Multiple Steps Research Articles

Adsorption and desorption strategy for recovering β-carotene from crude palm oil: Kinetics, equilibrium and thermodynamics studies

Palm oil uses are widespread in several industry segments. During refining process, minor compounds such as carotenoids, phytosterols, squalene and tocotrienols are lost. The β-carotene is lost due to the bleaching and the high temperature in the deodorization step. The aim of this work is to recover β-carotene before its degradation in the refining process, using adsorption-desorption strategy. Batch adsorption studies were evaluated for five adsorbents: Diaion HP20, Sepabeads SP70, Sepabeads SP700, Diaion HP2MGL, Amberlite XAD7HP. Modeling of kinetics and equilibrium curves were performed for the Sepabeads SP70, which had the best performance in adsorption. The best conditions for adsorption were at the concentration of 30% (w/w) oil in isopropyl alcohol (IPA) micelle at 30 °C for 180 min. Thermodynamics parameters of adsorption revealed a favorable, spontaneous and exothermic process associated with physical bonding. The studies performed on adsorbent reutilization proved that the regeneration is effective and allows the material reuse at least for 5 cycles without changing the adsorption capacity. Additionally, desorption was evaluated in single and multiple steps and the final enrichment factor was 3.40 ± 0.21. This process allows the palm oil utilization for edible purposes after the adsorption step while recovering β-carotene based on its physicochemical characterization.

Runx2 regulates peripheral nerve regeneration to promote Schwann cell migration and re-myelination.

Abstract JOURNAL/nrgr/04.03/01300535-202407000-00038/figure1/v/2023-11-20T171125Z/r/image-tiff Runx2 is a major regulator of osteoblast differentiation and function; however, the role of Runx2 in peripheral nerve repair is unclear. Here, we analyzed Runx2 expression following injury and found that it was specifically up-regulated in Schwann cells. Furthermore, using Schwann cell-specific Runx2 knockout mice, we studied peripheral nerve development and regeneration and found that multiple steps in the regeneration process following sciatic nerve injury were Runx2-dependent. Changes observed in Runx2 knockout mice include increased proliferation of Schwann cells, impaired Schwann cell migration and axonal regrowth, reduced re-myelination of axons, and a block in macrophage clearance in the late stage of regeneration. Taken together, our findings indicate that Runx2 is a key regulator of Schwann cell plasticity, and therefore peripheral nerve repair. Thus, our study shows that Runx2 plays a major role in Schwann cell migration, re-myelination, and peripheral nerve functional recovery following injury.

Leveraging flow chemistry for the synthesis of trisubstituted isoxazoles

The synthesis of trisubstituted isoxazoles generally requires multiple individual chemical steps, making them amenable to improvements in efficiency by telescoping as a multistep flow process. Three steps (oximation, chlorination and cycloaddition) were developed in continuous flow mode, aiming to function as an high-yielding and efficient sequence. We demonstrate this sequence using two aldehyde starting materials of interest: one carbocyclic and one heterocyclic. Between these two substrates, significant differences in solubility and reactivity necessitated modifications to the route. Most notably, the chlorination step could be carried out using either an organic N-Cl source (applicable for the carbocyclic aldehyde) or Cl2 generated on-demand in a flow setup (applicable for the heterocyclic aldehyde). By selecting the most effective method for each substrate, good yields could be achieved over the telescoped sequence.

MULTI-LEAF DISEASE DETECTION AND RECOMMENDS PESTICIDE USING DEEP LEARNING

This research describes a proposed system that uses deep learning and image processing methods to identify and categorize plant leaf diseases. The approach that is suggested comprises of two categorization methods and compares them. The first approach comprised of multiple steps leading up to the classification stage and was based on the support vector machine (SVM) algorithm. Because they are the most prevalent plant species worldwide and in Iraq specifically, tomatoes, peppers, and potatoes are the specific plant species that we use in our work. Convolution neural networks (CNNs) were employed in the second approach for classification. Fifteen classes were identified using these two methods: three classes for healthy leaves and twelve classes for illnesses of various plants that were found, such as fungi, bacteria, etc. The comparisons outcome demonstrates that the CNN algorithm is preferred over the SVM algorithm in terms of speed and accuracy, creating a system that is reliable and accurate for the identification and categorization of plant leaf diseases. The effectiveness of the system is evaluated using evaluation measures such as accuracy, precision, recall, and F1-score. Additionally discussed are the moral and environmental aspects of using pesticides. This strategys practical use is illustrated by case studies and real-world examples, which also highlight how it may be used to increase agricultural yields, lower resource consumption, and support sustainable farming methods. Finally, this study highlights how CNNs can revolutionize both pesticide recommendation and the detection of multi-leaf diseases. The integration of advanced technology with agricultural methods in this study promotes sustainable farming practices and global food security. KEYWORDS: Deep Learning, Convolutional Neural Networks (CNNs), Multi-Leaf Disease Detection, Pesticide Recommendation, Agriculture, Plant Disease Diagnosis, Image Analysis, Data Augmentation, Transfer Learning.

Partially explicit splitting method for a multi-physics problem

Multi-physics are widely studied and used in numerical analysis and simulation. Physics-based splitting methods are introduced, in which different methods are applied to solve each individual aspect of a physical system in multiple steps. The implicit methods are typically used for temporal discretization and are unconditionally stable such that the time step size can be large during the computation. However, the implicit methods are more complicated to solve, especially for nonlinear problems. In contrast, the explicit methods are relatively easier to compute, while they may require a much smaller time step size. In this paper, we propose a partially explicit scheme with physics-based splitting. We take the convection diffusion equation as an example. In this scheme, the convection equation is solved using the exact solution, and then we solve the diffusion equation via finite element methods. Some degrees of freedom in the diffusion equation are treated implicitly while others are treated explicitly. We can change the large-scale implicit system into one smaller-scale implicit system and one smaller-scale explicit system, which provides saving in computation. We analyze the stability and the order of accuracy. We also present some numerical results to show the performance of our proposed scheme.

Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing

Recent work has shown that machine learning (ML) models can skillfully forecast the dynamics of unknown chaotic systems. Short-term predictions of the state evolution and long-term predictions of the statistical patterns of the dynamics (“climate”) can be produced by employing a feedback loop, whereby the model is trained to predict forward only one time step, then the model output is used as input for multiple time steps. In the absence of mitigating techniques, however, this feedback can result in artificially rapid error growth (“instability”). One established mitigating technique is to add noise to the ML model training input. Based on this technique, we formulate a new penalty term in the loss function for ML models with memory of past inputs that deterministically approximates the effect of many small, independent noise realizations added to the model input during training. We refer to this penalty and the resulting regularization as Linearized Multi-Noise Training (LMNT). We systematically examine the effect of LMNT, input noise, and other established regularization techniques in a case study using reservoir computing, a machine learning method using recurrent neural networks, to predict the spatiotemporal chaotic Kuramoto–Sivashinsky equation. We find that reservoir computers trained with noise or with LMNT produce climate predictions that appear to be indefinitely stable and have a climate very similar to the true system, while the short-term forecasts are substantially more accurate than those trained with other regularization techniques. Finally, we show the deterministic aspect of our LMNT regularization facilitates fast reservoir computer regularization hyperparameter tuning.

The interplay between tumor and nodal microenvironments for the formation of nodal premetastatic niche in head and neck cancer.

Head and neck cancer (HNC) encompasses a number of malignancies originating in the head and neck area. In patients with HNC, cervical lymph nodes constitute metastatic sites for cancer cells that escape primary tumors. The premetastatic niche (PMN) is a crucial concept in understanding metastatic disease. PMN refers to the microenvironment resulting mainly from primary tumor cells to foster metastatic tumor cell growth at a distant organ. Tumor microenvironment (TME) plays an important part in the pathogenesis of PMN. A significant prognostic factor is the close association between metastases of lymph nodes and organ dissemination in many different malignancies. The nodal premetastatic niche (NPMN) is a particular type of PMN located within the lymph nodes. NPMN formation is specifically important in HNC as regional lymph node metastasis commonly occurs. The formation happens when tumor cells create a supportive microenvironment within lymph nodes, facilitating their survival, growth, spread, and invasion. This complex mechanism involves multiple steps and cellular interactions between the primary tumor and tumor microenvironment. Several extracellular matrix (ECM) macromolecules, cytokines, and growth factors are implicated in this process. The aim of this article is to present the most recent data on the regulation of the lymph node PMN at molecular and cellular levels in HNC, as well as insights with respect to the relationship between primary tumor cells and the microenvironment of lymph nodes, and the formation of NPMN. We also critically discuss on potential targets for preventing or disrupting nodal metastases and identify potential biomarkers for predicting HNC outcomes.

Sex pheromone biosynthesis in the sugarcane borer Diatraea saccharalis: paving the way for biotechnological production.

The sugarcane borer Diatraea saccharalis (Lepidoptera) is a key pest on sugarcane and other grasses in the Americas. Biological control as well as insecticide treatments are used for pest management, but economic losses are still significant. The use of female sex pheromones for mating disruption or mass trapping in pest management could be established for this species, provided that economical production of pheromone is available. Combining in vivo labelling studies, differential expression analysis of transcriptome data and functional characterisation of insect genes in a yeast expression system, we reveal the biosynthetic pathway and identify the desaturase and reductase enzymes involved in the biosynthesis of the main pheromone component (9Z,11E)-hexadecadienal, and minor components hexadecanal, (9Z)-hexadecenal and (11Z)-hexadecenal. We next demonstrate heterologous production of the corresponding alcohols of the pheromone components, by expressing multiple steps of the biosynthetic pathway in yeast. Elucidation of the genetic basis of sex pheromone biosynthesis in D. saccharalis, and heterologous expression in yeast, paves the way for biotechnological production of the pheromone compounds needed for pheromone-based pest management of this species. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The Development of Text Messages to Support People at Risk of Diabetes in Low-Resourced Communities: The South African Diabetes Prevention Programme.

Emerging evidence suggests that the addition of text messages to standard healthy lifestyle interventions may improve the outcomes of diabetes prevention programs (DPP). This paper describes the process of developing text messages targeting behavior change in people at risk of developing diabetes in low-resourced communities as part of the South African DPP (SA-DPP). The development comprised multiple steps led by nutrition and physical activity experts. The steps included the following: (1) text message development based on the existing SA-DPP curriculum and its formative research; (2) text message evaluation for readability/understandability in terms of content, language, and quality, with 75 participants from two low-resourced areas in Cape Town; (3) text message refinement by the expert panel; (4) evaluation of the refined text messages by participants from Step 2; and (5) text bank finalization. Based on the readability survey, 37 of the 67 formulated text messages [24 of the 44 encouraged healthy eating, and 13 of the 23 promoted physical activity] were refined. Based on focused discussions with participants, seven more messages were refined to consider alternative terminology. The final text bank includes a total of 67 messages comprising topics related to fruit and vegetable consumption as well as the importance of having variety in the diet (n = 15), limiting fat intake (n = 10), avoiding sugar (n = 11), avoiding salt (n = 5), promoting fiber-rich foods (n = 1), messages promoting physical activity (n = 21), and general check-in messages (n = 4). Most of the text messages were acceptable, understandable, and largely feasible to all participants, with some of the nutrition-related messages being less feasible for participants due to their socioeconomic position. The next step is to assess the text messages in the SA-DPP intervention trial.

In-process epimerisation of alginates from Saccharina latissima, Alaria esculenta and Laminaria hyperborea

Alginates are valued in many industries, due to their versatile properties. These polysaccharides originate from brown algae (Phaeophyceae) and some bacteria of the Azotobacter and Pseudomonas genera, consisting of 1 → 4 linked β-d-mannuronic acid (M), and its C5-epimer α-l-guluronic acid (G). Several applications rely on a high G-content, which confers good gelling properties. Because of its high natural G-content (FG = 0.60–0.75), the alginate from Laminaria hyperborea (LH) has sustained a thriving industry in Norway. Alginates from other sources can be upgraded with mannuronan C-5 epimerases that convert M to G, and this has been demonstrated in many studies, but not applied in the seaweed industry. The present study demonstrates epimerisation directly in the process of alginate extraction from cultivated Saccharina latissima (SL) and Alaria esculenta (AE), and the lamina of LH. Unlike conventional epimerisation, which comprises multiple steps, this in-process protocol can decrease the time and costs necessary for alginate upgrading. In-process epimerisation with AlgE1 enzyme enhanced G-content and hydrogel strength in all examined species, with the greatest effect on SL (FG from 0.44 to 0.76, hydrogel Young's modulus from 22 to 34 kPa). As proof of concept, an upscaled in-process epimerisation of alginate from fresh SL was successfully demonstrated.

Recycling of Wood–Plastic Composites—A Reprocessing Study

Wood–plastic composites, consisting of wood particles and a thermoplastic matrix, are common composites often used in buildings as decking boards or for similar non-load-carrying applications. As these are usually semi-finished products, a certain amount of material is available after cutting these to size, in the factory and also at installation sites. Especially for in-house waste streams in factories, the question remains whether these materials can be reprocessed without any negative influence on the materials’ properties. Therefore, the aim of this work is to investigate the influence of reprocessing on the property profile of polypropylene based wood–plastic composites. Two base formulations with 40 wt% of wood particles and two different polypropylene grades were investigated for their mechanical properties, wood particle size, color, weathering stability and water uptake. We found that most of the wood–plastic composites’ properties were not negatively influenced by the multiple processing steps; the most pronounced effect beside particle size reduction is color degradation, as the composites darken with increasing number of processing steps. In our opinion this shows, that wood–plastic composites can be recycled, especially if these are only reprocessed in smaller shares together with virgin materials.

The phylogenetic reconstruction of the Neotropical cycad genus Ceratozamia (Zamiaceae) reveals disparate patterns of niche evolution

The cycad genus Ceratozamia comprises 40 species from Mexico, Guatemala, Belize, and Honduras, where cycads occur throughout climatically varied montane habitats. Ceratozamia has the potential to reveal the history and processes of species diversification across diverse Neotropical habitats in this region. However, the species relationships within Ceratozamia and the ecological trends during its evolution remain unclear. Here, we aimed to clarify the phylogenetic relationships, the timing of clade and species divergences, and the niche evolution throughout the phylogenetic history of Ceratozamia. Genome-wide DNA sequences were obtained with MIG-seq, and multiple data-filtering steps were used to optimize the dataset used to construct an ultrametric species tree. Divergence times among branches and ancestral niches were estimated. The niche variation among species was evaluated, summarized into two principal components, and their ancestral states were reconstructed to test whether niche shifts among branches can be explained by random processes, under a Brownian Motion model. Ceratozamia comprises three main clades, and most species relationships within the clades were resolved. Ceratozamia has diversified since the Oligocene, with major branching events occurring during the Miocene. This timing is consistent with fossil evidence, the timing estimated for other Neotropical plant groups, and the major geological events that shaped the topographic and climatic variation in Mexico. Patterns of niche evolution in the genus do not accord with the Brownian Motion model. Rather, non-random evolution with shifts towards more seasonal environments at high latitudes, or shifts towards humid or dry environments at low latitudes explain the diversification of Ceratozamia. We present a comprehensive phylogenetic reconstruction for Ceratozamia and identify for the first time the environmental factors involved in clade and species diversification within the genus. This study alleviates the controversies regarding the species relationships in the genus and provides the first evidence that latitude-associated environmental factors may influence processes of niche evolution in cycads.

Patients with Private Insurance Endure Significantly Longer Delays in Time from Intent to CAR-T to Apheresis (Brain-2-Vein) in Multiple Treated Diffuse Large B-Cell Lymphoma: Analysis By Cellular Therapy Intent Quotient (CTIQ)

Introduction: Since FDA approval in 2017, chimeric antigen receptor T-cell (CAR-T) therapy has become an integral part of the treatment algorithm for diffuse large B-cell lymphoma (DLBCL). Despite CD19-modified CAR-T effectiveness in multiple prospective clinical trials, with the transition to a commercial product at an authorized treatment center (ATC) it became apparent that multiple steps additional steps were needed before apheresis for a commercial CAR-T cell product. The workflow for an ATC namely during the B2V time appeared to be significantly different than the clinical trial experience. There remains a dearth of data that evaluates the impact of the B2V time. Intent to pursue CAR-T therapy in the commercial environment has two time periods: Brain-to-Vain (B2V) and Vein-to-Vein (V2V). The B2V time encapsulates referral and evaluation for CAR-T, purchase authorization, when needed negotiation of a single case agreement (SCA), and slot assignment for collection of a cellular product. The time between apheresis and cellular product infusion is known as the V2V period, which is product specific and established from prospective clinical trials. We identified that patients with private insurance or Medicare with managed plans at our institution often require a SCA. A SCA is a contract between the insurance company and the ATC that allows the patient to receive therapy using their in-network benefits. We hypothesized there would be a discrepancy in the B2V time between patients who required a SCA and those who did not. We further hypothesized that patients who did not require a SCA would experience significantly improved treatment outcomes, including a higher percentage achieving the best response of complete response (CR) with a superior prolonged overall survival (OS). Methods: To test these hypotheses, we performed a single-center retrospective study of consecutively evaluated patients with DLBCL who had at least two prior lines of therapy and intended to receive CAR-T therapy with a single CAR-T product at the University of Nebraska from 2018-2022. Patient and disease characteristics were collected. Intent to CAR-T (iCAR-T) was defined as the date of consultation at the ATC to date of apheresis of the product. Cellular therapy intent quotient (CTIQ) was defined as the number of infused with a CAR-T product versus those who intended to go to CAR-T. Those patients who intended to go to CAR-T but did not proceed to apheresis or product infusion were included in the calculation of CTIQ and OS. Results: Of 64 patients who intended to receive CAR-T therapy, 42 required a SCA (66%). Most (39/42) of the patients requiring a SCA had private insurance. All (22/22) of the patients in the non-SCA cohort had public insurance. The was no difference between cohorts based on gender, disease characteristics, distance traveled to ATC, and prior lines of therapy. As expected, the non-SCA cohort was significantly older than the SCA cohort, with mean ages of 69 and 55 respectively (p=0.0001). The CTIQ for the entire group was 94% (60/64). Of the 42 patients who required a SCA before apheresis, 39 (CTIQ– 92.8%) underwent apheresis. Of the 22 patients who did not require a SCA, 21 (CTIQ–95.5%) underwent apheresis. Of the patients who were apheresed, the B2V time was significantly longer for the SCA (42 days; 15-92) compared to the non-SCA cohorts (24 days; range 7-78)(p=0.0005). The average V2V times for the SCA and non-SCA groups were comparable at 29 and 31 days, respectively. All patients who underwent apheresis had their CAR-T cells infused. No significant difference in best response of CR or OS was observed. The best response of CR for the SCA and non-SCA groups was 46% and 57%, respectively (p=0.417). The median OS post-iCAR-T for the SCA group was 19 months, and the median OS for the non-SCA group was 45.2 months (p=0.3327). Conclusion: Patients who require a SCA experienced a significantly longer time to CAR-T apheresis compared to those not requiring a SCA. The longer B2V time acknowledges a period that is often unaccounted for in other trials. Our assessment was limited due to small cohort size and implementation of bridging therapies (results to be presented). Further investigation comparing the CTIQ and B2V time to outcomes with commercial products is warranted to ensure patients are receiving equitable access regardless of insurance type.

To let go or not to let go: how ParA can impact the release of the chromosomal anchoring in Caulobacter crescentus.

Chromosomal maintenance is vital for the survival of bacteria. In Caulobacter crescentus, chromosome replication initiates at ori and segregation is delayed until the nearby centromere-like region parS is replicated. Our understanding of how this sequence of events is regulated remains limited. The segregation of parS has been shown to involve multiple steps including polar release from anchoring protein PopZ, slow movementand fast ParA-dependent movement to theopposite cell pole. In this study, we demonstrate that ParA's competing attractions from PopZ and from DNA are critical for segregation of parS. Interfering with this balance of attractions-by expressing a variant ParA-R195E unable to bind DNA and thus favoring interactions exclusively between ParA-PopZ-results in cell death. Our data revealed that ParA-R195E's sole interactions with PopZ obstruct PopZ's ability to release the polar anchoring of parS, resulting in cells with multiple parS loci fixed at one cell pole. We show that the inability to separate and segregate multiple parS loci from the pole is specifically dependent on the interaction between ParA and PopZ. Collectively, our results reveal that the initial steps in chromosome segregation are highly regulated.

Multi-Level Precues for Guiding Tasks Within and Between Workspaces in Spatial Augmented Reality.

We explore Spatial Augmented Reality (SAR) precues (predictivecues) for procedural tasks within and between workspaces and for visualizing multiple upcoming steps in advance. We designed precues based on several factors: cue type, color transparency, and multi-level (number of precues). Precues were evaluated in a procedural task requiring the user to press buttons in three surrounding workspaces. Participants performed fastest in conditions where tasks were linked with line cues with different levels of color transparency. Precue performance was also affected by whether the next task was in the same workspace or a different one.

UAV remote sensing image stitching via improved VGG16 Siamese feature extraction network

UAV remote sensing image stitching can provide a more comprehensive and continuous area by stitching several overlapping region images. It has been widely used in many fields, such as airborne reconnaissance and surveillance tasks, agriculture production, geological disaster monitoring, and so on. However, traditional feature-based image stitching methods often require hand-crafted features and multiple execution steps, which could extract many redundant feature points in non-overlapping regions and may fail to stitch images with weak textures. To solve this problem, we propose an improved VGG16 Siamese network for the UAV remote sensing image stitching model to achieve end-to-end stitching. The first 13 layers of the VGG16 network were intercepted to form a shared weights feature extraction network, and an improved Squeeze-and-Excitation module was introduced to effectively extract the features of the overlapping areas of the images. A network of regressing affine matrix was designed by using the LeakyReLu activation function to protect the relevant feature maps after feature fine matching, which improves the accuracy of image stitching. Besides, we constructed datasets to train our network: a single UAV remote sensing image was used to form a training image pair based on a limited degree of affine transformation, and the real label of affine transformation between the image pairs was obtained. We compared the SIFT+RANSAC, APAP, and deep homography estimation-based image stitching algorithm on the UAV remote sensing datasets. Experiments show the value of structural similarity(SSIM) increased by 24.1%, and the root mean square error(RMSE) was reduced by 14.69%. Moreover, the proposed stitching model also has good stitching results for UAV remote sensing images as well as weak texture images in subjective visual effects.

Lyophilized allogeneic costal cartilage graft for septorhinoplasty

Background As rhinoplasty techniques have become more complex, surgeons often need more than what septal or conchal cartilage can provide. While costal cartilage became more popular for that reason, some surgeons are still uncomfortable with its invasiveness and donor site morbidity. Here, we used lyophilized allogeneic costal cartilage for septorhinoplasty and investigated its safety and usefulness.Methods The costal cartilage was harvested from a cadaveric donor and treated via multiple steps, including defatting and lyophilization, to remove all viable cells and antigenicity. The cartilage was then stored at room temperature and rehydrated 24 hours before use. Lyophilized cartilage allografts were used in 20 patients. Three types of septal graft were performed — spreader, batten, and extension — to correct septal or columellar deviation and enhance the nasal tip.Results The mean follow-up period was 4.3 years. In all cases, the graft successfully met the rhinoplasty purpose. No significant deformation was detected in any of the patients. Although warping was observed in one patient (5%), there was no case of clinical infection, extrusion, or graft removal and no revisional surgery for an unfavorable aesthetic result.Conclusions Lyophilized allogeneic cartilage was used for septorhinoplasty very safely and effectively. It can be carved into any shape and has all other properties required for perfectly replacing autologous costal cartilage. The main advantage of cartilage allografts is a limitless supply of high-quality cartilage without donor site morbidity. The disadvantages include the need for special facilities and manpower and extra covering cost.

Revealing the role of double-layer microenvironments in pH-dependent oxygen reduction activity over metal-nitrogen-carbon catalysts

A standing puzzle in electrochemistry is that why the metal-nitrogen-carbon catalysts generally exhibit dramatic activity drop for oxygen reduction when traversing from alkaline to acid. Here, taking FeCo-N6-C double-atom catalyst as a model system and combining the ab initio molecular dynamics simulation and in situ surface-enhanced infrared absorption spectroscopy, we show that it is the significantly distinct interfacial double-layer structures, rather than the energetics of multiple reaction steps, that cause the pH-dependent oxygen reduction activity on metal-nitrogen-carbon catalysts. Specifically, the greatly disparate charge densities on electrode surfaces render different orientations of interfacial water under alkaline and acid oxygen reduction conditions, thereby affecting the formation of hydrogen bonds between the surface oxygenated intermediates and the interfacial water molecules, eventually controlling the kinetics of the proton-coupled electron transfer steps. The present findings may open new and feasible avenues for the design of advanced metal-nitrogen-carbon catalysts for proton exchange membrane fuel cells.

Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data

Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs – two hosts in which infection was transmitted from one to the other – is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within-host single nucleotide variants (iSNVs) are maintained over multiple transmission steps and present a model for inferring the likelihood that a given pair of sequenced samples are linked by transmission. In this work we show that, beyond the presence and absence of within-host variants, differences arising in the relative abundance of iSNVs (allelic frequency) can infer transmission pairs more precisely. Our approach further highlights the critical role bottlenecks play in reserving the within-host diversity during transmission.

A single step and rapid protein extraction protocol developed for cell lines and tissues: Compatible for gel based and gel free proteomic approaches

Proteins are crucial research molecules in modern biology. Almost every biological research area needs protein-based assays to answer the research questions. The study of the total protein content of a biological sample known as Proteomics, is one of the highly rated qualitative and quantitative approach to address numerous biological problems including clinical research. The key step to successfully generate high quality proteomics data is the efficient extraction of proteins from biological samples. Although different methods are in use for protein extraction from a wide variety of samples, however, because of their prolonged protocol and multiple steps involved, final protein yield is sacrificed. Here, we have shown the development of a simple single step method for extraction of proteins from mammalian cell lines as well as tissue samples in an effective and reproducible manner. This method is based on lysis of samples directly in a modified lysis buffer without CHAPS (7 M Urea, 2 M Thiourea, and 10 mM Tris-Cl; pH 8.5) that is compatible with gel based and gel free approaches. This developed protocol is reliable and should be useful for a wide range of proteomic studies involving various biological samples.