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The development of composite materials with thermo-optical properties based on smart polymeric systems and nanostructures have been extensively studied. Due to the fact of its ability to self-assemble into a structure that generates a significant change in the refractive index, one of most attractive thermo-responsive polymers is poly( N -isopropylacrylamide) (PNIPAM), as well as its derivatives such as multiblock copolymers. In this work, symmetric triblock copolymers of polyacrylamide (PAM) and PNIPAM (PAM x - b -PNIPAM y - b -PAM x ) with different block lengths were prepared by reversible addition-fragmentation chain-transfer polymerization (RAFT). The ABA sequence of these triblock copolymers was obtained in only two steps using a symmetrical trithiocarbonate as a transfer agent. The copolymers were combined with gold nanoparticles (AuNPs) to prepare nanocomposite materials with tunable optical properties. The results show that copolymers behave differently in solution due to the fact of variations in their composition. Therefore, they have a different impact on the nanoparticle formation process. Likewise, as expected, an increase in the length of the PNIPAM block promotes a better thermo-optical response.

Long document summarization poses obstacles to current generative transformer-based models because of the broad context to process and understand. Indeed, detecting long-range dependencies is still challenging for today's state-of-the-art solutions, usually requiring model expansion at the cost of an unsustainable demand for computing and memory capacities. This paper introduces Emma, a novel efficient memory-enhanced transformer-based architecture. By segmenting a lengthy input into multiple text fragments, our model stores and compares the current chunk with previous ones, gaining the capability to read and comprehend the entire context over the whole document with a fixed amount of GPU memory. This method enables the model to deal with theoretically infinitely long documents, using less than 18 and 13 GB of memory for training and inference, respectively. We conducted extensive performance analyses and demonstrate that Emma achieved competitive results on two datasets of different domains while consuming significantly less GPU memory than competitors do, even in low-resource settings.

Environmental health literacy (EHL) includes knowledge of health effects due to environmental exposure and skills to protect health from environmental risks. This study investigated some aspects about EHL of the Italian adult population. Data were collected through questionnaires ( n = 672) and analysed through multivariable logistic regression models. Results showed that participants with incomplete/insufficient self-perceived knowledge of health effects due to environmental risks verified less information about this topic (adjOR = 0.38 (CI95% 0.25-0.59)/0.09 (0.04-0.21); p < 0.001/<0.001), potentially spreading fake news. The self-perceived exposure to pollution was higher in participants living in towns than in rural areas (small, medium, big towns adjOR = 2.37 (1.41-3.97), 2.10 (1.11-3.96), 3.11 (1.53-6.31); p = 0.001, 0.022, 0.002) and lower in participants with incomplete/insufficient knowledge about pollution effects (adjOR = 0.54 (0.32-0.92)/0.30 (0.13-0.67); p = 0.022/0.004), confirming that knowledge is essential to achieve awareness. Since insufficient self-perceived knowledge of pollution effects was negatively associated with the adoption of pro-environmental behaviours (adjOR = 0.37 (0.15-0.90); p = 0.028), EHL was proven to be a virtuous behaviour promoter. Finally, a lack of institutional support, time and cost were identified as barriers to pro-environmental behaviours. This study provided useful data to design prevention programmes, underlined some barriers to pro-environmental behaviours and highlighted the need to promote attitudes and behaviours aimed at contrasting environmental pollution, thus protecting human health.

Cyberaggression (CyA) embraces a broad spectrum of hostile behaviors through electronic means. This cross-sectional study aimed to evaluate features and outcomes of this phenomenon among Italian adults. A nationwide survey was distributed on social media platforms. Being victim and being perpetrator of CyA were the primary outcomes; positive scores for GAD-2 (generalized anxiety disorder) and PHQ-2 (depressive symptoms) scales were the secondary outcomes. In total, 446 surveys were collected. Considering the primary outcomes, 46.3% and 13.5% reported having been victims and perpetrators of CyA, respectively. Politics, ethnic minority, and sexual orientation were main subjects triggering CyA. A higher likelihood of being cyber-victims was observed for women and the LGBTQA+ group. Women were less likely to be CyA perpetrators. There was an association between being a CyA victim and a CyA perpetrator. A total of 22.4% and 34.0% respondents scored positive for PHQ-2 and GAD-2, respectively. The main mental health consequences after CyA exposure were anger and sadness, whereas sleep alterations and stomach ache were the most experienced psychosomatics symptoms. No significant relationships between PHQ-2/GAD-2 and CyA emerged. CyA also represents a crucial public health issue among Italian adults. Further investigations are needed to better define the phenomenon and to study the potential consequences on mental health.

The modulation of nanoparticles' size, shape, and dispersion by polymers has attracted particular attention in different fields. Nevertheless, there is a lack of information regarding the use of charged macromolecules as assistants in the nanostructures' nucleation and growth processes. Prompted by this, the in situ synthesis of gold nanoparticles (AuNPs) aided by hydrolyzed polyacrylamides (HPAM), with different chemical structures, was developed. In contrast to the conventional synthesis of nanostructures assisted by polyacrylamide, here, the polymerization, hydrolysis, and nanostructure formation processes were carried out simultaneously in the same milieu. Likewise, the growing chains acted as a template for the nanoparticles' growth, so their conformations and chemical structure, especially the amount of charges along the chain, played an important role in the AuNPs' morphology, size, and some of the final composite features. The nanocomposite was thoroughly characterized with appropriate techniques, including ATR-FTIR, GPC, UV-Vis, and SEM.

The COVID-19 pandemic has been accompanied by an infodemic, which includes fake news (FNs) and conspiracy theories (CTs), and which may worsen vaccine refusal (VR), thus hindering the control of the transmission. This study primarily aimed to assess COVID-19 VR in Italy and its relationship with belief in FNs/CTs. Secondarily, it explored the conviction in FNs and CTs and associated variables. An online cross-sectional study was conducted in Italy (2021). The primary outcome was VR and secondary outcomes were FN misclassification score (0% to 100%: higher score means higher misclassification) and CT belief score (1 to 5: higher score means higher agreement). There were 1517 participants; 12.3% showed VR. The median FN and CT scores were: 46.7% (IQR = 40-56.7%) and 2.8 (IQR = 2.2-3.4). Age, education, FN, and CT scores had significant associations with VR. Education, economic situation, health and e-health literacy showed significant relationships with secondary outcomes. Study/work background had a significant association only with the FN score. FN and CT scores were associated. This work estimated a VR lower than before the first COVID-19 vaccine approval. The relationship between VR and FN/CT belief represents a new scenario, suggesting the need for planning effective strategies to tackle FNs and CTs to implement successful vaccination campaigns.

The need for an anti-COVID-19 booster dose posed an organizational challenge for health policy makers worldwide. Therefore, this study aimed to explore the health policies regarding the booster dose through an overview of recommendations issued in high-income countries. Between 10 November and 16 December 2021, the authors searched for state-level official documents about the offer of the booster dose, considering the 43 countries belonging to the European Union (EU) or the Organisation for Economic Co-operation and Development (OECD). Mainly due to the lack of English translation, 15 countries were excluded. A total of 135 documents were selected. Almost all the countries started administering the booster dose between September and November 2021. The most used products were mRNA vaccines, followed by Vaxzevria-AstraZeneca and Jcovden-Janssen/Johnson & Johnson. All countries established criteria to define categories of individuals to be vaccinated as a priority. A six/five-months interval was the main choice for general population vaccinated with mRNA vaccines, while shorter intervals were chosen for vulnerable individuals or other vaccines. Despite diversities related to the differences in health systems, economical resources, and population numbers, and the need to adapt all these factors to a massive vaccination campaign, a progressive convergence towards the same vaccination policies was highlighted.

Medical students (MSs) are healthcare workers and must also cope with education-related stressors. This study aims to assess factors associated with perceived stress in Italian MSs. A cross-sectional study was conducted in 12 Italian medical schools (MSCs) in November 2018. A questionnaire assessed socio-demographic characteristics, habits, opinions about MSC, and concerns about the future. Stress was assessed with the PSS-10. Descriptive and univariable tests were performed. A linear model was fitted to find associations of the PSS-10 score with characteristics. There were 2513 collected questionnaires. Median PSS-10 score was 18 (IQR 11). Median age was 22 (IQR 4) and 61% of the sample was female. Female gender, being part of a sexual minority, poor financial situation, competitive atmosphere, having hobbies, resting, and sleeping hindered by MSC were characteristics associated with higher PSS-10 scores. Current relationship, good family relationship, and no concerns about the future were protective factors. Being part of sexual minorities had greater effects in students not living away from home, while in the other group it was not having satisfying friendships. Medical students suffer higher levels of stress than the general population, and many MSC stressors are associated. Living away from home modifies risk and protective factors, offering the possibility to tailor group-specific interventions.

This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstacles' materials, and radar-obstacle distances. We examine two main scenarios according to the radar position: (i) placed on top of a mobile cart; (ii) handheld at different heights. We empirically analyze and compare several input representations and machine learning (ML) methods-supervised and unsupervised, symbolic and non-symbolic-according to both their accuracy in detecting NLOS human beings and their adaptability to unseen cases. Our study proves the effectiveness and flexibility of modern ML techniques, avoiding environment-specific configurations and benefiting from knowledge transference. Unlike traditional TLC approaches, ML allows for generalization, overcoming limits due to unknown or only partially known observation models and insufficient labeled data, which usually occur in emergencies or in the presence of time/cost constraints.

Gemfibrozil (GEM) is an orally administered lipid-regulating fibrate derivative drug sold under the brand name Lopid ® , among others. Since its approval in the early 80s, GEM has been largely applied to treat hypertriglyceridemia and other disorders of lipid metabolism. Though generally well tolerated, GEM can alter the distribution and the free, active concentration of some co-administered drugs, leading to adverse effects. Most of them appear to be related to the ability of GEM to bind with high affinity human serum albumin (HSA), the major drug-carrier protein in blood plasma. Here, we report the crystal structure of HSA in complex with GEM. Two binding sites have been identified, namely Sudlow's binding sites I (FA7) and II (FA3-FA4). A comparison of the crystal structure of HSA in complex with GEM with those of other previously described HSA-drug complexes enabled us to appreciate the analogies and differences in their respective binding modes. The elucidation of the molecular interaction between GEM and HSA might offer the basis for the development of novel GEM derivatives that can be safely and synergistically co-administered with other drugs, enabling augmented therapeutic efficacies.

The automatic extraction of biomedical events from the scientific literature has drawn keen interest in the last several years, recognizing complex and semantically rich graphical interactions otherwise buried in texts. However, very few works revolve around learning embeddings or similarity metrics for event graphs. This gap leaves biological relations unlinked and prevents the application of machine learning techniques to promote discoveries. Taking advantage of recent deep graph kernel solutions and pre-trained language models, we propose Deep Divergence Event Graph Kernels (DDEGK), an unsupervised inductive method to map events into low-dimensional vectors, preserving their structural and semantic similarities. Unlike most other systems, DDEGK operates at a graph level and does not require task-specific labels, feature engineering, or known correspondences between nodes. To this end, our solution compares events against a small set of anchor ones, trains cross-graph attention networks for drawing pairwise alignments (bolstering interpretability), and employs transformer-based models to encode continuous attributes. Extensive experiments have been done on nine biomedical datasets. We show that our learned event representations can be effectively employed in tasks such as graph classification, clustering, and visualization, also facilitating downstream semantic textual similarity. Empirical results demonstrate that DDEGK significantly outperforms other state-of-the-art methods.

The literature on coronaviruses counts more than 300,000 publications. Finding relevant papers concerning arbitrary queries is essential to discovery helpful knowledge. Current best information retrieval (IR) use deep learning approaches and need supervised training sets with labeled data, namely to know a priori the queries and their corresponding relevant papers. Creating such labeled datasets is time-expensive and requires prominent experts' efforts, resources insufficiently available under a pandemic time pressure. We present a new self-supervised solution, called SUBLIMER, that does not require labels to learn to search on corpora of scientific papers for most relevant against arbitrary queries. SUBLIMER is a novel efficient IR engine trained on the unsupervised COVID-19 Open Research Dataset (CORD19), using deep metric learning. The core point of our self-supervised approach is that it uses no labels, but exploits the bibliography citations from papers to create a latent space where their spatial proximity is a metric of semantic similarity; for this reason, it can also be applied to other domains of papers corpora. SUBLIMER, despite is self-supervised, outperforms the Precision@5 (P@5) and Bpref of the state-of-the-art competitors on CORD19, which, differently from our approach, require both labeled datasets and a number of trainable parameters that is an order of magnitude higher than our.

The primary aim was to evaluate the burnout prevalence among healthcare workers (HCWs) in intensive care units (ICUs) and emergency departments (EDs) during the COVID-19 pandemic. The secondary aim was to identify factors associated with burnout in this population. A systematic review was conducted following PRISMA guidelines by searching PubMed, Embase, PsychINFO, and Scopus from 1 January to 24 November 2020. Studies with information about burnout prevalence/level during the pandemic regarding ICU/ED HCWs were eligible. A total of 927 records were identified. The selection resulted in 11 studies. Most studies were conducted in April/May 2020. Samples ranged from 15 to 12,596 participants. The prevalence of overall burnout ranged from 49.3% to 58%. Nurses seemed to be at higher risk. Both socio-demographic and work-related features were associated with burnout. Many pandemic-related variables were associated with burnout, e.g., shortage in resources, worry regarding COVID-19, and stigma. This review highlighted a substantial burnout prevalence among ICU/ED HCWs. However, this population has presented a high burnout prevalence for a long time, and there is not sufficient evidence to understand if such prevalence is currently increased. It also outlined modifiable factors and the need to improve emergency preparedness both from an individual and structural level.

The increasing prevalence of mental health disorders and psychosocial distress among young people exceeds the capacity of mental health services. Social and systemic factors determine mental health as much as individual factors. To determine how best to address multi-level risk factors, we must first understand the distribution of risk. Previously, we have used psychometric methods applied to two epidemiologically-principled samples of people aged 14-24 to establish a robust, latent common mental distress (CMD) factor of depression and anxiety normally distributed across the population. This was linearly associated with suicidal thoughts and non-suicidal self-harm such that effective interventions to reduce CMD across the whole population could have a greater total benefit than those that focus on the minority with the most severe scores. In a randomised trial of mindfulness interventions in university students (the Mindful Student Study), we demonstrated a population-shift effect whereby the intervention group appeared resilient to a universal stressor. Given these findings, and in light of the COVID-19 pandemic, we argue that population-based interventions to reduce CMD are urgently required. To target all types of mental health determinants, these interventions must be multi-level. Careful design and evaluation, interdisciplinary work, and extensive local stakeholder involvement are crucial for these interventions to be effective.

Heavy metals ions (HMI), if not properly handled, used and disposed, are a hazard for the ecosystem and pose serious risks for human health. They are counted among the most common environmental pollutants, mainly originating from anthropogenic sources, such as agricultural, industrial and/or domestic effluents, atmospheric emissions, etc. To face this issue, it is necessary not only to determine the origin, distribution and the concentration of HMI but also to rapidly (possibly in real-time) monitor their concentration levels in situ. Therefore, portable, low-cost and high performing analytical tools are urgently needed. Even though in the last decades many analytical tools and methodologies have been designed to this aim, there are still several open challenges. Compared with the traditional analytical techniques, such as atomic absorption/emission spectroscopy, inductively coupled plasma mass spectrometry and/or high-performance liquid chromatography coupled with electrochemical or UV-VIS detectors, bio- and biomimetic electrochemical sensors provide high sensitivity, selectivity and rapid responses within portable and user-friendly devices. In this review, the advances in HMI sensing in the last five years (2016-2020) are addressed. Key examples of bio and biomimetic electrochemical, impedimetric and electrochemiluminescence-based sensors for Hg 2+ , Cu 2+ , Pb 2+ , Cd 2+ , Cr 6+ , Zn 2+ and Tl + are described and discussed.

Given the limited evidence of school closure effectiveness in containing the pandemic and the consequences for young people, reopening schools with appropriate measures is essential. This overview aimed to describe the main measures planned for the 2020-2021 academic year within the WHO European Region. A rapid systematic review of scientific databases was also performed. The websites of the government, Ministry of Health, and Ministry of Education of European Region countries were searched through 1 October for official documents about the prevention and management of suspected cases/confirmed cases in primary and secondary schools. To find further suggestions, a rapid systematic review was conducted through 20 October searching Pubmed, Scopus, and Embase. There were 23 official documents. France, Luxembourg, Malta, Ireland, Italy, Portugal, the UK, Spain, and San Marino were considered. Performing the rapid review, 855 records were identified and 7 papers were finally selected. The recommendations mostly agreed. However, there was no consensus on the criteria for the return to school of students that tested positive, and the flexibility between attendance at school and remote education for high-risk children often varied. School closure was commonly considered as the very last resort for COVID-19 control. Studies are required to evaluate the impact of different recommendations during this autumn term.

Italy was the first European country that entered a nationwide lockdown during the COVID-19 pandemic. Since quarantine can impact on mental health, this study aimed to estimate the prevalence of depressive symptoms, anxiety symptoms and sleeping disturbances in the Italian population during lockdown. The factors that might influence such outcomes were explored. A national cross-sectional survey was performed during the last 14 days of the Italian lockdown. Questionnaires assessed socio-demographics characteristic, behaviors and healthcare access. The outcomes were assessed using Patient Health Questionnaire-2 and Generalized Anxiety Disorder-2. Participants with sleep disturbances completed the Insomnia Severity Index. The sample size was 1515. Depression and anxiety symptom prevalence was 24.7% and 23.2%; 42.2% had sleep disturbances and, among them, 17.4% reported moderate/severe insomnia. Being female, an increased time spent on the internet and an avoidance of activities through peer pressure increased the likelihood of at least one mental health outcome. Increasing age, an absence of work-related troubles and being married or being a cohabitant reduced such a probability. Females and participants with chronic conditions were associated with a higher prevalence of sleep disturbances. It is crucial to study effective interventions, specifically planning strategies, for more vulnerable groups and to consider the role of the internet., Competing Interests: The authors declare no conflict of interest.

There is a growing interest in the technological transfer of highly performing electrochemical sensors within portable analytical devices for the in situ monitoring of environmental contaminants, such as perfluorooctanesulfonic acid (PFOS). In the redesign of biomimetic sensors, many parameters should be taken into account from the working conditions to the electrode surface roughness. A complete characterization of the surface modifiers can help to avoid time-consuming optimizations and better interpret the sensor responses. In the present study, a molecularly imprinted polymer electrochemical sensor (MIP) for PFOS optimized on gold disk electrodes was redesigned on commercial gold screen-printed electrodes. However, its performance investigated by differential pulse voltammetry was found to be poor. Before proceeding with further optimization, a morphological study of the bare and modified electrode surfaces was carried out by scanning electron microscopy-energy-dispersive X-ray spectrometry (SEM-EDS), atomic force microscopy (AFM) and profilometry revealing an heterogeneous distribution of the polymer strongly influenced by the electrode roughness. The high content of fluorine of the target-template molecule allowed to map the distribution of the molecularly imprinted polymer before the template removal and to define a characterization protocol. This case study shows the importance of a multi-analytical characterization approach and identify significant parameters to be considered in similar redesigning studies.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease (unknown pathogenesis) of the central nervous system that causes death within 1-5 years. Clinically, flabby paralysis, areflexia, muscular atrophy, and muscle fasciculations, signs of II motor neuron damage, appear. Sometimes, clinical manifestations of damage of the I motor neuron come out in lower limbs; spastic paralysis, iperflexia, and clonus emerge, and they impair deambulation and management of activities of daily living, such as personal hygiene or dressing. Thus, the first therapeutic approach in these patients involves antispasmodic drugs orally followed by botulinum toxin type A injection (BTX-A). In this study, we study the efficacy of BTX-A and physiotherapy in lower limb spasticity due to ALS and no response to treatment with oral antispastic drugs. We evaluated 15 patients (10 male and five female), with a mean age of 48.06 ± 5.2 with spasticity of adductor magnus (AM), at baseline (T0, before BTX-A treatment) and in the following three follow-up visits (T1 30 days, T2 60 days, and T3 90 days after infiltration). We evaluated myometric measure of muscle tone, the Modified Ashworth Scale of AM, Barthel Index, Adductor Tone Rating Scale, and Hygiene Score. The study was conducted between November 2018 and April 2019. We treated AM with incobotulinum toxin type A (Xeomin ® , Merz). Spasticity (myometric measurement, Adductor Tone Rating Scale, and Modified Ashworth Scale) and clinical (Barthel Index and Hygiene Score) improvements were obtained for 90 days after injection ( p < 0.05). Our study shows the possibility of using BTX-A in the treatment of spasticity in patients with ALS and no response to oral antispastic drugs, with no side effects. The limitation of the study is the small number of patients and the limited time of observation; therefore, it is important to increase both the number of patients and the observation time in future studies.

Many neurological diseases (ischemic and hemorrhagic stroke, multiple sclerosis, infant cerebral palsy, spinal cord injuries, traumatic brain injury, and other cerebrovascular disorders) may cause muscle spasticity. Different therapeutic strategies have been proposed for the treatment of spasticity. One of the major treatments for tone modulation is botulinum toxin type A (BTX-A), performed in addition to other rehabilitation strategies based on individualized multidisciplinary programs aimed at achieving certain goals for each patient. Therapeutic plans must be precisely defined as they must balance the reduction of spastic hypertonia and retention of residual motor function. To perform and optimize the treatment, an accurate clinical and instrumental evaluation of spasticity is needed to determine how this symptom is invalidating and to choose the best doses, muscles and times of injection in each patient. We introduce an &ldquo;appropriate treatment&rdquo; and no &ldquo;standard or high dosage treatment&rdquo; concept based on our retrospective observational study on 120 patients lasting two years, according to the larger Therapeutic Index and Therapeutic Window of Incobotulinumtoxin A doses from 100 to 1000 units. We studied the efficiency and safety of this drug considering the clinical spasticity significance for specialist physicians and patients.

We report single crystal X-ray diffraction (hereafter, SCXRD) analyses of derivatives featuring the electron-donor N-ethylcarbazole or the (4-diphenylamino)phenyl moieties associated with a -CN group attached to a double bond. The compounds are (2Z)-3-(4-(diphenylamino)-phenyl)-2-(pyridin-3-yl)prop-2-enenitrile (I), (2Z)-3-(4-(diphenylamino)phenyl)-2-(pyridin-4-yl)-prop-2-enenitrile (II) and (2Z)-3-(9-ethyl-9H-carbazol-3-yl)-2-(pyridin-2-yl)enenitrile (III). SCXRD analyses reveal that I and III crystallize in the monoclinic space groups P2/c with Z' = 2 and C2/c with Z' = 1, respectively. Compound II crystallized in the orthorhombic space group Pbcn with Z' = 1. The molecular packing analysis was conducted to examine the pyridine core effect, depending on the ortho, meta- and para-positions of the nitrogen atom, with respect to the optical properties and number of independent molecules (Z'). It is found that the double bond bearing a diphenylamino moiety introduced properties to exhibit a strong π-π-interaction in the solid state. The compounds were examined to evaluate the effects of solvent polarity, the role of the molecular structure, and the molecular interactions on their self-assembly behaviors. Compound I crystallized with a cell with two conformers, anti and syn, due to interaction with solvent. DFT calculations indicated the anti and syn structures of I are energetically stable (less than 1 eV). Also electrochemical and photophysical properties of the compounds were investigated, as well as the determination of optimization calculations in gas and different solvent (chloroform, cyclohexane, methanol, ethanol, tetrahydrofuran, dichloromethane and dimethyl sulfoxide) in the Gaussian09 program. The effect of solvent by PCM method was also investigated. The frontier HOMO and LUMO energies and gap energies are reported.

The synthesis and characterization of the precursor isomers trans-4-(2-(pyridin-2-yl)vinylbenzaldehyde (I), trans-4-(2-(pyridin-4-yl)vinylbenzaldehyde (II), trans-4-(2-(pyridin-2-yl)vinylbenzoic acid (III) and (E)-4-(2-(pydridin-4-yl)vinylbenzoic acid (IV) are reported. These compounds were prepared in order to obtain trans-4-((E)-2-(pyridin-2-yl)vinyl)benzamide-TEMPO (V). Compounds I and II were obtained by using a Knoevenagel reaction in the absence of a condensing agent and solvent. Oxidation of the aldehyde group using the Jones reagent afforded the corresponding acid forms III and IV. A condensation reaction with 4-amino-TEMPO using oxalyl chloride/DMF/CH2Cl2 provided the 4-((E)-2-(pyridin-2-yl)vinyl)benzamide-TEMPO. Single crystals of compounds I, II and III were obtained and characterized by X-ray diffraction. Compound I belongs to space group P2(1)/c, a = 12.6674(19) Å, b = 7.2173(11) Å, c = 11.5877(14) Å, b = 97.203(13)° and the asymmetric unit was Z = 4, whereas compound II was in the space group P2(1), with a = 3.85728(9) Å, b = 10.62375(19) Å, c = 12.8625(2) Å, b = 91.722 (2)° and the asymmetric unit was Z = 2. Compound III crystallized as single colorless needle crystals, belonging to the monoclinic system with space group P2(1), with Z = 2, with a = 3.89359(7) Å, b = 17.7014(3) Å, c = 8.04530(12) Å, b = 94.4030 (16)°. All compounds were completely characterized by IR, (1)H-NMR, EI-MS and UV-Vis.

The pathogenesis of Myotonic Dystrophy type 1 (DM1) is linked to unstable CTG repeats in the DMPK gene which induce the mis-splicing to fetal/neonatal isoforms of many transcripts, including those involved in cellular Ca2+ homeostasis. Here we monitored the splicing of three genes encoding for Ca2+ transporters and channels (RyR1, SERCA1 and CACN1S) during maturation of primary DM1 muscle cells in parallel with the functionality of the Excitation-Contraction (EC) coupling machinery. At 15 days of differentiation, fetal isoforms of SERCA1 and CACN1S mRNA were significantly higher in DM1 myotubes compared to controls. Parallel functional studies showed that the cytosolic Ca2+ response to depolarization in DM1 myotubes did not increase during the progression of differentiation, in contrast to control myotubes. While we observed no differences in the size of intracellular Ca2+ stores, DM1 myotubes showed significantly reduced RyR1 protein levels, uncoupling between the segregated ER/SR Ca2+ store and the voltage-induced Ca2+ release machinery, parallel with induction of endoplasmic reticulum (ER) stress markers. In conclusion, our data suggest that perturbed Ca2+ homeostasis, via activation of ER stress, contributes to muscle degeneration in DM1 muscle cells likely representing a premature senescence phenotype.

A combined theoretical and experimental study on the structure, infrared, UV-Vis and 1H NMR data of trans-2-(m-cyanostyryl)pyridine, trans-2-[3-methyl-(m-cyanostyryl)]pyridine and trans-4-(m-cyanostyryl)pyridine is presented. The synthesis was carried out with an efficient Knoevenagel condensation using green chemistry conditions. Theoretical geometry optimizations and their IR spectra were carried out using the Density Functional Theory (DFT) in both gas and solution phases. For theoretical UV-Vis and 1H NMR spectra, the Time-Dependent DFT (TD-DFT) and the Gauge-Including Atomic Orbital (GIAO) methods were used, respectively. The theoretical characterization matched the experimental measurements, showing a good correlation. The effect of cyano- and methyl- substituents, as well as of the N-atom position in the pyridine ring on the UV-Vis, IR and NMR spectra, was evaluated. The UV-Vis results showed no significant effect due to electron-withdrawing cyano- and electron-donating methyl-substituents. The N-atom position, however, caused a slight change in the maximum absorption wavelengths. The IR normal modes were assigned for the cyano- and methyl-groups. 1H NMR spectra showed the typical doublet signals due to protons in the trans position of a double bond. The theoretical characterization was visibly useful to assign accurately the signals in IR and 1H NMR spectra, as well as to identify the most probable conformation that could be present in the formation of the styrylpyridine-like compounds.