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The synthesis of porous organic 3D frameworks, wherein amine, hydroxyl and Li-alkoxide functions were built directly on the monomer-unit carbon core, realizes improved interactions with target gases. CO2 was retained by the amine group with a remarkable energy of 54 kJ mol−1, while 2D MAS NMR provided rare evidence of amine-to-gas short-distance interactions. Frameworks containing hydroxyl and Li-alkoxide functions show optimal interaction energies with CH4 of up to 25 kJ mol−1. The light network of 3-branch building units ensures the expandability of the nano-sponges. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of robust characteristic polynomial assignment for LTI systems whose parameters are assumed to belong to a semialgebraic uncertainty region. The objective is to design a dynamic fixed-order controller in order to constrain the coefficients of the closed-loop characteristic polynomial within prescribed intervals. First, necessary conditions on the plant parameters for the existence of a robust controller are reviewed, and it is shown that such conditions are satisfied if and only if a suitable Sylvester matrix is nonsingular for all possible values of the uncertain plant parameters. The problem of checking such a robust nonsingularity condition is formulated in terms of a nonconvex optimization problem. Then, the set of all feasible robust controllers is sought through the solution to a suitable robust diophantine equation. Convex relaxation techniques based on sum-of-square decomposition of positive polynomials are used to efficiently solve the formulated optimization problems by means of semidefinite programming. The presented approach provides a generalization of the results previously proposed in the literature on the problem of assigning the characteristic polynomial in the presence of plant parametric uncertainty. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A fast implementation of a given predictive controller for polynomial systems is introduced by approximating the optimal control law with a piecewise constant function defined over a hyper-cube partition of the system state space. Such a state-space partition is computed in order to guarantee stability, an a priori fixed trajectory error as well as input and state constraints fulfilment. The presented approximation procedure is achieved by solving a set of nonconvex polynomial optimization problems, whose approximate solutions are computed by means of semidefinite relaxation techniques for semialgebraic problems. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, a procedure for set-membership identification of block-structured nonlinear feedback systems is presented. Nonlinear block parameter bounds are first computed by exploiting steady-state measurements. Then, given the uncertain description of the nonlinear block, bounds on the unmeasurable inner signal are computed. Finally, linear block parameter bounds are evaluated on the basis of output measurements and computed inner-signal bounds. The computation of both the nonlinear block parameters and the inner-signal bounds is formulated in terms of semialgebraic optimization and solved by means of suitable convex LMI relaxation techniques. The problem of linear block parameter evaluation is formulated in terms of a bounded errors-in-variables identification problem. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Over the last two decades, water smart metering programs have been launched in a number of medium to large cities worldwide to nearly continuously monitor water consumption at the single household level. The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies. Research to date has been focusing on one or more of these aspects but with limited integration between the specialized methodologies developed so far. This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain. The paper contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments. In particular, the future challenges posed by growing population demands, constrained sources of water supply and climate change impacts are expected to require more and more integrated procedures for effectively supporting residential water demand modeling and management in several countries across the world. [ABSTRACT FROM AUTHOR]

Abstract Impacted by a complex mixture of urban, industrial, shipping and also natural emissions, Marseille, the second most populated city in France, represents a very interesting case study for the apportionment of PM 2.5 sources in a Mediterranean urban environment. In this study, daily PM 2.5 samples were collected over a one-year period (2011−2012) at an urban background site, and were comprehensively analyzed for the determination of organic carbon (OC), elemental carbon (EC), major ions, trace elements/metals and specific organic markers. A constrained positive matrix factorization (PMF) analysis using the ME-2 (multilinear engine-2) solver was applied to this dataset. PMF results highlighted the presence of two distinct fingerprints for biomass burning (BB1 and BB2). BB1, assigned to open green waste burning peaks in fall (33%; 7.4 μg m−3) during land clearing periods, is characterized by a higher levoglucosan/OC ratio, while BB2, assigned to residential heating, shows the highest contribution during the cold period in winter (14%; 3.3 μg m−3) and it is characterized by high proportions from lignin pyrolysis products from the combustion of hardwood. Another interesting feature lies in the separation of two fossil fuel combustion processes (FF1 and FF2): FF1 likely dominated by traffic emissions, while FF2 likely linked with the harbor/industrial activities. On annual average, the major contributors to PM 2.5 mass correspond to the ammonium sulfate-rich aerosol (AS-rich, 30%) and to the biomass burning emissions (BB1 + BB2, 23%). This study also outlined that during high PM pollution episodes (PM 2.5 > 25 μg m−3), the largest contributing sources to PM 2.5 were biomass burning (33%) and FF1 (23%). Moreover, 28% of the ambient mass concentration of OC is apportioned by the AS-rich factor, which is representative of an aged secondary aerosol, reflecting thus the importance of the oxidative processes occurring in a Mediterranean environment. Graphical abstract Unlabelled Image Highlights • A constrained PMF analysis (ME2) successfully applied with a large array of organic and inorganic markers. • Two distinct fingerprints for biomass burning resolved. • Two signatures for the fossil fuel combustion processes separated. • Secondary processes and biomass burning emissions are the major contributors to PM 2.5. [ABSTRACT FROM AUTHOR]

Taste perception plays a pivotal role in guiding nutrient intake and aiding in the avoidance of potentially harmful substances through five basic tastes - sweet, bitter, umami, salty, and sour. Taste perception originates from molecular interactions in the oral cavity between taste receptors and chemical tastants. Hence, the recognition of taste receptors and the subsequent perception of taste heavily rely on the physicochemical properties of food ingredients. In recent years, several advances have been made towards the development of machine learning-based algorithms to classify chemical compounds' tastes using their molecular structures. Despite the great efforts, there remains significant room for improvement in developing multi-class models to predict the entire spectrum of basic tastes. Here, we present a multi-class predictor aimed at distinguishing bitter, sweet, and umami, from other taste sensations. The development of a multi-class taste predictor paves the way for a comprehensive understanding of the chemical attributes associated with each fundamental taste. It also opens the potential for integration into the evolving realm of multi-sensory perception, which encompasses visual, tactile, and olfactory sensations to holistically characterize flavour perception. This concept holds promise for introducing innovative methodologies in the rational design of foods, including pre-determining specific tastes and engineering complementary diets to augment traditional pharmacological treatments., (© 2024. The Author(s).)

Inclusion body myositis (IBM) is a slowly progressive disorder belonging to the idiopathic inflammatory myopathies, and it represents the most common adult-onset acquired myopathy. The main clinical features include proximal or distal muscular asymmetric weakness, with major involvement of long finger flexors and knee extensors. The main histological findings are the presence of fiber infiltrations, rimmed vacuoles, and amyloid inclusions. The etiopathogenesis is a challenge because both environmental and genetic factors are implicated in muscle degeneration and a distinction has been made previously between sporadic and hereditary forms. Here, we describe an Italian patient affected with a hereditary form of IBM with onset in his mid-forties. Next-generation sequencing analysis disclosed a heterozygous mutation c.76C>T (p.Pro26Ser) in the PDZ motif of the LDB3/ZASP gene, a mutation already described in a family with a late-onset myopathy and highly heterogenous degree of skeletal muscle weakness. In the proband's muscle biopsy, the expression of ZASP, myotilin, and desmin were increased. In our family, in addition to the earlier age of onset, the clinical picture is even more peculiar given the evidence, in one of the affected family members, of complete ophthalmoplegia in the vertical gaze. These findings help extend our knowledge of the clinical and genetic background associated with inclusion body myopathic disorders.

Pathogenic variants impacting upon assembly of mitochondrial respiratory chain Complex IV (Cytochrome c Oxidase or COX) predominantly result in early onset mitochondrial disorders often leading to CNS, skeletal and cardiac muscle manifestations. The aim of this study is to describe a molecular defect in the COX assembly factor gene COX18 as the likely cause of a neonatal form of mitochondrial encephalo-cardio-myopathy and axonal sensory neuropathy. The proband is a 19-months old female displaying hypertrophic cardiomyopathy at birth and myopathy with axonal sensory neuropathy and failure to thrive developing in the first months of life. Serum lactate was consistently increased. Whole exome sequencing allowed the prioritization of the unreported homozygous substitution NM_001297732.2:c.667 G > C p.(Asp223His) in COX18. Patient's muscle biopsy revealed severe and diffuse COX deficiency and striking mitochondrial abnormalities. Biochemical and enzymatic studies in patient's myoblasts and in HEK293 cells after COX18 silencing showed a severe impairment of both COX activity and assembly. The biochemical defect was partially rescued by delivery of wild-type COX18 cDNA into patient's myoblasts. Our study identifies a novel defect of COX assembly and expands the number of nuclear genes involved in a mitochondrial disorder due to isolated COX deficiency., (© 2023. The Author(s), under exclusive licence to European Society of Human Genetics.)

Isolated mitochondrial respiratory chain Complex IV (Cytochrome c Oxidase or COX) deficiency is the second most frequent isolated respiratory chain defect. Causative mutations are mainly identified in structural COX subunits or in proteins involved in the maturation and assembly of the COX holocomplex. We describe an Italian familial case of mitochondrial myopathy due to a variant in the COX assembly factor 8 gene ( COA8 ). Patient 1 is a 52-year-old woman who presented generalized epilepsy and retinitis pigmentosa at 10 years of age. From her early adulthood she complained about cramps and myalgia after exercise, and bilateral hearing loss emerged. Last neurological examination (52 years of age) showed bilateral ptosis, muscle weakness, peripheral neuropathy, mild dysarthria and dysphonia, cognitive impairment. Muscle biopsy had shown the presence of ragged-red fibers. Patient 2 (Patient 1's sister) is a 53-year-old woman presenting fatigability, myalgia, and hearing loss. Neurological examination showed ptosis and muscle weakness. Muscle biopsy displayed a diffuse reduction of COX activity staining and ragged-red fibers. Both sisters presented secondary amenorrhea. After ruling out mtDNA mutations, Whole Exome Sequencing analysis identified the novel homozygous COA8 defect c.170_173dupGACC, p.(Pro59fs) in the probands. Loss-of-function COA8 mutations have been associated with cavitating leukoencephalopathy with COX deficiency in 9 reported individuals. Disease course shows an early-onset rapid clinical deterioration, affecting both cognitive and motor functions over months, followed by stabilization and slow improvement over several years. Our findings expand the clinical spectrum of COA8 -related disease. We confirm the benign course of this rare disorder, highlighting its (intrafamilial) clinical variability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Rimoldi, Magri, Antognozzi, Ripolone, Salani, Piga, Bertolasi, Zanotti, Ciscato, Fortunato, Moggio, Corti, Comi and Ronchi.)

Background: Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is a systemic disorder in which multi-organ dysfunction may occur from mitochondrial metabolism failure. Maternally inherited mutations in the MT-TL1 gene are the most frequent causes for this disorder. Clinical manifestations may include stroke-like episodes, epilepsy, dementia, headache and myopathy. Among these, acute visual failure, usually in association with cortical blindness, can occur because of stroke-like episodes affecting the occipital cortex or the visual pathways. Vision loss due to optic neuropathy is otherwise considered a typical manifestation of other mitochondrial diseases such as Leber hereditary optic neuropathy (LHON)., Case Presentation: Here we describe a 55-year-old woman, sister of a previously described patient with MELAS harbouring the m.3243A > G (p.0, MT-TL1) mutation, with otherwise unremarkable medical history, that presented with subacute, painful visual impairment of one eye, accompanied by proximal muscular pain and headache. Over the next weeks, she developed severe and progressive vision loss limited to one eye. Ocular examination confirmed unilateral swelling of the optic nerve head; fluorescein angiography showed segmental perfusion delay in the optic disc and papillary leakage. Neuroimaging, blood and CSF examination and temporal artery biopsy ruled out neuroinflammatory disorders and giant cell arteritis (GCA). Mitochondrial sequencing analysis confirmed the m.3243A > G transition, and excluded the three most common LHON mutations, as well as the m.3376G > A LHON/MELAS overlap syndrome mutation. Based on the constellation of clinical symptoms and signs presented in our patient, including the muscular involvement, and the results of the investigations, the diagnosis of optic neuropathy as a stroke-like event affecting the optic disc was performed. L-arginine and ubidecarenone therapies were started with the aim to improve stroke-like episode symptoms and prevention. The visual defect remained stable with no further progression or outbreak of new symptoms., Conclusions: Atypical clinical presentations must be always considered in mitochondrial disorders, even in well-described phenotypes and when mutational load in peripheral tissue is low. Mitotic segregation of mitochondrial DNA (mtDNA) does not allow to know the exact degree of heteroplasmy existent within different tissue, such as retina and optic nerve. Important therapeutic implications arise from a correct diagnosis of atypical presentation of mitochondrial disorders., (© 2023. The Author(s).)

Collagen VI is a heterotrimeric protein expressed in several tissues and involved in the maintenance of cell integrity. It localizes at the cell surface, creating a microfilamentous network that links the cytoskeleton to the extracellular matrix. The heterotrimer consists of three chains encoded by COL6A1 , COL6A2 and COL6A3 genes. Recessive and dominant molecular defects cause two main disorders, the severe Ullrich congenital muscular dystrophy and the relatively mild and slowly progressive Bethlem myopathy. We analyzed the clinical aspects, pathological features and mutational spectrum of 15 COL6-mutated patients belonging to our cohort of muscular dystrophy probands. Patients presented a heterogeneous phenotype ranging from severe forms to mild adult-onset presentations. Molecular analysis by NGS detected 14 different pathogenic variants, three of them so far unreported. Two changes, localized in the triple-helical domain of COL6A1, were associated with a more severe phenotype. Histological, immunological and ultrastructural techniques were employed for the validation of the genetic variants; they documented the high variability in COL6 distribution and the extracellular matrix disorganization, highlighting the clinical heterogeneity of our cohort. The combined use of these different technologies is pivotal in the diagnosis of COL6 patients.

The umami taste is one of the five basic taste modalities normally linked to the protein content in food. The implementation of fast and cost-effective tools for the prediction of the umami taste of a molecule remains extremely interesting to understand the molecular basis of this taste and to effectively rationalise the production and consumption of specific foods and ingredients. However, the only examples of umami predictors available in the literature rely on the amino acid sequence of the analysed peptides, limiting the applicability of the models. In the present study, we developed a novel ML-based algorithm, named VirtuousUmami, able to predict the umami taste of a query compound starting from its SMILES representation, thus opening up the possibility of potentially using such a model on any database through a standard and more general molecular description. Herein, we have tested our model on five databases related to foods or natural compounds. The proposed tool will pave the way toward the rationalisation of the molecular features underlying the umami taste and toward the design of specific peptide-inspired compounds with specific taste properties., (© 2022. The Author(s).)

Perception of taste is an emergent phenomenon arising from complex molecular interactions between chemical compounds and specific taste receptors. Among all the taste perceptions, the dichotomy of sweet and bitter tastes has been the subject of several machine learning studies for classification purposes. While previous studies have provided accurate sweeteners/bitterants classifiers, there is ample scope to enhance these models by enriching the understanding of the molecular basis of bitter-sweet tastes. Towards these goals, our study focuses on the development and testing of several machine learning strategies coupled with the novel SHapley Additive exPlanations (SHAP) for a rational sweetness/bitterness classification. This allows the identification of the chemical descriptors of interest by allowing a more informed approach toward the rational design and screening of sweeteners/bitterants. To support future research in this field, we make all datasets and machine learning models publicly available and present an easy-to-use code for bitter-sweet taste prediction., Competing Interests: No competing interest to be declared., (© 2022 The Authors.)

Introduction: Air pollution exposure is suspected to alter both the incidence and mortality in acute respiratory distress syndrome (ARDS). The impact of chronic air pollutant exposure on the incidence and mortality of ARDS from various aetiologies in Europe remains unknown. The main objective of this study was to evaluate the incidence of ARDS in a large European region, 90-day mortality being the main secondary outcome., Methods: The study was performed in the Provence-Alpes-Cote-d'Azur (PACA) region. Nitrogen dioxide (NO2), particulate matter (PM 2.5 and PM 10 ) and ozone (O3) were measured. The Programme de Médicalisation des Systèmes d'Information (PMSI), which captures all patient hospital stays in France, was used to identify adults coded as ARDS in an intensive care unit., Results: From 2016 to 2018, 4733 adults with ARDS treated in intensive care units were analysed. The incidence rate ratios for 1-year average exposure to PM 2.5 and PM 10 were 1.207 ([95% confidence interval (95% CI), 1.145-1.390]; P < 0.01) and 1.168 (95% CI, 1.083-1.259; P < 0.001), respectively. The same trend was observed for both 2- and 3-year exposures, while only chronic 1- and 2-year exposure NO 2 exposures were related to a higher incidence of ARDS. Increased PM 2.5 exposure was associated with a higher 90-day mortality for both 1- and 3-year exposures (OR 1.096 (95% CI, 1.001-1.201) and 1.078 (95% CI, 1.009-1.152), respectively). O 3 was not associated with either of incidence nor mortality., Conclusions: While chronic exposure to NO2, PM2.5, and PM10 was associated with an increased ARDS incidence and a higher mortality rate (for PM2.5) in those patients presenting with ARDS, further research on this topic is required., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Service robotics is a fast-developing sector, requiring embedded intelligence into robotic platforms to interact with the humans and the surrounding environment. One of the main challenges in the field is robust and versatile manipulation in everyday life activities. An appealing opportunity is to exploit compliant end-effectors to address the manipulation of deformable objects. However, the intrinsic compliance of such grippers results in increased difficulties in grasping control. Within the described context, this work addresses the problem of optimizing the grasping of deformable objects making use of a compliant, under-actuated, sensorless robotic hand. The main aim of the paper is, therefore, finding the best position and joint configuration for the mentioned robotic hand to grasp an unforeseen deformable object based on collected RGB image and partial point cloud. Due to the complex grasping dynamics, learning-from-simulations approaches (e.g., Reinforcement Learning) are not effective in the faced context. Thus, trial-and-error-based methodologies have to be exploited. In order to save resources, a samples-efficient approach has to be employed. Indeed, a Bayesian approach to address the optimization of the grasping strategy is proposed, enhancing it with transfer learning capabilities to exploit the acquired knowledge to grasp (partially) new objects. A PAL Robotics TIAGo (a mobile manipulator with a 7-degrees-of-freedom arm and an anthropomorphic underactuated compliant hand) has been used as a test platform, executing a pouring task while manipulating plastic (i.e., deformable) bottles. The sampling efficiency of the data-driven learning is shown, compared to an evenly spaced grid sampling of the input space. In addition, the generalization capability of the optimized model is tested (exploiting transfer learning) on a set of plastic bottles and other liquid containers, achieving a success rate of the 88%., (© 2022. The Author(s).)

The incidence of cardiac dyspnea (CD) and the distribution of pollution in the south of France suggests that environmental pollution may have a role in disease triggering. CD is a hallmark symptom of heart failure leading to reduced ability to function and engage in activities of daily living. To show the impact of short-term pollution exposure on the increment of CD emergency room visits, we collected pollutants and climate measurements on a daily basis and 43,400 events of CD in the Région Sud from 2013 to 2018. We used a distributed lag non-linear model (DLNM) to assess the association between air pollution and CD events. We divided the region in 357 zones to reconciliate environmental and emergency room visits data. We applied the DLNM on the entire region, on zones grouped by pollution trends and on singular zones. Each pollutant has a significant effect on triggering CD. Depending on the pollutant, we identified four shapes of exposure curves to describe the impact of pollution on CD events: early and late effect for NO 2 ; U-shape and rainbow-shape (or inverted U) for O 3 ; all the four shapes for PM10. In the biggest cities, O 3 has the most significant association along with the PM10. In the west side, a delayed effect triggered by PM10 was found. Zones along the main highway are mostly affected by NO 2 pollution with an increase of the association for a period up to 9 days after the pollution peak. Our results can be used by local authorities to set up specific prevention policies, public alerts that adapt to the different zones and support public health prediction-making. We developed a user-friendly web application called Health, Environment in PACA Region Tool (HEART) to collect our results. HEART will allow citizens, researchers and local authorities to monitor the impact of pollution trends on local public health., (© 2022. The Author(s).)

Taste is a sensory modality crucial for nutrition and survival, since it allows the discrimination between healthy foods and toxic substances thanks to five tastes, i.e., sweet, bitter, umami, salty, and sour, associated with distinct nutritional or physiological needs. Today, taste prediction plays a key role in several fields, e.g., medical, industrial, or pharmaceutical, but the complexity of the taste perception process, its multidisciplinary nature, and the high number of potentially relevant players and features at the basis of the taste sensation make taste prediction a very complex task. In this context, the emerging capabilities of machine learning have provided fruitful insights in this field of research, allowing to consider and integrate a very large number of variables and identifying hidden correlations underlying the perception of a particular taste. This review aims at summarizing the latest advances in taste prediction, analyzing available food-related databases and taste prediction tools developed in recent years., Supplementary Information: The online version contains supplementary material available at 10.1007/s00217-022-04044-5., Competing Interests: Conflict of interestThe authors declare no conflict interests., (© The Author(s) 2022.)

In the present paper we propose a novel blind docking protocol based on Autodock-Vina. The developed docking protocol can provide binding site identification and binding pose prediction at the same time, by a systematical exploration of the protein volume performed with several preliminary docking calculations. In our opinion, this protocol can be successfully applied during the first steps of the virtual screening pipeline, because it provides binding site identification and binding pose prediction at the same time without visual evaluation of the binding site. After the binding pose prediction, MM/GBSA re-scoring rescoring procedures has been applied to improve the accuracy of the protein-ligand bound state. The FRAD protocol has been tested on 116 protein-ligand complexes of the Heat Shock Protein 90 - alpha, on 176 of Human Immunodeficiency virus protease 1, and on more than 100 protein-ligand system taken from the PDBbind dataset. Overall, the FRAD approach combined to MM/GBSA re-scoring can be considered as a powerful tool to increase the accuracy and efficiency with respect to other standard docking approaches when the ligand-binding site is unknown.Communicated by Ramaswamy H. Sarma.

Ryanodine receptor type 1-related congenital myopathies are the most represented subgroup among congenital myopathies (CMs), typically presenting a central core or multiminicore muscle histopathology and high clinical heterogeneity. We evaluated a cohort of patients affected with Ryanodine receptor type 1-related congenital myopathy ( RYR1 -RCM), focusing on four patients who showed a severe congenital phenotype and underwent a comprehensive characterization at few months of life. To date there are few reports on precocious instrumental assessment. In two out of the four patients, a muscle biopsy was performed in the first days of life (day 5 and 37, respectively) and electron microscopy was carried out in two patients detecting typical features of congenital myopathy. Two patients underwent brain MRI in the first months of life (15 days and 2 months, respectively), one also a fetal brain MRI. In three children electromyography was performed in the first week of life and neurogenic signs were excluded. Muscle MRI obtained within the first years of life showed a typical pattern of RYR1 -CM. The diagnosis was confirmed through genetic analysis in three out of four cases using Next Generation Sequencing (NGS) panels. The development of a correct and rapid diagnosis is a priority and may lead to prompt medical management and helps optimize inclusion in future clinical trials., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The Handling Editor declared a past co-authorship with several of the authors VN, DC, GC, and FM., (Copyright © 2021 Mauri, Piga, Govoni, Brusa, Pagliarani, Ripolone, Dilena, Cinnante, Sciacco, Cassandrini, Nigro, Bresolin, Corti, Comi and Magri.)

Background: Several models have been developed to predict mortality in patients with COVID-19 pneumonia, but only a few have demonstrated enough discriminatory capacity. Machine learning algorithms represent a novel approach for the data-driven prediction of clinical outcomes with advantages over statistical modeling., Objective: We aimed to develop a machine learning-based score-the Piacenza score-for 30-day mortality prediction in patients with COVID-19 pneumonia., Methods: The study comprised 852 patients with COVID-19 pneumonia, admitted to the Guglielmo da Saliceto Hospital in Italy from February to November 2020. Patients' medical history, demographics, and clinical data were collected using an electronic health record. The overall patient data set was randomly split into derivation and test cohorts. The score was obtained through the naïve Bayes classifier and externally validated on 86 patients admitted to Centro Cardiologico Monzino (Italy) in February 2020. Using a forward-search algorithm, 6 features were identified: age, mean corpuscular hemoglobin concentration, PaO 2 /FiO 2 ratio, temperature, previous stroke, and gender. The Brier index was used to evaluate the ability of the machine learning model to stratify and predict the observed outcomes. A user-friendly website was designed and developed to enable fast and easy use of the tool by physicians. Regarding the customization properties of the Piacenza score, we added a tailored version of the algorithm to the website, which enables an optimized computation of the mortality risk score for a patient when some of the variables used by the Piacenza score are not available. In this case, the naïve Bayes classifier is retrained over the same derivation cohort but using a different set of patient characteristics. We also compared the Piacenza score with the 4C score and with a naïve Bayes algorithm with 14 features chosen a priori., Results: The Piacenza score exhibited an area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI 0.74-0.84, Brier score=0.19) in the internal validation cohort and 0.79 (95% CI 0.68-0.89, Brier score=0.16) in the external validation cohort, showing a comparable accuracy with respect to the 4C score and to the naïve Bayes model with a priori chosen features; this achieved an AUC of 0.78 (95% CI 0.73-0.83, Brier score=0.26) and 0.80 (95% CI 0.75-0.86, Brier score=0.17), respectively., Conclusions: Our findings demonstrated that a customizable machine learning-based score with a purely data-driven selection of features is feasible and effective for the prediction of mortality among patients with COVID-19 pneumonia., (©Geza Halasz, Michela Sperti, Matteo Villani, Umberto Michelucci, Piergiuseppe Agostoni, Andrea Biagi, Luca Rossi, Andrea Botti, Chiara Mari, Marco Maccarini, Filippo Pura, Loris Roveda, Alessia Nardecchia, Emanuele Mottola, Massimo Nolli, Elisabetta Salvioni, Massimo Mapelli, Marco Agostino Deriu, Dario Piga, Massimo Piepoli. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.05.2021.)

An anionic mechanism is used to create polymers and copolymers as confined to, or anchored to, high-surface-area porous nanoparticles. Linear polymers with soft and glassy chains, such as polyisoprene and polymethylmethacrylate, were produced by confined anionic polymerization in 3D networks of porous aromatic frameworks. Alternatively, multiple anions were generated on the designed frameworks which bear removal protons at selected positions, and initiate chain propagation, resulting in chains covalently connected to the 3D network. Such growth can continue outside the pores to produce polymer-matrix nanoparticles coated with anchored chains. Sequential reactions were promoted by the living character of this anionic propagation, yielding nanoparticles that were covered by a second polymer anchored by anionic block copolymerization. The intimacy of the matrix and the grown-in polymers was demonstrated by magnetization transfer across the interfaces in 2D 1 H- 13 C-HETCOR NMR spectra., (© 2020 Wiley-VCH GmbH.)

Biallelic TYMP variants result in the mitochondrial neurogastrointestinal encephalomyopathy (MNGIE), a juvenile-onset disorder with progressive course and fatal outcome. Milder late-onset (>40 years) form has been rarely described. Gene panel sequencing in a cohort of 60 patients featuring muscle accumulation of mitochondrial DNA (mtDNA) deletions detected TYMP defects in three subjects (5%), two of them with symptom onset in the fifth decade. One of the patients only displayed ptosis and ophthalmoparesis. Biochemical and molecular studies supported the diagnosis. Screening of TYMP is recommended in adult patients with muscle mtDNA instability, even in the absence of cardinal MNGIE features., (Copyright © 2020 Ronchi, Caporali, Manenti, Meneri, Mohamed, Bordoni, Tagliavini, Contin, Piga, Sciacco, Saetti, Carelli and Comi.)

It has been over half a century since polyacrylonitrile (PAN)-based carbon fibers were first developed. However, the mechanism of the carbonization reaction remains largely unknown. Structural evolution of PAN during the preoxidation reaction, a stabilization reaction, is one of the most complicated stages because many chemical reactions, including cyclization, dehydration, and cross-linking reactions, simultaneously take place. Here, we report the stabilization reaction of single PAN chains within the one-dimensional nanochannels of metal-organic frameworks (MOFs) to study an effect of interchain interactions on the stabilization process as well as the structure of the resulting ladder polymer (LP). The stabilization reaction of PAN within the MOFs could suppress the rapid generation of heat that initiates the self-catalyzed reaction and inevitably provokes many side-reactions and scission of PAN chains in the bulk state. Consequently, LP prepared within the MOFs had a more extended conjugated backbone than the bulk condition., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The maintenance of mitochondrial DNA (mtDNA) relies on proteins encoded by nuclear genes. Mutations in their coding sequences result in heterogenous clinical presentations featuring mtDNA instability in affected tissues. DNA2 is a multi-catalytic protein involved in the removal of single strand DNA during mtDNA replication or Long Patch Base Excision Repair pathway. We have previously described DNA2 mutations in adult patients affected with familial and sporadic forms of mitochondrial myopathy. Here we describe four novel probands presenting with limb weakness associated with novel DNA2 molecular defects. Biochemical assays were established to investigate the functional effects of these variants., (© 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.)

Duchenne and Becker muscular dystrophies are the most common muscle diseases and are both currently incurable. They are caused by mutations in the dystrophin gene, which lead to the absence or reduction/truncation of the encoded protein, with progressive muscle degeneration that clinically manifests in muscle weakness, cardiac and respiratory involvement and early death. The limits of animal models to exactly reproduce human muscle disease and to predict clinically relevant treatment effects has prompted the development of more accurate in vitro skeletal muscle models. However, the challenge of effectively obtaining mature skeletal muscle cells or satellite stem cells as primary cultures has hampered the development of in vitro models. Here, we discuss the recently developed technologies that enable the differentiation of skeletal muscle from human induced pluripotent stem cells (iPSCs) of Duchenne and Becker patients. These systems recapitulate key disease features including inflammation and scarce regenerative myogenic capacity that are partially rescued by genetic and pharmacological therapies and can provide a useful platform to study and realize future therapeutic treatments. Implementation of this model also takes advantage of the developing genome editing field, which is a promising approach not only for correcting dystrophin, but also for modulating the underlying mechanisms of skeletal muscle development, regeneration and disease. These data prove the possibility of creating an accurate Duchenne and Becker in vitro model starting from iPSCs, to be used for pathogenetic studies and for drug screening to identify strategies capable of stopping or reversing muscular dystrophinopathies and other muscle diseases., Competing Interests: Conflict of interest statement: The authors declare that there is no conflict of interest.

Background: Leber's hereditary optic neuropathy (LHON) is a mitochondrial disease characterized by visual loss consequent to optic nerve atrophy. In some cases, LHON is associated with heterogeneous neurological extraocular manifestations and is referred to as "Leber plus disease"; rarely it is associated with a multiple sclerosis (MS)-like syndrome known as Harding disease, but no pediatric extraocular acute spinal onset is reported., Case Presentation: We describe the case of a 5-year-old girl carrying the G3460A mtDNA mutation who was referred to clinical examination for bilateral upper and lower limb weakness with no sign of optic neuropathy. Spinal cord MRI showed hyperintense signal alterations in T2-weighted and restricted diffusion in DWI sequences in the anterior portion of the cervical and dorsal spinal cord resembling a spinal cord vascular injury. No association between this mutation and pediatric spinal cord lesions has previously been reported. Alternative diagnostic hypotheses, including infective, ischemic and inflammatory disorders, were not substantiated by clinical and instrumental investigations., Conclusions: Our case reports a novel pediatric clinical manifestation associated with the m.3460G > A mtDNA mutation, broadening the clinical spectrum of this disease. Early identification of new cases and monitoring of carriers beginning in childhood is important to prevent neurological deterioration and preserve long-term function.

The synthesis of porous organic 3D frameworks, wherein amine, hydroxyl and Li-alkoxide functions were built directly on the monomer-unit carbon core, realizes improved interactions with target gases. CO2 was retained by the amine group with a remarkable energy of 54 kJ mol-1, while 2D MAS NMR provided rare evidence of amine-to-gas short-distance interactions. Frameworks containing hydroxyl and Li-alkoxide functions show optimal interaction energies with CH4 of up to 25 kJ mol-1. The light network of 3-branch building units ensures the expandability of the nano-sponges.

Sporadic cases account for 90-95% of all patients with Parkinson's Disease (PD). Atypical Parkinsonism comprises approximately 20% of all patients with parkinsonism. Progressive Supranuclear Palsy (PSP) belongs to the atypical parkinsonian diseases and is histopathologically classified as a tauopathy. Here, we report that mesenchymal stem cells (MSCs) derived from the bone marrow of patients with PSP exhibit mitochondrial dysfunction in the form of decreased membrane potential and inhibited NADH-dependent respiration. Furthermore, mitochondrial dysfunction in PSP-MSCs led to a significant increase in mitochondrial ROS generation and oxidative stress, which resulted in decrease of major cellular antioxidant GSH. Additionally, higher basal rate of mitochondrial degradation and lower levels of biogenesis were found in PSP-MSCs, together leading to a reduction in mitochondrial mass. This phenotype was biologically relevant to MSC stemness properties, as it heavily impaired their differentiation into adipocytes, which mostly rely on mitochondrial metabolism for their bioenergetic demand. The defect in adipogenic differentiation was detected as a significant impairment of intracellular lipid droplet formation in PSP-MSCs. This result was corroborated at the transcriptional level by a significant reduction of PPARγ and FABP4 expression, two key genes involved in the adipogenic molecular network. Our findings in PSP-MSCs provide new insights into the etiology of 'idiopathic' parkinsonism, and confirm that mitochondrial dysfunction is important to the development of parkinsonism, independent of the type of the cell., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)