Mechanism of the antidiabetic action of Nigella sativa and Thymoquinone: a review.

Introduction: Long used in traditional medicine, Nigella sativa (NS; Ranunculaceae) has shown significant efficacy as an adjuvant therapy for diabetes mellitus (DM) management by improving glucose tolerance, decreasing hepatic gluconeogenesis, normalizing blood sugar and lipid imbalance, and stimulating insulin secretion from pancreatic cells. In this review, the pharmacological and pharmacokinetic properties of NS as a herbal diabetes medication are examined in depth, demonstrating how it counteracts oxidative stress and the onset and progression of DM. Methods: This literature review drew on databases such as Google Scholar and PubMed and various gray literature sources using search terms like the etiology of diabetes, conventional versus herbal therapy, subclinical pharmacology, pharmacokinetics, physiology, behavior, and clinical outcomes. Results: The efficiency and safety of NS in diabetes, notably its thymoquinone (TQ) rich volatile oil, have drawn great attention from researchers in recent years; the specific therapeutic dose has eluded determination so far. TQ has anti-diabetic, anti-inflammatory, antioxidant, and immunomodulatory properties but has not proved druggable. DM's intimate link with oxidative stress, makes NS therapy relevant since it is a potent antioxidant that energizes the cell's endogenous arsenal of antioxidant enzymes. NS attenuates insulin resistance, enhances insulin signaling, suppresses cyclooxygenase-2, upregulates insulin-like growth factor-1, and prevents endothelial dysfunction in DM. Conclusion: The interaction of NS with mainstream drugs, gut microbiota, and probiotics opens new possibilities for innovative therapies. Despite its strong potential to treat DM, NS and TQ must be examined in more inclusive clinical studies targeting underrepresented patient populations.

Therapeutic Potential of MgO and MnO Nanoparticles Within the Context of Thyroid Profile and Pancreatic Histology in a Diabetic Rat Model.

Magnesium oxide (MgO) and manganese oxide (MnO) have been reported to be effective against Diabetes Mellitus (DM). However, their nanoparticulate form has not been evaluated for antidiabetic effect. MgO and MnO nanoparticles (15-35 nm) were synthesized and subsequently characterized by ultraviolet-visible spectroscopy (UV-VIS), zeta sizer, and scanning electron microscopy. 6-7 weeks old rats weighing 200-220 mg were divided into 07 equal groups (n = 8), namely, negative control (NC), positive control (PC), standard control (Std-C), MgO high dose group (MgO-300) and low dose group (MgO-150), and MnO nanoparticle high dose (MnO-30) and low dose group (MnO-15). Diabetes was chemically induced (streptozotocin 60 mg/kg B.W) in all groups except the NC. Animals were given CMD and water was ad libitum. Nanoparticles were supplemented for 30 days after the successful induction of diabetes. Blood and tissue samples were collected after the 30th day of the trial. The mean serum glucose, insulin, and glucagon levels were improved maximally in the MgO-300 group followed by MgO-150 and MnO-30 groups. Whereas the MnO-15 group fails to show any substantial improvement in the levels of glucose, insulin, and glucagon as compared to the positive control group. Interesting the serum triiodothyronine, thyroxine, and thyroid-stimulating hormone levels were markedly improved in all the nanoparticle treatment groups and were found to be similar to the standard control group. These results highlight the modulatory properties of MgO and MnO nanoparticles and merit further studies delineating the molecular mechanisms through which these nanoparticles induce antidiabetic effects.

How growing tumour impacts intracranial pressure and deformation mechanics of brain.

Brain is an actuator for control and coordination. When a pathology arises in cranium, it may leave a degenerative, disfiguring and destabilizing impact on brain physiology. However, the leading consequences of the same may vary from case to case. Tumour, in this context, is a special type of pathology which deforms brain parenchyma permanently. From translational perspective, deformation mechanics and pressures, specifically the intracranial cerebral pressure (ICP) in a tumour-housed brain, have not been addressed holistically in literature. This is an important area to investigate in neuropathy prognosis. To address this, we aim to solve the pressure mystery in a tumour-based brain in this study and present a fairly workable methodology. Using image-based finite-element modelling, we reconstruct a tumour-based brain and probe resulting deformations and pressures (ICP). Tumour is grown by dilating the voxel region by 16 and 30 mm uniformly. Cumulatively three cases are studied including an existing stage of the tumour. Pressures of cerebrospinal fluid due to its flow inside the ventricle region are also provided to make the model anatomically realistic. Comparison of obtained results unequivocally shows that as the tumour region increases its area and size, deformation pattern changes extensively and spreads throughout the brain volume with a greater concentration in tumour vicinity. Second, we conclude that ICP pressures inside the cranium do increase substantially; however, they still remain under the normal values (15 mmHg). In the end, a correlation relationship of ICP mechanics and tumour is addressed. From a diagnostic purpose, this result also explains why generally a tumour in its initial stage does not show symptoms because the required ICP threshold has not been crossed. We finally conclude that even at low ICP values, substantial deformation progression inside the cranium is possible. This may result in plastic deformation, midline shift etc. in the brain.

Efficacy of Euphorbia helioscopia in context to a possible connection between antioxidant and antidiabetic activities: a comparative study of different extracts.

BACKGROUND: Euphorbia helioscopia, conventionally known as sun spurge, has been used as a traditional medicine to treat different diseases owing to its reported antitumor, antiviral and antioxidant activities. METHODS: The current research was formulated to assess the in-vitro antioxidant and antidiabetic ability of Euphorbia helioscopia subsequent to the phytochemical analysis of its various extracts. For this purpose, methanol, ethanol and aqueous extracts were prepared using the whole dried plant. Phytochemical analysis of the extracts was done to evaluate the total flavonoid components (TFC) and total phenolic components (TPC) in the extracts. A total of seven phenolic and three flavonoid contents were documented and quantified using HPLC. Antioxidant values were found by DPPH● assay, FRAP and ABTS assays. The antidiabetic potential of the extracts was evaluated by measuring the inhibition ability of the activity of enzymes α amylase and α glucosidase. RESULTS: After analyzing statistically, the results showed that methanolic extract possesses the highest TFC and TPC values while aqueous extract encompassed the lowest level of these contents. Invitro results showed that methanolic extract of the Euphorbia helioscopia has the maximum antioxidant capability since it showed the highest scavenging ability towards the DPPH● (IC50 value = 0.06 ± 0.02 mg/ml), FRAP (758.9 ± 25.1 µMFe+ 2/g), and ABTS (689 ± 25.94 µMTEq/g) due to the presence of high TPC (24.77 ± 0.35 mgGAEq/g) and TFC (17.95 ± 0.32 mgQEq/g) values. Antidiabetic activity in terms of inhibition potential of α amylase and α glucosidase activity was also observed maximum in methanolic extract having lowest IC50 value (0.4 ± 0.01 mg/ml and 0.45 ± 0.01 mg/ml respectively) and minimum in the aqueous extract (IC50 value = 0.57 ± 0.02 mg/ml and 0.76 ± 0.1 mg/ml respectively). CONCLUSION: The experiment outcomes have shown that Euphorbia helioscopia extracts used in the current study contain antioxidant and antidiabetic activities; however, it is highest in its methanolic extract. The presence of the same trend towards the highest antidiabetic activity of the methanolic extract in terms of maximum inhibiting activity of α amylase and α glucosidase enzymes suggests a close association of TFC and TPC in minimizing diabetes.

Wheat Yellow Rust Disease Infection Type Classification Using Texture Features.

Wheat is a staple crop of Pakistan that covers almost 40% of the cultivated land and contributes almost 3% in the overall Gross Domestic Product (GDP) of Pakistan. However, due to increasing seasonal variation, it was observed that wheat is majorly affected by rust disease, particularly in rain-fed areas. Rust is considered the most harmful fungal disease for wheat, which can cause reductions of 20-30% in wheat yield. Its capability to spread rapidly over time has made its management most challenging, becoming a major threat to food security. In order to counter this threat, precise detection of wheat rust and its infection types is important for minimizing yield losses. For this purpose, we have proposed a framework for classifying wheat yellow rust infection types using machine learning techniques. First, an image dataset of different yellow rust infections was collected using mobile cameras. Six Gray Level Co-occurrence Matrix (GLCM) texture features and four Local Binary Patterns (LBP) texture features were extracted from grayscale images of the collected dataset. In order to classify wheat yellow rust disease into its three classes (healthy, resistant, and susceptible), Decision Tree, Random Forest, Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), and CatBoost were used with (i) GLCM, (ii) LBP, and (iii) combined GLCM-LBP texture features. The results indicate that CatBoost outperformed on GLCM texture features with an accuracy of 92.30%. This accuracy can be further improved by scaling up the dataset and applying deep learning models. The development of the proposed study could be useful for the agricultural community for the early detection of wheat yellow rust infection and assist in taking remedial measures to contain crop yield.

Multi-objective regression test suite optimization using three variants of adaptive neuro fuzzy inference system.

In the process of software development, regression testing is one of the major activities that is done after making modifications in the current system or whenever a software system evolves. But, the test suite size increases with the addition of new test cases and it becomes in-efficient because of the occurrence of redundant, broken, and obsolete test cases. For that reason, it results in additional time and budget to run all these test cases. Many researchers have proposed computational intelligence and conventional approaches for dealing with this problem and they have achieved an optimized test suite by selecting, minimizing or reducing, and prioritizing test cases. Currently, most of these optimization approaches are single objective and static in nature. But, it is mandatory to use multi-objective dynamic approaches for optimization due to the advancements in information technology and associated market challenges. Therefore, we have proposed three variants of self-tunable Adaptive Neuro-fuzzy Inference System i.e. TLBO-ANFIS, FA-ANFIS, and HS-ANFIS, for multi-objective regression test suites optimization. Two benchmark test suites are used for evaluating the proposed ANFIS variants. The performance of proposed ANFIS variants is measured using Standard Deviation and Root Mean Square Error. A comparison of experimental results is also done with six existing methods i.e. GA-ANFIS, PSO-ANFIS, MOGA, NSGA-II, MOPSO, and TOPSIS and it is concluded that the proposed method effectively reduces the size of regression test suite without a reduction in the fault detection rate.

Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis.

Glaucoma is a progressive and deteriorating optic neuropathy that leads to visual field defects. The damage occurs as glaucoma is irreversible, so early and timely diagnosis is of significant importance. The proposed system employs the convolution neural network (CNN) for automatic segmentation of the retinal layers. The inner limiting membrane (ILM) and retinal pigmented epithelium (RPE) are used to calculate cup-to-disc ratio (CDR) for glaucoma diagnosis. The proposed system uses structure tensors to extract candidate layer pixels, and a patch across each candidate layer pixel is extracted, which is classified using CNN. The proposed framework is based upon VGG-16 architecture for feature extraction and classification of retinal layer pixels. The output feature map is merged into SoftMax layer for classification and produces probability map for central pixel of each patch and decides whether it is ILM, RPE, or background pixels. Graph search theory refines the extracted layers by interpolating the missing points, and these extracted ILM and RPE are finally used to compute CDR value and diagnose glaucoma. The proposed system is validated using a local dataset of optical coherence tomography images from 196 patients, including normal and glaucoma subjects. The dataset contains manually annotated ILM and RPE layers; manually extracted patches for ILM, RPE, and background pixels; CDR values; and eventually final finding related to glaucoma. The proposed system is able to extract ILM and RPE with a small absolute mean error of 6.03 and 5.56, respectively, and it finds CDR value within average range of ± 0.09 as compared with glaucoma expert. The proposed system achieves average sensitivity, specificity, and accuracies of 94.6, 94.07, and 94.68, respectively.

Neurotransmission cognitive theory: A novel approach for non-invasive brain stimulation using mechanical vibrations for the rehabilitation of neurological patients.

Patients suffering from neurological disorders require not only the treatment but also the rehabilitation to have their productive role in society. With the advent of modern technology and neuroscience techniques, different treatments are proposed and tested clinically. We propose a therapeutic and interventional noninvasive brain stimulation method that applies mechanical vibrations to different nerve points of the body to activate the stimuli. These stimuli reach and activate dead parts of the brain which will eventually help in neurorehabilitation of such patients. We get the theoretical basis of the procedure from the concept of neurotransmission cognitive theory which is also presented in the paper. For the pilot results of the theory and its procedure, we have applied the theory/therapy to three of the patients, suffering from dysarthria and cerebral palsy and results are quite promising. More detailed clinical studies are still required to have a strong evidential basis for the procedure.

Detection of Paracetamol as substrate of the gut microbiome.

Gut microbiome, a new organ; represent targets to alter pharmacokinetics of orally administered drugs. Recently, in vitro trials endorsed the idea that orally administered drugs interact and some of their quantity may be taken up by normal microbiome during transit through gut. Such transport mechanisms in microbiome may compete for drug with the host itself. Currently, no data confirms specific transport system for paracetamol uptake by gut microbiome. In vivo trial was conducted in normal healthy male rats (n=36). Paracetamol was administered orally in a single dose of 75mg/kg to isolate microbial mass after transit of 2, 3, 4, 5 and 6 hours post drug administration. Paracetamol absorbance by microbiome was pursued by injecting extracted microbial lysate in RP-HPLC-UV with C18 column under isocratic conditions at 207nm using acetonitrile and water (25:75 v/v) pH 2.50 as mobile phase. Paracetamol absorbance (14.10±0.75µg/mg of microbial mass) and percent dose recovery (13.16±0.55%) seen at transit of 4 hours was significantly higher (P<0.05) compared to other groups. Study confirms the hypothesis of homology between membrane transporters of the gut microbiome and intestinal epithelium. Orally administered drugs can be absorbed by gut microbes competitively during transit in small intestine and it varies at various transit times.

Supplementation of Cannabis sativa L. leaf powder accelerates functional recovery and ameliorates haemoglobin level following an induced injury to sciatic nerve in mouse model.

Peripheral nerve injury is a common condition with a multitude of signs and symptoms. The major consequence of injury is limited physical activity. Presently, we are lacking effective therapies for PNI and it is need of the hour is to explore potential remedies for the recovery of functional loss. Here, we have investigated the role of crude Cannabis sativa L. leaf powder in promoting functions recovery, in mouse model subjected to a traumatic sciatic nerve injury. A dose of 200mg/kg of the body weight per day was administered orally from the day of nerve crush till the end of the experiment. The motor functions were evaluated by measuring sciatic functional index, muscle grip strength and muscle mass; whereas the sensory functions were assessed by hotplate test. The haematology and serum analyses were carried out to estimate the effect of treatment on the systemic index and oxidative stress. The gain of motor functions was significantly improved and was early noticed in the treated mice. Restoration of muscle mass and elevated haemoglobin level were statistically significant in the treatment group. This study indicates that Cannabis sativa L. supplementation accelerates the motor functions recovery after nerve compression injury.

Incidence, predictors, management and outcomes of coronary perforations.

OBJECTIVES: We examined the contemporary incidence, types, predictors, angiographic characteristics, management and outcomes of coronary perforation. BACKGROUND: Coronary perforation is a rare, but important, complication of percutaneous coronary intervention (PCI). There is lack of data on perforations stratified as large and distal vessel perforations. METHODS: Retrospective, observational cohort study of all patients who underwent PCI at a high volume, tertiary hospital between the years 2009 and 2016. Angiograms of all coronary perforation cases were reviewed to determine the mechanism, type, and management of perforation. Risk-adjusted periprocedural complication rates were compared between patients with and without coronary perforation. One-year mortality outcomes of patients with large vessel vs. distal vessel perforation were also examined. RESULTS: Coronary perforation occurred in 68 of 13,339 PCIs (0.51%) performed during the study period: 51 (75%) were large vessel perforations and 17 (25%) distal vessel perforations. Most (67%) large vessel perforations were due to balloon/stent inflation, whereas most (94%) distal vessel perforations were due to guidewire exit. Patients with coronary perforations had significantly higher risk for periprocedural complications (adjusted odds ratio 7.57; 95% CI: 4.22-13.50; P < 0.001). Only one patient with large vessel perforation required emergency cardiac surgery, yet in-hospital mortality was high with both large vessel (7.8%) and distal vessel (11.8%) perforations. CONCLUSIONS: Coronary perforation is an infrequent, but potentially severe PCI complication. Most coronary perforations are large vessel perforations. Although coronary perforations rarely lead to emergency cardiac surgery, both distal vessel and large vessel perforations are associated with high in-hospital mortality, highlighting the importance of prevention.

Outcomes of Extracorporeal Membrane Oxygenation Support for Complex High-Risk Elective Percutaneous Coronary Interventions: A Single-Center Experience and Review of the Literature.

OBJECTIVES: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is most commonly used in patients with cardiac arrest and cardiogenic shock. There are limited data on the use of VA-ECMO for elective, high-risk percutaneous coronary intervention (PCI). We examined the in-hospital and mid-term clinical outcomes in patients undergoing complex, high-risk PCI with VA-ECMO support. METHODS: . We conducted a retrospective review of ECMO-supported elective high-risk PCIs performed at our institution between May 2012 and May 2017. The electronic medical records and angiograms were individually reviewed. We assessed the in-hospital and mid-term major adverse cardiovascular and cerebrovascular event (MACCE) rates, and reviewed bleeding and vascular complications. RESULTS: Five patients underwent elective high-risk PCI with ECMO support. Mean age was 66.8 ± 8.6 years and all patients were men. The mean ejection fraction was 26.6 ± 18.0%. Most procedures were unprotected left main PCIs. All PCIs were successful; 1 patient required femoral artery surgical repair. The mean hospital stay post procedure was 6.4 ± 2.0 days. ECMO was successfully weaned in all cases, and the duration of ECMO was <24 hours in 4 cases. There was no occurrence of in-hospital and 1-year MACCE. CONCLUSION: ECMO can be successfully used for hemodynamic support during elective high-risk PCI.

Use of chronic total occlusion percutaneous coronary intervention techniques for treating acute vessel closure.

Acute vessel closure due to dissection is a known complication of percutaneous coronary intervention and can be challenging to treat, especially if guidewire position is lost. Re-entering into the distal true lumen is commonly done during chronic total occlusion interventions, as part of antegrade dissection strategies. We report two cases of acute vessel closure and guidewire position loss in which the Stingray LP system was successfully used to advance a guidewire into the distal true lumen and recanalize the occluded vessel.

Analysis of PCG signals using quality assessment and homomorphic filters for localization and classification of heart sounds.

BACKGROUND AND OBJECTIVE: Accurate localization of heart beats in phonocardiogram (PCG) signal is very crucial for correct segmentation and classification of heart sounds into S1 and S2. This task becomes challenging due to inclusion of noise in acquisition process owing to number of different factors. In this paper we propose a system for heart sound localization and classification into S1 and S2. The proposed system introduces the concept of quality assessment before localization, feature extraction and classification of heart sounds. METHODS: The signal quality is assessed by predefined criteria based upon number of peaks and zero crossing of PCG signal. Once quality assessment is performed, then heart beats within PCG signal are localized, which is done by envelope extraction using homomorphic envelogram and finding prominent peaks. In order to classify localized peaks into S1 and S2, temporal and time-frequency based statistical features have been used. Support Vector Machine using radial basis function kernel is used for classification of heart beats into S1 and S2 based upon extracted features. The performance of the proposed system is evaluated using Accuracy, Sensitivity, Specificity, F-measure and Total Error. The dataset provided by PASCAL classifying heart sound challenge is used for testing. RESULTS: Performance of system is significantly improved by quality assessment. Results shows that proposed Localization algorithm achieves accuracy up to 97% and generates smallest total average error among top 3 challenge participants. The classification algorithm achieves accuracy up to 91%. CONCLUSION: The system provides firm foundation for the detection of normal and abnormal heart sounds for cardiovascular disease detection.

Safety and utility of dobutamine and pressure wire use in the hemodynamic assessment of low-flow, low-gradient aortic stenosis with reduced left ventricular ejection fraction.

BACKGROUND: The ACC/AHA guidelines recommend low-dose dobutamine challenge for hemodynamic assessment of the severity of AS in patients with low flow, low gradient aortic stenosis with reduced ejection fraction (EF) (LFLG-AS; stage D2). Inherent pitfalls of echocardiography could result in inaccurate aortic valve areas (AVA), which have downstream prognostic implications. Data on the safety and efficacy of coronary pressure wire and fluid-filled catheter use for low dose dobutamine infusion is sparse. METHODS: We retrospectively analyzed 39 consecutive patients with EF<50%, AVA<1cm2 and SVI<35ml/m2 on echocardiography who underwent simultaneous right and left heart catheterization. Hemodynamic assessments were performed at baseline and at every increment in the dobutamine infusion rate (The infusion was continued until maximal dose of dobutamine or a mean AV gradient>40mmHg was attained. The occurrence of sustained ventricular arrhythmias, symptomatic hypotension or intolerable symptoms leading to cessation of infusion was recorded. Transient ischemic attacks (TIAs) or clinically apparent strokes periprocedurally or up to 30days after the procedure were recorded. RESULTS: Dobutamine challenge confirmed true AS in 26 patients (67%) and pseudosevere AS in 34%. No sustained arrhythmias, hypotension or cessation of infusion from intolerable symptoms were observed. No clinical strokes or TIAs were observed up to 30days after procedure in any of these patients. CONCLUSIONS: Hemodynamic assessment of AS using a pressure wire with dobutamine challenge is a safe and effective tool in identifying truly severe AS in patients with LFLG-AS with reduced EF.

Etiology of gastrointestinal bleeding in patients on dual antiplatelet therapy.

OBJECTIVE: Dual antiplatelet therapy (DAPT) is associated with an increased risk of gastrointestinal (GI) bleeding and is thought to cause upper gastrointestinal bleeding (UGIB). However, recent reports indicate that the incidence of lower gastrointestinal bleeding (LGIB) in patients on DAPT may be increasing. We aimed to compare the endoscopic findings and etiology of GI bleeding between patients on DAPT compared with those not on DAPT. METHODS: This was a retrospective, single-center, case-control study. Cases were 114 consecutive patients admitted with a first episode of GI bleeding while on DAPT who underwent detailed GI evaluation. We chose 114 controls who had GIB but were not on DAPT. RESULTS: There was no significant difference in the incidence of UGIB or LGIB between the two groups (UGIB: 53.5% vs 51.3% and LGIB: 46.5% vs 48.7%, P = 0.10) or within groups (DAPT: 53.5% vs 46.5%, P = 0.30 and controls: 51.3% vs 48.7%, P = 0.80). Although the DAPT group had a lower prevalence of the usual UGIB risk factors, it had a higher likelihood of bleeding from varices or upper GI inflammation [odds ratio (OR) 3.54, 95% confidence interval (CI) 0.14-92.3; OR 13.98, 95% CI 1.40-140.36]. No etiology of bleeding was identified in a higher percentage of patients on DAPT than those who were not (22.8% vs 5.3%). CONCLUSION: In patients with GI bleeding, the incidences of UGIB and LGIB are similar irrespective of their DAPT use.

Hybrid Features and Mediods Classification based Robust Segmentation of Blood Vessels.

Retinal blood vessels are the source to provide oxygen and nutrition to retina and any change in the normal structure may lead to different retinal abnormalities. Automated detection of vascular structure is very important while designing a computer aided diagnostic system for retinal diseases. Most popular methods for vessel segmentation are based on matched filters and Gabor wavelets which give good response against blood vessels. One major drawback in these techniques is that they also give strong response for lesion (exudates, hemorrhages) boundaries which give rise to false vessels. These false vessels may lead to incorrect detection of vascular changes. In this paper, we propose a new hybrid feature set along with new classification technique for accurate detection of blood vessels. The main motivation is to lower the false positives especially from retinal images with severe disease level. A novel region based hybrid feature set is presented for proper discrimination between true and false vessels. A new modified m-mediods based classification is also presented which uses most discriminating features to categorize vessel regions into true and false vessels. The evaluation of proposed system is done thoroughly on publicly available databases along with a locally gathered database with images of advanced level of retinal diseases. The results demonstrate the validity of the proposed system as compared to existing state of the art techniques.

B-type natriuretic peptide-guided therapy and length of hospital stay post left ventricular assist device implantation.

B-type natriuretic peptide (BNP)-guided therapy during the early postoperative period following left ventricular assist device (LVAD) implantation has not been well described in the literature. We conducted a retrospective cohort study consisting of consecutive patients who underwent LVAD implantation at our institution during May 2009 to March 2013. The study was limited to patients receiving HeartMate II (Thoratec) or HVAD (HeartWare) LVADs. Patients with acute myocardial infarction were excluded. We compared between patients with multiple postoperative BNP tests (BNP-guided therapy) and earlier period patients who typically had only a baseline BNP measurement (non-BNP-guided therapy). A total of 85 patients underwent LVAD implantation during the study period. Eight patients were excluded (five acute myocardial infarction, three without BNP measurements). The only differences in the baseline characteristics of BNP versus non-BNP-guided therapy included age and female gender. The postoperative length of hospital stay (LOS) in the BNP-guided therapy group was 5 days shorter when compared with the non-BNP-guided therapy group. In multivariate analysis, BNP-guided therapy remained a significant predictor of reduced LOS. The use of repeated BNP measurements during the early postoperative period was associated with a significantly lower LOS post LVAD implantation.

Potential lung nodules identification for characterization by variable multistep threshold and shape indices from CT images.

Computed tomography (CT) is an important imaging modality. Physicians, surgeons, and oncologists prefer CT scan for diagnosis of lung cancer. However, some nodules are missed in CT scan. Computer aided diagnosis methods are useful for radiologists for detection of these nodules and early diagnosis of lung cancer. Early detection of malignant nodule is helpful for treatment. Computer aided diagnosis of lung cancer involves lung segmentation, potential nodules identification, features extraction from the potential nodules, and classification of the nodules. In this paper, we are presenting an automatic method for detection and segmentation of lung nodules from CT scan for subsequent features extraction and classification. Contribution of the work is the detection and segmentation of small sized nodules, low and high contrast nodules, nodules attached with vasculature, nodules attached to pleura membrane, and nodules in close vicinity of the diaphragm and lung wall in one-go. The particular techniques of the method are multistep threshold for the nodule detection and shape index threshold for false positive reduction. We used 60 CT scans of "Lung Image Database Consortium-Image Database Resource Initiative" taken by GE medical systems LightSpeed16 scanner as dataset and correctly detected 92% nodules. The results are reproducible.