Machine learning-based classification of Alzheimer's disease and its at-risk states using personality traits, anxiety, and depression.

BACKGROUND: Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages. METHODS: In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aß42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). RESULTS: Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets. CONCLUSION: Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages.

Linking early-life bilingualism and cognitive advantage in older adulthood.

Previous studies have identified bilingualism as a protective factor against dementia. Here we aimed to test whether being bilingual at different life stages impacts cognition and brain structure in older adulthood. We included 746 participants from the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). Assessment of bilingualism at 3 life stages (early: 13-30, middle: 30-65 and late: over 65 years old) was determined with the Lifetime of Experiences Questionnaire. Individuals reporting bilingualism (i.e., daily use of L2) in the early life stage outperformed monolinguals on learning & memory, working-memory, executive functions and language. Bilingualism in middle life stage showed a significant advantage on learning & memory, while no effect of bilingualism in old life stage was identified. Brain gray matter volume was not associated with L2 use and did not differ between groups. However, stronger correlations between brain gray matter volume in selected brain regions and cognitive performance were found in bilingual participants in the early and middle life stages. Our results indicate that bilingualism in early life might provide a long-lasting protective effect on cognition and shape the brain to sustain cognitive performance in older adulthood.

The Special Care Unit for People with Behavioral and Psychological Symptoms of Dementia (SCU- B) in the Context of the Project "RECage-Respectful Caring for Agitated Elderly": A Qualitative Study.

BACKGROUND: Dementia is a priority for global public health. The management of behavioral and psychological symptoms of dementia (BPSD) is one of the highest ongoing challenges and needs new approaches. The special care unit for people with dementia and BPSD (SCU-B) is viewed in this context as a further medical intervention. AIM: this study aims to explore SCU-B units in order to describe their main characteristics in relation to different implementation contexts, identify the characteristics of their replicability, and examine the social innovation elements promoted by SCU-B units. METHOD: This qualitative study is based on focus groups (FGs) and interviews involving nine international centers. Five of the centers have a memory clinic unit and SCU-B, compared with six that only have a memory clinic unit. A total number of 18 FGs were held, which altogether involved 164 participants. All data were transcribed verbatim and analyzed by means of a content analysis and a SWOT (strengths, weaknesses, opportunities, and threats) analysis. RESULTS: The qualitative analysis offers a vision of the SCU-B model as an innovative care unit for BPSD, promoting social innovation in the long-term care (LTC) sector. This system mainly targets people with dementia and BPSD and their informal caregivers but encourages collaboration between dementia care stakeholders at the micro and meso levels. CONCLUSIONS: Specific characteristics of the country's LTC systems and the organization of specialized units are determinants for the success of the SCU-B experience. The replicability of the entire SCU-B model was considered low; however, the implementation of single elements composing the SCU-B model may foster innovation. This study provides relevant suggestions on how to implement the SCU-B unit and innovative solutions for dementia care.

Chip calorimetry for evaluation of biofilm treatment with biocides, antibiotics, and biological agents.

Any growth or bioconversion in biofilms is accompanied by the release of heat. The heat (in J) is tightly related to the stoichiometry of the respective process via law of Hess, and the heat production rate (in W or J/s) is additionally related to the process kinetics. This heat and the heat production rate can nowadays be measured by modern calorimetry with extremely high sensitivity. Flow-through calorimetry allows the measurement of bioprocesses in biofilms in real time, without the need of invasive sample preparation and disturbing of biofilm processes. Furthermore, it can be applied for long-term measurements and is even applicable to turbid media. Chip or miniaturized calorimeters have the additional advantages of extremely short thermal equilibration times and the requirement of very small amounts of media and chemicals. The precision of flow-through chip calorimeters (about 3 mW/L) allows the detection of early stages of biofilm development (about 10(5) bacteria cm(-2)).

Chip-calorimetric monitoring of biofilm eradication with antibiotics provides mechanistic information.

Increased antibiotic resistance of pathogenic bacteria dwelling in biofilm structures has motivated the development of various monitoring tools specifically designed for biofilm investigations. In this study, the potential of the recently emerging chip calorimetry for this purpose was analysed. The activity of biofilms of Pseudomonas putida PaW340 was monitored chip-calorimetrically and compared with counts of colony forming units (CFU), bioluminescence-based ATP measurements, and quantitative confocal laser scanning microscopy (CLSM). The biofilms were treated with antibiotics differing in their mechanisms of action (bactericidal kanamycin vs. bacteriostatic tetracycline) and referenced to untreated biofilms. For untreated biofilms, all methods gave comparable results. Calorimetric killing curves, however, reflecting metabolic responses to biofilm eradication non-invasively in real time, differed from those obtained with the established methods. For instance, heat signals increased right after addition of the antibiotics. This transient increase of activity was not detected by the other methods, since only calorimetry delivers specific information about the catabolic part of the metabolism. In case of the bactericidal antibiotic, CFU misleadingly indicated successful biofilm eradication, whereas calorimetry revealed enduring activity. Our results show that calorimetry holds promise to provide valuable mechanistic information, thereby complementing other methods of biofilm analysis.

Potentials and limitations of miniaturized calorimeters for bioprocess monitoring.

In theory, heat production rates are very well suited for analysing and controlling bioprocesses on different scales from a few nanolitres up to many cubic metres. Any bioconversion is accompanied by a production (exothermic) or consumption (endothermic) of heat. The heat is tightly connected with the stoichiometry of the bioprocess via the law of Hess, and its rate is connected to the kinetics of the process. Heat signals provide real-time information of bioprocesses. The combination of heat measurements with respirometry is theoretically suited for the quantification of the coupling between catabolic and anabolic reactions. Heat measurements have also practical advantages. Unlike most other biochemical sensors, thermal transducers can be mounted in a protected way that prevents fouling, thereby minimizing response drifts. Finally, calorimetry works in optically opaque solutions and does not require labelling or reactants. It is surprising to see that despite all these advantages, calorimetry has rarely been applied to monitor and control bioprocesses with intact cells in the laboratory, industrial bioreactors or ecosystems. This review article analyses the reasons for this omission, discusses the additional information calorimetry can provide in comparison with respirometry and presents miniaturization as a potential way to overcome some inherent weaknesses of conventional calorimetry. It will be discussed for which sample types and scientific question miniaturized calorimeter can be advantageously applied. A few examples from different fields of microbiological and biotechnological research will illustrate the potentials and limitations of chip calorimetry. Finally, the future of chip calorimetry is addressed in an outlook.

Biofilm research using calorimetry--a marriage made in heaven?

Aggregated bacteria growing on a surface, so-called biofilms, play an important role in technical processes like wastewater treatment, bioremediation, or bioprocessing. In contrast, problems arise when biofilm growth results in undesired processes that may cause huge financial losses, e.g., clogged pipes, microbially influenced corrosion or pathogenic contamination. For observation purposes and to develop efficient control strategies, real-time monitoring tools for biofilms are required. Among the large variety of tools used in biofilm research, calorimetry is rarely applied, even though many characteristics qualify it for biofilm investigation and monitoring. Calorimetric measurements are non-invasive and non-destructive, and can be applied to nearly any kind of samples (including heterogeneous or turbid solutions) without the need of special sample preparation. Online and real-time data acquisition reduces the labor and facilitates high-throughput measurements. The following article is meant to introduce and promote calorimetry as a future tool in biofilm research. It attempts an assessment of common, existent monitoring tools and specifically addresses the potential of calorimetry in this field.

Responses of soil microbial communities to weak electric fields.

Electrokinetically stimulated bioremediation of soils (electro-bioremediation) requires that the application of weak electric fields has no negative effect on the contaminant degrading microbial communities. This study evaluated the hypothesis that weak direct electric current (DC) fields per se do not negatively influence the physiology and composition of soil microbial communities given that secondary electrokinetic phenomena such as soil pH changes and temperatures are minimized. Mildly buffered, water-saturated laboratory mesocosms with agricultural soil were subjected for 34 days to a constant electric field (X=1.4 V cm(-1); J approximately 1.0 mA cm(-2)) and the spatiotemporal changes of soil microbial communities assessed by fingerprints of phospholipids fatty acids (PLFA) and terminal restriction fragment length polymorphisms (T-RFLP) of bacterial 16S rRNA genes. DC-induced electrolysis of the pore water led to pH changes (<1.5 pH units) in the immediate vicinity of the electrodes and concomitant distinct soil microbial community changes. By contrast, DC-treated bulk soil distant to the electrodes showed no pH changes and developed similar PLFA- and T-RFLP-fingerprints as control soil in the absence of DC. Our data suggest that the presence of an electric field, if suitably applied, will not influence the composition and physiology of soil microbial communities and hence not affect their potential to biodegrade contaminants.

What heat is telling us about microbial conversions in nature and technology: from chip- to megacalorimetry.

The exploitation of microorganisms in natural or technological systems calls for monitoring tools that reflect their metabolic activity in real time and, if necessary, are flexible enough for field application. The Gibbs energy dissipation of assimilated substrates or photons often in the form of heat is a general feature of life processes and thus, in principle, available to monitor and control microbial dynamics. Furthermore, the combination of measured heat fluxes with material fluxes allows the application of Hess' law to either prove expected growth stoichiometries and kinetics or identify and estimate unexpected side reactions. The combination of calorimetry with respirometry is theoretically suited for the quantification of the degree of coupling between catabolic and anabolic reactions. New calorimeter developments overcome the weaknesses of conventional devices, which hitherto limited the full exploitation of this powerful analytical tool. Calorimetric systems can be integrated easily into natural and technological systems of interest. They are potentially suited for high-throughput measurements and are robust enough for field deployment. This review explains what information calorimetric analyses provide; it introduces newly emerging calorimetric techniques and it exemplifies the application of calorimetry in different fields of microbial research.