Vitamin B12 measurements across neurodegenerative disorders.

Background:Vitamin B12 deficiency causes a number of neurological features including cognitive and psychiatric disturbances, gait instability, neuropathy, and autonomic dysfunction. Clinical recognition of B12 deficiency in neurodegenerative disorders is more challenging because it causes defects that overlap with expected disease progression. We sought to determine whether B12 levels at the time of diagnosis in patients with Parkinson's disease (PD) differed from those in patients with other neurodegenerative disorders. Methods:We performed a cross-sectional analysis of B12 levels obtained around the time of diagnosis in patients with PD, Multiple System Atrophy (MSA), Dementia with Lewy Bodies (DLB), Alzheimer's disease (AD), Progressive Supranuclear Palsy (PSP), Frontotemporal Dementia (FTD), or Mild Cognitive Impairment (MCI). We also evaluated the rate of B12 decline in PD, AD, and MCI. Results:In multivariable analysis adjusted for age, sex, and B12 supplementation, we found that B12 levels were significantly lower at time of diagnosis in patients with PD than in patients with PSP, FTD, and DLB. In PD, AD, and MCI, the rate of B12 decline ranged from - 17 to - 47 pg/ml/year, much greater than that reported for the elderly population. Conclusions:Further studies are needed to determine whether comorbid B12 deficiency affects progression of these disorders

Supersolid and solitonic phases in one-dimensional Extended Bose-Hubbard model

We report our findings on quantum phase transitions in cold bosonic atoms in a one dimensional optical lattice using the finite size density matrix renormalization group method in the framework of the extended Bose-Hubbard model. We consider wide ranges of values for the filling factors and the nearest neighbor interactions. At commensurate fillings, we obtain two different types of charge density wave phases and a Mott insulator phase. However, departure from commensurate fillings yield the exotic supersolid phase where both the crystalline and the superfluid orders coexist. In addition, we obtain signatures for solitary waves and also superfluidity.Comment: 7 pages, 11 figure

Characterization of vitamin D supplementation and clinical outcomes in a large cohort of early Parkinson's disease.

BackgroundVitamin D (VitD) deficiency is common in Parkinson's disease (PD) and has been raised as a possible PD risk factor. In the past decade, VitD supplementation for potential prevention of age related conditions has become more common. In this study, we sought to characterize VitD supplementation in early PD and determine as an exploratory analysis whether baseline characteristics or disease progression differed according to reported VitD use.MethodsWe analyzed data from the National Institutes of Health Exploratory Trials in Parkinson's Disease (NET-PD) Long-term study (LS-1), a longitudinal study of 1741 participants. Subjects were divided into following supplement groups according to subject exposure (6 months prior to baseline and during the study): no VitD supplement, multivitamin (MVI), VitD ≥400 IU/day, and VitD + multivitamin (VitD+MVI). Clinical status was followed using the Unified Parkinson's Disease Rating Scale, Symbol Digit Modalities Test, total daily levodopa equivalent dose, and Parkinson's Disease Questionnaire.ResultsAbout 5% of subjects took VitD alone, 7% took VitD+MVI, 34% took MVI alone, while 54% took no supplement. Clinical outcomes at 3 years were similar across all groups.ConclusionThis study shows VitD supplementation ≥400 IU/day was not common in early PD and that its use was similar to that seen in the US population. At 3 years, there was no difference in disease progression according to vitamin D supplement use

Ceramic Matrix Composites (CMCs) at GE: From inception to commercialization

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Impact of Climate Variations on Soybean Yield in Eastern Arkansas: 1960-2014

Climate is the major factor affecting crop production; therefore, various agro-meteorological indicators have been frequently used to evaluate the impact of climate on crop production. In this study, we examined the temporal variations of agrometeorological indicators (growing degree days, total precipitation, dry spells and drought indices) during 1960-2014 and their impact on soybean yields in East Arkansas. Results show an increasing trend in growing degree days (GDDs) and dry spells, though the total precipitation during the soybean growing season remained nearly unchanged during the study period. Generally, GDDs and dry spells show a strong correlation with yields. We also evaluated drought variability based on different drought indices, including the Palmer Drought Severity Index (PDSI), the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). The drought indices are all negatively correlated to soybean yields. Overall, the one month SPEI showed the strongest impact on yields. After regression analysis, Dry spells and Total precipitation were the only significant factors in the General Linear Model (GLM)

Auditory category learning is robust across training regimes

Multiple lines of research have developed training approaches that foster category learning, with important translational implications for education. Increasing exemplar variability, blocking or interleaving by category-relevant dimension, and providing explicit instructions about diagnostic dimensions each have been shown to facilitate category learning and/or generalization. However, laboratory research often must distill the character of natural input regularities that define real-world categories. As a result, much of what we know about category learning has come from studies with simplifying assumptions. We challenge the implicit expectation that these studies reflect the process of category learning of real-world input by creating an auditory category learning paradigm that intentionally violates some common simplifying assumptions of category learning tasks. Across five experiments and nearly 300 adult participants, we used training regimes previously shown to facilitate category learning, but here drew from a more complex and multidimensional category space with tens of thousands of unique exemplars. Learning was equivalently robust across training regimes that changed exemplar variability, altered the blocking of category exemplars, or provided explicit instructions of the category-diagnostic dimension. Each drove essentially equivalent accuracy measures of learning generalization following 40 min of training. These findings suggest that auditory category learning across complex input is not as susceptible to training regime manipulation as previously thought

Influence of Humidity on the NO₂ Sensing Properties of SrCo₀.₁Ti₀.₉O₃

Strontium Cobalt Titanate (SCT) was synthesized via solid state route. Phase formation was analyzed using X-ray diffraction (XRD) technique. Resistive sensors were made using screen printing technique and corresponding sensing properties were investigated in dry as well as humid environment (RH 50%). Experimental results demonstrated that sensors displayed least humidity interference at 400 °C. The operating temperature of the sensor was optimized for best responsiveness. These type of sensors can be effectively used in environmental monitoring of NO2 gas at low ppm

Targeting neuroendocrine abnormalities in Parkinson’s disease with exercise

Parkinson’s Disease (PD) is a prevalent and complex age-related neurodegenerative condition for which there are no disease-modifying treatments currently available. The pathophysiological process underlying PD remains incompletely understood but increasing evidence points to multiple system dysfunction. Interestingly, the past decade has produced evidence that exercise not only reduces signs and symptoms of PD but is also potentially neuroprotective. Characterizing the mechanistic pathways that are triggered by exercise and lead to positive outcomes will improve understanding of how to counter disease progression and symptomatology. In this review, we highlight how exercise regulates the neuroendocrine system, whose primary role is to respond to stress, maintain homeostasis and improve resilience to aging. We focus on a group of hormones – cortisol, melatonin, insulin, klotho, and vitamin D – that have been shown to associate with various non-motor symptoms of PD, such as mood, cognition, and sleep/circadian rhythm disorder. These hormones may represent important biomarkers to track in clinical trials evaluating effects of exercise in PD with the aim of providing evidence that patients can exert some behavioral-induced control over their disease

Participatory evaluation of advanced potato (Solanum tuberosum) clones for water stress tolerance

An attempt was made to introduce potato (Solanum tuberosum L.) in hot arid water scarce zone of Western Rajasthan, India. Eight CIP-bred potato clones were evaluated along with two controls, viz. Kufri Pukhraj and Kufri Surya on farmer’s field at Jodhpur, Rajasthan under normal and moderate water stress regime during three winter crop seasons (2012-15). Pooled analysis revealed that CIP clone 397006.18 (34.0 tonnes/ha) out yielded Kufri Pukhraj (26.8 tonnes/ha) and Kufri Surya (20.2 tonnes/ha) for marketable tuber yield. This clone maintained yield under normal and deficit irrigation and attained 26.9% higher marketable yield under normal irrigations, which further improved by 31.3% under deficit water stress regime over the best control Kufri Pukhraj. This clone recorded highest tuber dry matter content (22.7%), statistically superior to both control Kufri Pukhraj (17.9%) and Kufri Surya (21.4%). Clone 397006.18 had highest mean drought tolerance index value (1.16) and least total weight loss under normal irrigation (4.9%) and water stress conditions (8.6%) up to 60 days of storage. Preference yield analysis by potato growers showed that they liked this clone most and its overall acceptability was fairly better for all organoleptic traits. Results of field study and participatory varietal selection indicated that clone 397006.18 performed better for tuber productivity under deficit water management, exhibited drought tolerance traits and achieved overall acceptance by the farmers in Western Rajasthan

Can Industry 5.0 Technologies Overcome Supply Chain Disruptions? - A Perspective Study on Pandemics, War, and Climate Change Issues

Industry 5.0 (I5.0) is the next industrial revolution that will leverage human intervention in collaboration with intelligent, logical, and smart machines to attain even more user-preferred and resource-efficient manufacturing and supply chain solutions. The main aim of this article is to study I5.0 technologies in supply chains when these are affected by disruptive phenomena such as those created by wars, climate change or pandemics. A systematic literature review methodology was conducted to understand the present knowledge connected with this theme. This study summarises 194 research articles from the period 2009 to 2022 to understand the present knowledge connected with this theme. The research findings show a significant gap related to the adoption of I5.0 technologies to prevent or overcome supply chain disruptions. 194 articles, including journal and review articles, were identified in the literature. The study provides a novel and insightful concept related to I5.0 within the context of supply chain disruptions. The potential applications of I5.0 and Industry 4.0 are elaborately discussed in three areas, namely: (1) disruptions in supply chains due to pandemics; (2) disruptions in supply chains due to war; and (3) disruptions in supply chains due to climate change. Finally, this study highlights research implications and proposes future research avenues that will contribute to further exploring the adoption of I5.0 technologies to prevent, manage and overcome disruptions in supply chains