The frequency of Klotho KL-VS polymorphism in a large Italian population, from young subjects to centenarians, suggests the presence of specific time windows for its effect

Objective.We examined whether specific time windows after hospital admission reflected a sharp transition between community and hospital acquisition of bacteremia. We further examined whether different time windows to distinguish between community acquisition, healthcare association (HCA), and hospital acquisition influenced the results of prognostic models.Design.Population-based cohort study.Setting.Hospitals in 3 areas of Denmark (2.3 million inhabitants) during 2000–2011.Methods.We computed graphs depicting proportions of males, absence of comorbidity, microorganisms, and 30-day mortality pertaining to bacteremia 0, 1, 2, …, 30, and 31 days and later after admission. Next, we assessed whether different admission (0–1, 0–2, 0–3, 0–7 days) and HCA (30, 90 days) time windows were associated with changes in odds ratio (OR) and area under the receiver operating characteristic (ROC) curve for 30-day mortality, adjusting for sex, age, comorbidity, and microorganisms.Results.For 56,606 bacteremic episodes, no sharp transitions were detected on a specific day after admission. Among the 8 combined time windows, ORs for 30-day mortality varied from 1.30 (95% confidence interval [CI], 1.23–1.37) to 1.99 (95% CI, 1.48–2.67) for HCA and from 1.36 (95% CI, 1.24–1.50) to 2.53 (95% CI, 2.01–3.20) for hospital acquisition compared with community acquisition. Area under the ROC curve changed marginally from 0.684 (95% CI, 0.679–0.689) to 0.700 (95% CI, 0.695–0.705).Conclusions.No time transitions unanimously distinguished between community and hospital acquisition with regard to sex, comorbidity, or microorganisms, and no difference in 30-day mortality was seen for HCA patients in relation to a 30- or 90-day time window. ORs decreased consistently in the order of hospital acquisition, HCA, and community acquisition, regardless of time window combination, and differences in area under the ROC curve were immaterial.

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Serotonin Signals Modulate Mushroom Body Output Neurons for Sustaining Water-Reward Long-Term Memory in Drosophila

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.755574 ◽

2021 ◽

Vol 9 ◽

Author(s):

Wang-Pao Lee ◽

Meng-Hsuan Chiang ◽

Li-Yun Chang ◽

Wei-Huan Shyu ◽

Tai-Hsiang Chiu ◽

...

Keyword(s):

Mushroom Body ◽

Molecular Mechanisms ◽

Time Window ◽

Time Windows ◽

Long Term Memory ◽

Specific Time ◽

Water Reward ◽

Term Memory ◽

Output Neurons

Memory consolidation is a time-dependent process through which an unstable learned experience is transformed into a stable long-term memory; however, the circuit and molecular mechanisms underlying this process are poorly understood. The Drosophila mushroom body (MB) is a huge brain neuropil that plays a crucial role in olfactory memory. The MB neurons can be generally classified into three subsets: γ, αβ, and α′β′. Here, we report that water-reward long-term memory (wLTM) consolidation requires activity from α′β′-related mushroom body output neurons (MBONs) in a specific time window. wLTM consolidation requires neurotransmission in MBON-γ3β′1 during the 0–2 h period after training, and neurotransmission in MBON-α′2 is required during the 2–4 h period after training. Moreover, neurotransmission in MBON-α′1α′3 is required during the 0–4 h period after training. Intriguingly, blocking neurotransmission during consolidation or inhibiting serotonin biosynthesis in serotoninergic dorsal paired medial (DPM) neurons also disrupted the wLTM, suggesting that wLTM consolidation requires serotonin signals from DPM neurons. The GFP Reconstitution Across Synaptic Partners (GRASP) data showed the connectivity between DPM neurons and MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3, and RNAi-mediated silencing of serotonin receptors in MBON-γ3β′1, MBON-α′2, or MBON-α′1α′3 disrupted wLTM. Taken together, our results suggest that serotonin released from DPM neurons modulates neuronal activity in MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3 at specific time windows, which is critical for the consolidation of wLTM in Drosophila.

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Comparing Maximal Mean and Critical Speed and Metabolic Powers in Elite and Sub-elite Soccer

International Journal of Sports Medicine ◽

10.1055/a-1065-2100 ◽

2020 ◽

Vol 41 (04) ◽

pp. 219-226

Author(s):

Cameron Lord ◽

Anthony John Blazevich ◽

Chris Richard Abbiss ◽

Eric James Drinkwater ◽

Fadi Ma’ayah

Keyword(s):

Critical Speed ◽

Moving Average ◽

Time Windows ◽

Absolute Distance ◽

Specific Time ◽

Metabolic Power ◽

Match Play ◽

Mean Values ◽

Premier League ◽

Least Energy

AbstractThe quantification of maximal mean speed (MMS), maximal mean metabolic power (MMPmet), critical speed (CS) and critical metabolic power (CPmet) was conducted over full A-League (elite) and National Premier League (NPL; sub-elite) seasons. Comparisons were made between levels of soccer competition and playing positions (i. e. centre backs, full backs, central midfielders, wide midfielders and strikers). A symmetric moving average algorithm was applied to the GPS raw data using specific time windows (i. e. 1, 5, 10, 60, 300 and 600 s) and maximal values were obtained. Additionally, these maximal values were used to derive estimates of CS and CPmet. Maximal mean values, particularly during smaller time windows (i. e. 1 and 5 s), were greater in A-League match play. Only MMPmet1 was identified as being consistently different between competitions (P=<0.001–0.049) in all playing positions. Significance was only observed in CS (P=0.005) and CPmet (P=0.005) of centre backs between competitions. Centre backs were identified as the least energy demanding playing position. The present findings suggests that both maximal mean and critical analyses are suitable alternatives to common absolute distance and speed assessments of match running performance during competitive matches.

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Botnet Behavior Detection using Network Synchronism

Privacy, Intrusion Detection and Response ◽

10.4018/978-1-60960-836-1.ch005 ◽

2011 ◽

pp. 122-144 ◽

Cited By ~ 5

Author(s):

Sebastián García ◽

Alejandro Zunino ◽

Marcelo Campo

Keyword(s):

Time Windows ◽

Expectation Maximization Algorithm ◽

Error Rates ◽

Behavioral Characteristics ◽

Specific Time ◽

False Positive Error ◽

Behavior Detection ◽

Specific Protocol ◽

False Positive Error Rate ◽

Analysis Of Error

Botnets’ diversity and dynamism challenge detection and classification algorithms depend heavily on static or protocol-dependant features. Several methods showing promising results were proposed using behavioral-based approaches. The authors conducted an analysis of botnets’ and bots’ most inherent characteristics such as synchronism and network load within specific time windows to detect them more efficiently. By not relying on any specific protocol, our proposed approach detects infected computers by clustering bots’ network behavioral characteristics using the Expectation-Maximization algorithm. An encouraging false positive error rate of 0.7% shows that bots’ traffic can be accurately separated by our approach by analyzing several bots and non-botnet network captures and applying a detailed analysis of error rates.

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The effect of the crust on the estimation of mantle Q from spectral ratios of multiple ScS phases

Bulletin of the Seismological Society of America ◽

10.1785/bssa0870030778 ◽

1997 ◽

Vol 87 (3) ◽

pp. 778-781

Author(s):

Takehi Isse ◽

Ichiro Nakanishi

Keyword(s):

Background Noise ◽

Numerical Experiments ◽

Time Window ◽

Time Windows ◽

Specific Time ◽

Spectral Ratios ◽

Arrival Times ◽

Numerical Tests ◽

Error Bars ◽

The Difference

Abstract To estimate Qscs, previous studies used the spectral ratios of multiple ScS phases calculated for specific time windows. They assumed that the spectral ratios had linear relation with frequency. However, the spectral ratios very often did not seem to be linear, and the error bars were very large for frequencies higher than about 0.05 Hz. We have performed numerical experiments to search for the cause of these anomalies and found that they are caused by the multiple reflection in the crust under the surface bounce point of ScS2. A method of suppressing the anomalies is to start the time of the time window at 40 sec prior to the theoretical arrival times of the multiple ScS phases. In numerical tests, the difference between the correct and estimated values of Qscs is only 0 to 5% using this method, but it is 10 to 50% in the conventional method. We find that the crustal effect is more important in the estimation of Qscs than background noise, which has been readily handled in previous studies using standard stacking techniques.

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Amygdala damage affects event-related potentials for fearful faces at specific time windows

Human Brain Mapping ◽

10.1002/hbm.20921 ◽

2009 ◽

Vol 31 (7) ◽

pp. 1089-1105 ◽

Cited By ~ 82

Author(s):

Pia Rotshtein ◽

Mark P. Richardson ◽

Joel S. Winston ◽

Stefan J. Kiebel ◽

Patrik Vuilleumier ◽

...

Keyword(s):

Time Windows ◽

Event Related Potentials ◽

Specific Time ◽

Fearful Faces ◽

Related Potentials

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Functional Cliques in Developmentally Correlated Neural Networks

10.1101/064147 ◽

2016 ◽

Author(s):

S. Luccioli ◽

A. Barzilai ◽

E. Ben-Jacob ◽

P. Bonifazi ◽

A. Torcini

Keyword(s):

Neural Networks ◽

Small Group ◽

Single Neuron ◽

Random Network ◽

Time Windows ◽

Total Degree ◽

Specific Time ◽

Short Term ◽

Brain Circuit ◽

Bursting Activity

AbstractWe consider a sparse random network of excitatory leaky integrate-andfire neurons with short-term synaptic depression. Furthermore to mimic the dynamics of a brain circuit in its first stages of development we introduce for each neuron correlations among in-degree and out-degree as well as among excitability and the corresponding total degree, We analyze the influence of single neuron stimulation and deletion on the collective dynamics of the network. We show the existence of a small group of neurons capable of controlling and even silencing the bursting activity of the network. These neurons form a functional clique since only their activation in a precise order and within specific time windows is capable to ignite population bursts.

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The Investigation of Behavior Change in EEG Signals During Induction of Anesthesia

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001421580106 ◽

2021 ◽

Author(s):

Shangkun Li ◽

Wei Dan ◽

Lihao Chen ◽

Bin Wu ◽

Li Ren ◽

...

Keyword(s):

Time Windows ◽

Age Groups ◽

Electrical Signal ◽

Anesthesia Induction ◽

Specific Time ◽

Eeg Signals ◽

Brain Wave ◽

Density Spectrum ◽

Anesthetic Drugs ◽

Anesthesia Depth

Anesthesiology aims to make anesthesia safer and increase the precision of prognoses. Correct assessment of the anesthesia depth is crucial to its safety. At present, intraoperative electroencephalogram (EEG) monitoring is the primary mode of anesthesia depth monitoring and judgment. However, most clinical anesthesiologists rely on commercial anesthesia depth monitors to judge anesthesia depth, such as bispectral index (BIS) and patient state index (PSI). This may lack an understanding of associated changes in brain wave quantization. Therefore, this study conducts quantitative analyses of EEG signals during anesthesia induction. EEG signals are processed within specific time windows and extracted brainpower density spectrum arrays with different frequency bands, brain electrical signal spectra, source frequencies and other key indicators. Analysis and comparison of these indicators clarifies patterns of variation in EEG signals during early anesthesia induction. The spectral edge frequencies (SEFs) of EEG signals within different time windows can be modeled accurately, from which the specific time points of EEG signal changes are derived. Furthermore, the relationship between patient age and the effect of anesthetic drugs is preliminarily investigated by analyzing the SEF variations of different age groups. This study quantifies changes in the EEG signals of patients at the initial stage of anesthesia induction and drug-related effects are observed, which opens a way for further exploration of EEG changes in patients under general anesthesia.

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A developmental perspective on the integration of language production and comprehension

Behavioral and Brain Sciences ◽

10.1017/s0140525x12002774 ◽

2013 ◽

Vol 36 (4) ◽

pp. 363-364

Author(s):

Saloni Krishnan

Keyword(s):

Language Production ◽

Language Skills ◽

Time Windows ◽

Developmental Studies ◽

Specific Time ◽

Time Production ◽

Specific Language ◽

Target Article ◽

Changes Over Time ◽

Over Time

AbstractThe integration of language production and comprehension processes may be more specific in terms of developmental timing than Pickering & Garrod (P&G) discuss in their target article. Developmental studies do reveal links between production and comprehension, but also demonstrate that the integration of these skills changes over time. Production-comprehension links occur within specific language skills and specific time windows.

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Inequalities and Impact of Socioeconomic-Cultural Factors in Suicide Rates Across Italy

Crisis ◽

10.1027/0227-5910/a000084 ◽

2011 ◽

Vol 32 (4) ◽

pp. 178-185 ◽

Cited By ~ 15

Author(s):

Maurizio Pompili ◽

Marco Innamorati ◽

Monica Vichi ◽

Maria Masocco ◽

Nicola Vanacore ◽

...

Keyword(s):

Suicide Rate ◽

Age Groups ◽

Premature Death ◽

Mortality Rates ◽

Mortality Data ◽

Italian Population ◽

Comprehensive Overview ◽

Suicide Rates ◽

Younger Age ◽

Age And Sex

Background: Suicide is a major cause of premature death in Italy and occurs at different rates in the various regions. Aims: The aim of the present study was to provide a comprehensive overview of suicide in the Italian population aged 15 years and older for the years 1980–2006. Methods: Mortality data were extracted from the Italian Mortality Database. Results: Mortality rates for suicide in Italy reached a peak in 1985 and declined thereafter. The different patterns observed by age and sex indicated that the decrease in the suicide rate in Italy was initially the result of declining rates in those aged 45+ while, from 1997 on, the decrease was attributable principally to a reduction in suicide rates among the younger age groups. It was found that socioeconomic factors underlined major differences in the suicide rate across regions. Conclusions: The present study confirmed that suicide is a multifaceted phenomenon that may be determined by an array of factors. Suicide prevention should, therefore, be targeted to identifiable high-risk sociocultural groups in each country.

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