protocols from CBCT images before surgery, suggesting the possibility of developing a decision-making support system to promote primary stability.Sakai T., Li H., Shimada T., et al. Development of artificial intelligence model for supporting implant drilling protocol decision making. Journal of Prosthodontic Research 67, 360 (2023); https://doi.org/10.2186/jpr.JPR_D_22_00053

RUNX1 transactivates BCR-ABL1 expression in Philadelphia chromosome positive acute lymphoblastic leukemia

The emergence of tyrosine kinase inhibitors as part of a front-line treatment has greatly improved the clinical outcome of the patients with Ph⁺ acute lymphoblastic leukemia (ALL). However, a portion of them still become refractory to the therapy mainly through acquiring mutations in the BCR-ABL1 gene, necessitating a novel strategy to treat tyrosine kinase inhibitor (TKI)-resistant Ph⁺ ALL cases. In this report, we show evidence that RUNX1 transcription factor stringently controls the expression of BCR-ABL1, which can strategically be targeted by our novel RUNX inhibitor, Chb-M'. Through a series of in vitro experiments, we identified that RUNX1 binds to the promoter of BCR and directly transactivates BCR-ABL1 expression in Ph⁺ ALL cell lines. These cells showed significantly reduced expression of BCR-ABL1 with suppressed proliferation upon RUNX1 knockdown. Moreover, treatment with Chb-M' consistently downregulated the expression of BCR-ABL1 in these cells and this drug was highly effective even in an imatinib-resistant Ph⁺ ALL cell line. In good agreement with these findings, forced expression of BCR-ABL1 in these cells conferred relative resistance to Chb-M'. In addition, in vivo experiments with the Ph⁺ ALL patient-derived xenograft cells showed similar results. In summary, targeting RUNX1 therapeutically in Ph⁺ ALL cells may lead to overcoming TKI resistance through the transcriptional regulation of BCR-ABL1. Chb-M' could be a novel drug for patients with TKI-resistant refractory Ph⁺ ALL

A Quantitative Study of Social Capital in the Tertiary Sector of Kobe : Has Social Capital Promoted Economic Reconstruction Since the Great Hanshin Awaji Earthquake?

Social capital is thought to have both positive and negative aspects. This paper examines how social capital has worked in the process of recovery and reconstruction in Kobe since the Great Hanshin Awaji Earthquake. The paper focuses on the tertiary sector of Kobe because since the earthquake there has been a structural shift from the secondary sector due to the damage caused by the earthquake, and because the sector accounted for 80% of employment, the most important factor for reconstruction in the mid- and long-term. The paper proves that both bonding and bridging social capital are important factors for employment. This finding provides empirical evidence for the on-going debate on how to rebuild Tohoku

High serum PD‐L1 level is a poor prognostic biomarker in surgically treated esophageal cancer

Abstract Background Programmed death ligand 1 (PD‐L1) inhibitor has been approved as one of the standard therapies for various cancers. Some reports have shown that serum PD‐L1 level is associated with advanced tumor stages and poor prognosis; however, corresponding pathological information in esophageal cancer patients is lacking. Therefore, we evaluated the clinicopathological and prognostic impact of serum PD‐L1 levels in surgically treated esophageal cancer. Methods A total of 150 patients who underwent radical resection for esophageal cancer were included in the study. Preoperative serum PD‐L1 levels were analyzed using the enzyme‐linked immunosorbent assay kit. A cutoff level of 65.6 pg/mL was used to divide the patients into two groups, and univariate and multivariate analyses were conducted to compare the clinicopathological characteristics and prognoses between these two groups. Results Although significant associations between serum PD‐L1 levels and clinicopathological variables were observed, serum PD‐L1 level was significantly associated with high neutrophil counts, high CRP levels, low albumin levels, and high squamous cell carcinoma antigen levels. Furthermore, serum PD‐L1 level was associated with poor overall survival independent to TNM factors. Conclusions High preoperative level of serum PD‐L1 is a prognostic factor for poor overall survival in patients with surgically treated esophageal cancer

Real-World Data of Trastuzumab Deruxtecan for Advanced Gastric Cancer: A Multi-Institutional Retrospective Study

Trastuzumab deruxtecan (T-DXd) has shown promising efficacy against HER2-positive advanced gastric cancer (AGC). However, data on its real-world efficacy in AGC patients are insufficient, and the predictive marker of T-DXd is unclear. In this multi-center retrospective study, we collected clinical information of 18 patients with HER2-positive AGC who received T-DXd after intolerant or refractory responses to at least two prior regimens and analyzed predictive factors. The median age was 71 years (range: 51–85), 13 men were included, and ECOG performance status (PS): 0/1/2/3 was 9/6/2/1. A total of 11 patients (61%) received prior immune checkpoint inhibitors (ICIs), 14 patients were HER2 3+, and 4 patients were HER2 2+/FISH positive. The median trastuzumab (Tmab)-free interval was 7.7 months (range: 2.8–28.6). The overall response rate was 41%, and the disease control rate was 76%. Median progression-free survival (PFS) was 3.9 months (95% CI: 2.6–6.5), and median overall survival (OS) was 6.1 months (95% CI: 3.7–9.4). PFS (6.5 vs. 2.9 months, p = 0.0292) and OS (9.2 vs. 3.7 months, p = 0.0819) were longer in patients who received prior ICIs than in those who had not. PFS (6.5 vs. 3.4 months, p = 0.0249) and OS (9.4 vs. 5.7 months, p = 0.0426) were longer in patients with an 8 month or longer Tmab-free interval. In patients with ascites, PFS (6.5 vs. 2.75 months, p = 0.0139) and OS (9.4 vs. 3.9 months, p = 0.0460) were shorter. T-DXd showed promising efficacy in HER2-positive AGC patients in a real-world setting. Pre-administration of ICIs and a sufficient Tmab-free interval may be predictive factors of T-DXd efficacy