Effect of vacuum induced nucleation on the final product homogeneity

In the field of freeze drying of pharmaceutics the homogeneity of the sublimation flux during drying is fundamental to allow a final product with the same characteristics. Previous studies have shown that the control of freezing stage, in addition to a dramatic reduction of cycle duration, can also improve the homogeneity of the final batch. In this framework, this study is focused on the investigation of the effects of the Vacuum Induced Nucleation control method (modified in a previous work)[1,2] on the final structure of the product. Two aspects will be taken into consideration: the uniformity among vials of the same batch (inter-vial) and the uniformity of the structure along the height of the product (intra-vial). It has to be pointed out that a non-uniform product structure can have an impact on the protein aggregation and redistribution, and cause a partial cake collapse or micro-collapse. This investigation is really useful to define some limits of the control method used in this work

Vacuum-Induced Surface Freezing for the Freeze-Drying of the Human Growth Hormone: How Does Nucleation Control Affect Protein Stability?

Abstract In the present work, the effect of controlled nucleation on the stability of human growth hormone (hGH) during freeze-drying has been investigated. More specifically, the vacuum-induced surface freezing technique has been compared to conventional freezing, both with and without an annealing step. Size exclusion chromatography and cell-based potency assays have been used to characterize the formation of soluble aggregates and the biological activity of hGH, respectively. The results obtained indicate that controlled nucleation has a positive effect on both cycle performance and product homogeneity because of the formation of bigger ice crystals, and characterized by a narrower dimensional distribution. From the point of view of hGH stability, we observed that vacuum-induced surface freezing is not detrimental to the biological activity of the protein, or aggregate formation. In addition, the effect of 2 different formulations, including trehalose or cellobiose, on protein preservation was also considered for this study

Double nucleus in M83

M 83 is one of the nearest galaxies with an enhanced nuclear star formation and it presents one of the best opportunities to study the kinematics and physical properties of a circumnuclear starburst. Our three-dimensional spectroscopy data in R band confirm the presence of a secondary nucleus or mass concentration (previously suggested by Thatte and coworkers). We determine the position of this hidden nucleus, which would be more massive than the visible one, and was not detected in the optical HST images due, probably, to the strong dust extinction. The optical nucleus has a mass of 5 x 10^6 M_Sun / sin i (r < 1''.5), and the hidden nucleus, located 3''.9 +/- 0''.5 at the NW (PA 271 +/- 15 deg) of the optical nucleus, would have a mass of 1 x 10^7 M_Sun / sin i (r < 1''.5). The emission line ratio map also unveils the presence of a second circumnuclear ring structure, previously discovered by IR imaging (Elmegreen and coworkers). The data allow us to resolve the behavior of the interstellar medium inside the circumnuclear ring and around the binary mass concentration.Comment: 28 pages, 11 figures. Discussion updated. Published versio

Detecting glaucoma from multi-modal data using probabilistic deep learning

Objective: To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields. Design: Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control study. Subjects and participants: Fundus photograph and visual field data from 1,655 eyes of 929 normal and glaucoma subjects to develop and test deep learning models and an independent group of 196 eyes of 98 normal and glaucoma patients to validate deep learning models. Main outcome measures: Accuracy and area under the receiver-operating characteristic curve (AUC). Methods: Fundus photographs and OCT images were carefully examined by clinicians to identify glaucomatous optic neuropathy (GON). When GON was detected by the reader, the finding was further evaluated by another clinician. Three probabilistic deep convolutional neural network (CNN) models were developed using 1,655 fundus photographs, 1,655 visual fields, and 1,655 pairs of fundus photographs and visual fields collected from Compass instruments. Deep learning models were trained and tested using 80% of fundus photographs and visual fields for training set and 20% of the data for testing set. Models were further validated using an independent validation dataset. The performance of the probabilistic deep learning model was compared with that of the corresponding deterministic CNN model. Results: The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and combined modalities using development dataset were 0.90 (95% confidence interval: 0.89–0.92), 0.89 (0.88–0.91), and 0.94 (0.92–0.96), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using the independent validation dataset were 0.94 (0.92–0.95), 0.98 (0.98–0.99), and 0.98 (0.98–0.99), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using an early glaucoma subset were 0.90 (0.88,0.91), 0.74 (0.73,0.75), 0.91 (0.89,0.93), respectively. Eyes that were misclassified had significantly higher uncertainty in likelihood of diagnosis compared to eyes that were classified correctly. The uncertainty level of the correctly classified eyes is much lower in the combined model compared to the model based on visual fields only. The AUCs of the deterministic CNN model using fundus images, visual field, and combined modalities based on the development dataset were 0.87 (0.85,0.90), 0.88 (0.84,0.91), and 0.91 (0.89,0.94), and the AUCs based on the independent validation dataset were 0.91 (0.89,0.93), 0.97 (0.95,0.99), and 0.97 (0.96,0.99), respectively, while the AUCs based on an early glaucoma subset were 0.88 (0.86,0.91), 0.75 (0.73,0.77), and 0.92 (0.89,0.95), respectively. Conclusion and relevance: Probabilistic deep learning models can detect glaucoma from multi-modal data with high accuracy. Our findings suggest that models based on combined visual field and fundus photograph modalities detects glaucoma with higher accuracy. While probabilistic and deterministic CNN models provided similar performance, probabilistic models generate certainty level of the outcome thus providing another level of confidence in decision making

A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis

The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 x 10–7 and 1.16 x 10–6], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors

Improving event-based progression analysis in glaucomatous visual fields

Glaucoma is a progressive optic neuropathy with characteristic changes to the optic nerve head and the visual field (VF). Detecting progression of VF damage with Standard Automated Perimetry (SAP) is of paramount importance for clinical care. One common approach to detecting progression is to compare each new VF test to a baseline SAP test (event analysis). This comparison is made difficult by the test-retest variability of SAP, which increases with the level of VF damage, and the limited range of measurement, meaning that damage cannot be assessed below a certain level. We performed a prospective international multi-centre data collection of SAP data on 90 eyes from 90 people with glaucoma and different levels of VF damage over a short period of time (6 tests in 60 days). Data were collected using a fundus tracked perimeter (Compass, CenterVue). We used these data (minus the first test) to develop an improved event analysis that accounts for both the change in variability with damage and the lower bound on the measurement imposed by SAP. Using simulations, we show that our approach is more sensitive compared to previously developed methods, especially in the case of advanced glaucoma, while retaining similar specificity

A Study of Time-Dependent CP-Violating Asymmetries and Flavor Oscillations in Neutral B Decays at the Upsilon(4S)

We present a measurement of time-dependent CP-violating asymmetries in neutral B meson decays collected with the BABAR detector at the PEP-II asymmetric-energy B Factory at the Stanford Linear Accelerator Center. The data sample consists of 29.7 ${\rm fb}^{-1}$ recorded at the $\Upsilon(4S)$ resonance and 3.9 ${\rm fb}^{-1}$ off-resonance. One of the neutral B mesons, which are produced in pairs at the $\Upsilon(4S)$, is fully reconstructed in the CP decay modes $J/\psi K^0_S$, $\psi(2S) K^0_S$, $\chi_{c1} K^0_S$, $J/\psi K^{*0}$ ($K^{*0}\to K^0_S\pi^0$) and $J/\psi K^0_L$, or in flavor-eigenstate modes involving $D^{(*)}\pi/\rho/a_1$ and $J/\psi K^{*0}$ ($K^{*0}\to K^+\pi^-$). The flavor of the other neutral B meson is tagged at the time of its decay, mainly with the charge of identified leptons and kaons. The proper time elapsed between the decays is determined by measuring the distance between the decay vertices. A maximum-likelihood fit to this flavor eigenstate sample finds $\Delta m_d = 0.516\pm 0.016 {\rm (stat)} \pm 0.010 {\rm (syst)} {\rm ps}^{-1}$. The value of the asymmetry amplitude $\sin2\beta$ is determined from a simultaneous maximum-likelihood fit to the time-difference distribution of the flavor-eigenstate sample and about 642 tagged $B^0$ decays in the CP-eigenstate modes. We find $\sin2\beta=0.59\pm 0.14 {\rm (stat)} \pm 0.05 {\rm (syst)}$, demonstrating that CP violation exists in the neutral B meson system. (abridged)Comment: 58 pages, 35 figures, submitted to Physical Review

Measurement of the Branching Fraction for B- --> D0 K*-

We present a measurement of the branching fraction for the decay B- --> D0 K*- using a sample of approximately 86 million BBbar pairs collected by the BaBar detector from e+e- collisions near the Y(4S) resonance. The D0 is detected through its decays to K- pi+, K- pi+ pi0 and K- pi+ pi- pi+, and the K*- through its decay to K0S pi-. We measure the branching fraction to be B.F.(B- --> D0 K*-)= (6.3 +/- 0.7(stat.) +/- 0.5(syst.)) x 10^{-4}.Comment: 7 pages, 1 postscript figure, submitted to Phys. Rev. D (Rapid Communications

Study of e+e- --> pi+ pi- pi0 process using initial state radiation with BABAR

The process e+e- --> pi+ pi- pi0 gamma has been studied at a center-of-mass energy near the Y(4S) resonance using a 89.3 fb-1 data sample collected with the BaBar detector at the PEP-II collider. From the measured 3pi mass spectrum we have obtained the products of branching fractions for the omega and phi mesons, B(omega --> e+e-)B(omega --> 3pi)=(6.70 +/- 0.06 +/- 0.27)10-5 and B(phi --> e+e-)B(phi --> 3pi)=(4.30 +/- 0.08 +/- 0.21)10-5, and evaluated the e+e- --> pi+ pi- pi0 cross section for the e+e- center-of-mass energy range 1.05 to 3.00 GeV. About 900 e+e- --> J/psi gamma --> pi+ pi- pi0 gamma events have been selected and the branching fraction B(J/psi --> pi+ pi- pi0)=(2.18 +/- 0.19)% has been measured.Comment: 21 pages, 37 postscript figues, submitted to Phys. Rev.