Abdominal aortic aneurysm (AAA) is a common human disease with a high estimated heritability (0.7); however, only a small number of associated genetic loci have been reported to date. In contrast, over 100 loci have now been reproducibly associated with either blood lipid profile and/or coronary artery disease (CAD) (both risk factors for AAA) in large-scale meta-analyses. This study employed a staged design to investigate whether the loci for these two phenotypes are also associated with AAA. Validated CAD and dyslipidaemia loci underwent screening using the Otago AAA genome-wide association data set. Putative associations underwent staged secondary validation in 10 additional cohorts. A novel association between the SORT1 (1p13.3) locus and AAA was identified. The rs599839 G allele, which has been previously associated with both dyslipidaemia and CAD, reached genome-wide significance in 11 combined independent cohorts (meta-analysis with 7048 AAA cases and 75 976 controls: G allele OR 0.81, 95% CI 0.76-0.85, P = 7.2 × 10(-14)). Modelling for confounding interactions of concurrent dyslipidaemia, heart disease and other risk factors suggested that this marker is an independent predictor of AAA susceptibility. In conclusion, a genetic marker associated with cardiovascular risk factors, and in particular concurrent vascular disease, appeared to independently contribute to susceptibility for AAA. Given the potential genetic overlap between risk factor and disease phenotypes, the use of well-characterized case-control cohorts allowing for modelling of cardiovascular disease risk confounders will be an important component in the future discovery of genetic markers for conditions such as AAA.

Background/AimsTo develop a deep learning system (DLS) that can automatically detect malignant melanoma (MM) in the eyelid from histopathological sections with colossal information density.MethodsSetting: Double institutional study.Study population: We retrospectively reviewed 225 230 pathological patches (small section cut from pathologist-labelled area from an H&E image), cut from 155 H&E-stained whole-slide images (WSI).Observation procedures: Labelled gigapixel pathological WSIs were used to train and test a model designed to assign patch-level classification. Using malignant probability from a convolutional neural network, the patches were embedded back into each WSI to generate a visualisation heatmap and leveraged a random forest model to establish a WSI-level diagnosis.Main outcome measure(s): For classification, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity were used to evaluate the efficacy of the DLS in detecting MM.ResultsFor patch diagnosis, the model achieved an AUC of 0.989 (95% CI 0.989 to 0.991), with an accuracy, sensitivity and specificity of 94.9%, 94.7% and 95.3%, respectively. We displayed the lesion area on the WSIs as graded by malignant potential. For WSI, the obtained sensitivity, specificity and accuracy were 100%, 96.5% and 98.2%, respectively, with an AUC of 0.998 (95% CI 0.994 to 1.000).ConclusionOur DLS, which uses artificial intelligence, can automatically detect MM in histopathological slides and highlight the lesion area on WSIs using a probabilistic heatmap. In addition, our approach has the potential to be applied to the histopathological sections of other tumour types.

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Immunotherapeutic interventions represent a promising approach to treating cancer, with strategies such as immune checkpoint blockade (ICB), immunogenic sonodynamic therapy (SDT), and immune adjuvant T cell delivery having exhibited clinical promise. In this report, we describe the use of cancer cell membrane-coated triphenylphosphonium (TPP) decorated nano-metal–organic framework (nMOF) constructs [Zr-TCPP(TPP)/R837@M] that were used to generate homologous, mitochondria-targeted platforms with a high rate of sonosensitizer loading. This construct was utilized to simultaneously promote tumor antigen presentation via enhancing SDT while synergistically promoting dendritic cell (DC) maturation through the delivery of the Toll-like receptor agonist R837. In vitro, these functionalized nMOFs were readily internalized by homologous tumor cells in which they were efficiently targeted to the mitochondria, promoting DC activation through the induction of immunogenic cell death (ICD) following ultrasound exposure. Moreover, this nanoplatform was able to achieve in vivo synergy with anti-CTLA-4 ICB to reverse immunosuppression tumor microenvironment (TME), thus achieving more robust antitumor efficacy capable of suppressing metastatic disease progression and facilitating the development of durable antitumor memory responses. Together, these results highlight a promising approach to achieving enhanced SDT activity while overcoming an immunosuppressive TME, thereby achieving more robust antitumor immunity.

Purpose. Three-dimensional (3D) printing technology has been widely used in orthopedics surgery. However, its efficacy in acetabular fractures remains unclear. The aim of this systematic review and meta-analysis was to examine the effect of using 3D printing technology in the surgery for acetabular fractures. Methods. The systematic review was performed following the PRISMA guidelines. Four major electronic databases were searched (inception to February 2021). Studies were screened using a priori criteria. Data from each study were extracted by two independent reviewers and organized using a standardized table. Data were pooled and presented in forest plots. Results. Thirteen studies were included in the final analysis. Four were prospective randomized trials, and nine used a retrospective comparative design. The patients aged between 32.1 (SD 14.6) years and 51.9 (SD 18.9) years. Based on the pooled analyses, overall, 3D printing-assisted surgery decreased operation time by 38.8 minutes (95% CI: -54.9, -22.8), intraoperative blood loss by 259.7 ml (95% CI: -394.6, -124.9), instrumentation time by 34.1 minutes (95% CI: -49.0, -19.1). Traditional surgery was less likely to achieve good/excellent function of hip (RR, 0.53; 95% CI: 0.34, 0.82) and more likely to have complications than 3D printing-assisted surgery (RR, 1.19; 95% CI: 1.07, 1.33). Conclusions. 3D printing technology demonstrated efficacy in the treatment of acetabular fractures. It may improve surgery-related and clinical outcomes. More prospective studies using a rigorous design (e.g., randomized trial with blinding) are warranted to confirm the long-term effects of 3D printing technology in orthopedics surgeries.