Influence of Potassium Fertilizer Application Timing on Cotton Production as Related to Soil Potassium on U.S. Coastal Plain Soils

Understanding soil K dynamics is highly significant in cotton production owing to its prominent role in cotton fiber quality. About 31 % of cotton production in the U.S. is concentrated in SE states, with coastal plain soils having low innate K availability. Crop fertilizer-K recommendations are primarily made worldwide and across the U.S. using pre-plant STK concentrations. A literature review on cotton K studies suggests that fertilizer-K recommendations based on pre-plant STK concentrations alone need fine-tuning to meet the increasing K demands in modern cultivars, variations in crop K requirement patterns, and varied soil K supplying capacity. Studies have been conducted to find the optimum fertilizer-K rate and split fertilizer-K application impact in cotton. However, there is a lack of studies assessing if whole K application at high nutrient requirement growth stages can improve K-use efficiency compared to the application at planting. Field studies were conducted at Edisto REC in Blackville, SC, from 2018 to 2021 on soils with varying STK concentrations to evaluate the impact of different fertilizer-K application timing on cotton growth, yield, fiber quality and K-use efficiency. Treatments included fertilizer-K application rates (KR) of 0, 46, 92, and 138 kg K ha-1 applied either at planting, first square growth stage, or first flower growth stage. In the 2018 to 2020 field studies, pre-plant STK concentrations were in the low category (16-30 mg kg-1 M-1 K), but a yield response was noted only in the 2020 study, with the highest yield recorded with KR of 92 kg K ha-1 applied at the time of cotton planting. In the 2018 and 2019 trials with low STK, the utilization of subsoil K in the clayey subsoil horizon (Bt) could have caused no yield response to the K application. Cotton growth was highest, with a 92 kg ha-1 rate, when applied at planting with no impact on lint percentage. The yield and fiber quality parameters showed similar trends across five years for parameters like fiber length, length uniformity, elongation, and contrasting trends concerning micronaire. However, fiber quality was reduced due to late planting and exposure to unfavorable weather conditions. Agronomic K-use efficiency increased two-fold with the single whole application at planting compared to the first square and flower stage application. Continued research on the impact of varying fertilizer-K rates and application timing in different soil types across South Carolina can give more insight into the soil-plant K dynamics existing in the region to further validate the fertilizer-K recommendations adopted in the state

Ceramic Materials for 3D Printing of Biomimetic Bone Scaffolds – Current state–of–the–art & Future Perspectives

Ceramic bone implants have potential properties ideal for long-term implantation applications. On comparison with other materials, ceramic biomaterials have advantages such as biocompatibility, low cost, osteoconductivity, osteoinductivity, corrosion resistance, and can be made into various shapes with desired surface properties. Among transplantation surgeries, bone transplantation is the second largest in the globe after blood transfusion which is an indication for rising hope on the potential treatment options for bone. 3D printing is one of the most advanced fabrication techniques to create customized bone implants using materials such as ceramics and their composites. Developing bone scaffolds that precisely recapitulate the mechanical properties and other biological functions of bone remains a major challenge. However, extensive research on ceramic biomaterials have resulted in the successful 3D printing of complex bony designs with >50% porosity with cortical bone mechanical properties. This review critically analyses the use of various 3D printing techniques to fabricate ceramic bone scaffolds. Further, various natural and synthetic ceramic materials for producing customized ceramic implants are discussed along with potential clinical applications. Finally, a list of companies that offer customized 3D printed implants and the future on clinical translation of 3D printed ceramic bone implants are outlined

Modeling the effects of genetic- and diet-induced obesity on melanoma progression in zebrafish

Obesity is a rising concern and associated with an increase in numerous cancers, often in a sex-specific manner. Preclinical models are needed to deconvolute the intersection between obesity, sex and melanoma. Here, we generated a zebrafish system that can be used as a platform for studying these factors. We studied how germline overexpression of Agrp along with a high-fat diet affects melanomas dependent on BRAF(V600E) and loss of p53. This revealed an increase in tumor incidence and area in male, but not female, obese fish, consistent with the clinical literature. We then determined whether this was further affected by additional somatic mutations in the clinically relevant genes rb1 or ptena/b. We found that the male obesogenic effect on melanoma was present with tumors generated with BRAF;p53;Rb1 but not BRAF;p53;Pten. These data indicate that both germline (Agrp) and somatic (BRAF, Rb1) mutations contribute to obesity-related effects in melanoma. Given the rapid genetic tools available in the zebrafish, this provides a high-throughput system to dissect the interactions of genetics, diet, sex and host factors in obesity-related cancers

Ceramic materials for 3D printing of biomimetic bone scaffolds – Current state-of-the-art & future perspectives

Ceramic bone implants have potential properties ideal for long-term implantation applications. On comparison with other materials, ceramic biomaterials have advantages such as biocompatibility, low cost, osteoconductivity, osteoinductivity, corrosion resistance, and can be made into various shapes with desired surface properties. Among transplantation surgeries, bone transplantation is the second largest in the globe after blood transfusion which is an indication for rising hope on the potential treatment options for bone. 3D printing is one of the most advanced fabrication techniques to create customized bone implants using materials such as ceramics and their composites. Developing bone scaffolds that precisely recapitulate the mechanical properties and other biological functions of bone remains a major challenge. However, extensive research on ceramic biomaterials have resulted in the successful 3D printing of complex bony designs with >50% porosity with cortical bone mechanical properties. This review critically analyses the use of various 3D printing techniques to fabricate ceramic bone scaffolds. Further, various natural and synthetic ceramic materials for producing customized ceramic implants are discussed along with potential clinical applications. Finally, a list of companies that offer customized 3D printed implants and the future on clinical translation of 3D printed ceramic bone implants are outlined

Lipid droplets are a metabolic vulnerability in melanoma

Abstract Melanoma exhibits numerous transcriptional cell states including neural crest-like cells as well as pigmented melanocytic cells. How these different cell states relate to distinct tumorigenic phenotypes remains unclear. Here, we use a zebrafish melanoma model to identify a transcriptional program linking the melanocytic cell state to a dependence on lipid droplets, the specialized organelle responsible for lipid storage. Single-cell RNA-sequencing of these tumors show a concordance between genes regulating pigmentation and those involved in lipid and oxidative metabolism. This state is conserved across human melanoma cell lines and patient tumors. This melanocytic state demonstrates increased fatty acid uptake, an increased number of lipid droplets, and dependence upon fatty acid oxidative metabolism. Genetic and pharmacologic suppression of lipid droplet production is sufficient to disrupt cell cycle progression and slow melanoma growth in vivo. Because the melanocytic cell state is linked to poor outcomes in patients, these data indicate a metabolic vulnerability in melanoma that depends on the lipid droplet organelle

SRC-2-mediated coactivation of anti-tumorigenic target genes suppresses MYC-induced liver cancer

<div><p>Hepatocellular carcinoma (HCC) is the fifth most common solid tumor in the world and the third leading cause of cancer-associated deaths. A <i>Sleeping Beauty</i>-mediated transposon mutagenesis screen previously identified mutations that cooperate with MYC to accelerate liver tumorigenesis. This revealed a tumor suppressor role for <i>Steroid Receptor Coactivator 2</i>/<i>Nuclear Receptor Coactivator 2</i> (<i>Src-2</i>/<i>Ncoa2</i>) in liver cancer. In contrast, SRC-2 promotes survival and metastasis in prostate cancer cells, suggesting a tissue-specific and context-dependent role for SRC-2 in tumorigenesis. To determine if genetic loss of SRC-2 is sufficient to accelerate MYC-mediated liver tumorigenesis, we bred <i>Src-2</i>^<i>-/-</i> mice with a MYC-induced liver tumor model and observed a significant increase in liver tumor burden. RNA sequencing of liver tumors and <i>in vivo</i> chromatin immunoprecipitation assays revealed a set of direct target genes that are bound by SRC-2 and exhibit downregulated expression in <i>Src-2</i>^<i>-/-</i> liver tumors. We demonstrate that activation of <i>SHP (Small Heterodimer Partner)</i>, <i>DKK4</i> (<i>Dickkopf-4)</i>, and <i>CADM4 (Cell Adhesion Molecule 4)</i> by SRC-2 suppresses tumorigenesis <i>in vitro</i> and <i>in vivo</i>. These studies suggest that SRC-2 may exhibit oncogenic or tumor suppressor activity depending on the target genes and nuclear receptors that are expressed in distinct tissues and illuminate the mechanisms of tumor suppression by SRC-2 in liver.</p></div

Overexpression of SRC-2 upregulates candidate gene expression and reduces HCC cell tumor formation <i>in vivo</i>.

<p>(A) Western blot demonstrating expression of SRC-2 and DKK4 levels in Huh7 cells. Cells were infected with pLJM1 lentiviruses expressing eGFP (as a control) or SRC-2. (B) Real-time PCR quantification of <i>SRC-2</i>, <i>SHP</i> and <i>DKK4</i> expression in Huh7 cells expressing eGFP or SRC-2. (C) MTS assay measuring proliferation of cells overexpressing SRC-2. Error bars in (B) and (C) represent SDs from triplicate measurements. Student’s unpaired t-test was used to evaluate statistical significance. * = p<0.05; ** = p<0.01; **** = p<0.0001. (D) Quantification of tumor volumes of nude mice injected subcutaneously with Huh7 cells overexpressing SRC-2 or control eGFP. Bar graphs represent mean tumor volumes. Error bars represent SDs from a total of ten subcutaneous injections (n = 5 mice) per experimental group tested. Student’s unpaired t-test was used to evaluate statistical significance * = p<0.05; ** = p<0.01; *** = p<0.001.</p

Inhibition of <i>SHP</i>, <i>DKK4</i>, and <i>CADM4</i> accelerate HCC cell proliferation <i>in vitro</i> and tumor growth <i>in vivo</i>.

<p>(A) Real-time PCR quantification of <i>SHP</i> expression in Huh7 cells after inhibition with two independent shRNAs. Bars graphs represent mRNA expression of <i>SHP</i> normalized to <i>ACTIN</i> and error bars represent SDs from triplicate measurements. (B) MTS proliferation assay measuring proliferation of <i>SHP</i> shRNA and control shRNA cells over time. (C) Quantification of tumor volumes in nude mice injected with Huh7 cells with <i>SHP</i> shRNAs or control shRNA. (D) Top, real-time PCR quantification of <i>DKK4</i> expression in HepG2 cells after inhibition with two independent shRNAs. Bar graphs represent <i>DKK4</i> mRNA expression normalized to <i>ACTIN</i> and error bars represent SDs from triplicate measurements. Bottom, western blot with quantification of DKK4 protein levels and normalized to Tubulin. (E) MTS proliferation assay measuring the proliferation of <i>DKK4</i> shRNA and control shRNA cells with over time. (F) Quantification of tumor volumes in nude mice injected with HepG2 cells with <i>DKK4</i> shRNAs or control shRNA. (G) Real-time PCR quantification and western blot analysis of <i>CADM4</i> mRNA and protein in HepG2 cells after inhibition with two independent shRNAs. (H) MTS assay measuring proliferation of <i>CADM4</i> shRNA and control cells over time. (I) Quantification of tumor volumes in nude mice injected with HepG2 cells with <i>CADM4</i> shRNAs or control shRNA. Bar graphs (C), (F), and (I) represent mean tumor volumes. For this and all subsequent xenograft experiments, the numbers below each bar represent the time (in days) after subcutaneous injection of cells into nude mice. Error bars in real-time quantitation and proliferation assays represent SDs from triplicate measurements. Error bars in xenograft experiments represent SDs from a total of ten subcutaneous injections (n = 5 mice) per shRNA tested. A student’s t-test was performed to determine statistical significance. * = p<0.05; ** = p<0.01; *** = p<0.001; **** = p<0.0001.</p

SHP and CADM4 rescue enhanced tumor burden upon SRC-2 inhibition.

<p>(A) Real-time PCR quantification of <i>SRC-2</i>, <i>SHP</i>, <i>CADM4</i>, and <i>DKK4</i> expression in HepG2 cells after inhibition of <i>SRC-2</i> with two independent shRNAs. Bar graphs represent mRNA expression of the labeled transcript normalized to <i>ACTIN</i> and error bars represent SDs from triplicate measurements. (B) Western blot analysis of SRC-2 and its targets CADM4 and DKK4 in HepG2 cells after SRC-2 inhibition with two independent shRNAs. Numbers in red represent quantification of protein levels relative to the control shRNA sample. (C) MTS assay measuring proliferation of HepG2 cells with control shRNA, <i>SRC-2</i> shRNA-1, or <i>SRC-2</i> shRNA-1 with overexpression of <i>SHP</i> or <i>CADM4</i> alone, or in combination with <i>THRSP</i> and <i>DKK4</i> (labeled as ALL 4). (D) Quantification of tumor volumes in nude mice injected with HepG2 cells as described in (C). Bars represent mean tumor volumes. Error bars in real-time quantitation and proliferation assays represent SDs from triplicate measurements. Error bars in xenograft experiments represent SDs from a total of ten subcutaneous injections (n = 5 mice) per shRNA tested. A student’s t-test was performed to determine statistical significance. * = p<0.05; ** = p<0.01; *** = p<0.001; **** = p<0.0001. Black asterisks represent comparisons to the control shRNA. Red asterisks represent comparisons to SRC-2 shRNA-1.</p

Identification of direct SRC-2 targets in MYC-driven liver tumors.

<p>(A) DAVID gene ontology analysis of downregulated genes in <i>Src-2</i>^-/- liver tumors. Individual p-values of enrichment are depicted next to each biological process. (B) Real-time PCR quantification of cell adhesion, glucose metabolism, and fatty acid metabolism genes in <i>Src-2</i>^-/- and <i>Src-2</i>^+/+ liver tumors. Bar graphs represent mRNA expression of genes relative to Actin. Error bars represent SDs from five independent samples per group. * = p<0.05; ** = p<0.01; *** = p<0.001; **** = p<0.0001. (C) DAVID gene ontology analysis of upregulated genes in <i>Src-2</i>^-/- liver tumors. (D) Real-time PCR quantification of inflammation and growth factor signaling genes in <i>Src-2</i>^-/- and <i>Src-2</i>^+/+ liver tumors. (E) Overlap of downregulated genes in <i>Src-2</i>^-/- liver tumors and <i>in vivo</i> mouse liver SRC-2 ChIP-Seq targets. (F) Real-time PCR quantification of candidate SRC-2 target genes <i>Shp</i>, <i>Dkk4</i>, <i>Thrsp</i> and <i>Cadm4</i> in <i>Src-2</i>^-/- and <i>Src-2</i>^+/+ liver tumors (left). As in (B) and (D), error bars represent SDs from five independent samples per group. SRC-2 ChIP-Seq peaks upstream of transcriptional start sites of candidate genes (right). SRC-2 binding sites are highlighted in red.</p