Life during COVID-19 lockdown in Italy: the influence of cognitive state on psychosocial, behavioral and lifestyle profiles of older adults.

OBJECTIVE: Few studies have examined lockdown effects on the way of living and well-being of older adults stratified by cognitive state. Since cognitive deficits are common in this population, we investigated how cognition influenced their understanding of the pandemic, socio-behavioral responses and lifestyle adaptations during lockdown, and how these factors affected their mood or memory. METHOD: Telephone-based survey involving 204 older adults ≥65 y/o (median: 82) with previous assessments of cognitive state: 164 normal-old (NOLD), 24 mild-neurocognitive disorder (mild-NCD), 18 mild-moderate dementia. A structured questionnaire was developed to assess psychological and socio-behavioral variables. Logistic regression was used to ascertain their effects on mood and memory. RESULTS: With increasing cognitive deficits, understanding of the pandemic and the ability to follow lockdown policies, adapt to lifestyle changes, and maintain remote interactions decreased. Participants with dementia were more depressed; NOLDs remained physically and mentally active but were more bored and anxious. Sleeping and health problems independently increased the likelihood of depression (OR: 2.29; CI: 1.06-4.93; p = 0.034 and OR: 2.45; CI: 1.16-5.16; p = 0.018, respectively); Regular exercise was protective (OR: 0.30; CI: 0.12-0.72; p = 0.007). Worsening subjective memory complaints were associated with dementia (p = 0.006) and depression (p = 0.004); New-onset sleeping problems raised their odds (OR: 10.26; CI: 1.13-93.41; p = 0.039). Finally, >40% with health problems avoided healthcare mainly due to fear of contagion. DISCUSSION: NOLD and mild-NCD groups showed similar mood-behavioral profiles suggesting better tolerance of lockdown. Those with dementia were unable to adapt and suffered from depression and cognitive complaints. To counteract lockdown effects, physical and mental activities and digital literacy should be encouraged.

Study of Wound Healing Dynamics by Single Pseudo-Particle Tracking in Phase Contrast Images Acquired in Time-Lapse.

Cellular contacts modify the way cells migrate in a cohesive group with respect to a free single cell. The resulting motion is persistent and correlated, with cells' velocities self-aligning in time. The presence of a dense agglomerate of cells makes the application of single particle tracking techniques to define cells dynamics difficult, especially in the case of phase contrast images. Here, we propose an original pipeline for the analysis of phase contrast images of the wound healing scratch assay acquired in time-lapse, with the aim of extracting single particle trajectories describing the dynamics of the wound closure. In such an approach, the membrane of the cells at the border of the wound is taken as a unicum, i.e., the wound edge, and the dynamics is described by the stochastic motion of an ensemble of points on such a membrane, i.e., pseudo-particles. For each single frame, the pipeline of analysis includes: first, a texture classification for separating the background from the cells and for identifying the wound edge; second, the computation of the coordinates of the ensemble of pseudo-particles, chosen to be uniformly distributed along the length of the wound edge. We show the results of this method applied to a glioma cell line (T98G) performing a wound healing scratch assay without external stimuli. We discuss the efficiency of the method to assess cell motility and possible applications to other experimental layouts, such as single cell motion. The pipeline is developed in the Python language and is available upon request.

Gut microbiota ecology: Biodiversity estimated from hybrid neutral-niche model increases with health status and aging.

In this work we propose an index to estimate the gut microbiota biodiversity using a modeling approach with the aim of describing its relationship with health and aging. The gut microbiota, a complex ecosystem that links nutrition and metabolism, has a pervasive effect on all body organs and systems, undergoes profound changes with age and life-style, and substantially contributes to the pathogenesis of age-related diseases. For these reasons, the gut microbiota is a suitable candidate for assessing and quantifying healthy aging, i.e. the capability of individuals to reach an advanced age, avoiding or postponing major age-related diseases. The importance of the gut microbiota in health and aging has been proven to be related not only to its taxonomic composition, but also to its ecological properties, namely its biodiversity. Following an ecological approach, here we intended to characterize the relationship between the gut microbiota biodiversity and healthy aging through the development a parsimonious model of gut microbiota from which biodiversity can be estimated. We analysed publicly available metagenomic data relative to subjects of different ages, countries, nutritional habits and health status and we showed that a hybrid niche-neutral model well describes the observed patterns of bacterial relative abundance. Moreover, starting from such ecological modeling, we derived an estimate of the gut microbiota biodiversity that is consistent with classical indices, while having a higher statistical power. This allowed us to unveil an increase of the gut microbiota biodiversity during aging and to provide a good predictor of health status in old age, dependent on life-style and aging disorders.

The Association between Education and Rehabilitation Outcomes: a Population Retrospective Observational Study.

OBJECTIVES: Retrospective observational study aiming at testing whether different education levels in older adults are associated with the rehabilitation outcome. STUDY DESIGN: The study planned to cover all patients of over 65 rehabilitated from 2015 to 2017 at Golgi-Redaelli, a large government-funded rehabilitation Institute in Northern Italy comprising of three centers. Different administrative datasets were linked to investigate the factors associated with the functional outcome. The cohort resulted in 2,486 older adults for whom information on education and rehabilitation outcome was available. MAIN OUTCOME MEASURES: Rehabilitation outcome was measured with the Barthel Index testing the ability in basic activities of daily living and the Tinetti Performance Oriented Mobility Assessment measuring stability and walking. Multiple linear and logistic regression models were run controlling for rehabilitation setting and center of care, age, gender, cognitive functioning and comorbidity. RESULTS: Education resulted negatively associated with functional recovery. Patients with at least 8 years of education improved 2.24 point less in Barthel Index (out of100) and 0.70 points less in Tinetti Performance Oriented Mobility Assessment (out of 28) than the less educated patients. Results confirmed the importance of cognitive functioning in predicting rehabilitation outcome in older patients. CONCLUSIONS: Different mechanisms can explain an unexpected negative association between education and rehabilitation outcome, when possible inequalities in access to care are controlled for by study design (the cohort was admitted to a NHS-funded institute). Additional studies are needed to confirm our results and to test more specific hypotheses about the degree of effectiveness of rehabilitation across socio-economic groups.

Prevalence and prognostic value of Delirium as the initial presentation of COVID-19 in the elderly with dementia: An Italian retrospective study.

BACKGROUND: Delirium may be one of the presenting symptoms of COVID-19, complicating diagnosis and care of elderly patients with dementia. We aim to identify the prevalence and prognostic significance of delirium as the sole onset manifestation of COVID-19. METHODS: This is a retrospective single-centre study based on review of medical charts, conducted during the outbreak peak (March 27-April 18, 2020) in a Lombard dementia facility, including 59 elderly subjects with dementia and laboratory-confirmed COVID-19. FINDINGS: Of the 59 residents, 57 (96⋅6%) tested positive (mean age: 82⋅8; women: 66⋅7%). Comorbidities were present in all participants, with 18/57 (31⋅6%) having three or more concomitant diseases. Delirium-Onset COVID-19 (DOC) was observed in 21/57 (36⋅8%) subjects who were chiefly older (mean age: 85⋅4 y/o) and with multiple comorbidities. Eleven/21 DOC patients (52⋅4%) had hypoactive delirium, while hyperactive delirium occurred in ten/21 (47⋅6%). Lymphopenia was present in almost all subjects (median: 1⋅3 × 109/L). Overall mortality rate was 24⋅6% (14/57) and dementia severity per se had no impact on short-term mortality due to COVID-19. DOC was strongly associated with higher mortality (p<0⋅001). Also, DOC and male gender were independently associated with increased risk of mortality (OR: 17⋅0, 95% CI: 2⋅8-102⋅7, p = 0⋅002 and 13⋅6, 95% CI: 2⋅3-79⋅2, p = 0⋅001 respectively). INTERPRETATION: Delirium occurrence in the elderly with dementia may represent a prodromal phase of COVID-19, and thus deserves special attention, especially in the presence of lymphopenia. Hypoxia and a severe inflammatory state may develop subsequently. DOC cases have higher short-term mortality rate. FUNDING: None.

Combinatorial Discriminant Analysis Applied to RNAseq Data Reveals a Set of 10 Transcripts as Signatures of Exposure of Cattle to Mycobacterium avium subsp. paratuberculosis.

Paratuberculosis or Johne's disease in cattle is a chronic granulomatous gastroenteritis caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP). Paratuberculosis is not treatable; therefore, the early identification and isolation of infected animals is a key point to reduce its incidence. In this paper, we analyse RNAseq experimental data of 5 ELISA-negative cattle exposed to MAP in a positive herd, compared to 5 negative-unexposed controls. The purpose was to find a small set of differentially expressed genes able to discriminate between exposed animals in a preclinical phase from non-exposed controls. Our results identified 10 transcripts that differentiate between ELISA-negative, clinically healthy, and exposed animals belonging to paratuberculosis-positive herds and negative-unexposed animals. Of the 10 transcripts, five (TRPV4, RIC8B, IL5RA, ERF, CDC40) showed significant differential expression between the three groups while the remaining 5 (RDM1, EPHX1, STAU1, TLE1, ASB8) did not show a significant difference in at least one of the pairwise comparisons. When tested in a larger cohort, these findings may contribute to the development of a new diagnostic test for paratuberculosis based on a gene expression signature. Such a diagnostic tool could allow early interventions to reduce the risk of the infection spreading.

Identification of a novel large EPCAM-MSH2 duplication, concurrently with LOHs in chromosome 20 and X, in a family with Lynch syndrome.

BACKGROUND: Lynch syndrome (LS) is associated with germline mutations in one of the mismatch repair genes or EPCAM. The majority of the causative alterations are point mutations. Large genomic rearrangements represent only 5-20%. Hypothetically, the allelic imbalance, like the loss of heterozygosity, may be another high penetrance risk factor. CASE PRESENTATION: We describe the case of a patient who developed 5 tumors during her lifetime and with a family history characterized by a high frequency of tumors associated with LS. The proband was tested for mutations and copy number alterations with a panel of hereditary cancer genes and by SNP array. She showed a 187 Kb duplication including EPCAM and the first 7 exons of MSH2, plus two loss of heterozygosity (LOHs) in chromosome 20 and one in chromosome X which include many tumor suppressor genes. CONCLUSION: We found a novel large EPCAM-MSH2 duplication associated with LS and the presence of LOHs in regions containing numerous tumor suppressors, raising the hypothesis that these alterations could contribute to cancer susceptibility. Our results underline the importance to deepen the knowledge of molecular mechanisms in order to determine the role in cancer predisposition of novel genetic alterations.

Corrigendum to "The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods".

[This corrects the article DOI: 10.1155/2017/6353510.].

Modelling the growth kinetics of Listeria monocytogenes in pasta salads at different storage temperatures and packaging conditions.

The aim of this study was to model Listeria monocytogenes growth kinetics in ready to eat full meal pasta salads, containing fresh and cooked ingredients. With this aim, laboratory prepared salads, representing two formulations of commercial pasta salads, were spiked with L. monocytogenes and tested under categorised packaging and storage temperature conditions. L. monocytogenes enumeration results collected in 15 different laboratory prepared salad datasets were analysed with primary and secondary models. The models showing the best fit to describe L. monocytogenes growth kinetics in the laboratory prepared salads were then validated within commercial pasta salads. Baranyi no-lag was the best primary model fitting datasets collected at 12 °C, whereas the exponential model gave the best results for datasets collected at 4 °C. The maximum microbial specific growth rate (µmax) mean values obtained at 4 and 12 °C for salads packaged under air packaging conditions were 0.008 ±â€¯0.003 and 0.036 ±â€¯0.006 log10 (cfu/g) h-1, respectively. At the same temperatures, the µmax mean values obtained under modified atmosphere were 0.005 ±â€¯0.005 and 0.026 ±â€¯0.005 log10 (cfu/g) h-1, respectively. The Gamma secondary model predicted the growth kinetics of L. monocytogenes at both temperatures and packaging conditions and the µmax at the optimum temperature and the optimum pH for Listeria growth (µopt) estimated by the model corresponded to 0.247 ±â€¯0.009 log10 (cfu/g) h-1. Baranyi model without lag phase was used to generate growth kinetics under different scenarios. In the comparison of the predicted log10 concentrations respect to the observed ones the residues rarely exceeded 1 Log10 cfu/g. The selected models can be applied to describe the growth kinetics of L. monocytogenes in similar types of pasta salads with comparable pH, shelf life and storage conditions.

Langevin equation in complex media and anomalous diffusion.

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modelling approaches for the description of anomalous diffusion in biological systems, such as the very complex and heterogeneous cell environment. Nevertheless, many questions are still open, such as the joint manifestation of statistical features in agreement with different models that can also be somewhat alternative to each other, e.g. continuous time random walk and fractional Brownian motion. To overcome these limitations, we propose a stochastic diffusion model with additive noise and linear friction force (linear Langevin equation), thus involving the explicit modelling of velocity dynamics. The complexity of the medium is parametrized via a population of intensity parameters (relaxation time and diffusivity of velocity), thus introducing an additional randomness, in addition to white noise, in the particle's dynamics. We prove that, for proper distributions of these parameters, we can get both Gaussian anomalous diffusion, fractional diffusion and its generalizations.

Subthreshold Depression and Clinically Significant Depression in an Italian Population of 70-74-Year-Olds: Prevalence and Association with Perceptions of Self.

Estimates of depressive disorders in the elderly vary depending on how cases are defined. We estimated the prevalence of subthreshold depression (SD) and clinically significant depression (D) in a population of 70-74-year-olds. We also looked for associations with sociodemographic factors and perceptions of self. Participants underwent a multidimensional assessment (social, medical, and neuropsychological). The estimated prevalence of SD was 15.71% (95% CI: 13.70-17.72), while that of D was 5.58% (95% CI: 4.31-6.85). Multinomial logistic regression analysis revealed that female gender and dissatisfaction with family relationships were related to SD and D. A self-perception of physical age as older than actual age (but not comorbidity) and greater self-perceived stress caused by negative life events both increased the probability of SD. The likelihood of D was decreased in those who perceived their own health as good, whereas a self-perception of mental age as older than actual age and dissatisfaction with relationships with friends were both significantly associated with D. Both SD and D emerged as key problems in our population. Female gender and self-perceptions of various characteristics, which can be explored through simple questions, are associated with late-life depression in elderly people independently of their actual physical condition and other characteristics.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

Microbiological and Modeling Approach to Derive Performance Objectives for Bacillus cereus Group in Ready-to-Eat Salads.

In this article, the performance objectives (POs) for Bacillus cereus group (BC) in celery, cheese, and spelt added as ingredients in a ready-to-eat mixed spelt salad, packaged under modified atmosphere, were calculated using a Bayesian approach. In order to derive the POs, BC detection and enumeration were performed in nine lots of naturally contaminated ingredients and final product. Moreover, the impact of specific production steps on the BC contamination was quantified. Finally, a sampling plan to verify the ingredient lots' compliance with each PO value at a 95% confidence level (CL) was defined. To calculate the POs, detection results as well as results above the limit of detection but below the limit of quantification (i.e., censored data) were analyzed. The most probable distribution of the censored data was determined and two-dimensional (2D) Monte Carlo simulations were performed. The PO values were calculated to meet a food safety objective of 4 log10 cfu of BC for g of spelt salad at the time of consumption. When BC grows during storage between 0.90 and 1.90 log10 cfu/g, the POs for BC in celery, cheese, and spelt ranged between 1.21 log10 cfu/g for celery and 2.45 log10 cfu/g for spelt. This article represents the first attempt to manage the concept of PO and 2D Monte Carlo simulation in the flow chart of a complex food matrix, including raw and cooked ingredients.

Stochastic neutral modelling of the Gut Microbiota's relative species abundance from next generation sequencing data.

BACKGROUND: Interest in understanding the mechanisms that lead to a particular composition of the Gut Microbiota is highly increasing, due to the relationship between this ecosystem and the host health state. Particularly relevant is the study of the Relative Species Abundance (RSA) distribution, that is a component of biodiversity and measures the number of species having a given number of individuals. It is the universal behaviour of RSA that induced many ecologists to look for theoretical explanations. In particular, a simple stochastic neutral model was proposed by Volkov et al. relying on population dynamics and was proved to fit the coral-reefs and rain forests RSA. Our aim is to ascertain if this model also describes the Microbiota RSA and if it can help in explaining the Microbiota plasticity. RESULTS: We analyzed 16S rRNA sequencing data sampled from the Microbiota of three different animal species by Jeraldo et al. Through a clustering procedure (UCLUST), we built the Operational Taxonomic Units. These correspond to bacterial species considered at a given phylogenetic level defined by the similarity threshold used in the clustering procedure. The RSAs, plotted in the form of Preston plot, were fitted with Volkov's model. The model fits well the Microbiota RSA, except in the tail region, that shows a deviation from the neutrality assumption. Looking at the model parameters we were able to discriminate between different animal species, giving also a biological explanation. Moreover, the biodiversity estimator obtained by Volkov's model also differentiates the animal species and is in good agreement with the first and second order Hill's numbers, that are common evenness indexes simply based on the fraction of individuals per species. CONCLUSIONS: We conclude that the neutrality assumption is a good approximation for the Microbiota dynamics and the observation that Volkov's model works for this ecosystem is a further proof of the RSA universality. Moreover, the ability to separate different animals with the model parameters and biodiversity number are promising results if we think about future applications on human data, in which the Microbiota composition and biodiversity are in close relationships with a variety of diseases and life-styles.

Systems medicine of inflammaging.

Systems Medicine (SM) can be defined as an extension of Systems Biology (SB) to Clinical-Epidemiological disciplines through a shifting paradigm, starting from a cellular, toward a patient centered framework. According to this vision, the three pillars of SM are Biomedical hypotheses, experimental data, mainly achieved by Omics technologies and tailored computational, statistical and modeling tools. The three SM pillars are highly interconnected, and their balancing is crucial. Despite the great technological progresses producing huge amount of data (Big Data) and impressive computational facilities, the Bio-Medical hypotheses are still of primary importance. A paradigmatic example of unifying Bio-Medical theory is the concept of Inflammaging. This complex phenotype is involved in a large number of pathologies and patho-physiological processes such as aging, age-related diseases and cancer, all sharing a common inflammatory pathogenesis. This Biomedical hypothesis can be mapped into an ecological perspective capable to describe by quantitative and predictive models some experimentally observed features, such as microenvironment, niche partitioning and phenotype propagation. In this article we show how this idea can be supported by computational methods useful to successfully integrate, analyze and model large data sets, combining cross-sectional and longitudinal information on clinical, environmental and omics data of healthy subjects and patients to provide new multidimensional biomarkers capable of distinguishing between different pathological conditions, e.g. healthy versus unhealthy state, physiological versus pathological aging.

Influence of socio-demographic features and apolipoprotein E epsilon 4 expression on the prevalence of dementia and cognitive impairment in a population of 70-74-year olds: the InveCe.Ab study.

The age-specific prevalence rates of dementia vary widely. Studies focusing on specific age groups are needed to provide reliable estimates for healthcare providers and policy makers. We estimated the prevalence of dementia, dementia subtypes and cognitive impairment in "InveCe.Ab" (ClinicalTrials.gov, NCT01345110), a single-step multidimensional population-based study of 70-74-year olds living in Abbiategrasso (Milan, Italy). We also looked for associations with socio-demographic factors and the presence of the apolipoprotein E-ɛ4 allele. The overall dementia prevalence was 3% (95%CI: 2.1-4.1%) [Alzheimer's disease (AD): 1.2% (95%CI 0.6-1.9%); vascular dementia (VD): 1.4% (95%CI: 0.8-2.2%)]. Being single was found to be a risk factor for vascular dementia; subjects born in southern Italy were shown to be at greater risk both of overall dementia and of vascular dementia. The prevalence of cognitive impairment, with or without subjective cognitive complaints (cognitive impairment, no dementia, CIND) was 7.8% (95%CI: 6.4-9.4%). As regards the CIND subgroups, the prevalence of subjects with subjective cognitive complaints (mild cognitive impairment, MCI) was 5.0% (95%CI 3.9-6.3%), while the prevalence of those without MCI (CIND-other) was 2.8% (95%CI: 1.9-3.8). The males had a higher risk of MCI and CIND-other; the older subjects were more likely to have MCI, and those born in north-eastern Italy to have CIND-other. The prevalence of AD was higher among the apolipoprotein E-ɛ4 carriers. Our data highlight the importance of dementia and cognitive impairment in the transitional period from adulthood to old age, and reveal the presence of different associations with socio-demographic and genetic factors.

Brain aging and dementia during the transition from late adulthood to old age: design and methodology of the "Invece.Ab" population-based study.

BACKGROUND: Developed countries are experiencing an unprecedented increase in life expectancy that is accompanied by a tremendous rise in the number of people with dementia. The purpose of this paper is to report on the study design and methodology of an Italian population-based study on brain aging and dementia in the elderly. This multi-domain study is structured in two phases. Our goal is to gather sufficient data to estimate the prevalence (phase I: cross-sectional study), the incidence and the progression of dementia and its subtypes as well as cognitive impairment (phase II: follow-up study) and to identify socio-demographic, clinical, and lifestyle factors associated with dementia and the quality of brain aging in people aged 70-74 years, a crucial point between late adulthood and old age. METHODS/DESIGN: We chose to contact all 1773 people born between 1935-39 residing in Abbiategrasso, Milan, Italy. Those who agreed to participate in the "Invece.Ab" study were enrolled in a cross-sectional assessment and will be contacted two and four years after the initial data collection to participate in the longitudinal survey. Both the cross-sectional and longitudinal assessments include a medical evaluation, a neuropsychological test battery, several anthropometric measurements, a social and lifestyle interview, blood analyses, and the storage of a blood sample for the evaluation of putative biological markers. DISCUSSION: Now at the end of the recruitment phase, the evaluable population has amounted to 1644 people. Among these, 1321 (80.35%) of the participants have completed phase I. This high return rate was likely due to the style of recruitment and personalization of the contacts.