Simple Summary Mastitis is defined as the inflammation of the mammary gland and is one of the most widespread and economically important diseases of dairy cows. Bacteria are the most reported mastitis-causative agents, while other pathogens are often overlooked because they are not routinely investigated. Incomplete diagnosis may result in inappropriate antimicrobial therapy, treatment failure, antimicrobial resistance, dissemination of pathogens, and mastitis recurrences. Thus, this study aimed to investigate the presence of not only bacteria but also other microorganisms associated with cattle mastitis on dairy farms in Bosnia and Herzegovina, a country that lacks an effective mastitis control programme and bacteriological analysis of mastitic milk. The current study revealed Mycoplasma bovis as the main pathogen and a variety of other mastitis-causing agents in cattle: bacteria (Escherichia coli, Staphylococcus aureus, coagulase negative staphylococci, Streptococcus agalactiae, Streptococcus uberis, and others), fungi (Candida spp.), and algae (Prototheca zopfii). The finding of mastitis cases requiring currently unavailable treatment and vaccines emerges in the broader scope of etiological agents in routine mastitis diagnosis. These measures applied at the herd and national levels are crucial for more effective mastitis control, animal health and welfare, the dairy industry, and public health. Abstract To obtain improved insights into the complex microbial aetiology of bovine mastitis, this study investigated the pathogens involved in cattle mastitis in Bosnia and Herzegovina. A total of 179 milk samples from cows with clinical mastitis (CM) and subclinical mastitis (SCM), as well as eight bulk tank milk (BTM) samples from 48 dairy farms, were analysed by standard bacteriological and mycological methods. Mycoplasma detection and identification were performed using culture techniques and real-time polymerase chain reaction (PCR). A total of 88 (49.2%) mastitis samples were positive for known mastitis pathogens at 32 of 47 farms (68.1%). Mycoplasma bovis was a predominant pathogen (25/187; 13.4%) in the majority of herds (14/48; 29.2%) and accounted for 48.9% of positive CM samples. Escherichia coli was the second most dominant CM pathogen (34%), followed by Streptococcus agalactiae (10.6%), whereas Staphylococcus aureus and coagulase-negative staphylococci were the most common in SCM samples (17.1%). Other mastitis pathogens included Candida spp. and Prototheca zopfii. Two BTM samples were positive for M. bovis only, and one was positive for a mixed culture of S. aureus and Streptococcus uberis. The finding of various causative agents of bovine mastitis, with M. bovis emerging as the main pathogen, emphasizes the significance of comprehensive testing that includes not only common mastitis pathogens but also mycoplasmas, fungi, and algae.

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 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.

This research paper delves into the two-dimensional discrete plant-herbivore model. In this model, herbivores are food-limited and affect the plants' density in their environment. Our analysis reveals that this system has equilibrium points of extinction, exclusion, and coexistence. We analyze the behavior of solutions near these points and prove that the extinction and exclusion equilibrium points are globally asymptotically stable in certain parameter regions. At the boundary equilibrium, we prove the existence of transcritical and period-doubling bifurcations with stable two-cycle. Transcritical bifurcation occurs when the plant's maximum growth rate or food-limited parameter reaches a specific boundary. This boundary serves as an invasion boundary for populations of plants or herbivores. At the interior equilibrium, we prove the occurrence of transcritical, Neimark-Sacker, and period-doubling bifurcations with an unstable two-cycle. Our research also establishes that the system is persistent in certain regions of the first quadrant. We demonstrate that the local asymptotic stability of the interior equilibrium does not guarantee the system's persistence. Bistability exists between boundary attractors (logistic dynamics) and interior equilibrium for specific parameters' regions. We conclude that changes to the food-limitation parameter can significantly alter the system's dynamic behavior. To validate our theoretical findings, we conduct numerical simulations.

Efficiently mapping quantum circuits onto hardware is an integral part of the quantum compilation process, wherein a quantum circuit is modified in accordance with the stringent architectural demands of a quantum processor. Many techniques exist for solving the quantum circuit mapping problem, many of which relate quantum circuit mapping to 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 information theory 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. 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 then construct a polynomial-time algorithm for calculating the SWAP gate lower 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 surpass our bound, implying utility as a precise estimation of minimal overhead when realizing quantum algorithms on constrained quantum hardware. This work 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, and we discuss several of these possibilities.

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.

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.

The aim of this study was to investigate attitudes and preferred therapy choice for first permanent molars (FPM) with Molar-Incisor Hypomineralization (MIH). An online questionnaire was sent out to general dentists (n = 559) working in the Public Dental Service in Region Västra Götaland, orthodontists (n = 293), and pediatric dentists (n = 156) (members from each interest association), in Sweden. The questionnaire contained three parts: general questions regarding the respondents, patient cases, and general questions regarding extraction of FPMs with MIH. Statistics were carried out using Chi-squared tests, with a significance level of 5%. A response rate of 36% was obtained. Orthodontists and pediatric dentists were more prone to extract FPMs with both moderate and severe MIH, compared to general dentists. When restoring FPMs with moderate MIH, resin composite was preferred. Compared to the general dentists, the pediatric dentists were more prone to choose glass-ionomer cement in the FPMs with severe MIH. The most common treatment choice for FPMs with mild MIH was fluoride varnish. “When root furcation is under development of the second permanent molar on radiographs” was chosen as the optimal time for extracting FPMs with severe MIH, and the general dentists based their treatment decisions on recommendations from a pediatric dentist. Extraction of FPMs with moderate and severe MIH is considered a therapy of choice among general dentists and specialists, and the preferred time of extraction is before the eruption of the second permanent molar.

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.