Aim To analyse the correlation between different surgical methodologies employed in valve diseases treatment and their subsequent impact on the duration of hospitalization. Methods This retrospective study conducted at the Clinical Centre of the University of Sarajevo analysed medical records of 163 valve disease patients treated between January 2019 and November 2022. The patients were divided into two groups: 77 had openheart valve surgery and 86 underwent minimally invasive cardiac surgery (MICS). Results The mean duration of the surgical procedures was 3.9±1.3 hours, with conventional open-heart surgery requiring an average of 3.6±1.1 hours and minimally invasive cardiac surgery (MICS) procedure 4.2±1.5 hours. No substantial disparities were found in the total length of hospitalization between the two groups, as both conventional (8.2±4.5 days) and MICS (8.7±7.0 days) demonstrated similar duration. Similarly, the total duration of intensive care unit (ICU) stay displayed similarity, with conventional surgery patients staying an average of 3.9±2.8 days and MICS patients of 4.2±4.1 days. The pattern of blood transfusion and fresh-frozen plasma usage revealed higher rates in the conventional valve surgery group comparing to the MICS group. Conclusion Minimally invasive valve surgery, despite slightly longer operative times, resulted in lower blood transfusion requirements and comparable hospitalization and ICU stay.

Clear cell Renal Cell Carcinoma (ccRCC) is profoundly angiogenic, characterised by complex yet heterogenous vascular networks. Blood vessels are an important constituent part of the tumour microenvironment (TME) and, in addition to immune cells, are the target of drug therapies in advanced disease. The TME plays an important role in determining disease progression and response to therapy, acting as a selective pressure on the tumour cells thus influencing evolutionary trajectory. This selective pressure is sculpted by cross-talk between blood vessels, immune cells and the tumour cells themselves. Whilst the details of these carefully orchestrated cellular interactions is not understood their final read-out is reflected in tissue morphology, which can be assessed using an H&E-stained slide, a fundamental component of clinical diagnostic histopathological workflows. A computational pathology approach to assess vascular networks from digital H&E whole slide images (H&E WSIs) would present a powerful tool to understand disease biology. It would permit high-throughput analysis of large cohorts where routine multi-regional sampling captures disease heterogeneity. Such work would lay the foundations for developing a computational pathology biomarker to predict survival outcomes that could be easily implemented into existing clinical workflows. Intricacy of vascular network structures makes reproducible analysis challenging, which can be approached either using morphology, a qualitative evaluation of a shape, or using topography to quantify feature dimensions. Here we reconcile the two methods to develop an interpretable computational pathology solution to study the blood vessels in ccRCC. Further, we have built a deep-learning attention UNET model to segment blood vessels from H&E WSIs. By combining these tools we have developed a computational pathology pipeline able to robustly characterise vascular networks directly from H&E WSIs. We leverage 1064 tumour regions from 82 ccRCC tumours of the TRACERx Renal dataset where ex-vivo multi-regional sampling with closely linked specimens for histological and genomic analysis permits interrogation of the histo:genomic relationship contextualised within the evolutionary dynamics of each tumour. We demonstrate that vascular intratumoral heterogeneity is pervasive and we link different vascular topologies to genetic alterations associated with opposing evolutionary trajectories (PBRM1 and BAP1 mutations) and the acquisition of metastatic competence (loss of 9p). Finally, we show that progressive accumulation of genetic alterations alters vascular network structure, suggesting that vascular topology could be used to assess tumour evolution. Our pipeline is a powerful tool to study ccRCC vasculature in large cohorts with multi-regional sampling to capture intratumoral heterogeneity and ultimately could form the basis of a computational pathology biomarker to predict outcome to therapy. Citation Format: Charlotte E. Spencer, Graham Ross, Thomas Mead, Amy Strange, Anna Song, Katie Bentley, Samra Turajlic. Interpretable computational pathology reveals that vascular networks reflect evolutionary dynamics in kidney cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR015.

Background: Although a range of therapeutic options are available in the management of invasive breast carcinomas, spatial segregation of tumour subclones has hampered biomarker identification in single-region samples. Representative sampling (RS) overcomes spatial bias by sampling from a homogenized and well-mixed cancer specimen. The Homogenization of Leftover Surgical Tissue Feasibility Study (HoLST-F - NCT03832062) is a prospective trial aiming to assess the feasibility of RS in tumor tissue leftover after pathology sampling. An interim analysis of the breast cancer cohort is presented. Methods: In the context of the HoLST-F study and pre-specified end-points, representative samples derived from 75 leftover invasive breast carcinoma specimens underwent flow cytometric analysis of CK8/18, CD3, Ki67 and DAPI. Tumor cell enrichment by CK8/18 positivity and ploidy (in aneuploid carcinomas) was performed for downstream DNA extraction and whole exome sequencing. Somatic variants were determined using a bespoke pipeline to remove artefacts associated with fixation. Variant oncogenicity and therapeutic evidence levels were assigned by OncoKB variant annotation. Quantitative image analysis was applied to tissue sections from diagnostic FFPE blocks stained with Ki67 immunohistochemistry (n=78) and H&E for lymphocytic infiltration scores (n=175) to correlate with flow cytometry. Results: In enriched representative samples, oncogenic mutations were commonly identified at high variant allele frequency (VAF) in known breast carcinoma driver genes including PIK3CA, CDH1, TP53, KMT2C and GATA3. Other clinically relevant oncogenic mutations were identified in ESR1, PTEN, ERBB2, RB1, AKT1, BRCA1, NF1 and FOXA1 which have been associated with resistance to various anti-cancer therapies. These mutations occurred at low and high VAFs indicative of both of clonal and sub-clonal resistance mechanisms. Recurrent variants in ESR1 (e.g. D538G) and PIK3CA (e.g. H1047R/L) were associated with Level 1 evidence for use as predictive biomarkers, while variants in twelve other genes across the cohort were associated with Level 2-4 evidence. Lymphocyte infiltration scores and Ki67 expression varied by tumor region, however RS by flow cytometry showed strong correlation with a weighted average across multiregional quantification of Ki67 expression (R=0.81, p=2.8 × 10-8) and lymphocyte infiltration (R=0.61, p<2.2 × 10-16). Conclusions: RS of invasive breast carcinoma in the HoLST-F trial has recapitulated the expected genomic driver landscape in breast cancer, in addition to identifying both clonal and subclonal genomic mechanisms of therapy resistance. Many of these mutations are either current or emerging therapeutic targets. Flow quantification of cells expressing phenotypic biomarkers (Ki67 and CD3) is feasible through RS and early analysis indicates that RS correlates with a weighted average across multiple regions. Leftover surgical tissue is an underutilized resource for biomarker assessment in breast carcinomas and can be examined by RS. Citation Format: Brian Hanley, Lisa Gallegos, Lavinia Spain, Husayn Pallikonda, Zayd Tippu, Samantha Hill, Aoune Barhoumi, Fiona Byrne, Yulia Dogva, Ashley Gilchrist, Glenn Noel-Storr, Hannah Veloz, Stacey Stanislaw, Harold Sansano, Kim Edmonds, Eleanor Carlyle, Nicholas Turner, James Larkin, Nelson Alexander, Samra Turajlic. Representative sampling of invasive breast carcinomas: Interim report from a prospective study (HOLST-F) [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A007.

Significance Existing targeted therapies for solid tumors harboring FGFR2 alterations include pan-FGFR inhibitors, which often cannot be dosed to maximum efficacy due to FGFR1- and FGFR4-mediated toxicities. The structural similarity among FGFR family members has thwarted conventional approaches to structure-based design of FGFR2-selective inhibitors, so we used long-timescale molecular dynamics simulations to identify differential motions of FGFR2 and FGFR1 that could be leveraged to design FGFR2-selective inhibitors. Our efforts led to lirafugratinib (RLY-4008), an FGFR2 inhibitor exhibiting substantial selectivity over other FGFRs. Lirafugratinib was reported to have a 73% objective response rate in early clinical studies in FGFR-inhibitor naive, FGFR2 fusion-positive intrahepatic cholangiocarcinoma patients treated orally (once daily doses ≥70 mg) without inducing clinically significant adverse effects by inhibiting off-targets.

Aim Lung adenocarcinoma (ADC) is a leading subtype of lung cancer, histologically defined with five different architectural growth patterns: lepidic, acinar, papillary, solid and micropapillary. The aim of this study was to explore the prevalence of epidermal growth factor receptor (EGFR) mutation and a relationship between the specific histological patterns of lung ADC in the population of Bosnia and Herzegovina. Methods The study included tumour tissue from 102 patients with completely resected lung ADC from 2015 to 2020. Molecular testing for the presence of EGFR mutations was performed by real-time PCR method. The relationship between EGFR mutation status and clinicopathological parameters was analysed. Results The EGFR mutation was detected in 12 (11.8%) cases of ADC, more often in non-smokers (p=0.007). A higher percentage of solid growth pattern presented in ADC may be an indicator of EGFR negativity (p=0.039), while a higher percentage of micropapillary growth pattern more common in the presence of EGFR mutation (p=0.047). Conclusion The prevalence of EGFR mutation is in accordance with the expected prevalence considering our studied population, Caucasians from South Europe. Better understanding of the relationship between histological patterns and molecular characteristics of lung ADC will enable earlier diagnosis and optimal treatment for patients.

liver

Aim To create a predictive score based on functional parameters of the liver and determine its prognostic value in survival of patients with decompensated cirrhosis. Methods Retrospective observational study included 91 consecutive patients with decompensated cirrhosis. Functional parameters (bilirubin, AST - aspartate aminotransferase, ALT - alanine aminotransferase, ALP - alkaline phosphatase, GGT - gammaglutamyltranferase, albumin, prothrombin time, platelet count, haematocrit and creatinine), Child-Pugh (CP) and Model of EndStage Liver Disease (MELD) scores have been measured at first hospitalization and at every exacerbation episode over follow-up period of 24 months. Results Using Cox regression analysis, we found that age (OR=1.206; p=0.03; 95% CI=1.019-1.428), serum bilirubin (OR=1.017; p=0.003; 95% CI=1.006-1.029), INR (International normalized ratio) (OR=6.262; p=0.002; 95% CI=1.924-20.378) and serum creatinine (OR=1.019; p=0.005; 95% CI=1.006- 1.032) had statistically strong association with the incidence of a six-month mortality. Age (OR=1.120; p=0.006; 95% CI=1.033- 1.214), serum bilirubin (OR=1.021; p=0.0001; 95% CI=1.010- 1.032), GGT (OR=1.007; p=0.023; 95% CI=1.001-1.014), INR (OR=9.571; p=0.001; 95% CI=2.610-35.098), haematocrit (OR=0.695; p=0.001; 95% CI=0.559-0.864) and serum creatinine (OR=1.023; p=0.0001; 95% CI=1.011-1.035) showed an increased the risk for a 24-month lethal outcome. Predictive score derived from liver functional parameters, CP and MELD scores, each independently has shown a high degree of death prediction after 6 or 24 months in patients with end-stage liver disease. Conclusion Predictive score derived from liver functional parameters had a better prognostic value for short-term and long-term mortality comparing to MELD and Child-Pugh score.

Aim To investigate the association between type 2 diabetes mellitus (T2DM) and pulmonary embolism, as well as to determine the prognostic value of troponin, D-dimer, prothrombotic, and proinflammatory markers in patients with T2DM. Methods The retrospective cohort study included 305 patients with pulmonary embolism, divided into two groups: the first group with type 2 diabetes mellitus (n=165) and the control group without type 2 diabetes mellitus (n=140). Data were collected from May 2018 to May 2023. In all patients the following parameters were analysed: anthropometric parameters, laboratory parameters (troponin, D-dimer, CRP, fibrinogen, uric acid, glucose, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides), arterial blood pressure, antiphospholipid antibodies, HOMA-IR index, CT angiography of the pulmonary artery, rate of adverse clinical events in pulmonary embolism (need for inotropic catecholamine support, fibrinolysis, cardiopulmonary resuscitation) and the rate of intrahospital mortality from pulmonary embolism. Results Patients with T2DM had elevated troponin, D-dimer, CRP, uric acid, fibrinogen, HOMA-IR and more severe clinical complications with higher mortality rates within 10 days of hospital admission. Significant predictors of PE in T2DM patients were found. Patients with pulmonary embolism in T2DM had a 4.38 times higher chance of death compared to patients with pulmonary embolism without T2DM. Conclusions Troponin, D-dimer, prothrombotic, and proinflammatory markers have good prognostic value for short-term outcomes in PE among patients with T2DM.

Aim To investigate the correlations between tumour characteristics, symptoms, intraoperative findings, and outcomes in patient with meningioma. Methods A retrospective study was conducted on 86 surgically treated patients at Department of Neurosurgery of Cantonal Hospital Zenica from 2010 to 2020. Patients with intracranial meningiomas underwent neurological evaluation and MRI scans to analyse tumour characteristics, including volume (TV), peritumoral brain oedema (PTBE) and oedema index (EI). Surgical treatment was performed, followed by postoperative MRI and outcome assessment. Intraoperatively, the tumour's relationship with cortex, pial membrane, skull bones, and sinuses was evaluated, and the extent of tumour resection was graded. Meningioma samples underwent histopathological analysis to assess the grade and regularity of borders, and Ki-67 labelling index was determined using immunohistochemistry. Results Significant correlations were found between PTBE and Ki67 expression (p<0.001), PTBE and vomiting/nausea (p=0.002), cognitive impairment (p=0.047), venous compression (p=0.001), cortical, pial and dural invasion (p<0.05), and the postoperative presence of oedema (p=0.002). Venous compression, cortical, pial, dural and bone invasion positively correlated with Ki-67 expression (p<0.001). Grade and tumour border positively correlated with Ki-67 expression (p<0.001). Oedema persistence postoperatively showed a positive correlation with Ki-67 expression (p<0.001). Conclusion The study revealed significant correlations between Ki-67 expression and PTBE, with notable associations with clinical symptoms, tumour characteristics, and postoperative oedema presence.

Aim This study provides a comprehensive review of the current literature on the use of ChatGPT, a generative Artificial Intelligence (AI) tool, in neurosurgery. The study examines potential benefits and limitations of ChatGPT in neurosurgical practice and education. Methods The study involved a systematic review of the current literature on the use of AI in neurosurgery, with a focus on ChatGPT. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to ensure a comprehensive and transparent review process. Thirteen studies met the inclusion criteria and were included in the final analysis. The data extracted from the included studies were analysed and synthesized to provide an overview of the current state of research on the use of ChatGPT in neurosurgery. Results The ChatGPT showed a potential to complement and enhance neurosurgical practice. However, there are risks and limitations associated with its use, including question format limitations, validation challenges, and algorithmic bias. The study highlights the importance of validating machine-generated content for accuracy and addressing ethical concerns associated with AI technologies. The study also identifies potential benefits of ChatGPT, such as providing personalized treatment plans, supporting surgical planning and navigation, and enhancing large data processing efficiency and accuracy. Conclusion The integration of AI technologies into neurosurgery should be approached with caution and careful consideration of ethical and validation issues. Continued research and development of AI tools in neurosurgery can help us further understand their potential benefits and limitations.

UBASH3A and UBASH3B are protein families of atypical protein tyrosine phosphatases that function as regulators of various cellular processes during mammalian development. As UBASH3A has only mild phosphatase activity, its regulatory effects are based on the phosphatase-independent mechanisms. On the contrary, UBASH3B has strong phosphatase activity, and the suppression of its receptor signalling is mediated by Syk and Zap-70 kinases. The regulatory functions of UBASH3A and UBASH3B are particularly evident in the lymphoid tissues and kidney development. These tyrosine phosphatases are also known to play key roles in autoimmunity and neoplasms. However, their involvement in mammalian development and its regulatory functions are largely unknown and are discussed in this review.

Efficiently mapping quantum circuits onto hardware is an integral part of the quantum compilation process, wherein a circuit is modified in accordance with the stringent architectural demands of a quantum processor. Many techniques exist for solving the quantum circuit mapping problem, in addition to several theoretical perspectives that relate quantum circuit mapping to problems in classical computer science. This work considers a novel perspective on quantum circuit mapping, in which the routing process of a simplified circuit is viewed as a composition of quantum operations acting on density matrices representing the quantum circuit and processor. Drawing on insight from recent advances in quantum circuit complexity and information geometry, we show that a minimal SWAP-gate count for executing a quantum circuit on a device emerges via the minimization of the distance between quantum states using the quantum Jensen-Shannon divergence, which we dub the lightcone bound. Additionally, we develop a novel initial placement algorithm based on a graph similarity search that selects the partition nearest to a graph isomorphism between interaction and coupling graphs. From these two ingredients, we construct an algorithm for calculating the lightcone bound, which is directly compared alongside the IBM Qiskit compiler for over $600$ realistic benchmark experiments, as well as against a brute-force method for smaller benchmarks. In our simulations, we unambiguously find that neither the brute-force method nor the Qiskit compiler surpasses our bound, signaling utility for estimating minimal overhead when realizing quantum algorithms on constrained quantum hardware. This work also constitutes the first use of quantum circuit uncomplexity to practically-relevant quantum computing. We anticipate that this method may have diverse applicability outside of the scope of quantum information science.