Adoptability of New Technology in the Small-Holdings Tea Sector

The degree of adoption of recommended technology is a crucial factor in the tea smallholdings sector of the low country Sri Lanka as far as the yield is concerned. An empirical study was carried out to ascertain the present situation. Almost all the recommendations were grouped into 11 packages (selection of clones, fertilizer application, soil and moisture conservation, field establishment, training, infilling, weed control, pruning, shading, pest and disease control and plucking). A package consisted of sub indicators to reveal farmers’ adoption level. High, middle, low and non-adopters were given justified scores (according to their importance to the yield). The total of marks given to sub indicators was the adoption index of farmers. Though the mean adoption level was 71%, some packages such as pest and disease control, and weed control were marginally adopted. Highest adopted packages included plucking, clone selection, field establishment, and fertilizer application (above 75% level). Adoption level was positively correlated to education, number of dependents, labour use pattern, and subsidies and further, it was negatively correlated to land extent

RNA-Seq and molecular docking reveal multi-level pesticide resistance in the bed bug

<p>Abstract</p> <p>Background</p> <p>Bed bugs (<it>Cimex lectularius</it>) are hematophagous nocturnal parasites of humans that have attained high impact status due to their worldwide resurgence. The sudden and rampant resurgence of <it>C. lectularius </it>has been attributed to numerous factors including frequent international travel, narrower pest management practices, and insecticide resistance.</p> <p>Results</p> <p>We performed a next-generation RNA sequencing (RNA-<it>Seq</it>) experiment to find differentially expressed genes between pesticide-resistant (PR) and pesticide-susceptible (PS) strains of <it>C. lectularius</it>. A reference transcriptome database of 51,492 expressed sequence tags (ESTs) was created by combining the databases derived from <it>de novo </it>assembled mRNA-<it>Seq </it>tags (30,404 ESTs) and our previous 454 pyrosequenced database (21,088 ESTs). The two-way GLMseq analysis revealed ~15,000 highly significant differentially expressed ESTs between the PR and PS strains. Among the top 5,000 differentially expressed ESTs, 109 putative defense genes (cuticular proteins, cytochrome P450s, antioxidant genes, ABC transporters, glutathione <it>S</it>-transferases, carboxylesterases and acetyl cholinesterase) involved in penetration resistance and metabolic resistance were identified. Tissue and development-specific expression of P450 CYP3 clan members showed high mRNA levels in the cuticle, Malpighian tubules, and midgut; and in early instar nymphs, respectively. Lastly, molecular modeling and docking of a candidate cytochrome P450 (CYP397A1V2) revealed the flexibility of the deduced protein to metabolize a broad range of insecticide substrates including DDT, deltamethrin, permethrin, and imidacloprid.</p> <p>Conclusions</p> <p>We developed significant molecular resources for <it>C. lectularius </it>putatively involved in metabolic resistance as well as those participating in other modes of insecticide resistance. RNA-<it>Seq </it>profiles of PR strains combined with tissue-specific profiles and molecular docking revealed multi-level insecticide resistance in <it>C. lectularius</it>. Future research that is targeted towards RNA interference (RNAi) on the identified metabolic targets such as cytochrome P450s and cuticular proteins could lay the foundation for a better understanding of the genetic basis of insecticide resistance in <it>C. lectularius</it>.</p

Multiscale mechanobiology: mechanics at the molecular, cellular, and tissue levels

Mechanical force is present in all aspects of living systems. It affects the conformation of molecules, the shape of cells, and the morphology of tissues. All of these are crucial in architecture-dependent biological functions. Nanoscience of advanced materials has provided knowledge and techniques that can be used to understand how mechanical force is involved in biological systems, as well as to open new avenues to tailor-made bio-mimetic materials with desirable properties. In this article, we describe models and show examples of how force is involved in molecular functioning, cell shape patterning, and tissue morphology

pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm

Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modeling situations within a single, consistent architecture

Single molecule force measurements of perlecan/HSPG2: A key component of the osteocyte pericellular matrix

Perlecan/HSPG2, a large, monomeric heparan sulfate proteoglycan (HSPG), is a key component of the lacunar canalicular system (LCS) of cortical bone, where it is part of the mechanosensing pericellular matrix (PCM) surrounding the osteocytic processes and serves as a tethering element that connects the osteocyte cell body to the bone matrix. Within the pericellular space surrounding the osteocyte cell body, perlecan can experience physiological fluid flow drag force and in that capacity function as a sensor to relay external stimuli to the osteocyte cell membrane. We previously showed that a reduction in perlecan secretion alters the PCM fiber composition and interferes with bone's response to a mechanical loading in vivo. To test our hypothesis that perlecan core protein can sustain tensile forces without unfolding under physiological loading conditions, atomic force microscopy (AFM) was used to capture images of perlecan monomers at nanoscale resolution and to perform single molecule force measurement (SMFMs). We found that the core protein of purified full-length human perlecan is of suitable size to span the pericellular space of the LCS, with a measured end-to-end length of 170 ± 20 nm and a diameter of 2–4 nm. Force pulling revealed a strong protein core that can withstand over 100 pN of tension well over the drag forces that are estimated to be exerted on the individual osteocyte tethers. Data fitting with an extensible worm-like chain model showed that the perlecan protein core has a mean elastic constant of 890 pN and a corresponding Young's modulus of 71 MPa. We conclude that perlecan has physical properties that would allow it to act as a strong but elastic tether in the LCS

An image-based model of brain volume biomarker changes in Huntington's disease

Objective: Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages. Methods: We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides. Results: The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers. Interpretation: We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease

Impurity-assisted tunneling in graphene

The electric conductance of a strip of undoped graphene increases in the presence of a disorder potential, which is smooth on atomic scales. The phenomenon is attributed to impurity-assisted resonant tunneling of massless Dirac fermions. Employing the transfer matrix approach we demonstrate the resonant character of the conductivity enhancement in the presence of a single impurity. We also calculate the two-terminal conductivity for the model with one-dimensional fluctuations of disorder potential by a mapping onto a problem of Anderson localization.Comment: 6 pages, 3 figures, final version, typos corrected, references adde