Development and realization of energy management system in process industry, Part II: Advanced functions

One of the specific functions of the energy management system is the prediction of energy consumption for the purpose of the timely reaction to and prevention of undesirable situations. Moreover, the energy consumption prediction enables better planning of the energy production and contributes to the reduction of all production costs. This paper shows a new original algorithm for energy consumption forecasting based on support vector machines. The developed energy management system is realized and it operates in Sojaprotein AD Bečej, soybean processing factory

Mechanisms of amyloid-β34 generation indicate a pivotal role for BACE1 in amyloid homeostasis

The beta‑site amyloid precursor protein (APP) cleaving enzyme (BACE1) was discovered due to its “amyloidogenic” activity which contributes to the production of amyloid-beta (Aβ) peptides. However, BACE1 also possesses an “amyloidolytic” activity, whereby it degrades longer Aβ peptides into a non‑toxic Aβ34 intermediate. Here, we examine conditions that shift the equilibrium between BACE1 amyloidogenic and amyloidolytic activities by altering BACE1/APP ratios. In Alzheimer disease brain tissue, we found an association between elevated levels of BACE1 and Aβ34. In mice, the deletion of one BACE1 gene copy reduced BACE1 amyloidolytic activity by ~ 50%. In cells, a stepwise increase of BACE1 but not APP expression promoted amyloidolytic cleavage resulting in dose-dependently increased Aβ34 levels. At the cellular level, a mislocalization of surplus BACE1 caused a reduction in Aβ34 levels. To align the role of γ-secretase in this pathway, we silenced Presenilin (PS) expression and identified PS2-γ-secretase as the main γ-secretase that generates Aβ40 and Aβ42 peptides serving as substrates for BACE1’s amyloidolytic cleavage to generate Aβ34

Mechanisms of amyloid-β34 generation indicate a pivotal role for BACE1 in amyloid homeostasis

The beta‑site amyloid precursor protein (APP) cleaving enzyme (BACE1) was discovered due to its "amyloidogenic" activity which contributes to the production of amyloid-beta (Aβ) peptides. However, BACE1 also possesses an "amyloidolytic" activity, whereby it degrades longer Aβ peptides into a non‑toxic Aβ34 intermediate. Here, we examine conditions that shift the equilibrium between BACE1 amyloidogenic and amyloidolytic activities by altering BACE1/APP ratios. In Alzheimer disease brain tissue, we found an association between elevated levels of BACE1 and Aβ34. In mice, the deletion of one BACE1 gene copy reduced BACE1 amyloidolytic activity by ~ 50%. In cells, a stepwise increase of BACE1 but not APP expression promoted amyloidolytic cleavage resulting in dose-dependently increased Aβ34 levels. At the cellular level, a mislocalization of surplus BACE1 caused a reduction in Aβ34 levels. To align the role of γ-secretase in this pathway, we silenced Presenilin (PS) expression and identified PS2-γ-secretase as the main γ-secretase that generates Aβ40 and Aβ42 peptides serving as substrates for BACE1's amyloidolytic cleavage to generate Aβ34

Development and realization of energy management system in process industry, Part II: Advanced functions

One of the specific functions of the energy management system is the prediction of energy consumption for the purpose of the timely reaction to and prevention of undesirable situations. Moreover, the energy consumption prediction enables better planning of the energy production and contributes to the reduction of all production costs. This paper shows a new original algorithm for energy consumption forecasting based on support vector machines. The developed energy management system is realized and it operates in Sojaprotein AD Bečej, soybean processing factory

Support vector machine classifier for diagnosis in electrical machines: Application to broken bar

[EN] This paper presents a support vector machine classifier for broken bar detection in electrical induction machine. It is a reliable online method, which has high robustness to load variations and changing operating conditions. The phase current is only physical value to be measured. The steady state current is analyzed for broken bar fault via motor current signature analysis technique based on Hilbert transform. A two dimensional feature space is proposed. The features are: magnitude and frequency of characteristic peak extracted from spectrum of Hilbert transform series of the phase current. For classification task support vector machine is used due to its good robustness and generalization performances. A comparative analysis of linear, Gaussian and quadratic kernel function versus error rate and number of support vectors is done. The proposed classifier successfully detects a broken bar in various operational situations. The proposed method is sufficiently accurate, fast, and robust to load changes, which makes it suitable for use in real-time online applications in industrial drives.This paper is produced as a result of work on FP7 project for area of information and communication technologies named "PRODI - Power plants Robustification based on fault Detection and Isolation algorithms" contract number 224233 financed from European Comity, General Manager for Information community and Media.Matic, D.; Kulic, F.; Pineda Sánchez, M.; Kamenko, I. (2012). Support vector machine classifier for diagnosis in electrical machines: Application to broken bar. Expert Systems with Applications. 39(10):8681-8689. https://doi.org/10.1016/j.eswa.2012.01.214S86818689391

The amyloid-beta degradation intermediate A beta 34 is pericyte-associated and reduced in brain capillaries of patients with Alzheimer's disease

An impairment of amyloid beta-peptide (A beta) clearance is suggested to play a key role in the pathogenesis of sporadic Alzheimer's disease (AD). Amyloid degradation is mediated by various mechanisms including fragmentation by enzymes like neprilysin, matrix metalloproteinases (MMPs) and a recently identified amyloidolytic activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). BACE1 cleavage of A beta 40 and A beta 42 results in the formation of a common A beta 34 intermediate which was found elevated in cerebrospinal fluid levels of patients at the earliest disease stages. To further investigate the role of A beta 34 as a marker for amyloid clearance in AD, we performed a systematic and comprehensive analysis of A beta 34 immunoreactivity in hippocampal and cortical post-mortem brain tissue from AD patients and non-demented elderly individuals. In early Braak stages, A beta 34 was predominantly detectable in a subset of brain capillaries associated with pericytes, while in later disease stages, in clinically diagnosed AD, this pericyte-associated A beta 34 immunoreactivity was largely lost. A beta 34 was also detected in isolated human cortical microvessels associated with brain pericytes and its levels correlated with A beta 40, but not with A beta 42 levels. Moreover, a significantly decreased A beta 34/A beta 40 ratio was observed in microvessels from AD patients in comparison to non-demented controls suggesting a reduced proteolytic degradation of A beta 40 to A beta 34 in AD. In line with the hypothesis that pericytes at the neurovascular unit are major producers of A beta 34, biochemical studies in cultured human primary pericytes revealed a time and dose dependent increase of A beta 34 levels upon treatment with recombinant A beta 40 peptides while A beta 34 production was impaired when A beta 40 uptake was reduced or BACE1 activity was inhibited. Collectively, our findings indicate that A beta 34 is generated by a novel BACE1-mediated A beta clearance pathway in pericytes of brain capillaries. As amyloid clearance is significantly reduced in AD, impairment of this pathway might be a major driver of the pathogenesis in sporadic AD

Aβ34 is a BACE1-derived degradation intermediate associated with amyloid clearance and Alzheimer’s disease progression

The beta-site APP cleaving enzyme 1 (BACE1) is known primarily for its initial cleavage of the amyloid precursor protein (APP), which ultimately leads to the generation of Aβ peptides. Here, we provide evidence that altered BACE1 levels and activity impact the degradation of Aβ40 and Aβ42 into a common Aβ34 intermediate. Using human cerebrospinal fluid (CSF) samples from the Amsterdam Dementia Cohort, we show that Aβ34 is elevated in individuals with mild cognitive impairment who later progressed to dementia. Furthermore, Aβ34 levels correlate with the overall Aβ clearance rates in amyloid positive individuals. Using CSF samples from the PREVENT-AD cohort (cognitively normal individuals at risk for Alzheimer’s disease), we further demonstrate that the Aβ34/Aβ42 ratio, representing Aβ degradation and cortical deposition, associates with pre-clinical markers of neurodegeneration. We propose that Aβ34 represents a marker of amyloid clearance and may be helpful for the characterization of Aβ turnover in clinical samples

Aβ34 is a BACE1-derived degradation intermediate associated with amyloid clearance and Alzheimer's disease progression

The beta-site APP cleaving enzyme 1 (BACE1) is known primarily for its initial cleavage of the amyloid precursor protein (APP), which ultimately leads to the generation of Aβ peptides. Here, we provide evidence that altered BACE1 levels and activity impact the degradation of Aβ40 and Aβ42 into a common Aβ34 intermediate. Using human cerebrospinal fluid (CSF) samples from the Amsterdam Dementia Cohort, we show that Aβ34 is elevated in individuals with mild cognitive impairment who later progressed to dementia. Furthermore, Aβ34 levels correlate with the overall Aβ clearance rates in amyloid positive individuals. Using CSF samples from the PREVENT-AD cohort (cognitively normal individuals at risk for Alzheimer's disease), we further demonstrate that the Aβ34/Aβ42 ratio, representing Aβ degradation and cortical deposition, associates with pre-clinical markers of neurodegeneration. We propose that Aβ34 represents a marker of amyloid clearance and may be helpful for the characterization of Aβ turnover in clinical samples

Risk of COVID-19 after natural infection or vaccinationResearch in context

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health