The operation of a dissipative network composed of two or three different crown‐ether receptors and an alkali metal cation can be temporally driven by the use (combined or not) of two orthogonal ...stimuli of a different nature. More specifically, irradiation with light at a proper wavelength and/or addition of an activated carboxylic acid, are used to modulate the binding capability of the above crown‐ethers towards the metal ion, allowing to control over time the occupancy of the metal cation in the crown‐ether moiety of a given ligand. Thus, application of either or both of the stimuli to an initially equilibrated system, where the metal cation is distributed among the crown‐ether receptors depending on the different affinities, causes a programmable change in the receptor occupancies. Consequently, the system is induced to evolve to one or more out‐of‐equilibrium states with different distributions of the metal cation among the different receptors. When the fuel is exhausted or/and the irradiation interrupted, the system reversibly and autonomously goes back to the initial equilibrium state. Such results may contribute to the achievement of new dissipative systems that, taking advantage of multiple and orthogonal stimuli, are featured with more sophisticated operating mechanisms and time programmability.
The motions of an alkali cation from and to the crown‐ether moieties of different ligands (up to three) is controlled over time and in a dissipative fashion by contextually employing two orthogonal stimuli, namely a radiative one and a chemical one. When the stimuli are no longer supplied, moving from out‐of‐equilibrium states, the system reversibly returns to its equilibrium state.
Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep ...learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention.
Summary
We explored the relevance of genomic microarrays (GM) in the refinement of prognosis in newly diagnosed low‐risk chronic lymphocytic leukaemia (CLL) patients as defined by isolated del(13q) ...or no lesions by a standard 4 probe fluorescence in situ hybridization (FISH) analysis. Compared to FISH, additional lesions were detected by GM in 27 of the 119 patients (22.7%). The concordance rate between FISH and GM was 87.4%. Discordant results between cytogenetic banding analysis (CBA) and GM were observed in 45/119 cases (37.8%) and were mainly due to the intrinsic characteristics of each technique. The presence of additional lesions by GM was associated with age > 65 years (p = 0.047), advanced Binet stage (p = 0.001), CLL‐IPI score (p < 0.001), a complex karyotype (p = 0.004) and a worse time‐to‐first treatment in multivariate analysis (p = 0.009). Additional lesions by GM were also significantly associated with a worse time‐to‐first treatment in the subset of patients with wild‐type TP53 and mutated IGHV (p = 0.025). In CLL patients with low‐risk features, the presence of additional lesions identified by GM helps to identify a subset of patients with a worse outcome that could be proposed for a risk‐adapted follow‐up and for early treatment including targeted agents within clinical trials.
In newly diagnosed low‐risk CLL patients as defined by a standard 4 probe FISH analysis, additional lesions by GM were detected in 27 out of 119 patients (22.7%). The presence of additional lesions was associated with a shorter TTFT, independently of CLL‐IPI. Additional lesions by GM were also associated with a shorter TTFT in the subset of patients with wild type TP53 and mutated IGHV. In low‐risk CLL, the presence of additional lesions by GM helps to identify a subset of patients with worse outcome that could be proposed for a risk‐adapted follow‐up and early treatments including targeted agents within clinical trials.
The 5' and 3' untranslated regions of eukaryotic mRNAs (UTRs) play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, ...translation efficiency, subcellular localization, and message stability. Since 1996, we have developed and maintained UTRdb, a specialized database of UTR sequences. Here we present UTRdb 2.0, a major update of UTRdb featuring an extensive collection of eukaryotic 5' and 3' UTR sequences, including over 26 million entries from over 6 million genes and 573 species, enriched with a curated set of functional annotations. Annotations include CAGE tags and polyA signals to label the completeness of 5' and 3'UTRs, respectively. In addition, uORFs and IRES are annotated in 5'UTRs as well as experimentally validated miRNA targets in 3'UTRs. Further annotations include evolutionarily conserved blocks, Rfam motifs, ADAR-mediated RNA editing events, and m6A modifications. A web interface allowing a flexible selection and retrieval of specific subsets of UTRs, selected according to a combination of criteria, has been implemented which also provides comprehensive download facilities. UTRdb 2.0 is accessible at http://utrdb.cloud.ba.infn.it/utrdb/.
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more ...comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.
This work reports that the composition of a dynamic library (DL) of interconverting imines can be controlled over time in a dissipative fashion by the addition of an activated carboxylic acid used as ...a chemical fuel. When the fuel is added to the DL, which is initially under thermodynamic equilibrium, the composition of the mixture dramatically changes and a new, dissipative (out of equilibrium) state is reached that persists until fuel exhaustion. Thus, a transient dissipative dynamic library (DDL) is generated that, eventually, reverts back to the initial DL when the fuel is consumed, closing a DL→DDL→DL cycle. The larger the amount of added fuel, the longer the time spent by the system in the DDL state. The transimination reaction is shown to be an optimal candidate for the realization of a dissipative dynamic covalent chemistry (DDCvC).
Dissipative dynamic libraries (DDLs) of imines are generated by addition of 2‐cyano‐2‐(4’‐chloro)phenylpropanoic acid employed as a chemical fuel to equilibrated dynamic libraries (DLs). At the addition of the fuel the initial composition of the library dictated by the thermodynamic equilibrium is perturbed and a transient, temporal controllable, out of equilibrium state is obtained, which reverts to the initial equilibrium when the fuel is exhausted.
Aim
Paediatric eosinophilia is a common clinical dilemma, often leading to resource‐ and time‐consuming assessments. We aim to evaluate the main aetiologies of eosinophilia in children from different ...socioeconomic settings and propose a diagnostic algorithm.
Methods
A systematic literature review was conducted through PubMed, Embase and the Cochrane Library. Studies published from January 2012 to June 2023 reporting the incidence and aetiology of peripheral eosinophilia in children were included. Evidence from studies on children originating from low‐ or high‐income countries was compared.
Results
A total of 15 observational studies, encompassing 3409 children, were included. The causes of eosinophilia varied based on the children's origin and the eosinophilia severity. In children from high‐income countries, allergic diseases were the leading cause, with a prevalence of 7.7%–78.2%, while parasitosis ranged from 1.0% to 9.1%. In children from low‐income countries, parasitosis was predominant, ranging from 17.7% to 88.3%, although allergic diseases were found in 2.5%–4.8% of cases. Concerning severity, allergic diseases were the leading cause of mild‐to‐moderate eosinophilia; parasitosis was associated with moderate‐to‐severe eosinophilia, while immunological disorders were mostly found in severe cases.
Conclusion
We developed a step‐up diagnostic algorithm that considers the child's origin and eosinophilia severity and could optimise resource allocation.
Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of ...precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments.
MicroRNAs (miRNAs) are emerging as biomarkers for the detection and prognosis of cancers due to their inherent stability and resilience. To summarize the evidence regarding the role of urinary miRNAs ...(umiRNAs) in the detection, prognosis, and therapy of genitourinary cancers, we performed a systematic review of the most important scientific databases using the following keywords: (urinary miRNA) AND (prostate cancer); (urinary miRNA) AND (bladder cancer); (urinary miRNA) AND (renal cancer); (urinary miRNA) AND (testicular cancer); (urinary miRNA) AND (urothelial cancer). Of all, 1364 articles were screened. Only original studies in the English language on human specimens were considered for inclusion in our systematic review. Thus, a convenient sample of 60 original articles was identified. UmiRNAs are up- or downregulated in prostate cancer and may serve as potential non-invasive molecular biomarkers. Several umiRNAs have been identified as diagnostic biomarkers of urothelial carcinoma and bladder cancer (BC), allowing us to discriminate malignant from nonmalignant forms of hematuria. UmiRNAs could serve as therapeutic targets or recurrence markers of non-muscle-invasive BC and could predict the aggressivity and prognosis of muscle-invasive BC. In renal cell carcinoma, miRNAs have been identified as predictors of tumor detection, aggressiveness, and progression to metastasis. UmiRNAs could play an important role in the diagnosis, prognosis, and therapy of urological cancers.
Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has ...potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.
PDF
