A numerical model for Hodgkin-Huxley neural stimulus reconstruction

The information about a neural activity is encoded in a neural response and usually the underlying stimulus that triggers the activity is unknown. This paper presents a numerical solution to reconstruct stimuli from Hodgkin-Huxley neural responses while retrieving the neural dynamics. The stimulus is reconstructed by first retrieving the maximal conductances of the ion channels and then solving the Hodgkin-Huxley equations for the stimulus. The results show that the reconstructed stimulus is a good approximation of the original stimulus, while the retrieved the neural dynamics, which represent the voltage-dependent changes in the ion channels, help to understand the changes in neural biochemistry. As high non-linearity of neural dynamics renders analytical inversion of a neuron an arduous task, a numerical approach provides a local solution to the problem of stimulus reconstruction and neural dynamics retrieval

Locally fitting hyperplanes to high-dimensional data

Problems such as data compression, pattern recognition and artificial intelligence often deal with a large data sample as observations of an unknown object. An effective method is proposed to fit hyperplanes to data points in each hypercubic subregion of the original data sample. Corresponding to a set of affine linear manifolds, the locally fitted hyperplanes optimally approximate the object in the sense of least squares of their perpendicular distances to the sample points. Its effectiveness and versatility are illustrated through approximation of nonlinear manifolds Möbius strip and Swiss roll, handwritten digit recognition, dimensionality reduction in a cosmological application, inter/extrapolation for a social and economic data set, and prediction of recidivism of criminal defendants. Based on two essential concepts of hyperplane fitting and spatial data segmentation, this general method for unsupervised learning is rigorously derived. The proposed method requires no assumptions on the underlying object and its data sample. Also, it has only two parameters, namely the size of segmenting hypercubes and the number of fitted hyperplanes for user to choose. These make the proposed method considerably accessible when applied to solving various problems in real applications

On the Complexity of Case-Based Planning

We analyze the computational complexity of problems related to case-based planning: planning when a plan for a similar instance is known, and planning from a library of plans. We prove that planning from a single case has the same complexity than generative planning (i.e., planning "from scratch"); using an extended definition of cases, complexity is reduced if the domain stored in the case is similar to the one to search plans for. Planning from a library of cases is shown to have the same complexity. In both cases, the complexity of planning remains, in the worst case, PSPACE-complete

Prediction of mortality rates in heart failure patients with data mining methods

Heart failure is one of the severe diseases which menace the human health and affectmillions of people. Half of all patients diagnosed with heart failure die within four years. For thepurpose of avoiding life-threatening situations and minimizing the costs, it is important to predictmortality rates of heart failure patients. As part of a HEIF-5 project, a data mining study wasconducted aiming specifically at extracting new knowledge from a group of patients suffering fromheart failure and using it for prediction of mortality rates. The methodology of knowledge discoveryin databases is analyzed within the framework of home telemonitoring. Several data mining methodssuch as a Bayesian network method, a decision tree method, a neural network method and a nearestneighbour method are employed. The accuracy for the data mining methods from the point of view ofavoiding life-threatening situations and minimizing the costs is discussed. It seems that the decisiontree method achieves the best accuracy results and is also interpretable for the clinicians

A case report on a rare presentation of Aeromonas hydrophila

The genus Aeromonas is a member of the family Vibrionaceae. Aeromonas hydrophila is a water-dwelling, gram-negative rod-shaped bacterium, associated with diarrheal illness and less commonly, bone and soft tissue infections, especially among immunocompromised patients. Here we reported a rare presentation of A. hydrophila causing septicemia, septic arthritis, and osteomyelitis in an immunocompetent patient. A 35-year-old female, known hypothyroidism, presented with low back pain for one and half months and left side hip pain radiating to the left lower limb for one month. While in the hospital, she subsequently developed overwhelming sepsis secondary to septic arthritis and osteomyelitis. Which was secondary to a multidrug-resistant strain of A. hydrophila. Despite broad-spectrum antibiotics and aggressive surgical management, she had a recurrence of the infection. Aeromonas species infection in both immunocompetent and immunocompromised patients may result in high morbidity and mortality. This organism is highly virulent and multidrug-resistant. So early diagnosis and early administration of antibiotics would give better outcomes

A Phase 1 study of intravenous infusions of tigecycline in patients with acute myeloid leukemia.

Acute myeloid leukemia (AML) cells meet the higher energy, metabolic, and signaling demands of the cell by increasing mitochondrial biogenesis and mitochondrial protein translation. Blocking mitochondrial protein synthesis through genetic and chemical approaches kills human AML cells at all stages of development in vitro and in vivo. Tigecycline is an antimicrobial that we found inhibits mitochondrial protein synthesis in AML cells. Therefore, we conducted a phase 1 dose-escalation study of tigecycline administered intravenously daily 5 of 7 days for 2 weeks to patients with AML. A total of 27 adult patients with relapsed and refractory AML were enrolled in this study with 42 cycles being administered over seven dose levels (50-350 mg/day). Two patients experienced DLTs related to tigecycline at the 350 mg/day level resulting in a maximal tolerated dose of tigecycline of 300 mg as a once daily infusion. Pharmacokinetic experiments showed that tigecycline had a markedly shorter half-life in these patients than reported for noncancer patients. No significant pharmacodynamic changes or clinical responses were observed. Thus, we have defined the safety of once daily tigecycline in patients with refractory AML. Future studies should focus on schedules of the drug that permit more sustained target inhibition

Autonomous clustering using rough set theory

This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency

Origins of Photoluminescence Decay Kinetics in CdTe Colloidal Quantum Dots

Recent experimental studies have identified at least two nonradiative components in the fluorescence decay of solutions of CdTe colloidal quantum dots (CQDs). The lifetimes reported by different groups, however, differed by orders of magnitude, raising the question of whether different types of traps were at play in the different samples and experimental conditions and even whether different types of charge carriers were involved in the different trapping processes. Considering that the use of these nanomaterials in biology, optoelectronics, photonics, and photovoltaics is becoming widespread, such a gap in our understanding of carrier dynamics in these systems needs addressing. This is what we do here. Using the state-of-the-art atomistic semiempirical pseudopotential method, we calculate trapping times and nonradiative population decay curves for different CQD sizes considering up to 268 surface traps. We show that the seemingly discrepant experimental results are consistent with the trapping of the hole at unsaturated Te bonds on the dot surface in the presence of different dielectric environments. In particular, the observed increase in the trapping times following air exposure is attributed to the formation of an oxide shell on the dot surface, which increases the dielectric constant of the dot environment. Two types of traps are identified, depending on whether the unsaturated bond is single (type I) or part of a pair of dangling bonds on the same Te atom (type II). The energy landscape relative to transitions to these traps is found to be markedly different in the two cases. As a consequence, the trapping times associated with the different types of traps exhibit a strikingly contrasting sensitivity to variations in the dot environment. Based on these characteristics, we predict the presence of a sub-nanosecond component in all photoluminescence decay curves of CdTe CQDs in the size range considered here if both trap types are present. The absence of such a component is attributed to the suppression of type I traps