Intra-Zero-Energy Landau Level Crossings in Bilayer Graphene at High Electric Fields.

The highly tunable band structure of the zero-energy Landau level (zLL) of bilayer graphene makes it an ideal platform for engineering novel quantum states. However, the zero-energy Landau level at high electric fields has remained largely unexplored. Here we present magnetotransport measurements of bilayer graphene in high transverse electric fields. We observe previously undetected Landau level crossings at filling factors ν = -2, 1, and 3 at high electric fields. These crossings provide constraints for theoretical models of the zero-energy Landau level and show that the orbital, valley, and spin character of the quantum Hall states at high electric fields is very different from low electric fields. At high E, new transitions between states at ν = -2 with different orbital and spin polarization can be controlled by the gate bias, while the transitions between ν = 0 → 1 and ν = 2 → 3 show anomalous behavior.

Single Atom Nucleation of Cobalt over Graphene Oxide: Theory and Experimental Study.

Nucleation and growth mechanism of Co electrodeposition over graphene oxide (GO) was studied using cyclic voltammetry (CV) and chronoamperometry techniques. The studies were performed over an aqueous electrolyte containing 10 mM CoSO4·7H2O maintained at an initial pH of 2.5. CV studies established that the deposition mechanism was diffusion-controlled and irreversible. Chronoamperometry studies revealed the presence of three concurrent processes: an initial adsorption current, which indicated adatom layer formation, 3D nucleation and growth of Co islands over GO, and hydrogen evolution over the deposited Co nanoclusters. It was observed that the nucleation rate increased with increasing the overpotential (η) for deposition (from 2.71 × 104 cm-2 s-1 at η = 0.35 V to 3.62 × 106 cm-2 s-1 at η = 0.90 V). Application of the classical theory of nucleation over the chronoamperometry results suggested that the free energy of formation of the critical nucleus was lower than room temperature thermal energy. This indicated that the nucleation and growth process was not activation-controlled but rather a kinetically controlled process. Application of Milchev's atomistic theory revealed that every single atom of Co deposited over the GO sheet was a supercritical nucleus that could grow into a cluster irreversibly.

A cellular automaton for modeling non-trivial biomembrane ruptures.

A novel cellular automaton (CA) for simulating biological membrane rupture is proposed. Constructed via simple rules governing deformation, tension, and fracture, the CA incorporates ideas from standard percolation models and bond-based fracture methods. The model is demonstrated by comparing simulations with experimental results of a double bilayer lipid membrane expanding on a solid substrate. Results indicate that the CA can capture non-trivial rupture morphologies such as floral patterns and the saltatory dynamics of fractal avalanches observed in experiments. Moreover, the CA provides insight into the poorly understood role of inter-layer adhesion, supporting the hypothesis that the density of adhesion sites governs rupture morphology.

To investigate the influence of machine operating variables on formulations derived from lactose types in capsule filling: part 2.

This study is the second in a series that examines the characterizing and selection of suitable grades of lactose for capsule formulation development. Based upon the previous study, four grades were selected for further study. The effects of drug load and operational variables on formulations derived from these four lactose types were evaluated for physicochemical and mechanical attributes of plugs and their capsules on an instrumented dosing-disc capsule filling machine (H&H KFM/3) using acetaminophen as a model, highly soluble and poorly compressible drug. The results obtained were as follows: (1) flowability reduced upon increasing drug load; (2) powder bed height (PBH) and compression force (CF) had positive significant effect on plug weight (p < 0.05); (3) ejection force was positively and significantly correlated with increasing speed and CF (p < 0.05); (4) AL capsule plugs had the highest plug crushing force which was followed by DCL15; (5) the crushing strength of plugs made from DCL11 increased with increasing acetaminophen concentration; (6) higher CF had a significant negative impact on acetaminophen release at 15 min time point (p < 0.05); (7) at 10% and 40% drug load, formulations containing AL showed the quickest drug release; and (8) increased drug load had a significant negative impact on the release rate at 15 and 45 min time points (p < 0.05). Overall, the results from this study provides information on risk based assessment of filler selection based on drug load and the range of machine operating variables which will help in defining criteria for meeting key quality attributes for capsule formulation development.

An index for evaluating difficulty of Chewing Index for chewable tablets.

Chewing difficulty index, a potential measure of difficulty in chewing the chewable tablets, has been described herein as the product of tablet thickness and tablet hardness measured under the diametral loading. The proposed index was evaluated by measuring the dimensions and mechanical strength of commercial and in-house prepared chewable tablets. Data collected on tablets with different thickness but same hardness or tensile strength suggests that the proposed index provides a good assessment of the force needed to chew the chewable tablets. Influence of brief exposure to salivary fluid during chewing on the mechanical strength of the chewable tablets was also evaluated. Thirty seconds exposure to the simulated salivary fluid was also found to significantly reduce (p < 0.05) the hardness and the chewing difficulty index of a number of evaluated chewable tablet drug products.

Development and optimization of taste-masked orally disintegrating tablets (ODTs) of clindamycin hydrochloride.

The purpose of this research was to develop an orally disintegrating tablet (ODT) dosage form containing taste-masked beads of clindamycin HCl. Several formulation strategies were evaluated and a taste-masked ODT of clindamycin HCl was prepared without the use of a waxy cushioning agent. Clindamycin HCl (ca. 46% w/w) was coated onto microcrystalline cellulose beads (Cellets® 200) followed by the addition of a taste-masking layer of amino methacrylate copolymer, NF (Eudragit EPO® (EPO)) coating suspension. The efficiency of both the drug coating process and the taste-masking polymer coating process, as well as the taste masking ODTs was determined using potency and drug release analysis. Magnesium stearate was found to be advantageous over talc in improving the efficiency of the EPO coating suspension. A response surface methodology using a Box-Behnken design for the tablets revealed compression force and levels of both disintegrant and talc to be the main factors influencing the ODT properties. Blending of talc to the EPO-coated beads was found to be the most critical factor in ensuring that ODTs disintegrate within 30 s. The optimized ODTs formulation also showed negligible (<0.5%) drug release in 1 min using phosphate buffer, pH 6.8 (which is analogous to the residence time and pH in the oral cavity). By carefully adjusting the levels of coating polymers, the amounts of disintegrant and talc, as well as the compression force, robust ODTs can be obtained to improve pediatric and geriatric patient compliance for clindamycin oral dosage forms.

Characterization and selection of suitable grades of lactose as functional fillers for capsule filling: part 1.

The purpose of this work is to characterize thermal, physical and mechanical properties of different grades of lactose and better understand the relationships between these properties and capsule filling performance. Eight grades of commercially available lactose were evaluated: Pharmatose 110 M, 125 M, 150 M, 200 M, 350 M (α-lactose monohydrate), AL (anhydrous lactose containing ∼80% ß-AL), DCL11 (spray dried α-lactose monohydrate containing ∼15% amorphous lactose) and DCL15 (granulated α-lactose monohydrate containing ∼12% ß-AL). In this study, different lactose grades were characterized by thermal, solid state, physical and mechanical properties and later evaluated using principal component analysis (PCA) to assess the inter-relationships among some of these properties. The lactose grades were characterized by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), moisture sorption/desorption isotherms, particle size distribution; the flow was characterized by Carr Index (CI), critical orifice diameter (COD) and angle of friction. Plug mechanical strength was estimated from its diametric crushing strength. The first and second principal components (PC) captured 47.6% and 27.4% of variation in the physical and mechanical property data, respectively. The PCA plot grouped together 110 M, AL, DCL11 and DCL15 on the one side of plot which possessed superior properties for capsule formulation and these grades were selected for future formulation development studies (part II of this work).

Development and validation of a HPLC method for dissolution and stability assay of liquid-filled cyclosporine capsule drug products.

To assay the dissolution samples of a drug product from several sources, a simple but broadly applicable analytical method is always desired. For the liquid-filled cyclosporine capsules, while analyzing the dissolution samples, the current compendial and literature HPLC methods have been found to be inadequate to provide satisfactory separation of the drug and the excipient peaks. Accordingly, a suitable isocratic reverse-phase HPLC method was developed for the analysis of dissolution samples of liquid-filled cyclosporine capsules. The method successfully separated the cyclosporine peak from the interfering chromatographic peaks of the excipients. The method was validated according to the ICH and FDA guidelines. Specificity, selectivity, linearity, accuracy, precision, and robustness were established over 3 days as part of method validation. Additionally, the degradation kinetics of cyclosporine in dissolution media was determined. Cyclosporine degradation followed a zero-order kinetics in the dissolution media with the respective rate constants of -3.5, -1.5, and -0.3%/h at 37°C, 25°C, and 10°C.

First clinical case series of frosted branch angiitis: A diagnostic algorithm is suggested.

Key Clinical Message: FBA is a clinical diagnosis of a diverse spectrum, which needs a high index of suspicion to identify the possible specific etiologies. The zones of retinal involvement can help in predicting the final visual outcome. The proposed diagnostic algorithm facilitates meticulous evaluation and targeted treatment to improve the final visual outcome. Abstract: Frosted branch angiitis is a clinical diagnosis of a diverse spectrum, which needs a high index of suspicion to identify the possible specific etiologies. We present a series of three cases of FBA with an attempt to formulate a diagnostic algorithm and refine the definition of FBA.

COVID-19 disease identification from chest CT images using empirical wavelet transformation and transfer learning.

In the current scenario, novel coronavirus disease (COVID-19) spread is increasing day-by-day. It is very important to control and cure this disease. Reverse transcription-polymerase chain reaction (RT-PCR), chest computerized tomography (CT) imaging options are available as a significantly useful and more truthful tool to classify COVID-19 within the epidemic region. Most of the hospitals have CT imaging machines. It will be fruitful to utilize the chest CT images for early diagnosis and classification of COVID-19 patients. This requires a radiology expert and a good amount of time to classify the chest CT-based COVID-19 images especially when the disease is spreading at a rapid rate. During this pandemic COVID-19, there is a need for an efficient automated way to check for infection. CT is one of the best ways to detect infection inpatients. This paper introduces a new method for preprocessing and classifying COVID-19 positive and negative from CT scan images. The method which is being proposed uses the concept of empirical wavelet transformation for preprocessing, selecting the best components of the red, green, and blue channels of the image are trained on the proposed network. With the proposed methodology, the classification accuracy of 85.5%, F1 score of 85.28%, and AUC of 96.6% are achieved.

Unifying the Clustering Kinetics of Lithium Polysulfides with the Nucleation Behavior of Li2S in Lithium-Sulfur Batteries.

Within the lithium-sulfur (Li-S) battery, a wide variety of soluble lithium polysulfide intermediates form during operation. Under lean-electrolyte or low-temperature conditions, the solution coordination of polysulfides dynamically shifts to highly clustered states, which is subsequently accompanied by inhibited electrochemical kinetics. In fact, it has been shown that the tendency for polysulfides to strongly aggregate is one of the dominant kinetically limiting obstacles towards achieving adequate utilization of active material under such conditions. While this association has been noted before, it is not explicitly understood what mechanism intrinsic to polysulfide clustering curtails the electrochemical utilization of active material, particularly during the conversion to insoluble Li2S. Here, we perform a series of investigations to unify and link the kinetic constraints that arise from polysulfide clustering to the nucleation and growth behavior of Li2S. We find that there is a drastic decrease in polysulfide diffusion coefficient arising from the advent of clustering, and that this decline functionally matches that seen for the nucleation and growth rate constants for Li2S deposition. Additionally, it is found that there is a less favorable minimization of energy during Li2S nucleation, arising from the altered solvation stability of polysulfide clusters. This knowledge expands our understanding of the Li-S materials chemistry and the primary factors dictating the electrochemical behavior.

Evoking High Donor Number-assisted and Organosulfur-mediated Conversion in Lithium-Sulfur Batteries.

The solution-mediated behavior of lithium-sulfur (Li-S) batteries presents a wide range of opportunity for evaluating and improving the performance at practical lean-electrolyte conditions. Here, we introduce methyl trifluoroacetate (CH3TFA) as an additive to the Li-S electrolyte to evaluate the joint effects of two distinct strategies: high donor number solvents/salts and organosulfur-mediated discharge. CH3TFA is shown to react with lithium polysulfides in-situ to form lithium trifluoroacetate (LiTFA) and dimethyl polysulfides. We find that both the methyl group and trifluoroacetate anion considerably enhance Li-S discharge behavior over the course of cycling, though they have distinctly beneficial effects. The TFA anion impacts solution coordination behavior, improving polarization and discharge kinetics during cycling. Meanwhile, the derivatization to dimethyl polysulfides improves the solubility of intermediate species, enhancing overall utilization under lean-electrolyte conditions. CH3TFA thus represents a new class of additives for Li-S batteries, enabling an in-situ systematic molecular engineering of intermediate species for improved performance.

Tailoring Lithium Polysulfide Coordination and Clustering Behavior through Cationic Electrostatic Competition.

The materials chemistry underlying lithium-sulfur (Li-S) batteries is uniquely dependent on the behavior of soluble lithium polysulfide intermediates, which form during operation and mediate the charge-transfer process in solution. The manner by which lithium polysulfides are solvated by surrounding solvent and salt compounds is a critical factor with regards to electrochemical utilization and reversibility of the sulfur active material. Particularly at low-temperature and lean electrolyte conditions, lithium polysulfides tend to coordinate with other polysulfide units in solution, forming large, aggregated clusters that stymie the electrochemical conversion process. However, the tendency to cluster is known to be influenced by the presence of strongly binding anionic species in solution, which present electrostatic competing interactions with Li+. The heightened electrostatic competition in turn can dissuade the formation of clustered Li+-Sx 2- bond networks. Here, we extend that understanding to the influence of distinct cationic species in solution, which can present analogous competing interactions with Sx 2- dianions to stymie polysulfide cluster formation. We find that introducing NH4 + cations into solution through an ammonium trifluoroacetate additive positively tailors the polysulfide coordination shell. This improves the electrochemical conversion kinetics at challenging lean electrolyte and subzero low-temperature conditions, and provides a more holistic understanding of polysulfide coordination behavior.

The Therapeutic and Diagnostic Potential of Amyloid ß Oligomers Selective Antibodies to Treat Alzheimer's Disease.

Improvements have been made in the diagnosis of Alzheimer's disease (AD), manifesting mostly in the development of in vivo imaging methods that allow for the detection of pathological changes in AD by magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. Many of these imaging methods, however, use agents that probe amyloid fibrils and plaques-species that do not correlate well with disease progression and are not present at the earliest stages of the disease. Amyloid ß oligomers (AßOs), rather, are now widely accepted as the Aß species most germane to AD onset and progression. Here we report evidence further supporting the role of AßOs as pathological instigators of AD and introduce promising anti-AßO diagnostic probes capable of distinguishing the 5xFAD mouse model from wild type mice by PET and MRI. In a developmental study, Aß oligomers in 5xFAD mice were found to appear at 3 months of age, just prior to the onset of memory dysfunction, and spread as memory worsened. The increase of AßOs is prominent in the subiculum and correlates with concomitant development of reactive astrocytosis. The impact of these AßOs on memory is in harmony with findings that intraventricular injection of synthetic AßOs into wild type mice induced hippocampal dependent memory dysfunction within 24 h. Compelling support for the conclusion that endogenous AßOs cause memory loss was found in experiments showing that intranasal inoculation of AßO-selective antibodies into 5xFAD mice completely restored memory function, measured 30-40 days post-inoculation. These antibodies, which were modified to give MRI and PET imaging probes, were able to distinguish 5xFAD mice from wild type littermates. These results provide strong support for the role of AßOs in instigating memory loss and salient AD neuropathology, and they demonstrate that AßO selective antibodies have potential both for therapeutics and for diagnostics.

Influence of formulation and processing factors on stability of levothyroxine sodium pentahydrate.

Stability of formulations over shelf-life is critical for having a quality product. Choice of excipients, manufacturing process, storage conditions, and packaging can either mitigate or enhance the degradation of the active pharmaceutical ingredient (API), affecting potency and/or stability. The purpose was to investigate the influence of processing and formulation factors on stability of levothyroxine (API). The API was stored at long-term (25 degrees C/60%RH), accelerated (40 degrees C/75%RH), and low-humidity (25 degrees C/0%RH and 40 degrees C/0%RH) conditions for 28 days. Effect of moisture loss was evaluated by drying it (room temperature, N(2)) and placed at 25 degrees C/0%RH and 40 degrees C/0%RH. The API was incubated with various excipients (based on package insert of marketed tablets) in either 1:1, 1:10, or 1:100 ratios with 5% moisture at 60 degrees C. Commonly used ratios for excipients were used. The equilibrium sorption data was collected on the API and excipients. The API was stable in solid state for the study duration under all conditions for both forms (potency between 90% and 110%). Excipients effect on stability varied and crospovidone, povidone, and sodium laurel sulfate (SLS) caused significant API degradation where deiodination and deamination occurred. Moisture sorption values were different across excipients. Crospovidone and povidone were hygroscopic whereas SLS showed deliquescence at high RH. The transient formulation procedures where temperature might go up or humidity might go down would not have major impact on the API stability. Excipients influence stability and if possible, those three should either be avoided or used in minimum quantity which could provide more stable tablet formulations with minimum potency loss throughout its shelf-life.

Designing Advanced Lithium-based Batteries for Low-temperature Conditions.

Energy-dense rechargeable batteries have enabled a multitude of applications in recent years. Moving forward, they are expected to see increasing deployment in performance-critical areas such as electric vehicles, grid storage, space, defense, and subsea operations. While this at first glance spells great promise for conventional lithium-ion batteries, all of these use-cases, unfortunately, share periodic and recurring exposures to extremely low-temperature conditions, a performance constraint where the lithium-ion chemistry can fail to perform optimally. Next-generation chemistries employing alternative anodes with increased solvent compatibility or altogether different operating mechanisms could present an avenue for overcoming many of the low-temperature hurdles intrinsic to the lithium-ion battery. In this article, we provide a brief overview of the challenges in developing lithium-ion batteries for low-temperature use, and then introduce an array of nascent battery chemistries that may be intrinsically better suited for low-temperature conditions moving forward. Specifically, we evaluate the prospects of using lithium-metal, lithium-sulfur, and dual-ion batteries for performance-critical low-temperature applications. These three chemistries are presented as prototypical examples of how the conventional low-temperature charge-transfer resistances can be overcome. However, these three chemistries also present their own unique challenges at low temperatures, highlighting the balance between traditional low-temperature electrolyte design and next-generation approaches.

Machine learning-based cognitive impairment classification with optimal combination of neuropsychological tests.

INTRODUCTION: An extensive battery of neuropsychological tests is currently used to classify individuals as healthy (HV), mild cognitively impaired (MCI), and with Alzheimer's disease (AD). We used machine learning models for effective cognitive impairment classification and optimized the number of tests for expeditious and inexpensive implementation. METHODS: Using random forests (RF) and support vector machine, we classified cognitive impairment in multi-class data sets from Rush Religious Orders Study Memory and Aging Project, and National Alzheimer's Coordinating Center. We applied Fischer's linear discrimination and assessed importance of each test iteratively for feature selection. RESULTS: RF has best accuracy with increased sensitivity, specificity in this first ever multi-class classification of HV, MCI, and AD. Moreover, a subset of six to eight tests shows equivalent classification accuracy as an entire battery of tests. DISCUSSIONS: Fully automated feature selection approach reveals six to eight tests comprising episodic, semantic memory, perceptual orientation, and executive functioning can accurately classify the cognitive status, ensuring minimal subject burden.

Influence of Lithium Polysulfide Clustering on the Kinetics of Electrochemical Conversion in Lithium-Sulfur Batteries.

The electrochemistry of lithium-sulfur (Li-S) batteries is heavily reliant on the structure and dynamics of lithium polysulfides, which dissolve into the liquid electrolyte and mediate the electrochemical conversion process during operation. This behavior is considerably distinct from the widely used lithium-ion batteries, necessitating new mechanistic insights to fully understand the electrochemical phenomena. Testing at low-temperature conditions presents a unique opportunity to glean new insights into the chemistry in kinetically constrained environments. Under such conditions, despite the low freezing point and favorable ionic conductivity of the glyme-based electrolyte, Li-S batteries exhibit counterintuitively poor performance. Here, we show that beyond just existing in single-molecule conformations, lithium polysulfides tend to cluster and aggregate in solution, particularly at low-temperature conditions, which subsequently constrains the kinetics of electrochemical conversion. Energetics and coordination implications of this behavior are extended towards a new framework for understanding the solution-coordination dynamics of dissolved lithium species. Based off this framework, a favorable strongly-bound lithium salt is introduced in the Li-S electrolyte to disrupt polysulfide clustered networks, enabling substantially enhanced low-temperature electrochemical performance. More broadly, this mechanistic insight heightens our understanding of polysulfide chemistry irrespective of temperature, confirming the link between the solution conformation of active material and electrochemical behavior.

Lesson from Ecotoxicity: Revisiting the Microbial Lipopeptides for the Management of Emerging Diseases for Crop Protection.

Microorganisms area treasure in terms of theproduction of various bioactive compounds which are being explored in different arenas of applied sciences. In agriculture, microbes and their bioactive compounds are being utilized in growth promotion and health promotion withnutrient fortification and its acquisition. Exhaustive explorations are unraveling the vast diversity of microbialcompounds with their potential usage in solving multiferous problems incrop production. Lipopeptides are one of such microbial compounds which havestrong antimicrobial properties against different plant pathogens. These compounds are reported to be produced by bacteria, cyanobacteria, fungi, and few other microorganisms; however, genus Bacillus alone produces a majority of diverse lipopeptides. Lipopeptides are low molecular weight compounds which havemultiple industrial roles apart from being usedas biosurfactants and antimicrobials. In plant protection, lipopeptides have wide prospects owing totheirpore-forming ability in pathogens, siderophore activity, biofilm inhibition, and dislodging activity, preventing colonization bypathogens, antiviral activity, etc. Microbes with lipopeptides that haveall these actions are good biocontrol agents. Exploring these antimicrobial compounds could widen the vistasof biological pest control for existing and emerging plant pathogens. The broader diversity and strong antimicrobial behavior of lipopeptides could be a boon for dealing withcomplex pathosystems and controlling diseases of greater economic importance. Understanding which and how these compounds modulate the synthesis and production of defense-related biomolecules in the plants is a key question-the answer of whichneeds in-depth investigation. The present reviewprovides a comprehensive picture of important lipopeptides produced by plant microbiome, their isolation, characterization, mechanisms of disease control, behavior against phytopathogens to understand different aspects of antagonism, and potential prospects for future explorations as antimicrobial agents. Understanding and exploring the antimicrobial lipopeptides from bacteria and fungi could also open upan entire new arena of biopesticides for effective control of devastating plant diseases.

Real-time on-line blend uniformity monitoring using near-infrared reflectance spectrometry: a noninvasive off-line calibration approach.

A robust, noninvasive, real-time, on-line near-infrared (NIR) quantitative method is described for blend uniformity monitoring of a pharmaceutical solid dosage form containing 29.4% (w/w) drug load with three major excipients (crospovidone, lactose, and microcrystalline cellulose). A set of 21 off-line, static calibration samples were used to develop a multivariate partial least-squares (PLS) calibration model for on-line prediction of the API content during the blending process. The concentrations of the API and the three major excipients were varied randomly to minimize correlations between the components. A micro electrical-mechanical system (MEMS) based portable, battery operated NIR spectrometer was used for this study. To minimize spectral differences between the static and dynamic measurement modes, the acquired NIR spectra were preprocessed using standard normal variate (SNV) followed by second derivative Savitzky-Golay using 21 points. The performance of the off-line PLS calibration model were evaluated in real-time on 16 laboratory scale (30 L bin size) blend experiments conducted over 3 months. To challenge the robustness of the off-line calibration model, several blend experiments were conducted using a different bin size, faster revolution speed and variations in the potency of the API. Employing the PLS calibration model developed using the off-line calibration approach, the real-time API NIR (%) predictions for all experiments were all within 90-110%. These results were confirmed using the conventional thief sampling of the final blend followed by high performance liquid chromatography (HPLC) analysis. Further confirmation was established through content uniformity by HPLC of manufactured tablets. Finally, the optimized off-line PLS method was successfully transferred to a production site which involved using a secondary NIR instrument with a 15-fold scale-up in bin size from development.