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Physical Review. E Aug 2019Hemodynamic modeling is used to explore the origin, predict, and analyze the power spectrum of the resting-state blood-oxygen-level-dependent (BOLD) signal measured by...
Hemodynamic modeling is used to explore the origin, predict, and analyze the power spectrum of the resting-state blood-oxygen-level-dependent (BOLD) signal measured by functional magnetic resonance imaging (fMRI), which has been reported to have a power-law form, i.e., P(f)∝f^{-s}, where P(f) is the power, f is the frequency, and s>0 is the power-law exponent. However, current fMRI experimental paradigms have limited acquisition durations, affecting the spectral resolution of fMRI data at the low-frequency regime. Here, the claimed power-law spectrum is investigated by using a recent hemodynamic model to analytically derive the BOLD power spectrum, with parameters that are related to neurophysiology. The theoretical results show that, for all realistic parameter combinations, the BOLD power spectrum is flat at f≲0.01Hz, has a weak resonance originating from intrinsic oscillations of vasodilatory response, and becomes a power law for high frequencies, all of which is in agreement with an empirical data set that describes the spectrum of one subject and brain region. However, the results are contrary to studies reporting a pure power-law spectrum at f≲0.2Hz. The discrepancy is attributed largely to data averaging employed by current approaches that averages together important properties of the BOLD power spectrum, such as its resonance, that biases the spectrum to only show a power law. Data averaging also reduces the high-frequency power-law exponent relative to individual cases. Overall, this work demonstrates how the model can reproduce BOLD dynamics and further analyze its low-frequency behavior. Moreover, it also uses the model to explain the impact of procedures, such as data averaging, on the reported features of the BOLD power spectrum.
Topics: Brain; Hemodynamics; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Biological; Oxygen; Rest
PubMed: 31574765
DOI: 10.1103/PhysRevE.100.022418 -
Pharmaceutical Statistics 2015Scientific progress in all empirical sciences relies on selecting models and performing inferences from selected models. Standard statistical properties (e.g., repeated... (Review)
Review
Scientific progress in all empirical sciences relies on selecting models and performing inferences from selected models. Standard statistical properties (e.g., repeated sampling coverage probability of confidence intervals) cannot be guaranteed after a model selection. This viewpoint reviews this dilemma, puts the role that pre-specification can play into perspective and illustrates model averaging as a way to relax the problem of model selection uncertainty.
Topics: Animals; Dose-Response Relationship, Drug; Humans; Models, Theoretical; Pharmaceutical Preparations; Uncertainty
PubMed: 25641863
DOI: 10.1002/pst.1671 -
International Journal of Clinical... Dec 2019Background Medication is frequently thrown away after a patient's discharge from hospital, with undesirable economic and environmental consequences. Because of the...
Background Medication is frequently thrown away after a patient's discharge from hospital, with undesirable economic and environmental consequences. Because of the rising costs of healthcare, interventions to reduce medication wastage (and associated costs) are warranted. Using Patient's Own Medication during hospitalisation might decrease medication wastage and associated costs. Objective To study the economic impact of patient's own medication use on medication waste and hospital staff's time spent during hospitalisation. Setting In seven Dutch hospitals, of which university, teaching, general, and specialised hospitals, eight different hospital wards, surgical and medical, were selected. Method In this prospective pre-post intervention study data on the economic value of medication waste and time spent by healthcare professionals were collected for a 2 months period each. The economic value of medication waste was defined as the value (€) of wasted medication per 100 patient days. For each ward, time spent on medication process activities was measured 10 times per staff member. The average time spent (in hours) on medication process steps (multiple activities) per staff member per 100 patients and associated salary costs were calculated for both periods. Main outcome measure The primary outcome of the study was the total economic value (€) of wasted medication per 100 patient days. Results Implementation of Patient's Own Medication decreased the economic value of wasted medication by 39.5% from €3983 to €2411 per 100 patient days. The mean time spent on the total medication process was reduced with 5.2 h per 100 patients (from 112.7 to 104.4 h per 100 patients). We observed a shift in professional activities, as physicians and nurses spent less time on the medication process, whereas pharmacy technicians had a greater role in it. When time spent was expressed as salary; €1219 could be saved per 100 patients. Conclusions This study showed that 'Patient's Own Medication' implementation may have a positive economic impact, as the value of medication waste decreases, hospital staff devoted less time on the medication process, and staff deployment is more efficient.
Topics: Adult; Aged; Aged, 80 and over; Hospital Costs; Hospitalization; Humans; Middle Aged; Netherlands; Outcome Assessment, Health Care; Ownership; Personnel, Hospital; Pharmaceutical Preparations; Prospective Studies; Time Factors; Waste Products
PubMed: 31705458
DOI: 10.1007/s11096-019-00932-1 -
Progress in Nuclear Magnetic Resonance... Nov 2017Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in... (Review)
Review
Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in pre-dose metabolite profiles between groups of subjects are used to predict post-dose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21st century healthcare.
Topics: Animals; Dose-Response Relationship, Drug; Humans; Magnetic Resonance Spectroscopy; Mass Spectrometry; Metabolome; Metabolomics; Pharmaceutical Preparations; Pharmacogenetics; Precision Medicine
PubMed: 29157489
DOI: 10.1016/j.pnmrs.2017.04.003 -
Physical Review. E May 2022This paper studies the synchronization of a network with linear diffusive coupling, which blinks between the variables periodically. The synchronization of the blinking...
This paper studies the synchronization of a network with linear diffusive coupling, which blinks between the variables periodically. The synchronization of the blinking network in the case of sufficiently fast blinking is analyzed by showing that the stability of the synchronous solution depends only on the averaged coupling and not on the instantaneous coupling. To illustrate the effect of the blinking period on the network synchronization, the Hindmarsh-Rose model is used as the dynamics of nodes. The synchronization is investigated by considering constant single-variable coupling, averaged coupling, and blinking coupling through a linear stability analysis. It is observed that by decreasing the blinking period, the required coupling strength for synchrony is reduced. It equals that of the averaged coupling model times the number of variables. However, in the averaged coupling, all variables participate in the coupling, while in the blinking model only one variable is coupled at any time. Therefore, the blinking coupling leads to an enhanced synchronization in comparison with the single-variable coupling. Numerical simulations of the average synchronization error of the network confirm the results obtained from the linear stability analysis.
PubMed: 35706266
DOI: 10.1103/PhysRevE.105.054304 -
Revista Espanola de Salud Publica Apr 2022Medications errors are a major problem that can cause a harm to inpatients. The main objective of the study was to compared medication errors in pharmacotherapeutic...
OBJECTIVE
Medications errors are a major problem that can cause a harm to inpatients. The main objective of the study was to compared medication errors in pharmacotherapeutic process before and after to carried out an intervention: to implant an automated dispensing cabine with to use Lean Six Sigma methodology. The secondary objective was to assess process performance, sigma level and defects per one million opportunities for medication error.
METHODS
Quasi-experimental and randomized study carried out in a Thoracic Surgery Unit of a Spanish Hospital. A pharmaceutic recorded and assesed the medication errors detected during pre-intervention period (july-august 2017) and post-intervention period (march-april 2018). The steps analyzed were dispensing, storage and compounding/administration. The pharmacist observed a third of the medication dispensed, stored and compounded/administered during the study period. The observed medication was randomly selected using AleatorMetod.xls software. To perform the statistical analysis, Student's t test and Mann-Whitney U test were used to compare quantitative variables, and Chi-square test for qualitative variables. A significance level of p<0.05 was considered.
RESULTS
The pharmaceutic recorded 4,538 drugs. After intervention, medication errors were decreased a 49% in total pharmacotherapeutic process (12.06% vs 6.15%; p<0.001). In addition, errors were decreased a 91.6% (4.27% vs 0.36%; p=0.004) in the step of medication storage; and a 75.8% (22.52% vs 5.46%; p<0.001) in the step of drugs compounding/administration. However, medication errors were increased in the step of medication dispensing (4.51% vs 15.29%; p<0.001). The process performance increased a 6% (87.9% vs 93.9%), sigma level increased from 2.67 to 3.04 and defects per one million opportunities for medication error decreased a 49%.
CONCLUSIONS
To implant an automated dispensing cabinet with Lean Six Sigma methodology helps create a safer environment for the inpatient, reducing medication errors in the steps of storage and preparation/administration, as well as improving the total process performance and sigma level.
Topics: Humans; Medication Errors; Pharmaceutical Preparations; Spain; Thoracic Surgery; Total Quality Management
PubMed: 35410988
DOI: No ID Found -
Bioinformatics (Oxford, England) May 2024Accurate inference of potential drug-protein interactions (DPIs) aids in understanding drug mechanisms and developing novel treatments. Existing deep learning models,...
MOTIVATION
Accurate inference of potential drug-protein interactions (DPIs) aids in understanding drug mechanisms and developing novel treatments. Existing deep learning models, however, struggle with accurate node representation in DPI prediction, limiting their performance.
RESULTS
We propose a new computational framework that integrates global and local features of nodes in the drug-protein bipartite graph for efficient DPI inference. Initially, we employ pre-trained models to acquire fundamental knowledge of drugs and proteins and to determine their initial features. Subsequently, the MinHash and HyperLogLog algorithms are utilized to estimate the similarity and set cardinality between drug and protein subgraphs, serving as their local features. Then, an energy-constrained diffusion mechanism is integrated into the transformer architecture, capturing interdependencies between nodes in the drug-protein bipartite graph and extracting their global features. Finally, we fuse the local and global features of nodes and employ multilayer perceptrons to predict the likelihood of potential DPIs. A comprehensive and precise node representation guarantees efficient prediction of unknown DPIs by the model. Various experiments validate the accuracy and reliability of our model, with molecular docking results revealing its capability to identify potential DPIs not present in existing databases. This approach is expected to offer valuable insights for furthering drug repurposing and personalized medicine research.
AVAILABILITY AND IMPLEMENTATION
Our code and data are accessible at: https://github.com/ZZCrazy00/DPI.
Topics: Proteins; Algorithms; Molecular Docking Simulation; Pharmaceutical Preparations; Computational Biology; Deep Learning
PubMed: 38648052
DOI: 10.1093/bioinformatics/btae271 -
Analytical Methods : Advancing Methods... May 2024Traditional sample preparation techniques based on liquid-liquid extraction (LLE) or solid-phase extraction (SPE) often suffer from a major error due to the matrix... (Review)
Review
Traditional sample preparation techniques based on liquid-liquid extraction (LLE) or solid-phase extraction (SPE) often suffer from a major error due to the matrix effects caused by significant co-extraction of matrix components. The implementation of a modern extraction technique such as solid-phase microextraction (SPME) was aimed at reducing analysis time and the use of organic solvents, as well as eliminating pre-analytical and analytical errors. Solid-phase microextraction (SPME) is an innovative technique for extracting low molecular weight compounds (less than 1500 Da) from highly complex matrices, including biological matrices. It has a wide range of applications in various types of analysis including pharmaceutical, clinical, metabolomics and proteomics. SPME has a number of advantages over other extraction techniques. Among the most important are low environmental impact, the ability to sample and preconcentrate analytes in one step, simple automation, and the ability to extract multiple analytes simultaneously. It is expected to become, in the future, another method for cell cycle research. Numerous available literature sources prove that solid-phase microextraction can be a future technique in many scientific fields, including pharmaceutical sciences. This paper provides a literature review of trends in SPME coatings and pharmacological applications.
Topics: Solid Phase Microextraction; Humans; Pharmaceutical Preparations
PubMed: 38717233
DOI: 10.1039/d4ay00187g -
Physical Review. E Feb 2021There is growing evidence that suggests the importance of astrocytes as elements for neural information processing through the modulation of synaptic transmission. A key...
There is growing evidence that suggests the importance of astrocytes as elements for neural information processing through the modulation of synaptic transmission. A key aspect of this problem is understanding the impact of astrocytes in the information carried by compound events in neurons across time. In this paper, we investigate how the astrocytes participate in the information integrated by individual neurons in an ensemble through the measurement of "integrated information." We propose a computational model that considers bidirectional communication between astrocytes and neurons through glutamate-induced calcium signaling. Our model highlights the role of astrocytes in information processing through dynamical coordination. Our findings suggest that the astrocytic feedback promotes synergetic influences in the neural communication, which is maximized when there is a balance between excess correlation and spontaneous spiking activity. The results were further linked with additional measures such as net synergy and mutual information. This result reinforces the idea that astrocytes have integrative properties in communication among neurons.
Topics: Astrocytes; Cell Communication; Models, Neurological; Neurons
PubMed: 33736090
DOI: 10.1103/PhysRevE.103.022410 -
European Journal of Pharmaceutical... Mar 2017The pharmaceutical development of new chemical entities can be hampered by their solubility and/or dissolution limitations. Currently, these properties are characterised... (Review)
Review
The pharmaceutical development of new chemical entities can be hampered by their solubility and/or dissolution limitations. Currently, these properties are characterised mostly during in vivo pre-clinical studies. The development of appropriate in vitro methods to study the solubility and dissolution properties in preclinical species would lead to a significant reduction or replacement of the animal experiments at this stage of development. During clinical development, media simulating the human gastrointestinal tract fluids are commonly used and a similar approach mimicking laboratory animals' gastrointestinal tract fluids would impact on the preclinical stage of development. This review summarises the current knowledge regarding the gastrointestinal physiology of the most common laboratory animals, and animal simulated gastric and intestinal media are proposed.
Topics: Administration, Oral; Animals; Gastrointestinal Tract; Humans; Intestinal Absorption; Pharmaceutical Preparations; Solubility
PubMed: 27940084
DOI: 10.1016/j.ejps.2016.12.004