Cellular clarity: a logistic regression approach to identify root epidermal regulators of iron deficiency response.

BACKGROUND: Plants respond to stress through highly tuned regulatory networks. While prior works identified master regulators of iron deficiency responses in A. thaliana from whole-root data, identifying regulators that act at the cellular level is critical to a more comprehensive understanding of iron homeostasis. Within the root epidermis complex molecular mechanisms that facilitate iron reduction and uptake from the rhizosphere are known to be regulated by bHLH transcriptional regulators. However, many questions remain about the regulatory mechanisms that control these responses, and how they may integrate with developmental processes within the epidermis. Here, we use transcriptional profiling to gain insight into root epidermis-specific regulatory processes. RESULTS: Set comparisons of differentially expressed genes (DEGs) between whole root and epidermis transcript measurements identified differences in magnitude and timing of organ-level vs. epidermis-specific responses. Utilizing a unique sampling method combined with a mutual information metric across time-lagged and non-time-lagged windows, we identified relationships between clusters of functionally relevant differentially expressed genes suggesting that developmental regulatory processes may act upstream of well-known Fe-specific responses. By integrating static data (DNA motif information) with time-series transcriptomic data and employing machine learning approaches, specifically logistic regression models with LASSO, we also identified putative motifs that served as crucial features for predicting differentially expressed genes. Twenty-eight transcription factors (TFs) known to bind to these motifs were not differentially expressed, indicating that these TFs may be regulated post-transcriptionally or post-translationally. Notably, many of these TFs also play a role in root development and general stress response. CONCLUSIONS: This work uncovered key differences in -Fe response identified using whole root data vs. cell-specific root epidermal data. Machine learning approaches combined with additional static data identified putative regulators of -Fe response that would not have been identified solely through transcriptomic profiles and reveal how developmental and general stress responses within the epidermis may act upstream of more specialized -Fe responses for Fe uptake.

POPEYE intercellular localization mediates cell-specific iron deficiency responses.

Plants must tightly regulate iron (Fe) sensing, acquisition, transport, mobilization, and storage to ensure sufficient levels of this essential micronutrient. POPEYE (PYE) is an iron responsive transcription factor that positively regulates the iron deficiency response, while also repressing genes essential for maintaining iron homeostasis. However, little is known about how PYE plays such contradictory roles. Under iron-deficient conditions, pPYE:GFP accumulates in the root pericycle while pPYE:PYE-GFP is localized to the nucleus in all Arabidopsis (Arabidopsis thaliana) root cells, suggesting that PYE may have cell-specific dynamics and functions. Using scanning fluorescence correlation spectroscopy and cell-specific promoters, we found that PYE-GFP moves between different cells and that the tendency for movement corresponds with transcript abundance. While localization to the cortex, endodermis, and vasculature is required to manage changes in iron availability, vasculature and endodermis localization of PYE-GFP protein exacerbated pye-1 defects and elicited a host of transcriptional changes that are detrimental to iron mobilization. Our findings indicate that PYE acts as a positive regulator of iron deficiency response by regulating iron bioavailability differentially across cells, which may trigger iron uptake from the surrounding rhizosphere and impact root energy metabolism.

Aggregation patterns of copper sulphate salt via droplet drying: mediation by surface hydrophobicity and salt concentration.

Patterns in drying droplets formed from colloidal solution of copper sulphate and gelatin are investigated with respect to variation of substrate hydrophobicity and salt concentration. Hydrophilic substrates as (i) glass, (ii) quartz and hydrophobic substrate as (iii) polypropylene (PP) have been used. It is observed that the dry residue pattern of salt crystals shows curved branches of crystalline aggregate growth about droplet centre for hydrophilic substrates, while thick, light and dark concentric bands of aggregates are observed for hydrophobic substrates. The geometry and topology of the patterns have been characterized through an analysis of fractal dimension and the topological measure, Euler characteristic. The fractal dimension of the deposit increases substantially with salt concentration for hydrophilic substrates, but decreases with concentration for hydrophobic substrate. Our analysis leads us to propose that an optimal viscosity contrast that facilitates prominent viscous fingers is a function of contact angle and salt concentration. We propose that substrate hydrophobicity and salt concentration together are responsible for DLA-like aggregation in evaporating droplets.

An Atypical Presentation of Metastatic Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is notorious for spreading to various organs, however, its occurrence in the gastrointestinal (GI) tract is uncommon and poses diagnostic challenges due to vague symptoms. Here, we present the case of a 64-year-old man experiencing recurrent RCC metastasis in the GI tract. He presented with multiple episodes of hematochezia and was found to have masses in the colon, liver, and peritoneum, with histopathology confirming RCC. The patient underwent systemic chemotherapy and palliative radiation therapy, leading to symptom relief. This case emphasizes the rarity of RCC metastasizing to the GI tract and the importance of timely recognition and frequent surveillance during the remission phase to detect recurrence.

Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform.

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in "real-life" patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Computational prediction of gene regulatory networks in plant growth and development.

Plants integrate a wide range of cellular, developmental, and environmental signals to regulate complex patterns of gene expression. Recent advances in genomic technologies enable differential gene expression analysis at a systems level, allowing for improved inference of the network of regulatory interactions between genes. These gene regulatory networks, or GRNs, are used to visualize the causal regulatory relationships between regulators and their downstream target genes. Accordingly, these GRNs can represent spatial, temporal, and/or environmental regulations and can identify functional genes. This review summarizes recent computational approaches applied to different types of gene expression data to infer GRNs in the context of plant growth and development. Three stages of GRN inference are described: first, data collection and analysis based on the dataset type; second, network inference application based on data availability and proposed hypotheses; and third, validation based on in silico, in vivo, and in planta methods. In addition, this review relates data collection strategies to biological questions, organizes inference algorithms based on statistical methods and data types, discusses experimental design considerations, and provides guidelines for GRN inference with an emphasis on the benefits of integrative approaches, especially when a priori information is limited. Finally, this review concludes that computational frameworks integrating large-scale heterogeneous datasets are needed for a more accurate (e.g. fewer false interactions), detailed (e.g. discrimination between direct versus indirect interactions), and comprehensive (e.g. genetic regulation under various conditions and spatial locations) inference of GRNs.

Mechanically robust 39 GHz cut-off frequency graphene field effect transistors on flexible substrates.

Graphene has been regarded as a promising candidate channel material for flexible devices operating at radio-frequency (RF). In this work we fabricated and fully characterized double bottom-gate graphene field effect transistors on flexible polymer substrates for high frequency applications. We report a record high as-measured current gain cut-off frequency (ft) of 39 GHz. The corresponding maximum oscillation frequency (fmax) is 13.5 GHz. These state of the art high frequency performances are stable against bending, with a typical variation of around 10%, for a bending radius of up to 12 mm. To demonstrate the reliability of our devices, we performed a fatigue stress test for RF-GFETs which were dynamically bend tested 1000 times at 1 Hz. The devices are mechanically robust, and performances are stable with typical variations of 15%. Finally we investigate thermal dissipation, which is a critical parameter for flexible electronics. We show that at the optimum polarization the normalized power dissipated by the GFETs is about 0.35 mW µm(-2) and that the substrate temperature is around 200 degree centigrade. At a higher power, irreversible degradations of the performances are observed. Our study on state of the art flexible GFETs demonstrates mechanical robustness and stability upon heating, two important elements to assess the potential of GFETs for flexible electronics.

DNA fingerprinting of jute germplasm by RAPD.

The genotype characteristic of cultivars was investigated, along with varieties of both of the jute species, Corchorus olitorius and Corchorus capsularis, in the germplasm collection at the Bangladesh Jute Research Institute (BJRI). DNA fingerprinting was generated for 9 different varieties and 12 accessions of jute cultivars by using random amplified polymorphic DNA (RAPD). A total of 29 arbitrary oligonucleotide primers were screened. Seven primers gave polymorphism within the varieties, and 6 primers detected polymorphism within the accessions that were tested. A dendrogram was engendered from these data, and this gave a distinct clustering of the cultivated species of jute. Therefore, we generated RAPD markers, which are species-specific. These primers can distinguish between C. olitorius and C. capsularis. From the dendrogram that we generated between the various members of these two species, we found the existing genetic classification that agrees with our molecular marking data. A different dendrogram showed that jute accessions could be clustered into three groups. These data will be invaluable in the conservation and utilization of the genetic pool in the germplasm collection.

Distinction between cold-sensitive and -tolerant jute by DNA polymorphisms.

Jute is the principal coarse fiber for commercial production and use in Bangladesh. Therefore, the development of a high-yielding and environmental-stress tolerant jute variety would be beneficial for the agro economy of Bangladesh. Two molecular fingerprinting techniques, random-amplified polymorphic DNA (RAPD) and amplified-fragment length polymorphism (AFLP) were applied on six jute samples. Two of them were cold-sensitive varieties and the remaining four were cold-tolerant accessions. RAPD and AFLP fingerprints were employed to generate polymorphism between the cold-sensitive varieties and cold-tolerant accessions because of their simplicity, and also because there is no available sequence information on jute. RAPD data were obtained by using 30 arbitrary oligonucleotide primers. Five primers were found to give polymorphism between the varieties that were tested. AFLP fingerprints were generated using 25 combinations of selective-amplification primers. Eight primer combinations gave the best results with 93 polymorphic fragments, and they were able to discriminate the two cold-sensitive and four cold-tolerant jute populations. A cluster analysis, based on the RAPD and AFLP fingerprint data, showed the population-specific grouping of individuals. This information could be useful later in marker-aided selection between the cold-sensitive varieties and cold-tolerant jute accessions.

Ultrafast graphene oxide humidity sensors.

Sensors allow an electronic device to become a gateway between the digital and physical worlds, and sensor materials with unprecedented performance can create new applications and new avenues for user interaction. Graphene oxide can be exploited in humidity and temperature sensors with a number of convenient features such as flexibility, transparency and suitability for large-scale manufacturing. Here we show that the two-dimensional nature of graphene oxide and its superpermeability to water combine to enable humidity sensors with unprecedented response speed (∼30 ms response and recovery times). This opens the door to various applications, such as touchless user interfaces, which we demonstrate with a 'whistling' recognition analysis.

Self-aligned coupled nanowire transistor.

The integration of multiple functionalities into individual nanoelectronic components is increasingly explored as a means to step up computational power, or for advanced signal processing. Here, we report the fabrication of a coupled nanowire transistor, a device where two superimposed high-performance nanowire field-effect transistors capable of mutual interaction form a thyristor-like circuit. The structure embeds an internal level of signal processing, showing promise for applications in analogue computation. The device is naturally derived from a single NW via a self-aligned fabrication process.