ABSTRACT
In a first-of-its-kind study, we assessed the capabilities of large language models (LLMs) in making complex decisions in haematopoietic stem cell transplantation. The evaluation was conducted not only for Generative Pre-trained Transformer 4 (GPT-4) but also conducted on other artificial intelligence models: PaLm 2 and Llama-2. Using detailed haematological histories that include both clinical, molecular and donor data, we conducted a triple-blind survey to compare LLMs to haematology residents. We found that residents significantly outperformed LLMs (p = 0.02), particularly in transplant eligibility assessment (p = 0.01). Our triple-blind methodology aimed to mitigate potential biases in evaluating LLMs and revealed both their promise and limitations in deciphering complex haematological clinical scenarios.
Subject(s)
Artificial Intelligence , Hematopoietic Stem Cell Transplantation , Humans , Language , Tissue DonorsABSTRACT
Disease progression to accelerated/blast phase (AP/BP) in patients with chronic phase chronic myeloid leukemia (CP-CML) after treatment discontinuation (TD) has never been systematically reported in clinical trials. However, recent reports of several such cases has raised concern. To estimate the risk of AP/BP among TD-eligible patients, we conducted TFR-PRO, a cohort retro-prospective study: 870 CP-CML patients eligible for TD formed a discontinuation cohort (505 patients) and a reference one (365 patients). The primary objective was the time adjusted rate (TAR) of progression in relation to TD. Secondary endpoints included the TAR of molecular relapse, that is, loss of major molecular response (MMR). With a median follow up of 5.5 years and 5188.2 person-years available, no events occurred in the TD cohort. One event of progression was registered 55 months after the end of TD, when the patient was contributing to the reference cohort. The TAR of progression was 0.019/100 person-years (95% CI [0.003-0.138]) in the overall group; 0.0 (95% CI [0-0.163]) in the discontinuation cohort; and 0.030 (95% CI [0.004-0.215]) in the reference cohort. These differences are not statistically significant. Molecular relapses occurred in 172/505 (34.1%) patients after TD, and in 64/365 (17.5%) patients in the reference cohort, p < .0001. Similar rates were observed in TD patients in first, second or third line of treatment. CML progression in patients eligible for TD is rare and not related to TD. Fears about the risk of disease progression among patients attempting TD should be dissipated.
ABSTRACT
Cognitive impairments figure prominently in COVID-19 survivors. Cognitive remediation therapy (CRT) improves functional outcomes reducing long-term cognitive deficits in several neurological and psychiatric conditions. Our case-control study investigates the efficacy of a CRT programme administered to COVID-19 survivors in the post-acute phase of the illness. Seventy-three COVID-19 survivors presenting cognitive impairments at one-month follow-up were enrolled. Among them, 15 patients were treated with a two-month CRT programme, and 30 non-treated patients were matched conditional to their baseline cognitive functioning. Cognitive functions were assessed before and after treatment. Depression and quality of life were also evaluated. Mixed model ANOVA revealed a significant effect over time of the CRT programme on global cognitive functioning (F = 4.56, p = 0.039), while no significant effect was observed in the untreated group. We observed a significant effect of the improvement in verbal fluency (χ2 = 7.20, p = 0.007) and executive functions (χ2 = 13.63, p < 0.001) on quality of life. A positive significant correlation was found between depressive symptomatology and verbal fluency (r = -0.35), working memory (r = -0.44), psychomotor coordination (r = -0.42), and executive functions (r = -0.33). Our results could pave the way to a plausible innovative treatment targeting cognitive impairments and ameliorating the quality of life of COVID-19 survivors.
Subject(s)
COVID-19 , Cognitive Dysfunction , Cognitive Remediation , Humans , Quality of Life , Case-Control Studies , Cognition , SurvivorsABSTRACT
The grail of gene delivery is the development of delivery vectors as effective and non-cytotoxic as possible. In this regard, there is an urgent need of new tools for the straightforward and quantitative assessment of transfection efficiency and cytotoxicity simultaneously. We herein reported the development and validation of an easy-to-use lab-on-chip platform to perform cell transfection assays for unbiased, high-throughput selection of more and more effective gene delivery vectors by using two commercially sourced lipids, Lipofectamine 2000® and FuGene® 6. A single PDMS-layer platform was endowed with: i) a chaotic serial dilution generator, designed for the automatic generation of a linear lipoplex dilution (from 100% to 0% with 25% steps) independently delivered to; and ii) the downstream culture and transfection module consisting in five units, each composed of 33 serially connected and fluidically connected culture chambers for trapping small populations of ≈10 cells/chamber. In the absence of any transfectant, cells spread and duplicated up to 2 days. Besides, cells were transfected with EGFP-encoding reporter gene. The very facile visual inspection of the microdevice by means of a microscope and a semi-automated analytical method allowed pinpointing the best transfection conditions in terms of efficiency, cytotoxicity, cell doubling rates, and morphological changes at once.
Subject(s)
Gene Transfer Techniques , Genetic Vectors , Lab-On-A-Chip Devices , Genetic Vectors/genetics , Genetic Vectors/pharmacology , HeLa Cells , HumansABSTRACT
To unveil possible changes in diatom communities in Cypriot streams over the last ten years or so, we selected samples from the years 2020, 2021, and 2022 for the "recent" dataset (N = 119) and samples from the years 2010 and 2011 for the "historical" dataset (N = 108). Biotic homogenization has become a truly global phenomenon. Here we show that, over the last ten years, in response to increased water temperature, conductivity, and discharge variability due to climate-change, Cypriot stream diatom communities include a higher number of trivial (= widespread, tolerant, and opportunistic), aerial, and thermophilic species, have reduced ß-diversity and increased nestedness. Moreover, IndVal analysis shows that indicator species from the historical dataset were characteristic, often relatively rare species, while the indicators of the recent dataset were a group of typical trivial, eutraphentic, and thermophilic species. As is almost always the case, the diatom communities we studied were subjected to multiple stressors, often affecting them in opposite ways. Besides the increase in trivial species, the reduction in ß-diversity, and the rise in nestedness mentioned above, the diatom assemblages we studied also showed an increase in α-diversity that could be due to a moderate reduction in nutrients in several sites. High-ecological-integrity ecosystems, such as springs, waterfalls, and dripping rock-walls, in particular springs that were shown to be excellent hydrologic refugia in climates heavily affected by climate change, and the stream sites close to them should be carefully protected, as they can be refugia for sensitive and characteristic species that can recolonize the adjacent streams after adverse climatic events.
Subject(s)
Climate Change , Diatoms , Rivers , Environmental Monitoring , Biodiversity , EcosystemABSTRACT
An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy. Our novel analytical pipeline integrated different machine learning algorithms to harmonize data, perform data dimensionality reduction, and provide a stability-based relative clustering validation. The obtained clusters were characterized for immune-inflammatory peripheral biomarkers, TRD, history of childhood trauma and depressive symptoms. Our results indicated two different clusters of patients, differentiable with 67 % of accuracy: one cluster (n = 59) was associated with a higher proportion of TRD, and higher scores of energy-related depressive symptoms, history of childhood abuse and emotional neglect; this cluster showed a widespread reduction in cortical thickness (d = 0.43-1.80) and volumes (d = 0.45-1.05), along with fractional anisotropy in the fronto-occipital fasciculus, stria terminalis, and corpus callosum (d = 0.46-0.52); the second cluster (n = 43) was associated with cognitive and affective depressive symptoms, thicker cortices and wider volumes. Multivariate analyses revealed distinct brain-inflammation relationships between the two clusters, with increase in pro-inflammatory markers being associated with decreased cortical thickness and volumes. Our stratification of MDD patients based on structural neuroimaging identified clinically-relevant subgroups of MDD with specific symptomatic and immune-inflammatory profiles, which can contribute to the development of tailored personalized interventions for MDD.
Subject(s)
Biomarkers , Depressive Disorder, Major , Depressive Disorder, Treatment-Resistant , Humans , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/immunology , Female , Male , Adult , Depressive Disorder, Treatment-Resistant/diagnostic imaging , Middle Aged , Brain/diagnostic imaging , Brain/pathology , Magnetic Resonance Imaging/methods , Neuroimaging/methods , Gray Matter/diagnostic imaging , Gray Matter/pathology , Machine Learning , Adverse Childhood Experiences , White Matter/diagnostic imaging , White Matter/pathologyABSTRACT
Cognitive impairment represents a leading residual symptom of COVID-19 infection, which lasts for months after the virus clearance. Up-to-date scientific reports documented a wide spectrum of brain changes in COVID-19 survivors following the illness's resolution, mainly related to neurological and neuropsychiatric consequences. Preliminary insights suggest abnormal brain metabolism, microstructure, and functionality as neural under-layer of post-acute cognitive dysfunction. While previous works focused on brain correlates of impaired cognition as objectively assessed, herein we investigated long-term neural correlates of subjective cognitive decline in a sample of 58 COVID-19 survivors with a multimodal imaging approach. Diffusion Tensor Imaging (DTI) analyses revealed widespread white matter disruption in the sub-group of cognitive complainers compared to the non-complainer one, as indexed by increased axial, radial, and mean diffusivity in several commissural, projection and associative fibres. Likewise, the Multivoxel Pattern Connectivity analysis (MVPA) revealed highly discriminant patterns of functional connectivity in resting-state among the two groups in the right frontal pole and in the middle temporal gyrus, suggestive of inefficient dynamic modulation of frontal brain activity and possible metacognitive dysfunction at rest. Beyond COVID-19 actual pathophysiological brain processes, our findings point toward brain connectome disruption conceivably translating into clinical post-COVID cognitive symptomatology. Our results could pave the way for a potential brain signature of cognitive complaints experienced by COVID-19 survivors, possibly leading to identify early therapeutic targets and thus mitigating its detrimental long-term impact on quality of life in the post-COVID-19 stages.
Subject(s)
COVID-19 , Cognitive Dysfunction , Humans , Diffusion Tensor Imaging/methods , Quality of Life , COVID-19/complications , Brain/physiology , Magnetic Resonance Imaging/methods , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/etiology , Cognitive Dysfunction/pathology , Cognition , SurvivorsABSTRACT
BACKGROUND: For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings. AIMS: To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample. METHODS: We studied 100 MDD inpatients admitted to our psychiatric ward, treated with various antidepressants upon clinical need. Hamilton Depression Rating Scale percentage decrease from admission to discharge was used as a measure of response. All patients underwent 3.0 T MRI scanning. Grey matter (GM) volumes were investigated both in a voxel-based morphometry (VBM), and in a regions of interest (ROI) analysis. In a subsample of patients, functional resting-state connectivity patterns were also explored. RESULTS: In the VBM analysis, worse response was associated to lower GM volumes in two clusters, encompassing the left hippocampus and parahippocampal gyrus, and the right superior and middle temporal gyrus. Investigating ROIs, lower bilateral hippocampi and amygdalae volumes predicted worse treatment outcomes. Functional connectivity in the right temporal and parahippocampal gyrus was also associated to response. CONCLUSION: Our results expand existing literature on the relationship between the structure and function of several brain regions and treatment response in MDD. While we are still far from routine use of MRI biomarkers in clinical practice, we confirm a possible role of these techniques in guiding treatment choices and predicting their efficacy.
Subject(s)
Depressive Disorder, Major , Humans , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/drug therapy , Depression , Brain , Antidepressive Agents/therapeutic use , Neuroimaging , Hippocampus/pathology , Magnetic Resonance Imaging/methods , BiomarkersABSTRACT
Applying machine learning (ML) to objective markers may overcome prognosis uncertainty due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA-compliant meta-analysis provides new systematic evidence of the BD classification accuracy reached by different markers and ML algorithms. We focused on neuroimaging, electrophysiological techniques, peripheral biomarkers, genetic data, neuropsychological or clinical measures, and multimodal approaches. PubMed, Embase and Scopus were searched through 3rd December 2020. Meta-analyses were performed using random-effect models. Overall, 81 studies were included in this systematic review and 65 in the meta-analysis (11,336 participants, 3903 BD). The overall pooled classification accuracy was 0.77 (95%CI[0.75;0.80]). Despite subgroup analyses for diagnostic comparison group, psychiatric disorders, marker, ML algorithm, and validation procedure were not significant, linear discriminant analysis significantly outperformed support vector machine for peripheral biomarkers (p = 0.03). Sample size was inversely related to accuracy. Evidence of publication bias was detected. Ultimately, although ML reached a high accuracy in differentiating BD from other psychiatric disorders, best practices in methodology are needed for the advancement of future studies.
Subject(s)
Bipolar Disorder , Algorithms , Biomarkers , Bipolar Disorder/diagnosis , Humans , Machine Learning , NeuroimagingABSTRACT
Boosting antitumor immunity has emerged as a powerful strategy in cancer treatment. While releasing T-cell brakes has received most attention, tumor recognition by T cells is a pre-requisite. Radiotherapy and certain cytotoxic drugs induce the release of damage-associated molecular patterns, which promote tumor antigen cross-presentation and T-cell priming. Antibodies against the "do not eat me" signal CD47 cause macrophage phagocytosis of live tumor cells and drive the emergence of antitumor T cells. Here we show that CXCR4 activation, so far associated only with tumor progression and metastasis, also flags tumor cells to immune recognition. Both CXCL12, the natural CXCR4 ligand, and BoxA, a fragment of HMGB1, promote the release of DAMPs and the internalization of CD47, leading to protective antitumor immunity. We designate as Immunogenic Surrender the process by which CXCR4 turns in tumor cells to macrophages, thereby subjecting a rapidly growing tissue to immunological scrutiny. Importantly, while CXCL12 promotes tumor cell proliferation, BoxA reduces it, and might be exploited for the treatment of malignant mesothelioma and a variety of other tumors.
Subject(s)
CD47 Antigen , Mesothelioma , Animals , Cell Line, Tumor , Immunization , Macrophages , Mesothelioma/immunology , Mesothelioma/metabolism , Mesothelioma/therapy , Mice , PhagocytosisABSTRACT
The paper discusses a Smoothed Particle Hydrodynamics (SPH) model for the analysis of the multiphase flow occurring in an experimental microfluidic device for conformal coating of pancreatic islets with a biocompatible and permeable polymer. The proposed numerical model, based on a weakly-compressible SPH approach, accurately mimics the encapsulation process while assuring phase conservation, thus overcoming potential limitations of grid-based models. The proposed SPH model is a triphasic multi-phase model that allows one: (i) to reproduce the physics of islet conformal coating, including the effects of surface tension at the interface of the involved fluids and of the islet diameter; and (ii) to evaluate how modulation of process parameters influences the fluid dynamics within the microfluidic device and the resulting coating characteristics. This model can represent a valuable, time- and cost-effective tool for the definition of optimized encapsulation conditions through in silico screening of novel combinations of conformal coating parameters, including polymeric coating blends, size range of insulin-secreting cell clusters, utilized chemical reagents, device geometry and scale.
Subject(s)
Hydrodynamics , Islets of Langerhans , Lab-On-A-Chip Devices , Models, Theoretical , Surface Tension , Time FactorsABSTRACT
Nuclear factor (NF)-κB controls the transcriptional response to inflammatory signals by translocating into the nucleus, but we lack a single-cell characterization of the resulting transcription dynamics. Here we show that upon tumor necrosis factor (TNF)-α transcription of NF-κB target genes is heterogeneous in individual cells but results in an average nascent transcription profile that is prompt (i.e., occurs almost immediately) and sharp (i.e., increases and decreases rapidly) compared with NF-κB nuclear localization. Using an NF-κB-controlled MS2 reporter we show that the single-cell nascent transcription is more heterogeneous than NF-κB translocation dynamics, with a fraction of synchronized "first responders" that shape the average transcriptional profile and are more prone to respond to multiple TNF-α stimulations. A mathematical model combining NF-κB-mediated gene activation and a gene refractory state is able to reproduce these features. Our work shows how the expression of target genes induced by transcriptional activators can be heterogeneous across single cells and yet time resolved on average.
ABSTRACT
Nuclear positioning within cells is important for multiple cellular processes in development and regeneration. The most intriguing example of nuclear positioning occurs during skeletal muscle differentiation. Muscle fibers (myofibers) are multinucleated cells formed by the fusion of muscle precursor cells (myoblasts) derived from muscle stem cells (satellite cells) that undergo proliferation and differentiation. Correct nuclear positioning within myofibers is required for the proper muscle regeneration and function. The common procedure to assess myoblast differentiation and myofiber formation relies on fixed cells analyzed by immunofluorescence, which impedes the study of nuclear movement and cell behavior over time. Here, we describe a method for the analysis of myoblast differentiation and myofiber formation by live cell imaging. We provide a software for automated nuclear tracking to obtain a high-throughput quantitative characterization of nuclear dynamics and myoblast behavior (i.e., the trajectory) during differentiation and fusion.
Subject(s)
Cell Differentiation , Cell Nucleus/metabolism , Molecular Imaging , Myoblasts/cytology , Animals , Cell Fusion , Cell Survival , Mice , Muscle, Skeletal/cytology , Satellite Cells, Skeletal Muscle/cytologyABSTRACT
In this review, we aim at describing the results obtained in the past years on dynamics features defining NF-κB regulatory functions, as we believe that these developments might have a transformative effect on the way in which NF-κB involvement in cancer is studied. We will also describe technical aspects of the studies performed in this context, including the use of different cellular models, culture conditions, microscopy approaches and quantification of the imaging data, balancing their strengths and limitations and pointing out to common features and to some open questions. Our emphasis in the methodology will allow a critical overview of literature and will show how these cutting-edge approaches can contribute to shed light on the involvement of NF-κB deregulation in tumour onset and progression. We hypothesize that this “dynamic point of view” can be fruitfully applied to untangle the complex relationship between NF-κB and cancer and to find new targets to restrain cancer growth.
ABSTRACT
After many years of basic research, regenerative medicine (RM) is now beginning to represent a valuable tool to cure several clinical conditions in both acute injuries and chronic diseases. The aim of this study is to update readers on current clinical applications of some selected organs and pathologies which may benefit from RM. An extensive literature research was performed using PubMed, Google and specialized journals. RM has achieved great successes, but there are still several challenges to tackle before it could be used on a daily basis in clinical practice. The crucial point of this revolution is represented by the appropriate and valid translation from bench to bedside.
ABSTRACT
PURPOSE: Malignant peripheral nerve sheath tumor (MPNST) can arise sporadically or in association with neurofibromatosis type 1. Deletions at the 9p21 locus have been reported in these tumors. To additionally characterize the status of this chromosomal region, in this study we performed a comprehensive, mostly PCR-based molecular analysis of the three tumor suppressor genes p15(INK4b), p14(ARF) and p16(INK4a) located at the 9p21 locus in 26 cryopreserved MPNSTs. EXPERIMENTAL DESIGN: Fourteen neurofibromatosis type 1-related and 12 sporadic cases were investigated for homozygous deletion coupled with fluorescent in situ hybridization, promoter methylation, and mutational analysis, as well as m-RNA expression. RESULTS: The results showed that an inactivation of one or more genes occurred in 77% of MPNSTs and was mainly achieved through homozygous deletion (46%), which, in turn, encompassed all of the three tandemly linked genes in 83% of the deleted cases. Promoter methylation was at a less extent involved in gene silencing (18%), and no mutations were found. Loss of function at DNA level strongly correlated with loss of mRNA expression accounting for 80% of the cases. Because of the close relationship between p14(ARF) and TP53 and between p15(INK4b)/p16(INK4a) and Rb, these results support a model of a coinactivation of TP53 and Rb pathways in 75% of MPNSTs, with functional consequences on cell growth control and apoptosis. CONCLUSIONS: The inactivation of the 9p21 locus is a frequent and peculiar hallmark of MPNST genetic profile leading also to an impaired apoptosis that could be taken into account in treatment planning of these tumors.
Subject(s)
Cell Cycle Proteins/genetics , Cyclin-Dependent Kinase Inhibitor p16/genetics , Nerve Sheath Neoplasms/genetics , Neurofibromatosis 1/genetics , Peripheral Nervous System Neoplasms/genetics , Tumor Suppressor Protein p14ARF/genetics , Tumor Suppressor Proteins/genetics , Adult , Aged , Base Sequence , Cell Cycle Proteins/antagonists & inhibitors , Cyclin-Dependent Kinase Inhibitor p15 , Cyclin-Dependent Kinase Inhibitor p16/antagonists & inhibitors , DNA Primers , Female , Humans , In Situ Hybridization, Fluorescence , Male , Middle Aged , Nerve Sheath Neoplasms/pathology , Neurofibromatosis 1/pathology , Peripheral Nervous System Neoplasms/pathology , Polymerase Chain Reaction , Tumor Suppressor Protein p14ARF/antagonists & inhibitors , Tumor Suppressor Proteins/antagonists & inhibitorsABSTRACT
Terrestrial life in Antarctica has been described as some of the simplest on the planet, and mainly confined to soil microfaunal communities. Studies have suggested that the lack of diversity is due to extreme environmental conditions and thought to be driven by abiotic factors. In this study we investigated soil microfauna composition, abundance, and distribution in East Antarctica, and assessed correlations with soil geochemistry and environmental variables. We examined 109 soil samples from a wide range of ice-free habitats, spanning 2000 km from Framnes Mountains to Bailey Peninsula. Microfauna across all samples were patchily distributed, from complete absence of invertebrates to over 1600 specimens/gram of dry weight of soil (gdw), with highest microfauna abundance observed in samples with visible vegetation. Bdelloid rotifers were on average the most widespread found in 87% of sampled sites and the most abundant (44 specimens/gdw). Tardigrades occurred in 57% of the sampled sites with an abundance of 12 specimens/gdw. Nematodes occurred in 71% of samples with a total abundance of 3 specimens/gdw. Ciliates and mites were rarely found in soil samples, with an average abundance of 1.3 and 0.04 specimens/gdw, respectively. We found that microfaunal composition and abundance were mostly correlated with the soil geochemical parameters; phosphorus, NO3 (-) and salinity, and likely to be the result of soil properties and historic landscape formation and alteration, rather than the geographic region they were sampled from. Studies focusing on Antarctic biodiversity must take into account soil geochemical and environmental factors that influence population and species heterogeneity.
Subject(s)
Biota/physiology , Ecotype , Soil , Animals , Antarctic RegionsABSTRACT
Intense blooms of the benthic dinoflagellate Ostreopsis cf. ovata have occurred in the northern Adriatic Sea since 2006. These blooms are associated with noxious effects on human health and with the mortality of benthic organisms because of the production of palytoxin-like compounds. The O. cf. ovata bloom and its relationships with nutrient concentrations at two stations on the Conero Riviera (northern Adriatic Sea) were investigated in the summer of 2009. O. cf. ovata developed from August to November, with the highest abundances in September (1.3×10(6) cells g(-1) fw corresponding to 63.8×10(3) cells cm(-2)). The presence of the single O. cf. ovata genotype was confirmed by a PCR assay. Bloom developed when the seawater temperature was decreasing. Nutrient concentrations did not seem to affect bloom dynamics. Toxin analysis performed by high resolution liquid chromatography-mass spectrometry revealed a high total toxin content (up to 75 pg cell(-1)), including putative palytoxin and all the ovatoxins known so far.
Subject(s)
Dinoflagellida/chemistry , Dinoflagellida/genetics , Harmful Algal Bloom , Marine Toxins/toxicity , Seawater/analysis , Ulva/chemistry , Acrylamides/chemistry , Analysis of Variance , Chromatography, High Pressure Liquid , Cnidarian Venoms , Dinoflagellida/physiology , Marine Toxins/analysis , Marine Toxins/chemistry , Mass Spectrometry , Mediterranean Sea , Microscopy, Fluorescence , Molecular Structure , Polymerase Chain Reaction , Population Dynamics , TemperatureABSTRACT
The stereoselective addition of aryl- and alkylacetylene derivatives to imines was studied. The reaction is catalyzed by copper complexes of enantiomerically pure bisimines, readily prepared in very high yields from the commercially available binaphthyl diamine. A very simple experimental procedure allowed to obtain at room temperature optically active propargylamines in high yields and enantioselectivity. Interestingly, bisimine/copper(I) complexes were able to promote the direct, enantioselective, catalytic addition to imines of alkylacetylenes. The effects of catalyst loading and other reaction parameters on the stereochemical outcome of the transformation were investigated. The extremely convenient methodology, the mild reaction conditions, and the possibility of a modular approach for developing new and more efficient bisimine-based chiral ligands make the present methodology very attractive.
Subject(s)
Amines/chemical synthesis , Copper/chemistry , Imines/chemistry , Pargyline/analogs & derivatives , Acetylene/analogs & derivatives , Acetylene/chemistry , Alkynes/chemistry , Catalysis , Ligands , StereoisomerismABSTRACT
New enantiomerically pure macrocycles have been prepared by combining 1,10-phenanthroline 2,9-dicarboxylic acid and two alpha-amino-acids linked through spacers. Different diamine linkers have been employed in order to modify the dimensions and the properties of the macrocycles whose structures have been studied by 1H and 13C NMR spectroscopy. The ability of the (L)-valine containing macrocycles to bind metal ions and phenolic molecules has been investigated by 1H NMR experiments and Molecular Mechanics calculations.